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TRANSCRIPT
Effects of Erythrocyte Aggregation on
Blood Rheology in Regard to Future
Sepsis Diagnosis Application
Darren Burley
Courtney Campagna
Aislinn Harte
Samantha Kelly
Max Spiegelhoff
Advisors:
Prof Raymond Page
Prof Ahmet Can Sabuncu
May 7th, 2020
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Contents
Authorship .................................................................................................................................................... 1
Acknowledgements ...................................................................................................................................... 2
Abstract ........................................................................................................................................................ 3
Chapter 1: Introduction ................................................................................................................................ 4
Chapter 2: Background ................................................................................................................................. 5
2.1 Sepsis Overview .................................................................................................................................. 5
2.2 Current Diagnostic Methods ............................................................................................................... 7
2.2.1 Blood Culture ............................................................................................................................... 7
2.2.2 Protein Analysis ............................................................................................................................ 8
2.2.3 Prothrombin and Partial Thromboplastin Time/Platelet Counts ................................................. 8
2.3 Potential Biological Tests for Sepsis Diagnosis ................................................................................... 9
2.3.1 Biomarkers ................................................................................................................................... 9
2.4 Potential Mechanical Tests for Sepsis Diagnosis .............................................................................. 16
2.4.1 Red Blood Cell Deformability ..................................................................................................... 16
2.4.2 RBC Aggregation ........................................................................................................................ 20
2.4.3 White Blood Cells ....................................................................................................................... 23
Chapter 3: Project Strategy ........................................................................................................................ 26
3.1 Client Statement ............................................................................................................................... 26
3.2 Design Requirements ........................................................................................................................ 27
3.2.1 Standards ................................................................................................................................... 27
3.3 Revised Project Statement ................................................................................................................ 29
Chapter 4: Design Process .......................................................................................................................... 30
4.1 Needs Analysis .................................................................................................................................. 30
4.2 Conceptual Designs and Prototype Testing ...................................................................................... 31
4.2.1 Erythrocyte Sedimentation Rate ................................................................................................ 32
4.2.2 Capillary Fill ................................................................................................................................ 34
4.2.3 Vibration Syllectometry ............................................................................................................. 36
4.3 Alternative Designs ........................................................................................................................... 37
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4.4 Final Design Selection ....................................................................................................................... 38
4.4.1 Blood Preparation ...................................................................................................................... 38
4.4.2 Micro-ESR Methodology & Materials ........................................................................................ 39
4.4.3 Capillary Fill Methodology & Materials...................................................................................... 40
4.4.4 Laser Syllectometry Methodology & Materials ......................................................................... 42
Chapter 5: Design Verification ................................................................................................................... 44
5.1 Micro-ESR Results ............................................................................................................................. 44
5.2 Capillary Fill Results........................................................................................................................... 46
5.3 Laser Syllectometry Results .............................................................................................................. 47
Chapter 6: Final Design and Validation ..................................................................................................... 55
6.1 Final Design CAD Prototype .............................................................................................................. 55
6.2 Standards .......................................................................................................................................... 56
6.3 Economics ......................................................................................................................................... 57
6.4 Environmental Impact ....................................................................................................................... 58
6.5 Societal Influence .............................................................................................................................. 58
6.6 Political Ramifications ....................................................................................................................... 59
6.7 Ethical Concerns ................................................................................................................................ 59
6.8 Health and Safety .............................................................................................................................. 59
6.9 Manufacturability ............................................................................................................................. 60
6.10 Sustainability ................................................................................................................................... 61
Chapter 7: Discussion/Future .................................................................................................................... 62
7.1 Micro-ESR .......................................................................................................................................... 62
7.1.1 Implications ................................................................................................................................ 62
7.1.2 Limitations .................................................................................................................................. 62
7.1.3 Future ......................................................................................................................................... 63
7.2 Capillary Fill ....................................................................................................................................... 64
7.2.1 Implications ................................................................................................................................ 64
7.2.2 Limitations .................................................................................................................................. 64
7.2.3 Future ......................................................................................................................................... 65
7.3 Syllectometry .................................................................................................................................... 66
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7.3.1 Implications ................................................................................................................................ 66
7.3.2 Limitations .................................................................................................................................. 67
7.3.3 Future ......................................................................................................................................... 68
7.4 Device Discussion .............................................................................................................................. 69
Chapter 8: Conclusions and Recommendations ........................................................................................ 70
8.1 Conclusions ....................................................................................................................................... 70
8.2 Recommendations ............................................................................................................................ 70
References .................................................................................................................................................. 72
Appendix A – Interviews ............................................................................................................................ 80
Appendix B – Pros and Cons of Different Testing Methods ...................................................................... 85
Appendix C – Pairwise Analysis ................................................................................................................. 86
Appendix D – Lab Gantt Chart ................................................................................................................... 87
Appendix E – Micro-ESR Data and Analysis ............................................................................................... 88
Appendix F – Capillary Fill Data and Analysis ............................................................................................ 94
Appendix G – Laser Syllectometry Data and Analysis ............................................................................... 99
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Authorship
The five project team members, Courtney Campagna, Darren Burley, Aislinn Harte,
Samantha Kelly, and Max Spiegelhoff, contributed equally to the content found in this report.
Extensive collaboration was demonstrated within each section while writing, revising,
compiling, correcting, and finalizing the report.
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Acknowledgements
The project team would like to thank the following group of individuals and
organizations for their assistance in completing this project:
Lisa Wall, Laboratory Manager, for her training and support of all lab-based activities
Dr. Michael Puskarich, Dr. Kate Madden, and the doctors at Brigham/Faulkner
hospital for helping the team to better understand sepsis from a certified medical
perspective as well as inform us of current sepsis diagnostic methods used within the
field today
Funding from the Biomedical Engineering Department at WPI
WPI Tinkerbox I & E Program for the additional monetary support
Most importantly, the team would like to thank our MQP advisors Professor Raymond Page,
PhD and Professor Ahmet Can Sabuncu, PhD. Their guidance and expertise over the past
academic year have not only helped enhance the quality of our work but also provided invaluable
professional engineering experience and education that will serve us for years to come.
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Abstract
Sepsis is a condition resulting from the overreaction of the body to an infectious agent
and results in millions of deaths worldwide each year. Sepsis has a very short infection-to-
mortality time and can be hard to detect and treat before related afflictions become permanent. A
device that could quickly and effectively diagnose sepsis could be incredibly beneficial to
ensuring proper treatment is given to septic patients. Furthermore, providing alternative methods
of testing than the currently used standard would allow for additional in-depth analysis and the
possibility of increased diagnostic success. This paper works to therefore describe the design of
a prototype, the included tests, and the reason for use in regard to future septic diagnosis.
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Chapter 1: Introduction
Every year, at least 1.7 million adults develop sepsis within the United States of America
and almost 270,000 die as a result [1]. Across the globe, almost 30 million people are diagnosed
with sepsis which leads to approximately 6 million deaths per year, averaging a mortality rate
between 15-30%. In severe cases of sepsis, the mortality rate can jump up to anywhere between
40-60%, mainly amongst infants and those in intensive care units [2]. Despite such jarring death
rates, there are currently no methods to effectively treat patients who have developed severe
cases of sepsis; if the disease isn’t treated within the first few days of diagnosis, sepsis can lead
to kidney failure, immune system disruption, and permanent organ damage [1]. Currently, many
methods of testing sepsis are based around clinical observations rather than a direct diagnosis.
According to Dr. Kate Madden, a doctor in critical care medicine at Boston Children’s Hospital:
We have many patients whom we may suspect [have] sepsis, but a large proportion do
not end up having a clear diagnosis. For research and quality improvement purposes, we
use the judgement of the clinical team, usually the attending physician, as well as specific
treatments that go along with sepsis. [Appendix A]
This inability to accurately test for sepsis can make it incredibly difficult to ensure the
patient is getting the proper treatment they need; the quick-acting nature of the disease makes
early diagnosis critical for survival. Therefore, the goal of our project is to create a device that
allows for an accurate and specific diagnosis of sepsis that can be used by the medical
community. To do so, we plan on designing a small device capable of using a sample of the
patient’s blood and performing a series of quick turnaround and low-cost tests that can provide
better clarity for a sepsis-positive prognosis to a physician. Our developed device will be
inexpensive and require little-to-no user training to successfully perform a test. It is our hope that
production and distribution of the device will help medical centers worldwide to better support
patients who could potentially be battling this life-threatening disease.
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Chapter 2: Background
2.1 Sepsis Overview
Sepsis is a serious medical condition commonly characterized as an overwhelming
immune response to an infection and is a common complication of medical surgery or poor
treatment of a wound. In many cases, the first stage of sepsis is presented by Systemic
Inflammatory Response Syndrome, or SIRS, in which the body begins to overcompensate for an
infectious agent. According to the America College of Physicians/Society of Critical Care, SIRS
often presents itself through “extreme increases or decreases in body temperature, expedited
heartrate, and increased respiratory rate usually greater than 20 breaths/minute” [3]. Early
treatment of SIRS is a necessity to minimize further medical complications that can occur.
However, while almost all septic patients have SIRS, the presence of SIRS does not
indicate that a person will automatically have sepsis. Sepsis is primarily characterized by the
presence of an infectious agent entering the blood stream, commonly referred to as “blood
poisoning” [4]. In the instances of surgery, or in the event of an open wound occurring on the
body, improper cleaning and management of the wound will increase the probability of an
infectious agent entering the body. Once the agent begins to disperse throughout the blood
stream - and it becomes harder for the immune system to combat the pathogen - is when SIRS
begins to transition to officially being declared as “sepsis”. This usually occurs around 3-5 days
after the initial wound or infection occurs. A timeline of sepsis stages can be seen with Figure 1.
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Figure 1: SIRS-sepsis patient timeline
Once immunosuppression begins and the body starts being unable to fight back the
increased concentration of pathogens in the blood, the severity of sepsis increases dramatically.
During this stage, colloquially referred to as “severe sepsis”, the natural physiology of the body
becomes incredibly hampered. From the period of approximately five to fifteen days after the
initial point of infection, patients diagnosed with sepsis can see decreased levels of urination,
more prevalent respiratory issues like pneumonia or shortness of breath, chills or fevers, and
patches of discolored skin [5]. Internally, sepsis can be categorized through decreased blood
platelet count, increased formation of blood clots, abnormal heart pumping, and drops in blood
pressure. Proper treatment of sepsis using antibiotics and vasoactive medications during this
phase is critical; if left unchecked for too long, the mortality rate of sepsis jumps up to almost
50% as many patients become afflicted with “septic shock” [6]. At this stage of the disease,
organ failure is incredibly common. Lactate levels begin to rise within the body and the
combination of decreased blood pressure and blood clotting leads to gangrene within body tissue.
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The disease becomes almost untreatable at this point. While “severe sepsis” commonly produces
a negative blood culture (due to the delicacy of the test and blood sensitivity during
immunization), “septic shock” commonly results in a renewal of positive blood cultures [7]. This
is assumed to be because the body develops an inability to overcome infection at this point as
total immune system shutdown occurs, allowing microorganisms to once again prevalently exist
in the blood [8]. Around approximately 28 days from the starting point of infection - or 20 days
from the diagnosis of severe sepsis - the body begins total shutdown and patient death occurs.
According to the UK Sepsis Trust, if a patient is able to recover from sepsis, it can take “up to 18
months before the survivor starts to feel like their normal self” with “around 50 percent of
survivors dealing with post-sepsis syndrome (PPS)” that can include insomnia, fatigue, damaged
organs and a severely hampered mental state [9]. Patients who recover from sepsis also have an
increased chance of becoming affected again due to their previously weakened immune system.
2.2 Current Diagnostic Methods
2.2.1 Blood Culture
Currently, there are no truly effective methods for diagnosing sepsis; the primary method
for sepsis evaluation lies within blood cultures. Being that sepsis primarily spawns from bacteria
entering and dispersing itself throughout the blood stream, samples of blood taken can
commonly be tested for bacteremia that might be present within the blood. In many instances
surrounding blood cultures, tests can take anywhere from 2-5 days to develop and don’t always
guarantee positive outcomes [10]. Furthermore, testing for blood cultures does not directly
signify the specific bacteria or fungi that exists within the body. In the case of sepsis, where the
dispersion of bacteria throughout the blood occurs rapidly from the point of infection, patients
may already be in the stage of severe sepsis before positive blood culture results occur [11]. As
mentioned, blood cultures only work for testing bacteremia found in the blood; in the event that a
fungi or virus was the cause of sepsis, these tests would be completely ineffective. Therefore,
while certainly fundamental for the most part, it is the rather long testing periods coupled with
the delicate specificity that hinder blood cultures from being the superior diagnostic method.
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2.2.2 Protein Analysis
Since sepsis starts with a massive inflammation of the body, it is common for increased
concentration of inflammation proteins like C-reactive protein (or CRP) to be present. In many
instances, the increased concentration of C-reactive proteins allows for medical doctors to catch
sepsis during the earlier stages of testing. The problem lies in the fact that protein increases are
not always consistent. In a case study performed at Westminster Hospital in London, 43 out of
49 patients exhibited increased concentration of C-reactive protein but only by a maximum of
about 25%, a relatively small change that could be attributed to other factors like age and gender
[12].
According to Dr. Michael Puskarich, an associate professor at the University of
Minnesota medical school:
Clinically SIRS, "sepsis-3", [and] procalcitonin occasionally have all been tried and they
are not consistently successful. These tools are primarily ways for clinicians to make sure
they are "getting the points" for treatment of sepsis patients and meeting CMS [Centers
for Medicare and Medicaid Services] core measure success but suffers from terrible
usability. For true patient care, good clinicians rely on gestalt and experience combined
with overall lab and diagnostic test results to diagnose sepsis more than any single tool,
which in and of itself is also problematic due to the highly variable nature and clinical
presentation of the disease. Sepsis is also confusing because it exists on a spectrum - it's
not a "yes / no" despite many people wanting it to be. You don't go from routine flu to
"sepsis," it exists on a spectrum with other infectious diseases that the body does or does
not control on its own. [Appendix A]
2.2.3 Prothrombin and Partial Thromboplastin Time/Platelet Counts
Sepsis can have a major impact on the ability of blood to clot within the body.
“Prothrombin” and “Partial Thromboplastin Time” refer to how long it takes for clotting within
the body to form, usually measured within seconds [13]. More specifically, “Prothrombin time”
measures the integrity of the extrinsic system as well as factors common to both systems while
“Partial Thromboplastin Time” measures the integrity of the intrinsic system and the common
components. On average, clotting time generally takes about 20 to 35 seconds for a healthy
person but can be significantly lower within patients who have sepsis, indicating excess blood
clotting [10, 14]. In contrast, another common symptom of sepsis is a decrease in the number of
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platelets that enter the body. Platelets are smaller cells that are instrumental in the formation of
clotting blood; if platelet counts are low, red blood cells are less likely to clot at the presence of
an open wound [10]. This vicious contradictory cycle therefore causes increased blood clotting
internally within the body amongst red blood cells rather than at the presence of an open wound
or injury. This is further elaborated on in section “2.4.2 RBC Aggregation”. While such testing
via a d-dimer test (which indicates clot levels in the blood) can be done as early as the starting
stages of SIRS, there is currently not enough evidence to determine if testing for clots is an
effective method for properly diagnosing sepsis. These challenges are once again further
elaborated on within section 2.4.2.
2.3 Potential Biological Tests for Sepsis Diagnosis
2.3.1 Biomarkers
In regard to all possible diagnostic methods for sepsis, biomarkers have found prevalence
for their diversity and adaptability. Biomarkers, as defined by the National Cancer Institute, are
“biological molecule[s] found in blood, other bodily fluids, or tissues that [are] a sign of a
normal or abnormal process, or of a condition or disease” [15]. Of all the possible biomarkers,
the three that emerged to have the most promise in the diagnosis of sepsis (based off extensive
literature review) include procalcitonin, Interleukin- 6 and presepsin.
2.3.1.1 Procalcitonin
Procalcitonin is currently the most studied of the three biomarkers and has been
recognized for its potential in diagnosing sepsis within patients. Procalcitonin (PCT) is a
propetide of calcitonin consisting of 116 amino acids and produced by the parafollicular cells of
the thyroid and parenchymal cells found in the lungs, liver, kidney, adipocytes and muscle
during normal production [16, 17]. Normally, PCT does not make it into the bloodstream
because it is converted to calcitonin leaving the blood concentration at about 0.05 ng/mL [18].
The levels of PCT released in the bloodstream are induced by bacterial endotoxins, cytokines,
lipopolysaccharides and other inflammatory signals. PCT production is reduced when interferon
- signaling proteins produced and released by host cells in the presence of viruses and other
pathogens - are present meaning that, during viral infections, the concentration levels do not
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increase significantly or at all [19]. Therefore, PCT can only be used for sepsis brought upon by
bacterial infections and to differentiate between bacterial and viral sepsis [20].
The current methods to measure PCT concentrations in blood use immunoassays. PCT is
the only one of the three biomarkers discussed with an FDA approved assay for sepsis risk
assessment in the ICU. The VIDAS BRAHMS PCT test is an automated test that measures the
procalcitonin concentrations from a patient’s blood sample. It performs enzyme-linked
fluorescent immunoassay (ELFA) on 200 μl samples of whole human blood with a limit of
detection of 0.03ng/mL and a range of 0.05-200ng/mL [21]. ELFA is a newer version of the
enzyme-linked immunosorbent assay (ELISA). The main difference is that it allows for a much
shorter testing time. All steps can be completed, and results are produced in about twenty
minutes, though it is noted that this test should be used in conjunction with other laboratory tests
for more accurate results [20]. Currently, this device is being sold as a kit including all the
reagents needed and the machine needed to carry out the tests [21].
Many research studies have found that PCT allows for the early detection of sepsis. PCT
level changes are detectable between two to four hours after inflammation begins and will reach
their peak concentration at about fourteen hours, remaining elevated for about twenty-four hours
after the inflammatory stimulus [17]. This allows for quick testing of the patient which is a
necessity due to the rapid attack of sepsis on the body. According to a study published by the
American Thoracic Journal, there were significant differences between the varying severities
(SIRS, sepsis, severe sepsis and septic shock) and the concentration of PCT in the plasma of
those patients. The study was conducted with 78 patients -18 of whom were diagnosed with
SIRS, 14 with sepsis, 21 with “severe sepsis”, and 25 with “septic shock” [22]. The study found
that the PCT concentrations for SIR, sepsis, “severe sepsis”, and “septic shock” “(ng/mL) were
0.6 (0 to 5.3) for SIRS; 3.5 (0.4 to 6.7) for sepsis, 6.2 (2.2 to 85) for severe sepsis; and 21.3 (1.2
to 654) for septic shock (p < 0.001)” [22]. By being able to determine the severity of the patient’s
condition, a recommendation on treatment will be more accurate. As seen in Figure 2, based off
of the PCT concentration in the blood sample, antibiotics use is either encouraged or
discouraged. Antibiotics, if prescribed when unnecessary, may cause additional harm, delaying
proper treatment and simultaneously increasing resistance of antibiotics among present bacteria
[23]. The same study found that procalcitonin had a specificity of 78%, a sensitivity (the
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proportion of people who test positive relative to those who have the disease) of 97%, and a
positive and negative accuracy predictive value (which determines how accurate positive and
negative tests outcomes are) of 94% and 88% respectively [22]. This reliability to differentiate
between severities allows doctors to decide on the type and aggressiveness of their treatment,
hopefully saving those patients.
Figure 2: Shows the different severities of illness related to sepsis and the associated PCT blood concentration
values. Also illustrates what values signify the use of antibiotic treatment [18].
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Though many studies show the reliability of PCT, concentrations can be increased in the
absence of sepsis. According to a study done by the Journal of Applied Laboratory Medicine,
PCT concentrations can increase in the blood:
In many clinical settings in the absence of infection, including after major surgery,
transplant, trauma, and severe burns, prolonged or severe cardiogenic shock, severe organ
perfusion anomalies, autoimmune disorders, malignancies and metastasis, noninfectious
systemic inflammation, chronic kidney disease (CKD), and physiologically in the neonate
[24].
Fungal and malarial infections (along with certain medications) can also increase PCT
concentrations by simulating the release of cytokines [25]. A meta-analysis study in 2007 found
that the mean values of sensitivity and specificity were around 71% meaning that the diagnostic
value of sepsis was low and that it cannot reliably differentiate sepsis from other conditions [22].
Not only can different diseases increase PCT concentrations but so can the age of patients;
neonates’ baseline PCT levels are higher than that of adults during the first 48 hours of life [25].
These differences in PCT concentrations must be studied further to determine how much of a
difference they make in patients’ PCT blood concentrations and how this affects their sepsis
diagnosis.
2.3.1.2 Interleukin-6
Interleukin-6 (IL-6) has garnered attention from scientists and researchers as one of the
next best sepsis diagnostic tools. IL-6 is one of the most commonly used cytokines in diagnosing
bacterial infections and is produced by T cells, macrophages, fibroblasts, endothelial cells and
more in response to infection/tissue trauma [26]. IL-6 helps to defend the host by stimulating
acute phase responses, hematopoiesis and immune reactions and “is strictly controlled by
transcriptional and posttranscriptional mechanisms, dysregulated continual synthesis of IL-6
plays a pathological effect on chronic inflammation and autoimmunity” [27]. IL-6 plays an
important part in homeostasis of the body; these molecules regulate serum, iron, and zinc
concentrations through control of their transporters, promote platelet creation in the bone
marrow, induce the production of phase proteins, reduce production of fibronectin, albumin and
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transferrin (other proteins with important regulatory functions), promote differentiation of T-
cells, and other effects that occur in many chronic diseases [27].
IL-6 has been found to be a reliable biomarker for diagnosing, determining severity, and
predicting the outcome of patients with sepsis. IL-6 concentration increases within two hours
from point of infection and can continue increasing for up to twenty-four hours after [28]. This
means that sepsis can be diagnosed early and allows for a longer testing window after the initial
infection. According to a meta-data analysis of 21 studies, IL-6 was found to have a sensitivity of
68% and a specificity of 73% [30]. This provides moderately accurate results for the diagnosis of
sepsis. Though not as helpful in differentiating severities of sepsis as PCT, IL-6 is an effective
alternative in diagnosing different stages of sepsis [28]. This can be seen below in Figure 3:
Figure 3: IL-6 concentrations as severities of sepsis increase [28].
2.3.1.3 Presepsin
Presepin, also known as CD14, is another biomarker that shows great promise in
diagnosing sepsis. Presepsin is a glycoprotein that is a receptor of the lipopolysaccharide-
lipopoly-saccharide (LSP-LBP) binding protein [31]. This receptor can activate signal
transduction pathways which trigger systemic inflammatory responses. Presepsin has two forms -
mCD14 and sCD14 - which are membrane and soluble forms respectively. Membrane bound
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presepsin is found on the surfaces of monocytes and macrophages and sometimes on neutrophils.
Likewise, sCD14 is created from mCD14 falling-off or secretion by these cells [32]. When used
in diagnosing sepsis, sCD14 is the preferred form of measurement [31].
Immunoassays are primarily used to measure the concentration of presepsin in the blood.
Most studies use chemiluminescent immunoassays, which combine chemiluminescence and
immunochemical reactions to produce variable light emission, to measure the presepsin
concentration in whole blood samples [33]. When performed in a test setting, the blood sample is
collected and mixed with a reagent before being diluted. Afterwards, a luminescent substrate is
added and automatically processed with an immunoassay analyzer to measure how vibrant the
given light is, showing overall presepsin concentration [34]. Currently, there is an immunoassay
analyzer called PATHFAST created by the Mitsubishi Chemical Medicine Corporation of Japan
that can analyze samples in just seventeen minutes and costs anywhere from $800 to $1,200 [35].
Presepsin is a fast-appearing and reliable biomarker for diagnosing severity of sepsis and
estimating 28-day mortality for patients. Presepsin concentrations rise in the first two hours after
infection, peak at 4 hours, and decrease between 4-8 hours after infection [32]. This quick
timeframe allows for early diagnosis of sepsis but can also be deemed too quick to effectively
work. A study conducted by Ma et. al, with 41 patients found significance between the presepsin
concentrations between different severities of infection [34]. The study identified ranges for
normal, SIRS, local infection sepsis and “severe sepsis” at 294.2±121.4 pg/mL, 721±611pg/mL,
333.5±130.130.6 pg/mL, 817.9±572.7 pg/mL and 1992.9± 1509.2 pg/mL respectively [34]. As
seen in Figure 4, all of the values are significantly different from one another, allowing analysis
of severity. The same study found that presepsin has a sensitivity of 91.9% and another study
found that presepsin has a sensitivity of 85.7% in predicting sepsis [31, 34].
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Figure 4: Comparison of presepsin concentrations in different severities of sepsis and infection [34].
Although presepsin does have lots of promise, there are some limitations with its use as a
biomarker for sepsis. Though many studies found a high sensitivity and specificity, a meta-data
analysis conducted by Zhang et al., of eight studies with 1757 patients found that it may not be as
useful as once thought [36]. This meta-analysis found that the pooled sensitivity was 0.77 and
the sensitivity was 0.73 meaning that, from these eight studies, there was only a moderate
diagnostic capacity for diagnosing sepsis [36]. As LPS, the binding protein, is a component of
gram-positive bacteria, presepsin is much more sensitive to gram-positive bacterial infections
than gram-negative bacterial infections with a sensitivity of 95.5% versus 77.8% [32]. Presepsin,
as it is produced in response to bacterial infection, will therefore not be a successful predictor of
viral infection which can also lead to sepsis. Lastly, in patients with renal failure compared to
those without, there was no significance between the presepsin concentration values [32]. This
may create false results if the patient has any disease which caused kidney failure and needs to
be considered when deciding upon which test is the best.
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2.4 Potential Mechanical Tests for Sepsis Diagnosis
2.4.1 Red Blood Cell Deformability
Analyzing red blood cell deformability could be helpful as a means of indirectly
detecting sepsis. A technique known as laser diffraction, a relatively recent development, offers a
way to detect the shape and size of cells.
Laser diffraction is based upon the basic principles of the way light interacts with
surfaces. There are four ways in which light interacts when it strikes the surface of an object: the
light could be diffracted, refracted, reflected, or absorbed (as seen in Figure 5). Reflected light is
light that hits the object and gets “reflected” back directly along the path that the light traveled to
the object on, making analysis for this purpose nonexistent. Diffraction makes relatively acute
angles in reference to the horizontal plane. In contrast, higher intensities caused by refraction
makes wider angles along the positive x axis [37]. As “intensity of light” is easier to measure
from a fundamental standpoint, it is the recommended to use diffraction when analyzing smaller
particles.
Figure 5: Schematic of refracted, reflected, and absorbed light [37].
Fundamentally, information can be obtained about a particle by observing the intensity of
scattered light and the angle of the diffracted light.
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Figure 6: Scattering of light from particles of different sizes [38].
Scattered light is essentially a bunch of randomly directed light rays whereas diffraction
is used to delineate how the light rays are spread out by passing across an edge at a certain angle.
An image of the shape of a cell can be extrapolated from the pattern that the diffracted light rays
form [39]. The pattern that is generated by the scattered light is analogous to how a shadow can
be formed on a wall when you shine a light on an object. The shadow could be seen as the
pattern being made by the scattered light except for in laser diffraction, the actual light (laser) is
the pattern. Figure 7 is a simple diagram of a diffraction pattern.
Figure 7: Schematic of laser passing through a sample to form a light pattern [39].
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Here, the blue arrow is a suspension of particles, the red arrow is a laser beam, and the
red circles are simplified diffraction patterns from the diffracted scattering of the laser. As the
pattern is from a sample of particles as opposed to a single particle, it is therefore possible to
calculate each particle’ size based on the projected light pattern. From there, it is then possible to
distinguish the amount of particles that exist of a specific size based on the particle’s respective
light intensity. Similarly, once raw data has been collected from the scattered laser light through
means of sensors, the data can then be analyzed to derive a particle size. The data is analyzed
using software such as LA-960 software from HORIBA. The general theory for how particle size
can be derived is depicted in the schematic below in Figure 8. In Figure 8 a circular aperture is
cut into a thin 2D medium, as shown by the grey square. In the equations, “theta” is the angle
relative to the positive x axis that a given laser beam ray makes from the aperture to the point
that the ray hits on the projecting screen behind the aperture, “d” is the diameter of the circular
aperture, “lambda” is the wavelength of the laser light, “D” is the distance between the aperture
and the projecting screen (the black square), “y” is the distance between the center of the
projecting screen and each point of contact on the projecting screen by the laser from the
diffracted rays, and “m” is the refractive index. “d” which is the diameter of the circular aperture,
would be representative of the particle diameter and therefore the diameter of the particle could
be found from calculating “d” using the equations below.
Here, the blue arrow is a suspension of particles, the red arrow a laser beam, and the red
circles are simplified diffraction patterns from the diffracted scattering of the laser. As the
resulting pattern is from a sample of particles as opposed to a single particle, it is therefore
possible to calculate each particle’s size based on the projected light pattern. From this
calculation, one can then calculate the quantity of particles of a set size based on the intensity of
light within the pattern. In summary, the pattern itself indicates the size of the particles and the
intensity of light in the pattern indicates how many particles there are.
Once raw data has been collected from the scattered laser light through means of sensors,
the data can then be analyzed to derive a particle size. Commonly, the data is analyzed using
software such as LA-960 software from HORIBA. In Figure 8, a circular aperture is cut into a
thin 2D medium as shown by the grey square. In the presented equations, “theta” is the angle
relative to the horizontal plane that a given laser beam ray makes from the aperture to the point
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that the ray hits on the projecting screen behind the aperture. “d” is the diameter of the circular
aperture, “lambda” is the wavelength of the laser light, “D” is the distance between the aperture
and the projecting screen (the black square), “y” is the distance between the center of the
projecting screen and each point of contact on the projecting screen by the laser from the
diffracted rays, and “m” is the refractive index. As “d” would also be representative of the
particle diameter, the diameter of the calculated particle could be found from calculating “d”
using the equations below:
Figure 8: Fraunhofer circular aperture diffraction theory [40].
The basic concept of how a “particle size analyzer” or a laser diffraction device works is
that it first measures scattered light intensity and angle and then secondly it transforms the
scattered data into a particle size distribution [41]. Figure 9 shows an example plot of raw data
from different particle sizes. In Figure 9 the vertical axis, “I”, is intensity and the horizontal axis,
“alpha”, is the distance from the center of the diffraction pattern. The “y” shown in Figure 8
above is a good representation of “alpha”.
The basic components of how a “particle size analyzer” or a laser diffraction device
works is that it first measures scattered light intensity and angle and then secondly it transforms
the scattered data into a particle size distribution [41]. Figure 9 shows an example plot of raw
data from different particle sizes. In figure 9, the vertical axis, “I”, is intensity and the horizontal
axis, “alpha”, is the distance from the center of the diffraction pattern. The “y” shown in figure 8
above is seen as a good representation of “alpha”.
20
Figure 9: Intensity plot: Overlapping diffraction patterns of a sample containing particles of different sizes (left),
and a sum of diffraction patterns, i.e. intensities measured by the detector (right) [39].
Laser diffraction is useful in detecting deformability or non-deformability of red blood
cells. Normal red blood cells in healthy humans will readily deform when under shear stress. In
sepsis, red blood cell deformability has been observed to decrease significantly [42]. Red blood
cell deformability has also been known to be the cause of surprisingly low viscosity at high shear
rates [43]. For this reason, an effort can be made to study both the deformability of red blood
cells and its correlation to viscosity.
2.4.2 RBC Aggregation
RBC aggregation is promoted when inflammation, infection, or trauma occur in the body.
In low shear conditions, RBCs tend to aggregate into stacks resembling a roll of coins. These
stacks, called rouleaux, can further aggregate parallel to one another to create larger aggregates.
In normal blood, shear rates of 7-10 s-1 are sufficient to disperse these aggregates [44].
Aggregate formation is also resisted by RBC surface charge since cells are electrostatically
repelled. RBC aggregation is largely a result of macromolecules in plasma, especially fibrinogen
[43]. The University of Southern California Medical School conducted a study of experimental
sepsis in rats that examined the differences in RBC aggregation between healthy rats, rats who
had undergone a cecum ligation/puncture to induce sepsis, and rats who experienced sham
operations to cause inflammation without infection [42]. Blood samples were collected from
each group, with sham-operated and septic samples collected 18 hours after the operation.
Fibrinogen levels and RBC aggregation were found to be significantly higher in the sham
operated and septic rats, compared to control. When blood plasma was replaced by a 3% dextran
70 solution, RBC aggregation in the septic rats was again found to be significantly higher than
21
the control, as seen in Figure 11. Furthermore, aggregation was found to be significantly higher
in the septic group than the sham-operated group. Without the effects of fibrinogen from the
plasma, this difference must be the result of cellular properties such as RBC surface charge [42].
This experiment displays potential towards differentiating between patients with sepsis compared
to those with non-septic inflammation.
Figure 11: RBC aggregation indexes (M1) measured using a Myrenne aggregometer [42]
A similar study of experimentally induced sepsis in pigs at the University of Debrecen by
Nemeth et. al. found more controversial results [45]. Five pigs were administered Escherichia
coli intravenously in increasing amounts over three hours while four pigs were given a similar
volume of an isotonic saline solution. Blood samples were collected from all pigs at the
beginning of the experiment and every second hour afterwards for eight hours. The intravenous
administration of E. coli initially caused bacteremia. This then developed into fulminant (sudden
or severe) sepsis. Of the five pigs in the septic group, two died in 3-4 hours and the remaining
three died in 6-7 hours. Instead of the expected increase in RBC aggregation in the sepsis group,
RBC aggregation decreased over time. Nemeth et. al. speculated this result may have been due to
the experiment investigating the early hours of fulminant sepsis rather than a study of a slower-
developing sepsis over a longer period of time, or from the effects of the specific E. coli strain
used, which contained hemolysin. This hemolysin affects the RBC membrane and causes
swelling, which could affect its aggregability [45]. The results may also have been affected by
the deaths of pigs in the septic group. If some factors contributed both towards pigs surviving
22
longer and towards decreased RBC aggregation, the early deaths of some pigs would skew
results towards traits of the pigs that survived longer.
RBC aggregation can be measured in a variety of ways. The erythrocyte sedimentation
rate (ESR) is a widely used test in which a sample of blood is placed in a vertical glass tube and
the rate at which RBCs, also known as erythrocytes, settle to the bottom of the tube is observed.
The greater the aggregation, the faster the RBCs will sediment. This test takes about an hour to
perform [43]. Another test uses low shear viscometry to measure the viscosity of blood, which
increases with RBC aggregation, but is also affected by hematocrit. RBCs can also be observed
directly using a microscope and can be used in conjunction with an image analysis program to
track aggregation over time [44]. Finally, a test called “syllectometry” analyzes the light
scattering of RBC suspensions; as light is shone through a thin layer of blood, the resultant rays
impact a photodetector on the other side that records the light intensity. If blood is disaggregated,
each RBC scatters light and the intensity that reaches the photodetector will be low. As RBCs
aggregate, the light will be able to shine more directly through to the photodetector. Therefore,
the intensity of light measured by the photodetector can be used to determine RBC aggregation
[46].
These two experiments embody the challenge in developing a conclusive diagnostic test
for sepsis. As sepsis is very broad, it may develop suddenly or slowly. Furthermore, whether it is
bacterial or viral, as well as specifics of the infection and the patient, can all have effects on
blood. While results may seem promising in one experiment, a similar experiment may have
entirely different results. In a hospital setting, patients will be of different ages and backgrounds,
with different comorbidities to consider. For example, patients with diabetes mellitus are likely
to have increased RBC aggregation in the absence of infections or inflammation [42]. There is
also the question of how well experiments on animal models translate to humans. Further studies
focused on humans are therefore required.
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2.4.3 White Blood Cells
White blood cells have been recognized for their use as indicators in the diagnosis of
sepsis. The primary function of white blood cells is to “fight bacteria, viruses, and other
organisms your body identifies as a danger” [10]. A high white blood cell count is generally an
indication of infection as a greater amount of white blood cells are needed to keep the body
healthy.
Neutrophil to lymphocyte ratio (NLR) is a specific method based on white blood cells
that may be used for early sepsis diagnosis. Neutrophils, a type of granulocyte, are the first white
blood cells to respond and travel to sites of acute inflammation in the body [47]. Due to this fast
response time, neutrophils act as the first line of defense, “directly phagocytosing and killing
microorganisms” while lymphocytes “determine the specificity of the immune response to
infectious microorganisms and other foreign substances” [48, 49]. The primary function of
lymphocytes is to bind to receptors to detected antigens and aid in their removal from the
patient’s body. Lymphocytes undergo cloning to produce multiple identical cells and to fight
against the detected infection. Sepsis generally causes an increase in neutrophil count; this is due
in part to neutrophil dysfunction, “a hallmark of sepsis, contributing to weak immune responses
to the causative infections, as well as additional off-target organ damage” [50]. This dysfunction
affects neutrophil response to the chemical stimulus of infection and negatively affects
antimicrobial activity. Since preliminary neutrophils cannot properly fulfill their functions, more
neutrophils are therefore needed to quell the spread of pathogens, weakening the stopping power
of the body in fighting off newer infections. The lifespan of these neutrophils thereby increases,
increasing the number of immature neutrophils circulating in the body [51]. On the contrary,
sepsis generally causes a decrease in lymphocyte count. As sepsis progresses and neutrophils
cannot properly control responses against infection, lymphocyte apoptosis occurs. This induces
“a state of 'immune paralysis' that renders the host vulnerable to invading pathogens” [52]. The
death of these lymphocyte cells causes a lower lymphocyte count.
NLR is calculated as the ratio of neutrophil count to lymphocyte count in a blood sample.
This blood sample is collected from a simple blood differential test, which is relatively easy to
perform and inexpensive compared to other methods of diagnosis. Normal NLR values for an
adult in good health are between 0.78 and 3.53 [53]. A higher NLR value corresponds to a
24
greater amount of physiological stress and systemic inflammation within the patient's body.
However, there is currently no standardized level of measurement demonstrating the significance
of a value when it is higher than that of the average healthy patient. Greater physiological stress
and systemic inflammation may be a result of sepsis, coronary interventions, coronary artery
bypass grafting, inflammatory conditions, etc. Therefore, utilizing only NLR as the primary
method of diagnosis for sepsis is not ideal as NLR cannot currently diagnose a specific
condition. However, NLR in combination with another method of diagnosis may be more
promising.
Designing a microfluidic device based on spontaneous neutrophil motility may also be a
promising strategy in the diagnosis of sepsis. Motility can be described as the ability of an
organism to move by itself, utilizing its own metabolic energy [54]. Patients with sepsis
generally have high spontaneous motility when compared to healthy patients. Along with
motility, the effectiveness of neutrophils in attacking pathogens is important to observe as sepsis
negatively affects the ability of neutrophils to respond properly to chemotactic signals. In one
specific study, Dr. Muldur of Harvard Medical School and Massachusetts General Hospital and
his team created a microfluidic device to measure spontaneous neutrophil migration from a
single drop of diluted blood [55]. The device contained eight migration mazes with each maze
consisting of several migration channels and a red blood cell (RBC) filter. An image of this
microfluidic device is shown below in Figure 12 [55].
Figure 12: The microfluidic device with a detailed view of the maze [55]
25
Spontaneous neutrophil motility is then detected through microscopy techniques and
tracked through ImageJ/Fiji analysis software. The “Sepsis Score” can then be calculated using
the equation below:
Sepsis Score=N*(O+P+R+AD)/103 Eq. 1
In this equation, “… N, is the total number of migrated neutrophils, O, the total number
of oscillation phenotype, defined as ‘the total number of cells that switch direction twice in a
channel and migrate for more than 15μm in each segment’, P, the total number of arrest
phenotype, defined as ‘a cell with zero velocity’, R, the total number of retrotaxis phenotype,
defined as ‘any cell that leaves the maze back into the central chamber’, and AD, average
distance of all neutrophils traveled in the two mazes, divided by four” [55]. A patient is
considered septic if their “Sepsis Score” is greater than 30. This microfluidic device proved to be
very specific to sepsis with 98% specificity and 97% sensitivity [55]. This device also proves to
be simple to use as an operator would only need to be trained for preparing and loading the
patient’s blood sample, as data analysis and the “Sepsis Score” results are automated [50].
26
Chapter 3: Project Strategy
3.1 Client Statement
While the scope of the project is vast, the initial client statement from Professor Sabuncu,
a project advisor, is as follows:
Red Blood Cell (RBC) aggregation is central to the study and diagnosis
of sepsis. At low shear rates and during hemostasis, RBCs pile together to form a
“rouleau”. At high shear rates, these aggregates are dispersed, whereas, in the
microcirculation, shear forces are not strong enough to dissociate the aggregates.
In infectious diseases, where the RBC aggregation is elevated, the local viscosity
increases in the microvasculature and this increase contributes to low perfusion and
tissue ischemia. Therefore, knowledge of the amount of RBC aggregation at low
shear rates could allow early diagnosis of septic shock and organ failure. Currently,
the gold standard clinical methods to identify sepsis rely on microbiological
techniques that require 2-3 days to complete. However, a point of care technology
that can diagnose sepsis from the RBC physical properties does not exist. In
addition, the current techniques do not allow for comprehensive characterization of
RBC aggregation. For a complete analysis of RBC aggregation, RBC aggregate
size distribution, aggregate resistance to disaggregation (shear stress), aggregate
morphology, and aggregation kinetics need to be quantified. Also, a comprehensive
technique should be able to distinguish between plasmatic and cellular factors that
lead to aggregation.
Shortly after the initial client statement was provided, a decision was made between the
team and the project advisors, Professor Sabuncu and Professor Page, to examine the issue of
diagnosing sepsis more broadly. The team is to determine the most important criteria for a sepsis
diagnostic test, devise a test/series of tests that best meets those criteria, and design a device to
conduct said test(s).
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3.2 Design Requirements
3.2.1 Standards
Throughout the design process, the team must ensure that all requirements from relevant
industry standards are met.
ISO 13485:2016 specifies requirements for a quality management system where an
organization needs to demonstrate its ability to provide medical devices and related services that
consistently meet customer and applicable regulatory requirements. Such organizations can be
involved in one or more stages of the lifecycle, including design and development, production,
storage and distribution, installation, or servicing of a medical device and design and
development or provision of associated activities (e.g. technical support). ISO 13485:2016 can
also be used by suppliers or external parties that provide product, including quality management
system-related services to such organizations [56].
Another important standard that is relevant to our design is ISO 11737-2:2009 which
addresses standard requirements for the sterilization of medical devices. ISO 11737-2:2009
“specifies the general criteria for tests of sterility on medical devices that have been exposed to a
treatment with the sterilizing agent reduced relative to that anticipated to be used in routine
sterilization processing” [57]. Sterilization is used to kill bacteria and other biological agents that
may have been in contact with the device in order to protect the user. ISO 11737-2:2009 further
defines a medical device as an “instrument, apparatus, implement, machine, appliance, implant,
in vitro reagent or calibrator, software, material or other related article, intended by the
manufacturer to be used, … for human beings for one or more of the specific purpose(s) of: -
diagnosis, prevention, monitoring, treatment or alleviation of disease …” [57]. The team’s
design will therefore fall under the definition of medical device provided in this and the prior
standard. As the team will be trying to diagnosis sepsis using an instrument, the design will be
considered a medical device. As the device will be interacting with human patients and blood,
the device must be sterilized as to keep all patients safe.
ISO 10993-1 is based on biocompatibility and biological evaluations of medical devices.
The major goal of this standard is to protect humans from biological risks associated with
medical devices. This standard provides requirements on how to develop a risk management
28
process and assess all potential biological hazards in order to keep all users safe [58]. ISO
10993-1 will be incorporated into the design as it will be interacting with human patients and
blood and the team will need to perform biocompatibility evaluations in order to guarantee safety
to all users.
ISO/TC 76 is another relevant standard that is centered around blood processing
equipment. ISO/TC 76 is a “standardization of containers (such as infusion bottles and bags,
injection vials, ampoules, glass cylinders, cartridges, prefillable syringes, etc.) application
systems (such as giving sets, non-electrically driven portable infusion devices, blood collection
systems, etc.) and accessories for infusion, transfusion, injection and blood processing in blood
banks, terms, definitions, requirements and test methods for these devices, specifications and test
methods for quality and performance of their materials and components (such as elastomeric
closures, caps and ports, pipettes, etc.)” [59]. This standard is relevant to the team’s design and
will be incorporated into a system that will collect and process a human patient’s blood.
ISO 10993-11 is based upon biological evaluation of medical devices in regard to
systemic toxicity and adverse systemic reactions. This standard provides requirements for
developing a process to evaluate systemic toxicity of medical devices to determine whether the
medical device is safe to use on humans [60]. ISO 10993-11 will be incorporated into the design
as it will be utilized with human patients and blood and the team will need to perform
biocompatibility and toxicity evaluations in order to guarantee the highest safety to all users.
In addition to these industry standards, the team will also adhere to all relevant standards
related to ethics. One specific ethical standard is the HIPAA Privacy Rule. This rule “…
establishes national standards to protect individuals’ medical records and other personal health
information …” [61]. This rule preserves the privacy of personal health information obtained
from patients. Information that is protected under this law includes “information your doctors,
nurses, and other health care providers put in your medical record, conversations your doctor has
about your care or treatment with nurses and others, information about you in your health
insurer’s computer system, billing information about you at your clinic, and most other health
information about you held by those who must follow these laws” [62]. The team will
incorporate the HIPAA Privacy Rule by keeping all patient information safe and private unless
given patient authorization.
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3.3 Revised Project Statement
From our research on the methods and limitations of sepsis testing, a revised project
statement was developed. The goal of this project is “to development a point-of-care device that
prioritizes accuracy, a rapid testing time, and a low cost.” The device will be used when sepsis is
suspected in patients in order to provide strong evidence towards or against a diagnosis of sepsis.
By obtaining results in hours or minutes rather than days, sepsis can be treated earlier in order to
increase chances of survival.
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Chapter 4: Design Process
4.1 Needs Analysis
Table 1: Pairwise Analysis for Device Designs
When it comes to designing the final device, it is important to consider what both the
client and the team find valuable in terms of design elements and overall purpose. If the team
focuses on elements that emphasize different components from the client, the device would be
considered a failure regardless of its effectiveness in tackling the problem. As a result, we
decided to create a pairwise analysis of the different components that the client desired to
determine which aspects of the device should be more focused on than others. A pairwise
analysis matrix works by comparing and ranking a design element (low cost, easy to
manufacture, etc.) and comparing it against the following columns of the same criteria. If the
former characteristic is more important than its column counterpart, it is given a value of “1”. If
equal, it is assigned a value of “1/2” and if less important, a value of “0”. All values are then
totaled following the end of the process and those with the highest total score are therefore the
most important traits to focus on when designing our device.
In this instance, comparing the qualities found in Table 1 to those desired by the client, it
was determined that “effectiveness in diagnosing” sepsis within the patients was the most
important task for our device to accomplish, followed closely by a “low cost” solution and the
ability to provide a “quick testing time”. The ability to effectively diagnose the disease captures
the highest position since the device’s primary function is to help characterize those with sepsis
as accurately as possible. The concept of a low cost yet quick testing design also plays into the
notion that sepsis has a very small window in which the disease can be properly monitored
31
before negative effects begin hampering the body. If a procedure takes too long to perform or
costs too much that it might propose doubt in the mind of a doctor to use, it would also serve as
an ineffective diagnostic method.
Keeping in mind what is important in the device design, it is now possible for our team to
test and adapt methods that focus on achieving these three aspects. Possible methods used in
conjunction with the device are discussed in detail in the next section “4.2 Conceptual Designs
and Prototype Testing”.
4.2 Conceptual Designs and Prototype Testing
Following the pairwise analysis, a concept map was created to allow deeper analysis into
potential methods for sepsis diagnosis. Based on the concept map seen in Figure 13, the team
then narrowed our focus to RBC aggregation due to its variable testing methods, speed of testing
time, and for being the most specific in relation to a septic diagnosis than all other methods. In
choosing RBC aggregation, we are further ensuring that we meet the criteria set by our pairwise
analysis. Methods to measure RBC aggregation in relation to sepsis are discussed in further
detail in the following sections.
Figure 13: Concept map
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4.2.1 Erythrocyte Sedimentation Rate
4.2.1.1 ESR
One diagnostic blood test that can be used to compare septic and non-septic blood is the
erythrocyte sedimentation rate (ESR), first mentioned in section “2.4.2 RBC Aggregation”. ESR
measures the rate at which erythrocytes in an anti-coagulated whole blood sample settle in a test
tube within the time frame of one hour, expressed in units of millimeters [63]. Throughout the
test, the test tube must remain perfectly vertical as the resultant values are determined by the
height of plasma at the top of the tube after the set one-hour period [64]. Primarily, ESR can be
used as an indicator of inflammation; patients with inflammation have an increase in the amount
of proteins in their blood, which causes red blood cells to clump together [64]. Due to this
clumping, red blood cell aggregates within the patient’s blood will settle at the bottom of the
tube at a faster rate than those that remain independent. Therefore, a patient with inflammation
will have a greater ESR level. Figure 14 shows how red blood cells aggregate when introduced
to inflammation. Sepsis involves widespread inflammation in the body so it can be assumed that
septic patients will have high ESR levels.
Figure 14: Normal erythrocyte sedimentation compared to inflamed [64]
The Westergren method is considered the gold standard for ESR. Materials required for
the Westergren method include anti-coagulated blood, sodium citrate solution, a tube support
33
rack, and “standardized colorless, circular glass or plastic tubes, with an inner diameter of at least
2.55 mm and sufficient length to include a 200 mm sedimentation scale” [63]. A representation
of three different situations is shown in Figure 15 below. Sample A shows the whole blood
sample mixed with sodium citrate at the start of the ESR test. Sample B shows normal results for
ESR at the end of the 60-minute test time. Sample C shows results for a higher ESR level at the
end of the 60-minute test time.
Figure 15: Three possible ESR situations [63]
When using the Westergren method, normal ESR values are ≤15 mm/hr for men and ≤20
mm/hr for women [63]. ESR may increase with age and the highest ESR values generally come
from people between 65-74 years of age [63]. Although ESR is a non-specific marker, it will be
beneficial to study as there may be a distinguishing feature between septic and non-septic blood
that can be measured using this method.
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4.2.1.2 Micro-ESR
Micro-ESR is another diagnostic blood test that can be used to compare septic and non-
septic blood and, similar to its full-sized companion, Micro-ESR requires capillary blood
samples, micro hematocrit capillary tubes, a lancet, laboratory slides, sodium citrate, antiseptic
solution, and a rack to hold all of the tubes [65].
The biggest comparison between ESR and micro-ESR tests are their testing timeframes.
During a specific procedure performed by Reza Hashemi, a scientist of the Department of
Internal Medicine at Shohadaye Tajrish Hospital in Iran, a patient’s fingertip was carefully
punctured with a lancet after properly cleaning with antiseptic solution [65]. Four drops of blood
were collected and added to a laboratory slide with a single drop of sodium citrate. The blood
and sodium citrate would then be gently mixed on the slide. Next, “a 7.5-centimeter capillary
tube was placed on the slide immediately with a 30 to 45-degree angle” [65]. The blood sample
would then rise through the capillary tube. When the blood sample would reach the 7-centimeter
mark, the tube would be placed vertically and placed into a tube rack to ensure all tubes would
be vertical [65]. Based on the statistical analysis of Hashemi’s results, a correlation was made
between micro-ESR and traditional ESR. Hashemi’s results proved that micro-ESR results can
be successfully interrupted at 20 minutes [65]. Therefore, micro-ESR is faster than traditional
ESR, which requires 60 minutes to complete, while still using less materials to perform.
However, like ESR, micro-ESR is still a non-specific marker of inflammation. Therefore, this
teams feels it will be beneficial to study as there may be a distinguishing feature between septic
and non-septic blood that can be measured using this method.
4.2.2 Capillary Fill
Capillary action is “the tendency of a polar liquid to rise against gravity into a small-
diameter tube” [66]. There are two opposing forces that drive capillary action – cohesion and
adhesion. Cohesion results from intermolecular forces, and there is a correlation between these
intermolecular forces and a liquid’s viscosity. Adhesion results from attractive forces between
the liquid and another surface. In capillary action, adhesion seeks to maximize the amount of
capillary surface the liquid touches, while cohesion seeks to minimize the liquid’s surface area
[66].
35
For a capillary tube placed into a liquid at an angle, the liquid will rise along the tube to a
specific height. As it does so, it experiences a force that is described by the following equation,
illustrated in Figure 16 [67]:
𝐹 = 2𝜋𝑟𝛾 cos 𝜃 − 𝜌𝑔𝜋𝑟 cos 𝛽 𝑠(𝑡), Eq. 2
where
F is the force the liquid exerts on the capillary tube
γ is the surface tension of the liquid
θ is the contact angle between the liquid and the capillary
ρ is the density of the liquid
r is the radius of the capillary tube
β is the angle of the capillary tube with respect to the vertical
s(t) is the distance traveled by the liquid along the capillary as a function of time t
Figure 16: Liquid rising in a capillary tube [66]
The first term in this equation describes the force upward due to surface tension, and the
second term describes the force downward as a result of gravity. The upward force features two
properties of the liquid – surface tension γ and contact angle θ. Surface tension increases with
larger intermolecular forces. The contact angle is determined by the balance between cohesive
and adhesive forces, with a smaller contact angle contributing to a larger upward force [68].
36
As red blood cells aggregate, blood viscosity increases [43]. It is suspected that, as red blood
cells aggregate, cohesive forces in the blood will also increase [68]. Since there is a correlation
between viscosity and the intermolecular forces that affect capillary action, it is possible that
different levels of aggregation will cause differences in the speed at which blood will fill a
capillary tube [66]. Measurements of this speed can be made and compared to the relative
aggregation of these blood samples to investigate a potential relationship between aggregation
and capillary fill speeds.
4.2.3 Vibration Syllectometry
Most commercial aggregometers today disaggregate RBCs using a shearing system
which can be very expensive. In order to simplify aggregometer design, reduce costs, and allow
for simpler cleaning between tests, a team at Kyungpook National University developed an
instrument that disaggregates blood through vibrations, then measures aggregation through
syllectometry, as seen in Figure 17 [69]. The disaggregation mechanism consists of a function
generator, amplifier and speaker. A jig is attached to the speaker diagram such that the jig will
vibrate when the speaker is turned on. A glass test slide to hold a small amount (around 10 μl) of
blood is then fixed to the jig [69]. This slide has a cavity for the blood and can be easily disposed
of after use [69, 70].
Figure 17: Vibration syllectometry device using backscattered light [69]
37
The syllectometry is conducted using a laser diode (650 nm, 1.5-5mW) that emits a laser
beam through the blood sample. A photo diode then measures the intensity of light transmitted
through or backscattered by the blood [69, 70]. Measurements from the photo diode are recorded
to a computer and the resultant intensity is then used to describe the degree of aggregation in the
RBCs. For measurements of transmitted light, a higher intensity indicates a higher degree of
aggregation [70]. In backscattered light measurements, a lower intensity indicates a higher
degree of aggregation [69].
Following the procedure laid out by Shin et. al, a blood sample is vibrated for 40 seconds
at a frequency and amplitude of 150 Hz and 0.5 mm, respectively [69]. The exact timing,
frequency, and amplitude can be varied based on the results observed in order to refine the
resultant values. The duration should be long enough that the RBCs completely disaggregate
while the vibration frequency and amplitude should be mild enough to avoid damaging the cells.
Once the blood is fully disaggregated, measurements of the variation in light intensity over time
are collected and the application of a curve-fitting program is used to quantify aggregation [69].
For collection of research data, especially when comparing septic and healthy blood, it is helpful
to use samples with a similar hematocrit since this affects light intensity.
4.3 Alternative Designs
As RBC aggregation is our main focus, any additional methods need to also focus on
RBC aggregation as the main conditional testing criteria. Referring back to our concept map
from section “4.2 Concept Map”, our main alternative methods would be incorporating either a
standard ESR test or the use of image tracking. Standard ESR tests, while requiring more blood
and a longer testing time, are still effective at looking at erythrocyte sedimentation rate. In regard
to image tracking, red blood cells can be analyzed over a set period of time to determine how
long it takes for rouleaux to form. Specific RBCs can be placed with a virtual marker and tracked
as aggregation occurs through a series of photos, making use of continual time periods to detail
rouleaux formation.
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4.4 Final Design Selection
4.4.1 Blood Preparation
The preparation of the blood dextran solutions for the micro-ESR, capillary fill, and
vibration syllectometry were all done as one big batch. Blood was obtained from AllCells, LLC, a
reputable blood and marrow cell supplier from Quincy, Massachusetts. The blood was fresh
whole blood shipped in a small vial, mixed with an anti-coagulant (Citrate Dextrose Solution –
A), and placed in a climate-controlled shipping container before being stored in a fridge. To
make our dextran-blood solutions, we used dextran with a 50k molecular weight (MW), whole
human blood, and phosphate-buffered saline (PBS). To create the concentrations, five different
masses of Dextran 50k MW, obtained from Sigma-Aldrich, were measured using an automated
scale. The actual masses of dextran, in comparison to the desired thresholds, can be seen in Table
2. These masses were measured on an electronic scale with an accuracy of +0.1mg:
Table 2: Shows the nominal and actual masses of dextran used in blood sample preparation
Mass of Dextran (grams) Actual Mass of Dextran (grams)
0.025 0.025
0.05 0.051
0.10 0.099
0.15 0.152
0.20 0.201
These measured dextran amounts were each placed in their own 15mL conical tube and
labelled with the dextran mass added. Using a graduated cylinder, 10mL of PBS were measured
and added to each conical tube. The PBS-dextran solutions were then stirred until all the dextran
dissolved in the PBS. To sterilize the PBS-dextran solutions, each solution was passed through a
sterile vacuum pump filter inside of a laminar hood. These solutions were then placed in a new
sterile 15mL conical tube and labelled by the amount of dextran they contained. Next, inside the
same laminar hood, 4mL of 40% hematocrit blood obtained from All Cells was measured with a
serological pipette and placed into a separate15mL conical tube. This was repeated for six
conical tubes total. Those conical tubes filled with 4mL of blood were then placed inside a
centrifuge and spun at 200xg for 10 minutes to allow the full separation of plasma from the
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blood cells. After centrifuging, the plasma was then aspirated from each of the conical tubes until
there was about 1.6mL of hematocrit left inside the conical tubes. To maintain a 40% hematocrit
and produce 4mL of each test, 2.4mL of the dextran-PBS solutions were added to five of the
conical tubes containing blood and appropriately labelled. For the sixth tube, 2.4mL of pure PBS
was added for a control of 0 grams of dextran. These dextran-blood solutions were then mixed.
All solutions were stored in a refrigerator at four degrees Celsius for the duration of the
experiment.
4.4.2 Micro-ESR Methodology & Materials
This set-up included a clay capillary tube sealer stand, a blank backdrop made from paper
towels, and a sterile cover placed far above the tubes. To begin the Micro-ESR test, a capillary
tube filled with blood was placed vertically within a clay-sealant stand, as seen in Figure 18. The
capillary tubes were previously sterilized by leaving them in 70% isopropanol for 10 minutes and
then allowing them to dry for an hour, until no more isopropanol was present. The cover was
used to prevent the downward air of the laminar hood from evaporating or drying out the plasma
layer.
Figure 18: Capillary tubes in a clay stand for micro-ESR
Throughout the experiment, pictures were taken every thirty minutes for four hours,
starting at time zero, using the phone’s camera. Each timer was started immediately after the
capillary tube was placed into the clay sealing stand and ended after the test was completed.
Once all pictures had been collected, the blood inside the capillary tube was aspirated and the
capillary tube was disposed of inside the bio-sharps container while the images were prepped to
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be analyzed using the ImageJ software. Using the backdrop in conjunction with ImageJ, the
known length of the stand was used to determine the height of the plasma layer in mm. The
plasma was measured from the bloodline to the horizontal height between the two sides of the
meniscus. This was done to prevent confusion between shadows and the line of the meniscus.
This experiment was then repeated three times for each different dextran-blood mixture
concentration. The trials were then averaged to find the average aggregation rate of the blood-
dextran solution.
4.4.3 Capillary Fill Methodology & Materials
Figure 19: A capillary fill test in progress
In order to complete the capillary fill tests, a stand for the experiment was constructed
using two conical tube stands of known dimensions, a piece of cardboard, and a large latex
glove, shown in Figure 19. The cardboard was cut to be the same size as the top of the stand. It
was then placed on the top of the stand and covered with the large latex glove, which acted as a
hydrophobic layer during the testing period. This layer was further controlled by sterilization
using 70% isopropanol before it was placed in the laminar hood. A second sterile stand of the
same size was placed in the laminar hood directly in front of the stand with the glove. A phone,
which was used to record the experiment, was then set-up in a way that allowed for both stands
to be fully in view outside the laminar hood. The rest of the experiment was then conducted
inside the hood. The blood solutions that were to be tested were then removed from the fridge
and given time to rise to room temperature, which was about 30 minutes. The conical tube with
the blood-dextran sample was then lightly shaken to breakup any rouleaux that had formed while
resting.
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Using a similar method as before, a capillary was sterilized with 70% isopropanol. Using
a P2000 pipette, 500 microliters of the blood sample were then removed and placed on the latex
glove covered stand. The tube was filled by manually laying it between the two stands, which
created a slope of negative five degrees from the plane (cardboard) the blood sample laid on. The
capillary tube was then pushed into the blood droplet and allowed to fill from one end to another.
Prior to completion, the tube was then plugged with the experimenter's gloved thumb and
removed from between the stands. The filled capillary tube was then placed vertically into the
clay stand for the micro-ESR experiment. The purpose of joining these experiments was done to
conserve blood.
The video of the experiment, taken on the phone, was then uploaded to a computer. The
video was cut into four frames where the blood had flowed to different locations. These frame
images were then analyzed using the prior ImageJ software to determine how far the blood had
flowed from the opening of the tube that was inserted into the blood droplet. The length was
determined by finding the conversion from pixels to mm from the known length of the stand.
The flow rate was then calculated by using the frames/second of the video to convert each frame
to seconds before timed relative to each other. For example, if the video had a frame rate of two
seconds, and frame one was the tenth frame of the video and frame two was the twentieth frame
of the video, frame one would be converted to zero seconds and frame two would be at time ten
seconds. This time, and the length travelled, was then used to determine flow rate of the blood
sample. The flow rates of all three trials were averaged to determine the average flow rate for
each dextran-blood solution. This was repeated for each additional dextran-blood mixture.
It is important to note that the capillary tubes were placed at a negative angle, unlike the
positive angles described in section “4.2.2 Capillary Fill Test”. This angle was chosen because
initial trials found that the dextran-blood solutions did not rise far enough into the capillary
tubes. Suitable measurements could not be made at a positive angle. This is likely a result of
replacing blood plasma with PBS, which has different properties. For example, PBS has a lower
viscosity, which suggests weaker intermolecular forces [71]. From equation (2), increasing the
surface tension but maintaining the same contact angle allows a liquid to rise further in a tube
[67]. These different properties of PBS meant that angles typically used to draw whole blood into
a capillary tube were not viable for this test.
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4.4.4 Laser Syllectometry Methodology & Materials
Unlike the micro-ESR and capillary fill tests, the test for laser syllectometry required
more personalized equipment than what was present within our laboratory. To begin, a 3D stand
was modelled using SolidWorks, sitting 6 inches tall, 4.02 inches wide, and 2.42 inches deep.
Three notches were made at 1.67, 2.18, and 3.17 inches respectively and served as holders for an
attachment piece meant to house the slide within the device itself. Cut directly into the device’s
top was a hole for the placement of a DZS Elec 650nm laser diode (part number 5VLD-R650-
5MW-12). This diode was aligned with a Texas Instruments OPT101P photodiode with an on-
chip trans-impedance amplifier that sat within the middle of a breadboard holstered at the bottom
of the device. The breadboard, photodiode, and laser diode were all connect to an Arduino Mega
2560 system at the back of the device that regulated voltage control, controlled the laser diode,
and recorded output from the photodiode. The Arduino was attached directly to a laptop for
power and data transfer. The 3D drawing of our design can be seen below in Figure 20:
Figure 20: The stand designed for syllectometry
Using the prepared blood samples mentioned in section “4.4.1 Blood Preparation”, a
small drop of about 100 µL was placed into the center of an AmScope BS-C12 deep-welled
slide. The slide was then fixed with a glass cover and placed within the slide holder before being
inserted into the device. Prior to activation, two BestTong vibrational coin motors (part number
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A00000117) were placed on the left and right of the slide and ran at a frequency of 150hz for
approximately 10 seconds. Once the blood had disaggregated, the laser was activated and the
signal output from the photodiode was recorded for approximately 5-7 minutes. Following test
completion, the slide was disposed of in the proper biohazard container and another was
prepared. Five tests were performed for each dextran solution concentration using the same
methods.
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Chapter 5: Design Verification
The team tested the three separate methods of measuring RBC aggregation – micro-ESR,
capillary fill, and syllectometry – to validate how effective they would be in achieving the
project goal. The first test, micro-ESR, measured the plasma height of blood in a capillary tube
as RBCs settled over a period of four hours. The capillary fill test measured the flow rate of
blood in a capillary tube held at an angle. Finally, the syllectometry test measured the intensity of
a laser shone through a few drops of blood as its RBCs aggregated.
5.1 Micro-ESR Results
Figure 21: Buffer height of all amounts of added Dextran 50K MW
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Figure 22: Comparison of buffer heights of all Dextran 50K MW amounts
As seen in Figure 21 and 22, the slope of the linear trend lines increases with an increase
in dextran. The only exception is 0.1 g/dL of dextran since it has a smaller slope than that of 0.05
g/dL of dextran. Otherwise, there is a positive correlation between the amount of dextran and
plasma height. The R-squared value of all the linear trend lines for 0, 0.05, 0.1, 0.15 and 0.2
grams are above 0.94 meaning that there is very low variation between trials. For 0.025 grams,
the R-squared value is 0.8252 which is still relatively high and gives confidence in the found
trend.
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5.2 Capillary Fill Results
Table 3: Average flow rate of different grams of Dextran
Grams of Dextran Average Flow Velocity
(mm/s)
Standard Deviation (mm/s)
0.025 1.03 +0.209
0.05 2.73 +0.497
0.1 1.02 +0.150
0.15 2.40 +0.486
0.2 1.21 +0.595
Table 3 shows all of the calculated flow rates of dextran amounts 0.025 g/dL to 0.2 g/dL.
For all solutions, three trials were conducted except for 0.1 and 0.2 grams, where only two trials
were usable due to angle differences. The data shows that the average flow rate for each
trial varies from trial to trial. In this testing period, 0 g/dL of dextran was unable to be tested and
is further elaborated on in section “7.2.2 Limitations”.
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5.3 Laser Syllectometry Results
Figure 23: Laser Syllectometry Initial Setup
Our testing of aggregation via laser syllectometry yielded interesting results. The main
notion of testing is that, for each blood sample at a different dextran concentration, there should
be an increase in the rate of change and larger difference between the maximum and minimum
values of the sampled values. These values can be seen in Table 4 below:
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Table 4: Average Testing Values
Each row of Table 4 represents the average value as a result of all tests performed at the
noted dextran concentration (g/dL of PBS) with the “Control” row referring to directly extracted
whole blood with plasma still intact. After the tests were conducted, the resulting values were
imported into an Excel spreadsheet and individually calculated for the same values as shown
above. As the input into the system was originally a 1024-ADC byte count, each byte was
converted to a voltage resolution before being processed. From the newly acquired voltage, the
minimum and maximum values were taken immediately following the start of the test until the
final recorded value, ignoring the starting values from before the sample was properly situated
within the system (these pre-test values are more clearly show in the data presented in Appendix
H). After the minimum and maximum for each of the five tests per data set were recorded, the
difference was taken between the two values. From there, the rate of change for each test was
taken using Excel’s SLOPE() function with the y-values corresponding to the voltage and the x-
values corresponding to time.
The range of initial and ending voltage values were different depending on how precisely
the laser was interacting with the blood; samples that were not aligned exactly the same as others
49
might see increased or decreased voltage values, hence why it was essential to look at the change
in voltages over the time period. When looking at the dextran solutions ranging from 0.025g/dL
to 0.05g/dL, there is a slight increase between the average min-max voltage difference (a change
of ~0.001 volts or 1 mV) and a similar change between the rates of change (~0.000025V/s or
0.025mV/s). This trend continues with each increase in dextran concentration for both the min-
max difference and rate of change. It is important to note that, while these trends increase with
each concentration, the number of tests within each dextran sample isn’t the same. This
limitation is further discussed in section “7.3.1 Limitations”.
The individual values for each test, as well as graphs displaying their rates of change, can
be seen in the Figures 24 to 29 and Table 5 to 10 below:
Table 5: Control Tests Information
Figure 24: Control Tests Rate of Change
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Table 6: 0.025g/dL Tests
Figure 25: 0.025g/dL Tests Rate of Change
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Table 7: 0.05g/10mL Tests
Figure 26: 0.05g/dL Tests Rate of Change
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Table 8: 0.1g/dL Tests
Figure 27: 0.1g/dL Tests Rate of Change
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Table 9: 0.15g/dL Tests
Figure 28: 0.15g/dL Tests Rate of Change
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Table 10: 0.2g/dL Tests
Figure 29: 0.2g/dL Tests Rate of Change
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Chapter 6: Final Design and Validation
6.1 Final Design CAD Prototype
The development of the final device design was in large part a combination of what was
initially used for testing and awareness of the problems that were faced when performing said
tests for the first time. With reference to the syllectometry test, issues with the voltage reading at
which to start recording data, the ability to watch the test in action while minimizing the amount
of excess light on the photodiode, and wiring were all present. Keeping these aspects in mind, as
well as other smaller additional features, we developed our final design shown in Figure 30
below:
Figure 30: Final Design Front (L) and Back (R)
As a comparison to the initial design, it is clear that both the width, height, and depth of
the device has been increased. That said, the device was still kept relatively small to minimize
production cost and increase portability, having a new width of 7.87 inches, height of 11 inches,
and depth of 4.72 inches. One of the most prominent new features is the attached 5-inch LCD
touchscreen display at the top of the device. Connecting directly to the Arduino, the touchscreen
allows control of the device and its parameters without the need of a computer such as modifying
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testing parameters or displaying live data during a testing period. To further this notion of a
“stand-alone device”, an additional opening has been created in the back of the device to allow
the connection of a USB drive for data storage.
On both the front and back of the device, there exists a one-way acrylic pane. This allows
the user to ensure that, during syllectometry testing, the laser is properly aligned with the blood
sample without increasing ambient light to the photodiode. This notion is further supported by a
voltage-recording threshold where data won’t be recorded until a proper starting voltage is
achieved. Additional holes have also been cut in both the top and back paneling for better wire
management.
On the side of the device sits an opening attachment to a brushless DC stepper motor.
Stepper motors allow for a high degree of modular control when it comes to angular analysis and
can be easily adjusted when attached to our main Arduino control system. This motor, when
connected to a small capillary holder, allows easy modulation in controlling the starting angle
during a capillary fill test. Furthermore, this same motor can be used in our micro-ESR testing.
By plugging the capillary tube with clay, the motor can rotate the tube to ensure it is perfectly
vertical during the recording period. Beside the stepper motor also exists a small spot for holding
an internal battery in the event the device cannot be connected to a continuous power source.
6.2 Standards
Our design incorporated many engineering, industry, and manufacturing standards. Our
team incorporated SolidWorks drafting standards when creating the stand for vibration
syllectometry testing and our final design using computer-aided design. Our team also
incorporated IEEE standards for computer and electronic equipment, such as the 1641-2010
IEEE standard for signal and test definition. Our team incorporated this standard when
performing vibration syllectometry experiments, which involved electrical signals.
However, as the team was not able to fully manufacture our final design due to time
constraints and issues regarding the pandemic, most of the other applicable standards would only
be incorporated if the design were to be manufactured and marketed in the industry. For
example, the HIPAA Privacy Rule would only be fully incorporated when patients are actually
using our device. ISO 10993-11 also would not be fully incorporated until the final design is
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manufactured and patients are using the device since it requires biocompatibility and toxicity
evaluation on the device. These evaluations cannot be conducted until the device is fabricated.
ISO 13485:2016 focuses on quality management systems of medical devices, with the goal of
continuously meeting customer and regulatory requirements, and would not be fully incorporated
until device manufacturing. ISO 11737-2:2009 also would not be fully incorporated until the
final design is manufactured and is put into use in a hospital setting since this standard involves
the sterilization of medical devices. ISO/TC 76 also would not be fully incorporated until the
final design is being used with patient blood samples since this standard is centered around blood
processing equipment.
6.3 Economics
As sepsis is a serious condition requiring a hospital stay, it can be very costly. According
to the Agency for Healthcare Research and Quality, sepsis is “the most expensive condition
treated in U.S. hospitals, costing nearly $24 billion in 2013” [1]. The lasting effects and chances
of reoccurrence of sepsis can lead to expensive re-hospitalization of patients two to three times
as frequently as other conditions (such as pneumonia or heart failure). The sooner a patient
receives treatment, the more likely they will be to recover without lasting symptoms or requiring
readmission. Since current tests can take time, patients are treated when sepsis is suspected,
while awaiting test results.
There are also issues with false positive tests, with one study finding that “a single false-
positive blood culture event results in an additional 2.4 days stay in the hospital for the patient”
[72]. This is estimated to cost the U.S. healthcare system $7.5 billion per year. The short time
required for our tests to achieve results, and the ability for them and other tests to validate one
another, can help reduce delays in treatment or extended hospital stays, providing significant
savings for patients and hospitals.
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6.4 Environmental Impact
The final design will have environmental impacts due to the materials our team has
chosen to utilize. The final design includes an LCD touchscreen display. LCD screens contain
toxic substances that could have negative effects on ecosystems if they are not disposed of
properly. Additionally, the manufacturing process of LCD screens “requires sulfur hexafluoride,
a chemical substance that is believed to be responsible for 29 percent of all global warming”
[73]. The final design also contains acrylic panels. Acrylic plastic material is not easy to recycle.
In some cases, “large pieces can be reformed into other useful objects if they have not suffered
too much stress, crazing, or cracking, but this accounts for only a very small portion of the
acrylic plastic waste” [74]. Acrylic plastic is also not easily biodegradable. Considering these
factors, the final design’s use of acrylic may have a negative impact on the environment.
However, the final design will also contain PLA, which is recyclable and biodegradable. PLA
would not have any negative impacts on the environment.
6.5 Societal Influence
As a service, being able to diagnose sepsis with any form of confidence can certainly be
beneficial to helping save the lives of millions of people and would, therefore, be an incredibly
helpful addition to the world of healthcare. While not directly revolutionizing the global market,
our device certainly can help in furthering the investigation in sepsis diagnosis, laying the
groundwork for devices of similar nature. Furthermore, the limited amount of blood needed for
testing samples ensures that the risk of increased infection remains limited in an already
immuno-compromised patient.
The effect on the individual should also not be ignored. Awaiting a diagnosis can be
stressful for patients and loved ones. Faster results lessen the time spent fearing the unknown,
and ensure proper treatment is provided to increase chances of recovery. Currently, when sepsis
is suspected, treatment is provided before testing is completed. This is due to the fast-acting
nature of sepsis, where every hour of delayed treatment may increase the odds of a poor outcome
by 3-7% [75]. Receiving faster results will prevent unnecessary treatment for non-septic patients,
allowing hospital resources to be used for other patients, positively influencing others’ outcomes
when resources are limited.
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6.6 Political Ramifications
While sepsis can affect anyone, diagnosis and treatment largely depends on one’s
socioeconomic status. A recent study from January 2020 estimated the global deaths from sepsis
to be 11 million – twice the previously-believed amount. This revised estimate accounts for new
data from areas with a lower socio-demographic index (SDI), while previous estimates were
based on hospital data from high-income countries. The burden of sepsis is higher in areas with a
lower SDI, where many cases occur outside of hospitals and are unrecorded [76]. In areas of
poverty or with limited resources, our device can help in reducing the amount of sepsis-based
fatilities and can decrease the cost and turnaround time of septic tests.
6.7 Ethical Concerns
The major goal of our product is to help give patients a good and satisfying life by
accurately diagnosing sepsis in a safe and efficient way. Diagnosing sepsis early on could save
many patient lives. Although there may be concerns regarding the ethics of our product since it is
a medical device, our team followed ethical guidelines and moral principles to make sure our
product was centered around meeting the needs of patients. Our underlying motivation was to do
what was morally right and good for patients. Another important goal was to prevent harm. Our
team made sure that our product met technical standards and safety standards so that our product
was completely safe for patient use. Our product was also designed to respect the autonomy of
patients. Patients will have the right to deny using our product. Patient data will never be
released and will always remain protected under the HIPAA Privacy Rule.
6.8 Health and Safety
One of the most important tasks of our device is to help better diagnose sepsis within a
potential patient. Through the usage of the tests incorporated into our device, we can say that
such an achievement is possible in a variety of ways. As a septic patient might already be in a
weakened state, avoiding as much additional stress as possible on a person is essential. As our
system requires a relatively small blood sample size to perform tests and has a fast turnaround
time, we can ensure that no additional harm would come to a patient during the testing period.
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6.9 Manufacturability
If the device we are designing were to be marketed, we recommend that a good way to
manufacture it would be through injection molding and/or compression molding. Injection
molding is a fast manufacturing process and when mass producing a product in this manner, the
cost per item produced is relatively low. Initially the cost of the machines and the creation of
molds for startup companies is high, but once the right investments have been made, products
can be produced at a quick rate. Compression molding is another manufacturing option which
could potentially be used. One benefit of compression molding is that tooling costs are cheap,
making it good for small production runs. Also, compression molding can produce very durable
products. However, compression molding is slow and cannot be used for intricate geometry. The
device does not need to be highly durable as it will only be required to withstand small force
loads. Therefore, the most advisable method for manufacturing would be injection molding. In
order to produce the device inexpensively but also meet the design requirements, we would
advise that the device be made of plastic. Injection molding is primarily used with plastics and
thus our device could easily be made from plastic. For the initial prototyping of our device, we
would use an additive manufacturing method such as 3D printing. 3D printing can produce the
prototype model that we need, and the cost of a 3D printer is small compared to the machinery
required for mass producing. The material we would use would be PLA (Polylactic acid-
biodegradable filament) or ABS (Acrylonitrile Butadiene Styrene). These are basic and common
3D printing materials that are low cost and would be sufficient for producing a working model of
our device. We would probably opt to use PLA for prototyping as PLA tends to be more precise
because it prints at lower temperatures making it less likely to warp. The electronic hardware
involved with our device such as the vibration syllectometry circuitry and laser diodes, the 5-
inch LCD touchscreen display, and the brushless DC stepper motor, are things that have already
been produced and thus we do not need to worry about manufacturing the electronic hardware
ourselves.
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6.10 Sustainability
A great benefit of making our device primarily out of PLA is that PLA, which is a plastic,
is easily recyclable, so our product could be made at least in part from recycled material. Another
benefit of making our device primarily out of PLA is that it is biodegradable, so it is safe for the
environment. The energy costs associated with our device are very low. For one, the tests that
require electrical power can be performed relatively quickly. Secondly, the power usage required
during that time is negligible. Therefore, it is unlikely that any piece of electrical machinery will
burn out within a short period of time.
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Chapter 7: Discussion/Future
7.1 Micro-ESR
7.1.1 Implications
The micro-ESR data shows a strong positive correlation between an increase in the
amount of dextran and an increase in plasma height. Plasma height is representative of the
amount of space where fluid is present, but blood cells are not. Therefore, the higher the plasma
height the higher the aggregation. As a result of these tests, it can be concluded that an increase
in dextran increases aggregation of the red blood cells and that the micro-ESR test is capable of
recognizing this increased aggregation. For this reason, it is believed that micro-ESR is a
beneficial method in determining aggregation rate for the potential diagnosis of sepsis.
7.1.2 Limitations
Errors and limitations in the micro-ESR testing could be results from bubbles within the
dextran-blood sample, the placement of the capillary tubes within the clay stand, tools used to
measure the plasma height, the amount of time and labor it took for each test, and lastly, the
limited number of tests conducted. As the same tubes and samples used in the capillary fill test
were used for the micro-ESR tests, the movement during filling caused some of the samples to
include air bubbles. These air bubbles cause sections of the entire blood sample to aggregate
separately. If the dextran were unevenly split between sections, this could have caused more
aggregation in one section than the other.
After the capillary tubes were filled, they were pushed into a stand containing clay that
would seal the bottom of the capillary tube. During placement into the clay, the capillary tubes
were not always completely vertical. This angle could have caused the blood to aggregate at an
angle that would not be reflected during measurements. The entire test itself took four hours with
an individual taking images of the capillary tubes every thirty minutes. This always required
someone to be present in the lab and to keep track of multiple timers at once. The juggling of
trials and long hours is not ideal for someone who wants to run many trials at
once. Furthermore, as we used a phone camera for all our image collection, the resolution was
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not extremely high. This made it difficult to differentiate the top of the plasma and the start of
the aggregated blood from reflections and shadows in the capillary tube. Similar to the capillary
fill experiments, all measurements were made using ImageJ. As image length measurements
were made manually, human error in choosing locations to start and stop
measurements introduces a new area for error to be introduced. Lastly, although most results
supported the trend that an increase in dextran amount increased aggregation, the 0.10 g/dL
dextran test did not follow this trend. This anomaly could be due to any of the errors mentioned
before or could be due to not properly mixing the dextran-blood sample before use. Lastly, as
there were only three trials for all six tested dextran amounts (except for 0g/dL of dextran which
only had two) there is a limited sample size to statistically determine the accuracy of this test.
7.1.3 Future
For the future, further testing and refinement of the tests should be completed to ensure
the results of this study are reproducible. To decrease the inconsistencies between tests, the
capillary tubes should be filled in a way that ensures little to no air bubbles get caught in the
samples. This will allow for even aggregation throughout tube and more accurate measurements
of aggregation. After using the clay stand to plug the end of the capillary tubes, the capillary tube
should be placed on a stand that will ensure that the tube is held completely vertical for the
duration of the experiment. This will make the blood aggregation flat within the tube which will
allow for accurate measurements. Additionally, the camera used for tracking the height of
plasma should have a resolution high enough to allow for minute detail changes within the tube
to be tracked which will also allow for more accurate measurements. To reduce the amount of
required labor time, either the dimension of the capillary tubes could be changed, or the
collection periods could be changed. To change the collection period to every hour instead of
every 30 minutes would allow fewer required hours in the lab. Otherwise, instead of frequent
imaging, a time-lapse video recording of the capillary tube could be taken over the four hours. A
software could then be used to autonomously track the aggregation of red blood cells within the
tube. This would allow for more data points per trial and significantly reduce labor time. The
inner diameter of the capillary tube could also be changed to require a smaller amount of blood
and or to reduce the amount of blood in contact with the wall which reduces forces against
aggregation. This would also decrease the amount of labor time required. Lastly, more tests
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should be conducted. Currently, there are only three trials for each dextran-blood solution. By
increasing the number of trials, this will increase the statistical significance of results and ensure
the reliability of the findings.
7.2 Capillary Fill
7.2.1 Implications
The capillary fill tests had little to no correlation between the amount of dextran and the
flow rate time. The results were inconclusive as there were increases and decreases between the
flow rates as the amount of dextran increased. As an increase in the concentration of dextran in
the blood increases aggregation of the red blood cells, it can be concluded that there is no
relationship between aggregation and flow rate within our current setup. Therefore, it is
recommended that further analysis into the angles involved in the capillary fill test be conducted
using the final design prototype to determine the viability of this method in terms of RBC
aggregation.
7.2.2 Limitations
As previously explained, the capillary fill tests cannot be applied to the final design as the
results could not provide any correlation between aggregation and flow rate. This inability to
find a correlation could be a result of inconsistencies due to the materials used, human error, and
the limited number of tests conducted. For our tests, we intended to mechanically set the angle
each tube was held at. The angle for testing was intended to be positive. But in preliminary tests,
it was found that to keep the angle consistent between all tests, the angle had to be negative to
allow for capillary flow. To create this negative testing angle, the capillary tube was held by
hand between two stands. This did allow for an angle that was generally consistent, but variation
was still present that could have been minimized with a mechanical device. This also introduced
increased movement of the capillary tube as it was held by a human. This movement could have
disrupted flow, changing the results of the study. The capillary tubes could have also had
variation in their hydrophilic properties. Although each tube was sterilized, manufacturing of
each tube could have been inconsistent in the coatings. Thus, different capillary tubes could have
had different hydrophilic properties which would have helped or hindered capillary flow of the
blood in the tube.
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Placing the blood on a latex glove for a hydrophobic surface was also not ideal. The
latex glove was originally hydrophobic, though it still has some pores. But after repeated use, the
hydrophobicity of the gloves decreased, causing the contact angle of the blood droplet to
decrease between tests. During some tests, bubbles were present in the blood that disrupted flow.
For some other tests, the capillary tube had to be placed into the blood droplet multiple times
before flow could be generated. In relation to the specific dextran tests, the 0 g/dL tests were
unable to be conducted and, due to large differences in angles, only two tests, out of three, could
be analyzed for 0.2g/dL and 0.1g/dL concentrations.
Lastly, there were only three trials for each tested dextran solution which is not a large
enough study to provide statistically significant results. The measuring of each test was done by
measuring the travelled distance of the blood in capillary tubes in four frames from the recorded
video. The video of the trial’s resolution was too low to see minute changes thereby making the
measuring of the blood’s location difficult. As the measuring was done using ImageJ, each line
was drawn by a person. As people are not precise with any consistency, the exact measuring of
the blood location was a variable to consider. These inconsistencies, and limited trials in testing
the dextran-blood solutions, were mainly due to the shortened testing times resulting from the
shutting of the lab because of the COVID-19 pandemic. Without this interruption, many changes
to our testing protocol would have been made to improve reliability of the study.
7.2.3 Future
For future testing of the relationship between capillary fill and aggregation, many
changes would be made to the materials and automation of testing would have been used. To
address the inconsistent angle and location of the capillary tube, a mechanical stand could be
built to introduce the capillary tube to the blood droplet at a set angle and then hold the capillary
tube still for the entirety of the trial, similar to what is present in the final device prototype. This
would eliminate the effect of movement of the capillary tube on the flow rate of the blood and
ensure no air bubbles would be introduced to the samples. The tube itself could also be plasma
cleaned to create consistent surfaces between capillary tubes. This would have ensured that the
blood stuck to the tube to relatively the same degree between each test providing the same
potential for each blood sample to flow. To increase hydrophobicity and consistency of the
surface that the blood is placed on, a glass slide coated with Acryl-Glide or a similar agent that
66
creates a hydrophobic surface should also be used. Using this glass slide would ensure a flat
surface for every test. The coating would also induce a consistent contact angle for the blood
samples; by having a consistent contact angle, the pressure difference within the capillary tube
would be the same for every test.
The measuring of the capillary fill should also be automated. This could be done by using
a higher resolution camera, allowing for clearer pictures to be analyzed, and in conjunction with
a software that could track the location of the blood in the tube throughout the video. This would
also significantly reduce the amount of time to analyze each trial within each dextran-blood
solution test. Therefore, more tests could be conducted and analyzed in a shorter amount of
time. This would also reduce variation between test operators and allow the test to be conducted
with less operator influence. In the future, the testing should encompass all the dextran-blood
solutions. By including the 0 g/dL dextran-blood solution, there would be more comparable data.
This would allow for any anomalies or trends to be spotted. Lastly, every dextran-blood solution
should include more than three trials. A larger sample size would create statistically significant
results. With these more accurate and precise tools, the inconsistencies between tests could be
significantly decreased. With this new set of data, the usefulness of capillary fill in determining
increased aggregation would be re-evaluated.
7.3 Syllectometry
7.3.1 Implications
The main focus of the laser syllectometry test was to develop a way of measuring blood
aggregation via an experimental and unconventional method of RBC disaggregation and use of
light scattering. The notion present was that, if blood aggregation was occurring at a faster rate,
you would see the intensity of transmitted light increase at a faster rate and therefore a higher
voltage climb would be recorded. Being that the resolution for capturing data was relatively low
and, initially, very sensitive to outside light sources, the average min-max difference as well as
the rate of change of volts over time was key for our analysis.
67
Referring back to Table 4 (which summarized the syllectometry results and can be found
on pg. 48), it can clearly be seen that increasing the concentration of the dextran solution leads to
an increase in the min-max voltage difference and in the rate of change. As dextran has been
found to increase RBC aggregation, when the concentration of dextran increases, an expected
increase in aggregation should also be present. If aggregation is occurring at a faster rate, an
increase in rouleaux should also be expected, causing less light to be scattered through the
sample and more directly hitting the photodiode. Therefore, based on the data present in Table
11, we can say that laser syllectometry is a valid method for testing blood aggregation.
It is important to note that, while informative, the “control” row isn’t accurately involved
with the data present in the 0.025g/dL tests to the 0.2g/dL. Ideally, this data was meant to serve
as a basis for confirmed septic blood; this will be further discussed in “7.3.2 Limitations” and
“7.3.3 Future”.
7.3.2 Limitations
One of the largest limitations on the syllectometry tests, as with many of the other tests,
was the inability to be present in the lab during the entirety of D-term due to the COVID-19
global pandemic. Given that lab time was hindered during the final term, limited testing data was
recorded; this can be seen in Appendix H for all the test data, noting how some tested dextran
concentrations have one- or two-sample tests. Another hindrance, in relation to the pandemic,
was the inability to re-test data using the improved device design. Some of the flaws recognized
within the design were corrected – as mentioned in section “6.1 Final Design CAD Prototype” –
and would therefore allow for more precision with the produced results. An improved blackout
system, threshold voltage control, and resolution adjustments would have made for significantly
more stable outcomes with each dextran solution. Unfortunately, this could not be achieved and
would certainly be a recommended point of continuation if possible.
Finally, in relation to the syllectometry test itself, while the data present does show an
increase in blood aggregation as reflected by a change in voltage over time, it doesn’t speak to
any certainty on whether a patient absolutely has sepsis. The blood sample used has the potential
to display a variety of other conditions that a patient might be dealing with besides sepsis. This
68
test is meant to work in conjunction with the other tested methods to help improve the accuracy
of a sepsis diagnosis and is therefore not recommended as a standalone test for diagnosis.
7.3.3 Future
When conducting additional tests using laser syllectometry, there are a few instances that
the team would like to test. For one, the inability for the team to acquire valid samples of septic
blood was a major hindrance and is what resorted to the use of dextran solutions. Being able to
use clinically certified septic blood in conjunction with that received from AllCells would allow
the team to speak with more certainty regarding the success of the laser syllectometry test.
Furthermore, if testing were to continue, it would be ideal to use the updated device design for
both increased precision and control of testing parameters, leading to fewer variables present in
the data.
69
7.4 Device Discussion
As mentioned in chapter 4, a few of the tests carried out did not require extensive
fabrication of a device or system. However, the final device design provides a platform to help
carry out the tests in a more controlled fashion. For instance, the final design allows us to hold
capillary tubes at desirable angles with increased precision than what someone would be able to
perform manually. Furthermore, the increased parameters regarding the syllectometry test allow
more control over the data being recorded. There are, however, some limitations to the amount of
control the device has on certain things. One such limitation is that the device is subject to
whatever external conditions are present within the testing environment. These include, but are
not limited to, temperature, moisture, ambient light, and vibrations. Therefore, it is recommended
that tests be conducted using the device in a controlled laboratory setting to minimize extraneous
effects during the testing periods. Another limitation to the device is that it doesn’t have any
features that guarantee keeping a person sterile from the blood they are working on. When
conducting tests with our device, users would need to take the necessary precautions to make
sure they are working safely with a blood sample. These precautions include wearing gloves and
cleaning surfaces that may need to be cleaned. The single-use disposable nature of the glass
slides and capillary tubes do help to reduce the cleaning required between tests, allowing for a
faster testing turnabout than a device that needs a deep cleaning with each use.
70
Chapter 8: Conclusions and Recommendations
8.1 Conclusions
Sepsis is a life-threatening condition that kills millions each year. Many physicians
consider diagnosis the most difficult aspect of sepsis, as due to its wide range of symptoms with
high variability, there exists no conclusive test for the disease. Existing tests face the issues of
low sensitivity and specificity, slow turnaround times, and uncertain results. Physicians must
therefore rely on experience and a range of tests and symptoms when attempting to diagnose a
patient. Backed by extensive literature review, the team investigated the possibility of measuring
erythrocyte aggregation as a sepsis diagnosis tool.
Of the three aggregation measurement methods tested, micro-ESR and laser
syllectometry were capable of differentiating levels of aggregation among blood samples
containing various concentrations of dextran in PBS with a degree of confidence. The final
design focused on building around laser syllectometry (as it was the most complex in terms of
tools and equipment) while also featuring an attachment that would assist in further testing the
methods of micro-ESR and capillary fill with greater precision. Therefore, using at least two of
the three proposed testing methods, the final device design creates a system that allows for the
possible diagnosis of sepsis via red blood cell aggregation.
8.2 Recommendations
The team was successful in identifying two methods capable of measuring blood
aggregation, but these results could be further improved through recommended adjustments to
the experimental procedures and direct validation with septic blood.
For the capillary fill tests, further testing had been planned using plasma-treated capillary
tubes and drops of blood placed on glass slides coated in Acryl-Glide, a hydrophobic substance.
These were expected to increase blood adhesion to the capillary tubes and drive capillary action
more strongly, possibly allowing measurements to be made at a positive angle. This would allow
for existing theory to quantitatively describe blood flow, and better differentiate the effects of
71
capillary action from gravity. This may lead to a correlation between RBC aggregation and flow
rate whereas none was observed in the current tests.
The final design contained improvements to all three tests, allowing more accurate and
precise control of capillary tube angles for the micro-ESR and capillary fill tests and
improvements on laser alignment for the syllectometry test. The team was unable to fabricate
and validate this design to assess its functionality or use it to conduct further trials. This,
combined with the limited number of tests that could be performed, leads to our recommendation
that further testing be conducted to validate the ability of each test to measure RBC aggregation
using the newly created final design.
Finally, the team recommends validation of these tests with septic blood. The team could
not obtain septic blood for testing within a reasonable time period and instead induced
aggregation using dextran. Ideally, tests would be conducted with septic and non-septic blood
samples from a variety of people, including those with non-septic inflammatory conditions, to
determine the specificity and sensitivity of our tests.
72
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Appendix A – Interviews
Dr. Kate Madden, MD, MMSc Associate in Critical Care Medicine Boston
Children’s Hospital and Instructor in Anesthesia, Harvard Medical School What is your experience with sepsis or SIRS-related illnesses in?
As an attending physician in a pediatric intensive care unit (PICU), I care for many
patients with suspected or proven sepsis. I have also been involved in some multicenter
initiatives to increase consistency of response to suspected sepsis in terms of the actions of
doctors and nurses. Through these collaborative, we have instituted tools to help doctors and
nurses identify sepsis, communicate about the plan for care, and make informed decisions about
the management of suspected sepsis.
What has your work revolved around?
Mostly covered above. PICU and hospital-wide education about sepsis and need for
timely care, development of tools to help nurses and doctors identify sepsis and communicate
about the plan.
Can you please explain what are how sepsis is currently diagnosed in the hospital? What steps
are involved? And who makes the final call?
Sepsis is a set of clinical signs, and not truly a diagnosis per se. We have many patients in
whom we may suspect sepsis, but a large proportion do not end up having a clear diagnosis.
Only a small proportion have a bacteria or virus grow from a lab test that confirms the diagnosis.
For research and quality improvement purposes, we use the judgement of the clinical team,
usually the attending physician, as well as the specific treatments that go along with sepsis.
Who performs these steps? What qualifications are required?
Not sure if above answers this? What steps specifically?
How successful are these current protocols in diagnosing sepsis?
It depends how you define success. We currently want to screen a large number
of patients for a few that might really have sepsis, as we know it is a very morbid condition and
we don’t want to miss any patients. As a result, we screen many patients who do not really have
sepsis, just fever and maybe one other SIRS criteria, but in the end will not develop severe sepsis
or septic shock.
What are the challenges with these current hospital protocols?
As with any large hospital initiatives – getting engagement from all different disciplines
involved, changing culture, the burden of documentation on nursing especially, communication
challenges.
What are the limitations when working with patients when diagnosing sepsis? How do infants
differ from adults (if any)?
Not sure exactly what this refers to? Infants are certainly much more difficult to assess in
terms of mental status, focal symptoms, etc. We tend to screen very broadly for all infants who
might have sepsis, because it can be quite easy to miss in young infants.
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What is the largest challenge when diagnosing sepsis in a hospital setting?
Many challenges, but probably the biggest is distinguishing fever and tachycardia (very
common) from true sepsis that might progress to severe sepsis or septic shock.
What would you like to see in future sepsis diagnostic tools?
More objective tools to diagnose sepsis at the bedside – measures of oxygen delivery to
the tissues, organ function, and rapid microbiologic diagnostics. In pediatrics, we have a lot of
challenges assessing mental status and thus brain perfusion, especially in young patients, so
some bedside objective measure would be very helpful. Folks are working on bedside tools to
evaluate for response from fluid resuscitation, including ultrasound tools, which could be helpful
as we see the side effects of excessive fluid resuscitation in these patients as well. Knowing
specific microbiological data would help tailor therapy and anticipate outcomes.
How would patient care be changed with faster diagnostic methods?
More accurate and timely management.
Dr. Jouha Min, PHD, Postdoctoral Fellow in Center for Systems Biology at
Mass General Hospital What is your experience with sepsis or SIRS-related illnesses?
Sepsis is an often-fatal condition that arises when the body launches an overwhelming immune
response to an infection that causes more damage to the body than the infection itself. A critical
unmet need in combating sepsis is the lack of accurate early biomarkers that can alert clinicians
to this potential life-threatening situation and allow them to take preventative action.
Why did you choose to research sepsis?
When I joined the Center for Systems Biology at MGH, I learned about the IL-3 work
that just got published by another PI at the Center, Dr. Filip Swirski, and I as an engineer thought
that it would be a straightforward project to design and develop a point-of-care device to
measure IL-3 levels in the patient’s blood to “predict” sepsis.
How did you choose what biomarker to use in your diagnostic method?
Did you consider IL-6,8 or 10? Or Procalcitonin?
The IBS (integrated biosensor for sepsis) prototype measures levels of a protein called cytokine
interleukin-3 (IL-3) in the blood. We (our collaborator at the center) have IL-3 as an independent
predictor of septic shock and death being produced by innate response activator (IRA) B cells
following TLR activation. IL-3 operates upstream of key cytokines including TNFα, IL-1β and
IL-6; high IL-3 level and can trigger a detrimental cytokine storm. Measuring IL-3 thus can give
an early window to monitor immune responses through minimally invasive blood testing.
Why did you choose Interleukin-3 as your diagnostic method?
Refer to my answer to Question #3.
Where did you get your ideas for your Interleukin-3 device?
How it works: Simply put, the platform uses magnetic beads to directly and quickly
extract target protein IL-3 from blood samples. The beads are adorned with antibodies and
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electron mediators, and through a series of reactions, generate an electrical current which
provides an analytical readout of IL-3 levels.
Why magnetic beads approach: We advanced a portable biosensor consisting of a
disposable kit for blood processing and an electrical detection system. The kit is used to capture
IL-3 on magnetic beads and label it for electrochemical reaction; the detector then measures
electrical currents for IL-3 quantification. This strategy has practical advantages: i) target protein
(IL-3) can be enriched directly from blood; ii) the assay achieves high detection sensitivity
through magnetic enrichment and enzymatic signal amplification; iii) based on the electrical
measurements, the sensor can be easily miniaturized and easy-to-use.
What skills sets are required to use your device and who was the intended user?
It was originally intended to be used by doctors and/or nurse practitioners in the
emergency room or intensive care unit. But with further improvement (i.e., full automation), any
technician (or even a caregiver) would be able to use it.
Would you consider combining different methods (such as Procalcitonin and IL-3)?
Yes, our next generation device will be able to measure multiple markers (e.g., IL-3,
TNFα, IL-1β, PCT, IL-6) for even more robust characterization of host response, further
improving diagnostic accuracy.
What do you feel are aspects of sepsis that get overlooked?
Medical doctors, scientists, and engineers are working their best to overcome the unmet
needs in combating sepsis. But its such complex pathophysiology of systemic nature hampers us
from inventing new ways to diagnose and/or treat. Long story short, we need a better scientific
understanding of sepsis (i.e., mechanisms/pathways, new biomarkers).
How did you decide what needs were to be fulfilled by your project?
Based on discussions with some doctors specializing infectious diseases as well as
literature research, it was so evident what the unmet need is for sepsis.
What is the goal for sepsis diagnostics in the future?
The immediate need for sepsis diagnostics is to develop a reliable clinical tool that could
be readily integrated into clinical workflows, enabling timely diagnosis and proactive treatment
of sepsis.
Dr. Michael Puskarich, MD, Associate Professor, University of Minnesota What is your experience with sepsis or SIRS-related illnesses?
Clinically I am an emergency physician, so I see these patients regularly and have
to differentiate patients with sepsis from those with non-infectious etiologies on every one of my
shifts. This has become an increasingly important problem not only for patient care, but also
with the advent of the CMS Sepsis Core measure. I have been intimately involved in
developing internal EMR-based screening and recognition tools for sepsis which are terribly un-
specific. I have also published extensively on the relationship between SIRS, sepsis, and various
consensus definitions of the disease. I have also been involved in many sepsis trials that use
these criteria for inclusion in the study.
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What has your work revolved around?
I am most interested in the role of metabolism in sepsis as a therapeutic target, related to my
work describing the prognostic value of lactate. With this, as well as clinical trial work in the
field in general, I have observed (along with many in the field) that the clinical consensus
definitions suffer from poor specificity and variable sensitivity for the disease. The clinical
presentation of
sepsis differs from animal models leading to failure to translate animal results to improvements
in human health. Part of my work is involved in finding ways to disambiguate early sepsis
presentations from non-infectious etiologies, so as to only select patients most likely to benefit
from a therapy prior to enrollment in a clinical trial.
What are the current methods utilized to diagnose sepsis? Is it successful?
Clinically SIRS, "sepsis-3", procalcitonin occasionally have all been tried and they are
not consistently successful. These tools are primarily ways for clinicians to make sure they are
"getting the points" for treatment of sepsis patients and meeting CMS core measure success,
but suffers from terrible usability. For true patient care, good clinicians rely on gestalt and
experience combined with overall lab and diagnostic test results to diagnose sepsis more than
any single tool, which in and of itself is also problematic due to the highly variable nature and
clinical presentation of the disease. Sepsis is also confusing because it exists on a spectrum - it's
not a "yes / no" despite many people wanting it to be. You don't go from routine flu to "sepsis,"
it exists on a spectrum with other infectious diseases that the body does or does not control on its
own.
Who carries out these sepsis diagnostic tests? What skills sets are required?
Generally, the used tools are based on vital signs and laboratory tests, including white
blood cell count, measure of organ failure (creatinine, bilirubin, platelets), mental status, lactate
as an indicator of disease severity, and others. An astute clinician is needed for excellent
diagnostic acumen. Sometimes labs and vitals outperform the clinician, sometimes vice versa.
Set standardized criteria almost always suffer from a severe over sensitivity and poor specificity.
The consequence of this if applied too broadly is that by diagnosing patients without sepsis with
sepsis ("just to be safe"), it diverts attention and resources of the doctor towards these patients
who do not necessarily have sepsis and diverts it from other sick patients being cared for
simultaneously by the doctor. In the emergency department, we frequently managed 10-20
patients simultaneously, so poor specificity tests have a real cost to OTHER patients in the
department that is not considered in sepsis care mandates. Meanwhile, poor sensitivity tests lead
to potentially missing patients that can have consequences that include death, as we know sepsis
is a time sensitive disease process.
What is the goal for sepsis diagnostics in the future?
Tests with an excellent balance of both sensitivity and specificity to know who time sensitive
treatment must be delivered to ASAP. Alternatively, diagnostic tests that reliably determine
the causative organism and / or pathophysiologic process that predominates in the patient at any
given time could lead to tailored / personalized therapies.
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What is the largest issue when diagnosing sepsis in a hospital setting? What are the biggest
challenges with the current hospital methods?
See above.
What symptoms prompt initial sepsis testing?
Fever (or hypothermia) with hypotension is the most obvious. Fever with other signs of
hemodynamic instability (tachycardia, high respiratory rate, high or low white blood cell count)
can increase clinical suspicion, particularly if it persists after giving IV fluids. In elderly patients
and immunosuppressed patients there is not always a fever, and malaise or fatigue can be the
first symptoms. Some patients have respiratory distress without fever. Most patients with a
fever, however, do not have sepsis. In general, sepsis is considered in patients having: a) a fever,
b) hypothermia, c) hemodynamic instability, and d) vague symptoms in an elderly
or immunocompromised patient. Unfortunately, this means 1/4 to 1/3 of all patients in the
emergency department (nearly 100 patients per day in my ED) received at least a superficial
consideration of sepsis, while 95% of these likely will not have it.
What would you like to see in a sepsis diagnostic tool? What functions would be useful? Are
there any variables that need to be considered when creating such as tool such as time or
resources?
1. specificity
2. sensitivity
3. rapid (has to have results in 15-30 minutes at longest). A point of care bedside device would
be ideal but not necessary
4. likely blood based
5. simplicity - need to be able to be run by a routine laboratory technician or nurse with minimal
training.
6. ease of interpretation - generally a yes / no, or yes / maybe / no answer will be required to
ensure clinical uptake by clinicians. This is a sticking point, as I had mentioned previously,
sepsis is not a yes / no disease. However, a "go/no go" answer will be required for broad uptake
by clinicians downstream.
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Appendix B – Pros and Cons of Different Testing
Methods
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Appendix C – Pairwise Analysis
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Appendix D – Lab Gantt Chart
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Appendix E – Micro-ESR Data and Analysis
0 g/dL
Trial 1
Trial 2
Average Results
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0.025 g/dL
Trial 1
Trial 2
Trial 3
Average Results
0.05 g/dL
90
Trial 1
Trial 2
Trial 3
Average Results
0.10 g/dL
Trial 1
91
Trial 2
Trial 3
Average Results
0.15 g/dL
Trial 1
92
Trial 2
Trial 3
Average Results
0.20 g/dL
Trial 1
93
Trial 2
Trial 3
Average Results
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Appendix F – Capillary Fill Data and Analysis
0.025 g/dL
Trial 1
Trial 2
Trial 3
Average Results
95
0.05 g/dL
Trial 1
Trial 2
Trial 3
Average Results
96
0.10 g/dL
Trial 1
Trial 2
Average Results
97
0.15 g/dL
Trial 1
Trial 2
Trial 3
Average Results
98
0.20 g/dL
Trial 1
Trial 2
Average Results
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Appendix G – Laser Syllectometry Data and Analysis
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Control Values
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102
103
0.025 g/dL Values
104
105
106
0.05 g/dL Values
107
108
109
0.10 g/dL Values
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0.15 g/dL Values
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0.20 g/dL Values