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Determining the Risk Factors for General Anesthesia Usage for Cesarean Section
Evanie AngladeSUMR ScholarUniversity of Pennsylvania, 2019
Benjamin Cobb, MDMentorHospital of the University of Pennsylvania Obstetric Anesthesia Fellow
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Outline• Background• Project Overview• My Role
o Methodso Results
• My Learning Experience
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Cesarean Section (CS)• Abdominal surgery to deliver a baby• 32% of deliveries in U.S. are by CS
o CS is most common non-diagnostic surgical procedure in the country1
• CS may be required for several reasons • Due to advancements in surgical technique,
women can request to have CS
1. Medline Plus. "Cesarean Section." Medline Plus. Last modified July 20, 2017. Accessed August 9, 2017. https://medlineplus.gov/cesareansection.html.
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Anesthesia Type for CS• Neuraxial anesthesia CS (NACS) à state of
consciousnesso Spinalso Epidurals
• General anesthesia CS (GACS) à state of unconsciousnesso Asleep with a breathing tube and ventilator
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Neuraxial vs. GeneralNeuraxial Anesthesia General Anesthesia
PROS
CONS
• Failed intubation2
• Aspiration of stomach contents during intubation2
• Intraoperative awareness2
• Respiratory problems2
• Greater maternal blood loss2
• Administered more quickly2• Lower incidence rate of GA complications2
• Lower rate of analgesictransfer to breast milk3
• Less need for opioids4
• Being awake for delivery
• Hypotension2
• Severe postdural headaches2
• Longer to administer2
• Uncomfortable for patients already in pain
2. Afolabi, Bosede B., and Foluso EA Lesi. "Regional versus general anaesthesia for caesarean section." The Cochrane Library (2012).3. Sumikura, Hiroyiki, Hidetomo Niwa, Masaki Sato, Tatsuo Nakamoto, Takashi Asai, and Satoshi Hagihira. "Rethinking general anesthesia for cesarean section." Journal of anesthesia 30, no. 2 (2016): 268-273.4. Dahl, Jørgen B., Inge S. Jeppesen, Henrik Jørgensen, Jørn Wetterslev, and Steen Møiniche. "Intraoperative and Postoperative Analgesic Efficacy and Adverse Effects of Intrathecal Opioids in Patients Undergoing Cesarean Section with Spinal Anesthesia A Qualitative and Quantitative Systematic Review of Randomized Controlled Trials." Anesthesiology: The Journal of the American Society of Anesthesiologists 91, no. 6 (1999): 1919-1919.
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Neuraxial vs. GeneralNeuraxial Anesthesia General Anesthesia
PROS
CONS
• Failed intubation2
• Aspiration of stomach contents during intubation2
• Intraoperative awareness2
• Respiratory problems2
• Greater maternal blood loss2
• Administered more quickly2• Lower incidence rate of GA complications2
• Lower rate of analgesictransfer to breast milk3
• Less need for opioids4
• Being awake for delivery
• Hypotension2
• Severe postdural headaches2
• Longer to administer2
• Uncomfortable for patients already in pain
2. Afolabi, Bosede B., and Foluso EA Lesi. "Regional versus general anaesthesia for caesarean section." The Cochrane Library (2012).3. Sumikura, Hiroyiki, Hidetomo Niwa, Masaki Sato, Tatsuo Nakamoto, Takashi Asai, and Satoshi Hagihira. "Rethinking general anesthesia for cesarean section." Journal of anesthesia 30, no. 2 (2016): 268-273.4. Dahl, Jørgen B., Inge S. Jeppesen, Henrik Jørgensen, Jørn Wetterslev, and Steen Møiniche. "Intraoperative and Postoperative Analgesic Efficacy and Adverse Effects of Intrathecal Opioids in Patients Undergoing Cesarean Section with Spinal Anesthesia A Qualitative and Quantitative Systematic Review of Randomized Controlled Trials." Anesthesiology: The Journal of the American Society of Anesthesiologists 91, no. 6 (1999): 1919-1919.
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Systematic Review• Identify factors associated with the use of GACS• PubMed, MEDLINE, Scopus, Web of Science, and
Ovid Embase databases• 14 studies from 9 countries between 1998-2015• Emergency CS, maternal demographics, and
maternal comorbidities
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GACS Indications/Associations
Indications• Emergent cases• Neuraxial
contraindications• Failed neuraxial
anesthesia• Maternal request
Associations• BMI < 40• Age > 35• Non-obstetric
anesthesiologists• Perceived lack of
time to give epidural
• VAS > 3 during labor
• Black race• Hispanic ethnicity
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GACS Indications/Associations
Indications• Emergent cases• Neuraxial
contraindications• Failed neuraxial
anesthesia• Maternal request
Associations• BMI < 40• Age > 35• Non-obstetric
anesthesiologists• Perceived lack of
time to give epidural
• VAS > 3 during labor
• Black race• Hispanic ethnicity
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Project Overview• Question: What factors affect clinicians’ decisions
about obstetric anesthesia care?
• Goal: To determine the risk factors of GACS and better understand clinician decision-making to ultimately, mitigate the use of GACS
• Mixed methods studyo Quantitative: retrospective cohort studyo Qualitative: surveys and interviews
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Significance• Large, young population of people affected
o Childbirth is the most common reason for hospital admission in the US5
• Disparities in careo 6% of CS in U.S. are managed with general anesthesia6
o 9% of CS at HUP are managed with general anesthesia
5. Lange, Elizabeth MS, Suman Rao, and Paloma Toledo. "Racial and ethnic disparities in obstetric anesthesia." In Seminars in Perinatology. WB Saunders, 2017.6. Juang, Jeremy, Rodney A. Gabriel, Richard P. Dutton, Arvind Palanisamy, and Richard D. Urman. "Choice of Anesthesia for Cesarean Delivery: An Analysis of the National Anesthesia Clinical Outcomes Registry." Anesthesia & Analgesia 124, no. 6 (2017): 1914-1917.
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Specific Aims1. Build two parallel databases (local and national) to
elucidate variability relating to obstetric anesthesia care.
1. Using multivariable regression and the databases created in SA1, identify the patient-, provider-, and system-level risk factors for GACS.
1. Using qualitative methods, develop theory about clinician decision-making in obstetric anesthesia care.
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HypothesesPatient-level
1. Demographics, obesity/BMI, parity, and intrapartum disorders are associated with GACS.
2. GACS rate is higher for CS during night and weekend shifts.
Provider-level1. Obstetric anesthesiologists perform less GACS compared to non-
obstetric anesthesiologists.2. The rate of GACS is lower for patients admitted to Family
Medicine service compared to Obstetrics service.
System-level1. The greater the distance between labor room and operating
room, the lower GACS rate is.
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Study Design
Phase 1Variability in
CareIdentification
Phase 2Clinician Decision-
Making Theory Development
Phase 3Patient-Related
OutcomesIdentification
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Conceptual ModelAttributes Process
OutcomePatientOutcome
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Conceptual ModelAttributes Process
OutcomePatientOutcome
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Penn Obstetric Database• 3 Data Sources
1. Centricity Perinatal & Epic Perinatal2. Inpatient medical records3. Anesthesia Preoperative Forms
• Includes CS in the HUP L&D unit from July 2013 to June 2017
• 4,034 CS• > 40 variables
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Variables of Interest in PODPatient-level
characteristicsProvider-level characteristics
System-level characteristics
• Age• Race/ethnicity• ZIP code• Marital status• Smoking status• Prenatal care
service• Parity• Intrapartum
disorders
• Day, month, and time of delivery
• Obstetric anes vs. non-obstetric anes
• Gender of anes• MFM ob vs. non-
MFM ob
• On-call (night and weekend)assignment of physicians
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POD Race Breakdown
4220
2,603
42 51 79 172 6 62
804
0
500
1000
1500
2000
2500
3000
Num
bero
fPatients
Race/Ethnicity
HUPLaborandDeliveryPatientPopulation
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American Asian Black EastIndian
Hispanic/Black
Hispanic/White Other Pacific Unknown White Total
GACS 0 15 277 2 8 6 11 0 5 45 369NACS 4 205 2,326 40 43 73 161 6 57 759 3,674
80%
82%
84%
86%
88%
90%
92%
94%
96%
98%
100%
Percen
tageofG
ACSan
dNAC
S
Race/Ethnicity
Race/EthnicityforAnesthesiaType
GACS
NACS
Pr =0.001
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75%
80%
85%
90%
95%
100%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Percen
tageofG
ACSan
dNAC
S
HourofDelivery
HourofDeliverybyAnesthesiaType
GACS
NACS
Pr =0.006
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My Role
Phase 1Variability in
CareIdentification
Phase 2Clinician Decision-
Making Theory Development
Phase 3Patient-Related
OutcomesIdentification
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My Role: Specific Aims1. Use the Penn Obstetric Database (POD) and
multivariable regression analysis to identify patient-level risk factors for GACS.
1. Learn about the challenges in defining variables to understand the effects of risk factors.
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My Variable of Interest in PODPatient-level
characteristicsProvider-level characteristics
System-level characteristics
• Age• Race/ethnicity• ZIP code• Marital status• Smoking status• Prenatal care
service• Parity• Intrapartum
disorders
• Day, month, and time of delivery
• Obstetric anes vs. non-obstetric anes
• Gender of anes• MFM ob vs. non-
MFM ob
• On-call (night and weekend)assignment of physicians
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My Variable of Interest in PODPatient-level
characteristicsProvider-level characteristics
System-level characteristics
• Age• Race/ethnicity• ZIP code• Marital status• Smoking status• Prenatal care
service• Parity• Intrapartum
disorders
• Day, month, and time of delivery
• Obstetric anes vs. non-obstetric anes
• Gender of anes• MFM ob vs. non-
MFM ob
• On-call (night and weekend)assignment of physicians
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ZIP Code Variable• Proxy for household income• Hypothesis: Lower household incomes are
associated with GACS.
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My Role: Methods• 1000 patient chart review
o Epic data June 2016 – February 2017o REDCap format conversion with Data Import Tool on Excel
• Merging databaseso Centricity database and Epic databaseo Overlap July 2013 to June 2017
• Classify zip codes by median household incomeo Via Esri
• Data analysiso Via STATA 14.2
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Esri• GIS mapping software• Updated annually• Data sources
o American Community Survey (1-year and 5-year estimates)o Bureau of Economic Analysis’ Local Personal Income serieso Current Population Surveyo Bureau of Labor Statistics’ Consumer Price Index
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<$32,984 $32,985-$47,727
$47,728-$67,106
$67,107–$99,321
$99,322-$200,001
GACS 222 71 46 20 10NACS 1,917 812 496 308 141
84%
86%
88%
90%
92%
94%
96%
98%
100%Pe
rcen
tageofN
ACSan
dGA
CS
MedianHouseholdIncomeofZIPcode
MedianHouseholdIncomeforAnesthesiaType
GACS
NACS
Pr =0.035
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Low-Income Middle-Highincome OtherGACS 244 118 7NACS 2,085 1,542 47
80%
82%
84%
86%
88%
90%
92%
94%
96%
98%
100%
Percen
tageofG
ACSan
dNAC
S
PrenatalCarePracticeType
PrenatalCarePracticeforAnesthesiaType
GACS
NACS
Pr =0.001
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Patient-relatedVariableAssociatedwithGACS
OddsRatio 95%ConfidenceInterval
p-value
UnivariableRegression
Blackrace 1.74 1.36-2.22 0.00
Smokingstatus 1.42 1.12-1.81 0.00
Singlemaritalstatus 1.76 1.38-2.24 0.00
Low-incomeZ.I.P.code 1.38 1.11-1.72 0.00
Low-incomeprenatalcarepractice 1.48 1.34-2.51 0.00
MultivariableRegression
Blackrace 1.38 1.05-1.88 0.03
Smokingstatus 1.38 1.09-1.76 0.00
Singlemaritalstatus 1.31 0.99-1.74 0.54
Low-incomeZ.I.P.code 1.05 0.82-1.33 0.70
Low-incomeprenatalcarepractice 1.15 0.89-1.48 0.25
*Controlled for age, ASA status, HTNsive disorders, neurologic disorders, hematologic disorders, on-call deliveries, high-risk obstetrics specialty, obstetric anesthesia specialty, gestational age at delivery, obesity, diabetes, thyroid disease, depression.
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Limitations• ZIP code may not be the best surrogate for
household incomeo Ex: 19104 à median household income of ~$19,000 may be
falsely low• More impoverished areas further west, wealthier areas closer
to Penn• Substantial amount of patients from that ZIP code
o Proxy for distance from hospital instead
• Secondary data
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My Learning Experience• A well-organized and well-cleaned database
makes the difference during data analysis• Being thorough• STATA basics• Developing a research question• L&D shadowing experience
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AcknowledgementsDr. Benjamin Cobb Leonard Davis Institute
HUP OB Anesthesiologists Wharton Dean’s Office
Joanne Levy 2017 SUMR Cohort
Safa Browne
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Questions?