interim user guide for covid-19 - balramchauhan
TRANSCRIPT
Interim User Guide
for COVID-19
Version 1.0
Revision History
Date Version
2020-04-21 1.0
See Appendix D for Representations and Warranties, Limitations of Liability, and Disclaimers
Notes to Readers
This document is based on SDTM v1.7 and SDTMIG v3.3.
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CONTENTS
1 INTRODUCTION ................................................................................................................. 3
2 RISK FACTORS ................................................................................................................... 4 2.1 PRE-EXISTING MEDICAL CONDITIONS ................................................................................................................... 4 2.2 PERSONAL PROTECTIVE EQUIPMENT (PPE) ........................................................................................................... 4 2.3 TRAVEL .................................................................................................................................................................. 5 2.4 CONTACTS ............................................................................................................................................................. 6 2.5 SUBSTANCE USE .................................................................................................................................................... 7 2.6 EXPOSURE TO ANIMALS ......................................................................................................................................... 8
3 ONSET OF DISEASE ........................................................................................................... 9
4 SIGNS AND SYMPTOMS ................................................................................................. 10
5 LABORATORY TEST RESULTS .................................................................................... 16
6 DIAGNOSTICS AND VIROLOGY .................................................................................. 18 6.1 VIRUS IDENTIFICATION ........................................................................................................................................ 18 6.2 ANTIBODY TESTING ............................................................................................................................................. 18 6.3 SARS-COV-2 VIRAL LOAD ................................................................................................................................. 19
7 VITAL SIGNS AND URINE OUTPUT ............................................................................ 21
8 CONCOMITANT MEDICATIONS .................................................................................. 23
9 RESPIRATORY FINDINGS.............................................................................................. 24 9.1 IMAGING .............................................................................................................................................................. 24 9.2 PULMONARY FUNCTION TESTS ............................................................................................................................ 25
10 CARDIAC EVENTS/FINDINGS ....................................................................................... 26
11 HOSPITALIZATION ......................................................................................................... 27
12 PROCEDURES .................................................................................................................... 28 12.1 ASSISTED VENTILATION AND OXYGEN TREATMENTS ......................................................................................... 28 12.2 RENAL TREATMENT ............................................................................................................................................. 30
13 VACCINES .......................................................................................................................... 31
14 QUESTIONNAIRES, RATINGS, AND SCALES............................................................ 33 14.1 CLINICAL GLOBAL IMPRESSION AND SPONSOR-CREATED INSTRUMENTS ............................................................ 33
15 APPENDICES ...................................................................................................................... 35 APPENDIX A: NON-STANDARD VARIABLES (NSVS) ..................................................................................................... 35 APPENDIX B: GLOSSARY AND ABBREVIATIONS ............................................................................................................ 36 APPENDIX C: REFERENCES ........................................................................................................................................... 38 APPENDIX D: REPRESENTATIONS AND WARRANTIES, LIMITATIONS OF LIABILITY, AND DISCLAIMERS ....................... 39
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1 Introduction In March 2020, CDISC launched a team to rapidly develop guidance on standardizing COVID-19 research data.
Due to the public health significance of COVID-19, a task force was assembled with participants from industry, the
US Food & Drug Association, the US National Institutes of Health (NIH), the World Health Organization (WHO),
and academia, who worked alongside CDISC over several weeks to develop this Interim User Guide. This
development did not follow the usual CDISC Standards Development Process detailed in COP-001 (available
at https://www.cdisc.org/system/files/about/cop/CDISC-COP-001-Standards_Development_2019.pdf). CDISC
publicized the development of this document through a press release and updates on the CDISC website
(www.cdisc.org). In order to increase transparency, the development of this guidance was publicly visible
throughout the accelerated development process.
This Interim User Guide provides examples and guidance on implementing CDISC standards for COVID-19 so that
researchers can collect, structure, and analyze data more effectively to amplify the full value of data, drive clinical
research forward, and improve global health.
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2 Risk Factors At the time of publication of the Interim User Guide for COVID-19, information on risk factors is still limited.[1] Current information shows that risk factors for
COVID-19 may include old age or pre-existing medical conditions, including heart disease, lung disease, and diabetes.[2] This section also discusses personal
protective equipment (PPE), travel, contacts, substance use/smoking, and exposure to animals.
2.1 Pre-existing Medical Conditions
Example 1
Individuals with pre-existing medical conditions such as asthma, human immunodeficiency virus (HIV), and diabetes may be at higher risk for developing severe
illness from COVID-19. The following example shows how high-risk underlying medical conditions from a pre-specified list can be represented in the Medical
History (MH) domain. MHCAT = "RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19" is used to group risk factors together. Subject 101 has asthma
and HIV, but does not have diabetes.
mh.xpt
Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHDECOD MHCAT MHPRESP MHOCCUR MHDTC
1 COV-1 MH 101 1 ASTHMA Asthma RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y Y 2020-03-05
2 COV-1 MH 101 2 DIABETES Diabetes mellitus RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y N 2020-03-05
3 COV-1 MH 101 3 HIV HIV infection RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y Y 2020-03-05
2.2 Personal Protective Equipment (PPE)
During the COVID-19 pandemic, it is recommended that health care workers use personal protective equipment (PPE) such as N95 respirators, gowns, goggles,
and face shields. Additionally, the general population is advised and, in some cases, required to wear face masks when out in public. Use of PPE can be
represented in the draft Environmental and Social Factors (ER) domain using ERCAT = "PPE".
Example 1
This example shows data from a study on health care workers. An overall question about the use of PPE was asked, followed by questions about the use of
specific PPE in the past 14 days. Information about the type and manufacture of the PPE was also collected. PPE can be considered a device and this additional
information can be represented in the Device Identifiers (DI) domain. The Sponsor Defined Device Identifier (SPDEVID) variable is used in ER to specify which
PPE was used.
Row 1: Shows that the subject used PPE.
Rows 2-4: Show that the subject used an N95 respirator, a gown, and a face shield.
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er.xpt
Row STUDYID DOMAIN USUBJID ERSEQ SPDEVID ERTERM ERCAT ERPRESP EROCCUR ERDTC EREVLINT
1 CVD-4 ER 400 1 Use of Personal Protective Equipment PPE Y Y 2020-04-10 -P14D
2 CVD-4 ER 400 2 100 Use of N95 Respirator PPE Y Y 2020-04-10 -P14D
3 CVD-4 ER 400 3 200 Use of Gown PPE Y Y 2020-04-10 -P14D
4 CVD-4 ER 400 4 300 Use of Face Shield PPE Y Y 2020-04-10 -P14D
The DI domain is used to represent information about the PPE type and manufacturer.
di.xpt
Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL
1 CVD-4 DI 100 1 DEVTYPE Device Type N95 Respirator
2 CVD-4 DI 100 2 MANUF Manufacturer Company A
3 CVD-4 DI 200 1 DEVTYPE Device Type Gown
4 CVD-4 DI 200 2 MANUF Manufacturer Company B
5 CVD-4 DI 300 1 DEVTYPE Device Type Face Shield
6 CVD-4 DI 300 2 MANUF Manufacturer Company C
2.3 Travel
Traveling to areas with confirmed COVID-19 cases may increase an individual's risk of becoming infected. Studies may collect information about international,
interregional, and interstate travel during a specified period of time in order to assess risk of exposure to COVID-19. Questions about travel can be represented in
the draft Environmental and Social Factors (ER) domain.
Studies may require investigators to ask questions of varying levels of specificity regarding a subject's travel history. There may be differences in how countries
describe geographic regions within a country (e.g., state, province). Examples of these variations include:
• Have you traveled to an area with confirmed COVID-19 cases?
• Have you traveled internationally? If yes, to which countries?
• Have you traveled between States? If yes, to which States?
• Have you traveled between Provinces? If yes, to which Provinces?
Example 1
The example below shows how data regarding travel can be represented in the draft Environmental and Social Factors (ER) domain. Subjects were asked
whether or not they traveled to 14 days prior to symptom onset. If yes, subjects were asked to list country, region, and start and end dates for each location
visited. ERCAT = "COVID-19 RISK FACTOR" and ERSCAT="TRAVEL" is used to group these questions together. Subjects were asked if they had traveled
in the 14 days prior to onset of symptoms (EVINTX). If a subject had traveled, the study collected: country, region, and dates of travel. Start and end dates of
travel are represented in ERSTDTC and ERENDTC. Details about the county and region can be represented as non-standard variables. In this example, the NSV
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CNTRY is populated with ISO 3166-1-alpha-3 country codes, whereas the NSV REGION is populated with ISO 3166-2 codes. To allow separate timing of individual countries/regions visited within the past 14 days
prior to symptom onset, each country and/or region is represented on a separate row.
Row 1: Shows that subject 100 did travel 14 days prior to symptom onset.
Row 2: Shows that subject 100 traveled to the US state of Massachusetts within the between shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.
Row 3: Shows that subject 100 traveled to the US state of New York within the between shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.
Row 4: Shows that subject 101 did travel 14 days prior to symptom onset.
Row 5: Shows that subject 101 traveled to the Lombardy region of Italy during the dates shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.
Row 6: Shows that subject 101 traveled to Madrid, Spain during the dates shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.
Row 7: Shows that subject 102 did not travel 14 days prior to symptom onset.
er.xpt
Row STUDYID DOMAIN USUBJID ERSEQ ERGRPID ERTERM ERCAT ERSCAT ERPRESP EROCCUR ERDTC ERSTDTC ERENDTC EVINTX ERCNTRY ERREGION
1 COV-7 ER 100 1 1 TRAVEL COVID-19 RISK FACTOR TRAVEL Y Y 2020-02-23 14 DAYS PRIOR TO SYMPTOM ONSET
2 COV-7 ER 100 2 1 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-11 2020-02-14 14 DAYS PRIOR TO SYMPTOM ONSET USA US-MA
3 COV-7 ER 100 3 1 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-14 2020-02-16 14 DAYS PRIOR TO SYMPTOM ONSET USA US-NY
4 COV-7 ER 101 1 2 TRAVEL COVID-19 RISK FACTOR TRAVEL Y Y 14 DAYS PRIOR TO SYMPTOM ONSET
5 COV-7 ER 101 2 2 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-10 2020-02-13 14 DAYS PRIOR TO SYMPTOM ONSET ITA IT-25
6 COV-7 ER 101 3 2 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-13 2020-02-19 14 DAYS PRIOR TO SYMPTOM ONSET ESP ES-M
7 COV-7 ER 102 1 TRAVEL COVID-19 RISK FACTOR TRAVEL Y N 2020-02-23 14 DAYS PRIOR TO SYMPTOM ONSET
ER NSV Metadata
Variable Label Type Codelist Role Origin
ERCNTRY Country text ISO 3166-1 alpha-3 Non-standard Record Qualifier CRF
ERREGION Geographical Region text ISO 3166-2 Non-standard Record Qualifier CRF
2.4 Contacts
Example 1
Information about exposure to people or facilities that could potentially increase the risk of developing a COVID-19 infection can be represented in the draft Environmental and Social Factors (ER) domain.
Row 1: Shows that the subject was in close contact with a COVID-19 case in the past 14 days.
Row 2: Shows that the subject was not present at a health care facility where COVID-19 infections have been managed in the past 14 days.
Row 3: Shows that the subject was not present in a laboratory handling suspected or confirmed COVID-19 samples in the past 14 days.
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er.xpt
Row STUDYID DOMAIN USUBJID ERLNKID ERSEQ ERTERM ERCAT ERPRESP EROCCUR ERSTDTC EREVLINT
1 COVID-3 ER 100 1 1 Close contact with a confirmed or probable case of COVID-19, while that case was symptomatic COVID-19 RISK FACTOR Y Y 2020-02-25 -P14D
2 COVID-3 ER 100 2 Presence in a healthcare facility where COVID-19 infections have been managed COVID-19 RISK FACTOR Y N -P14D
3 COVID-3 ER 100 3 Presence in a laboratory handling suspected or confirmed COVID-19 samples COVID-19 RISK FACTOR Y N -P14D
When a subject has been in close contact with a person who has a confirmed or probable case of COVID-19, additional information may be collected on this potential source case. Data on the potential source case
can be represented in the Associated Persons (AP) domains. In this case, additional information was collected regarding the diagnosis of this potential source and has been represented in APMH. The RSUBJID
corresponds to the subject's USUBJID; SREL indicates the associated person's relationship to the subject. The variables MHLNKID and ERLNKID are used to connect the diagnosis information of the confirmed
case to the ER record describing the exposure.
apmh.xpt
Row STUDYID DOMAIN APID MHSEQ RSUBJID SREL MHLNKID MHTERM MHDECOD MHSTDTC
1 COVID APMH 200 1 100 MOTHER, BIOLOGICAL 1 COVID-19 Coronavirus infection 2020-04-01
This relrec dataset shows that the ER and APMH datasets can be connected using --LNKID.
relrec.xpt
Row STUDYID RDOMAIN USUBJID IDVAR IDVARVAL RELTYPE RELID
1 COVID ER ERLNKID ONE A
2 COVID APMH MHLNKID ONE A
All subsequent data collected on the potential source are handled in APxx datasets, where "xx" is the 2-letter code for the corresponding domain where data from the subject would be represented (e.g., potential
source case COVID-19 identification tests would be represented in the APMB domain).
2.5 Substance Use
Example 1
This example shows how substance use data could be represented. In this case, the case report form (CRF) collected smoking status of "current", "never", and "former" cigarette use.
Row 1: Shows that the subject is a current smoker, starting sometime in 2001.
Row 2: Shows that the subject has never smoked. SUOCCUR="N" and the dosing and timing fields are null.
Row 3: Shows that the subject is a former smoker, quitting sometime in 2010.
Row 4: Shows that the subject is a current user of e-cigarettes, beginning sometime in 2018.
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su.xpt
Row STUDYID DOMAIN USUBJID SUSEQ SUTRT SUCAT SUPRESP SUOCCUR SUDOSE SUDOSU SUDOSFRQ SUSTDTC SUENDTC SUSTTPT SUSTRTPT SUENTPT SUENRTPT
1 CVD-7 SU 700 1 CIGARETTES TOBACCO Y Y 2 PACK QD 2001 2020-01-01 BEFORE 2020-01-01 ONGOING
2 CVD-7 SU 701 1 CIGARETTES TOBACCO Y N
3 CVD-7 SU 702 1 CIGARETTES TOBACCO Y Y 1 PACK QD 2010 2020-03-15 BEFORE
4 CVD-7 SU 703 1 E-CIGARETTES E-LIQUID Y Y 5 mL QD 2018 2020-04-01 BEFORE 2020-04-01 ONGOING
2.6 Exposure to Animals
In rare cases, coronaviruses may be spread from infected animals to humans (zoonotic transmission), and then spread between humans. Examples of zoonotic diseases include severe acute respiratory syndrome
(SARS) and Middle East respiratory syndrome (MERS). The exact source of COVID-19 is unknown at this time.[3]
Example 1
This example shows the representation of data for pre-specified questions regarding animal exposure within the past 14 days, using the draft Environmental and Social Factors (ER) domain. In this example study,
exposure to animals was considered a potential risk factor for COVID-19; thus, ERCAT = "COVID 19 RISK FACTOR" and ERSCAT = "ANIMAL EXPOSURE" were used to group these questions together. The
variable EREVLINT was used to indicate that the question was intended to capture animal exposure during the past 14 days.
er.xpt
Row STUDYID DOMAIN USUBJID ERSEQ ERTERM ERCAT ERSCAT ERPRESP EROCCUR ERDTC EREVLINT
1 CVD-01 ER 100 1 EXPOSURE TO BIRDS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D
2 CVD-01 ER 100 2 EXPOSURE TO BATS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D
3 CVD-01 ER 100 3 EXPOSURE TO LIVESTOCK COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D
4 CVD-01 ER 100 4 INSECT OR TICK BITE COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D
5 CVD-01 ER 100 5 EXPOSURE TO SICK OR DEAD ANIMAL COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D
6 CVD-01 ER 100 6 EXPOSURE TO ANIMAL FECES COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D
7 CVD-01 ER 100 7 EXPOSURE TO PIGS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D
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3 Onset of Disease Example 1
In this example, the date of onset of symptoms and date of diagnosis were collected for the study. The date of
diagnosis was based on a positive test, and the CRF collected an identifier for the laboratory test with the positive
result.
Row 1: Shows the date of onset of symptoms.
Row 2: Shows the date of diagnosis. MHLNKID has been populated so that it can be related to the lab record
which confirmed diagnosis. Neither the lab dataset nor the related records (RELREC) dataset are
included in this example.
mh.xpt
Row STUDYID DOMAIN USUBJID MHSEQ MHLNKID MHTERM MHEVDTYP MHDTC MHSTDTC MHENDTC MHDY MHSTDY MHENDY
1 COVID-6 MH 103 1 COVID-19
SYMPTOM ONSET
2020-04-05
2020-03-31
1 -5
2 COVID-6 MH 103 2 1 COVID-19
DIAGNOSIS 2020-04-05
2020-04-04
1 -1
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4 Signs and Symptoms In COVID-19 studies, data about signs and symptoms is likely to focus on occurrence. Vaccine trials may include
assessments of reactogenicity symptoms; see Vaccines. For the purpose of this guide, the term symptoms is used to
refer to both signs and symptoms.
The examples in this section include the variable --DY, Study Day. Study day is relative to the study reference start
date (RFSTDC) in the Demographics domain. In interventional studies, the reference start date is usually the date of
start of treatment.
The domain in which data about the occurrence events is represented depends on whether data is about the event as
a whole, or is an assessment for a part of the event—that is, an assessment at a point in time (a snapshot) or a period of time within the event (a slice). Occurrence data about an event as a whole is represented in the Events domains,
whereas data about a part of an event is represented in the Findings About (FA) domain.
Occurrence data about symptoms collected at the beginning of the study are generally represented in the Medical
History (MH) domain or in the FA domain, in the famh.xpt dataset. There is an exception if data collected at the
beginning of the study are the same as data collected repeatedly during the study; in this case all data are represented
in the same findings about dataset, usually the face.xpt dataset. In either case, records are likely to include a --CAT
value (e.g., "COVID-19 SYMPTOMS").
Questions about pre-specified symptoms may vary, as illustrated in the following table.
Question Domain/Dataset Timing variables
Has the symptom occurred since the onset of acute illness?
MH MHDTC is date of assessment, EVINTX="SINCE ONSET OF ACUTE ILLNESS".
Was the symptom present at diagnosis?
FAMH FADTC is date of diagnosis. If diagnosis is defined as a disease milestone, MIDS is diagnosis, RELMIDS is "AT TIME OF".
Is the symptom present now? FAMH FADTC is date of assessment.
Data collection forms may include a place to enter symptoms which are not pre-specified. Those terms would be
represented in the MH domain.
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Example 1
In this example, data were collected at entry about symptoms that had occurred since the start of COVID-19.
Rows 1-7: Show occurrence data for pre-specified symptoms.
Row 8: Shows a symptom entered in a field for specifying other symptoms.
mh.xpt
Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHDECOD MHCAT MHPRESP MHOCCUR MHSTAT MHREASND MHDTC MHDY MHEVINTX
1 COV6 MH 102 1 Fever Fever COVID-19 SYMPTOMS
Y Y 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
2 COV6 MH 102 2 Chills Chills COVID-19 SYMPTOMS
Y Y 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
3 COV6 MH 102 3 Muscle aches Myalgia COVID-19 SYMPTOMS
Y Y 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
4 COV6 MH 102 4 Sore throat Sore throat COVID-19 SYMPTOMS
Y N 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
5 COV6 MH 102 5 Shortness of breath
Dyspnoea COVID-19 SYMPTOMS
Y Y 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
6 COV6 MH 102 6 Loss of smell Anosmia COVID-19 SYMPTOMS
Y N 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
7 COV6 MH 102 7 Loss of taste Ageusia COVID-19 SYMPTOMS
Y Y 2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
8 COV6 MH 102 8 Nausea Nausea COVID-19 SYMPTOMS
2020-04-02
1 SINCE ONSET OF ACUTE ILLNESS
Example 2
In this example, eligibility criteria included diagnosis of COVID-19. At entry, questions on the CRF asked whether pre-specified symptoms were present at
diagnosis. Because these were assessments about a point in time, the data are represented in FAMH. Although the data were gathered at the start of the study (as
indicated by the visit variables), FADTC was populated with the date of diagnosis, which was the time that was the focus of the question.
famh.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTAT FAREASND VISITNUM VISIT FADTC FADY
1 COVID3 FA 123 1 OCCUR Occurrence Indicator
Cough COVID-19 SYMPTOMS
Y Y 1 Entry 2020-04-02
-2
2 COVID3 FA 123 2 OCCUR Occurrence Indicator
Dyspnoea COVID-19 SYMPTOMS
N N 1 Entry 2020-04-02
-2
3 COVID3 FA 123 3 OCCUR Occurrence Indicator
Fever COVID-19 SYMPTOMS
Y Y 1 Entry 2020-04-02
-2
4 COVID3 FA 123 4 OCCUR Occurrence Indicator
Myalgia COVID-19 SYMPTOMS
N N 1 Entry 2020-04-02
-2
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Sponsors may choose to identify diagnosis as a trial disease milestone in the Trial Disease Milestones (TM) domain (not shown). In such a case, the Subject Disease Milestones (SM) domain (not shown) would be
submitted; the FAMH dataset would include the additional timing variables MIDS, RELMIDS, and MIDSDTC, as presented in the following table.
famh.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTAT FAREASND VISITNUM VISIT FADTC FADY MIDS RELMIDS MIDSDTC
1 COVID3 FA 123 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02
2 COVID3 FA 123 2 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS N N 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02
3 COVID3 FA 123 3 OCCUR Occurrence Indicator Fever COVID-19 SYMPTOMS Y Y 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02
4 COVID3 FA 123 4 OCCUR Occurrence Indicator Myalgia COVID-19 SYMPTOMS N N 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02
Data collection may include questions about groups of symptoms, such as
• Gastrointestinal (GI) symptoms (e.g., nausea, vomiting, diarrhea)
• Cough (e.g., non-productive, productive, haemoptysis)
In general, a name for the group of symptoms would be represented in --TERM and --SCAT; the --SCAT value would also be used for subsequent questions about specific symptoms within the group.
Example 3
In this example, the collection at study entry of data about COVID-19 symptoms included a question about cough. If the subject answered yes, subsequent questions were asked about more specific kinds of cough.
Row 1: Shows occurrence data for the term "cough". Because more detailed subsequent questions were asked, this was treated as a question about a group of symptoms. MHTERM and MHSCAT have the same
value "COUGH". Records for this question were created so that records for subjects without cough would be available for use in analysis.
Rows 2-4: Show occurrence data for more specific kinds of cough within the group "COUGH". Note different types of cough could have occurred; in this case, a subject had both a non-productive cough and a
productive cough but did not have a cough that produced bloody sputum.
mh.xpt
Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHLLT MHDECOD MHCAT MHSCAT MHPRESP MHOCCUR MHSTAT MHREASND MHDTC MHDY MHEVINTX
1 COV6 MH 102 1 COUGH COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS
2 COV6 MH 102 2 Non-productive cough Cough, non-productive Cough COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS
3 COV6 MH 102 3 Productive cough Productive cough Productive cough COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS
4 COV6 MH 102 4 Cough with bloody sputum Bloody sputum Haemoptysis COVID-19 SYMPTOMS COUGH Y N 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS
Data collected about symptoms during a study are often represented in the Clinical Events (CE) domain, rather than the Adverse Events (AE) domain. Note that there may be criteria under which especially severe or
long-lasting symptoms are reportable as adverse events.
Note that the following examples showing symptom data collected during the study do not include fever; temperature measurements are more accurate for determining whether fever occurred and how severe it was.
Temperature would be represented in the Vital Signs (VS) domain.
Known Issue: If a clinical event meets criteria for reporting as an adverse event, a record will be created in the AE domain (along with, possibly, record(s) in the faae.xpt dataset), but it is not clear whether data
about the event should be removed from the CE domain (and, possibly, from the face.xpt dataset). It is recommended to consult the regulatory division to which the data will be submitted on this point.
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Data collected about symptoms during the study may include approaches such as illustrated in the following table.
Question/Instruction Domain/Dataset Timing variables
Record symptoms related to COVID-19 (not pre-specified) CE (or AE) CESTDTC, CEENDTC
Did the symptom occur during the study? CE (or AE and FAAE) EVINTX = "DURING THE STUDY"
Did the symptom occur within the past day? FACE (or FAAE) FADTC is date of assessment, EVLINT = "-P1D"
Has the symptom occurred since the last visit? FACE (or FAAE) FADTC is date of assessment, EVINTX = "SINCE LAST VISIT"
If symptoms are assessed periodically for occurrence or for occurrence and severity, data are represented in the FA domain. If this type of data is collected using
the same questions at baseline as during the study, then the baseline assessment should be represented in the face.xpt dataset rather than the famh.xpt dataset.
Example 4
In this example, data were collected daily about the occurrence of pre-specified symptoms. In this study, because subjects were hospitalized, date and study day
(rather than visit) were used to identify the timing of assessments. Note that although the values in FAOBJ are Medical Dictionary for Regulatory Activities
(MedDRA) terms, the CRF may have used language more familiar to subjects (e.g., "runny nose" instead of or in addition to the medical term "rhinorrhea").
face.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FADTC FADY FAEVLINT
1 CVD-5 FA 500 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
2 CVD-5 FA 500 2 OCCUR Occurrence Indicator Rhinorrhoea COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
3 CVD-5 FA 500 3 OCCUR Occurrence Indicator Ear pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
4 CVD-5 FA 500 4 OCCUR Occurrence Indicator Wheezing COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
5 CVD-5 FA 500 5 OCCUR Occurrence Indicator Chest Pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
6 CVD-5 FA 500 6 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
Severity of symptoms can be assessed using the traditional adverse event severity mild/moderate/severe codes, but also can be represented using numeric rating
scales or visual analog scales (VAS). The following examples illustrate each of these approaches.
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Example 5
In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using the codes "MILD", "MODERATE", and "SEVERE".
face.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FADTC FADY FAEVLINT
1 CVD-5 FA 500 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS SEVERE SEVERE 2020-04-01 2 -P1D
3 CVD-5 FA 500 3 OCCUR Occurrence Indicator Rhinorrhoea COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
4 CVD-5 FA 500 4 OCCUR Occurrence Indicator Ear pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
5 CVD-5 FA 500 5 OCCUR Occurrence Indicator Wheezing COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS SEVERE SEVERE 2020-04-01 2 -P1D
7 CVD-5 FA 500 7 OCCUR Occurrence Indicator Chest pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
8 CVD-5 FA 500 8 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19 SIGNS AND SYMPTOMS MODERATE MODERATE 2020-04-01 2 -P1D
Example 6
In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using a scale of 1 to 5 (where 1 = "Very mild" and 5 = "Very severe",
but no text was associated with intermediate values).
face.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTRESN FADTC FADY FAEVLINT RNGVALLO RNGTXTLO RNGVALHI RNGTXTHI
1 CVD-5 FA 500 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS 4 4 4 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE
3 CVD-5 FA 500 3 OCCUR Occurrence Indicator Rhinorrhoea COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
4 CVD-5 FA 500 4 OCCUR Occurrence Indicator Ear pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
5 CVD-5 FA 500 5 OCCUR Occurrence Indicator Wheezing COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS 3 3 3 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE
7 CVD-5 FA 500 7 OCCUR Occurrence Indicator Chest pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D
8 CVD-5 FA 500 8 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D
9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19 SYMPTOMS 2 2 2 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE
FACE NSV Metadata
Variable Label Type Codelist Role Origin Comment
RNGVALLO Range Value Low integer Non-standard Record Qualifier CRF Pre-specified on CRF
RNGTXTLO Range Text Low text Non-standard Record Qualifier CRF Pre-specified on CRF
RNGVALHI Range Value High integer Non-standard Record Qualifier CRF Pre-specified on CRF
RNGTXTHI Range Text High text Non-standard Record Qualifier CRF Pre-specified on CRF
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Example 7
In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using a 50mm VAS where the text at the low end of the scale was "Not
at all severe" and the text at the high end of the scale was "As severe as possible".
face.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FAORRESU FASTRESC FASTRESN FASTRESU FAMETHOD FADTC FADY FAEVLINT RNGVALLO RNGTXTLO RNGVALHI RNGTXTHI
1 CVD-5 FA 500 1 OCCUR Occurrence Indicator
Cough COVID-19 SYMPTOMS
Y Y 2020-04-01
2 -P1D
2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS
41 mm 41 41 mm VISUAL ANALOG SCALE (50 MM)
2020-04-01
2 -P1D 0 Not at all severe
50 As severe as possible
3 CVD-5 FA 500 3 OCCUR Occurrence Indicator
Rhinorrhoea COVID-19 SYMPTOMS
N N 2020-04-01
2 -P1D
4 CVD-5 FA 500 4 OCCUR Occurrence
Indicator
Ear pain COVID-19
SYMPTOMS
N N 2020-
04-01
2 -P1D
5 CVD-5 FA 500 5 OCCUR Occurrence Indicator
Wheezing COVID-19 SYMPTOMS
Y Y 2020-04-01
2 -P1D
6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS
30 mm 30 30 mm VISUAL ANALOG SCALE (50 MM)
2020-04-01
2 -P1D 0 Not at all severe
50 As severe as possible
7 CVD-5 FA 500 7 OCCUR Occurrence Indicator
Chest pain COVID-19 SYMPTOMS
N N 2020-04-01
2 -P1D
8 CVD-5 FA 500 8 OCCUR Occurrence Indicator
Dyspnoea COVID-19 SYMPTOMS
Y Y 2020-04-01
2 -P1D
9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19
SYMPTOMS
28 mm 28 28 mm VISUAL ANALOG
SCALE (50 MM)
2020-
04-01
2 -P1D 0 Not at all
severe
50 As severe as
possible
FACE NSV Metadata
Variable Label Type Codelist Role Origin Comment
RNGVALLO Range Value Low integer Non-standard Record Qualifier CRF Pre-specified on CRF
RNGTXTLO Range Text Low text Non-standard Record Qualifier CRF Pre-specified on CRF
RNGVALHI Range Value High integer Non-standard Record Qualifier CRF Pre-specified on CRF
RNGTXTHI Range Text High text Non-standard Record Qualifier CRF Pre-specified on CRF
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5 Laboratory Test Results The LB domain is a findings domain that contains laboratory test data such as hematology, clinical chemistry, and urinalysis. This domain does not include microbiology, virology, or pharmacokinetic data, which are
stored in separate domains. For information about virus identification and viral load for COVID-19, see Virus Identification.
Additional information on the LB domain may be found in the SDTMIG v3.3, Section 6.3.6 (available at https://www.cdisc.org/standards/foundational/sdtmig)
Example 1
This example shows data from an arterial blood gas panel. The Sponsor Device Identifier (SPDEVID) was included because the sponsor was interested in the device used for the testing. Information about the device
identified by SPDEVID was represented in the Device Identifiers (DI) domain.
lb.xpt
Row STUDYID DOMAIN USUBJID SPDEVID LBSEQ LBTESTCD LBTEST LBCAT LBSCAT LBORRES LBORRESU LBORNRLO LBORNRHI LBSTRESC LBSTRESN LBSTRESU LBSTNRLO LBSTNRHI LBSTNRC LBNRIND LBLOINC LBSPEC VISITNUM VISIT VISITDY LBDTC
1 CVD-12 LB CVD-123 ABG01 1 PH pH CHEMISTRY BLOOD GAS ANALYSIS
7.39 7.35 7.45 7.39 7.39 7.35 7.45 NORMAL 2744-1 ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
2 CVD-12 LB CVD-123 ABG01 2 PCO2 Partial Pressure Carbon Dioxide
CHEMISTRY BLOOD GAS ANALYSIS
52 mmHg 35 45 52 52 mmHg 35 45 HIGH 2019-8 ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
3 CVD-12 LB CVD-123 ABG01 3 PO2 Partial Pressure Oxygen
CHEMISTRY BLOOD GAS ANALYSIS
60 mmHg 80 100 60 60 mmHg 80 100 LOW 2703-7 ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
4 CVD-12 LB CVD-123 ABG01 4 BICARB Bicarbonate CHEMISTRY BLOOD GAS ANALYSIS
30 mmol/L 22 26 30 30 mmol/L 22 26 HIGH 1960-4 ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
5 CVD-12 LB CVD-123 ABG01 6 OXYSAT Oxygen Saturation
CHEMISTRY BLOOD GAS ANALYSIS
90 % 94 100 90 90 % 94 100 LOW 2708-6 ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
6 CVD-12 LB CVD-123 ABG01 7 FIO2 Fraction of Inspired Oxygen
CHEMISTRY BLOOD GAS ANALYSIS
40 % 40 % ARTERIAL BLOOD
1 1 1 2020-03-07T08:30
The sponsor was interested in the details of the particular blood gas analyzer used for the blood gas analysis. In this example, the blood gas analyzer was identified using device type, manufacturer, and model.
di.xpt
Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL
1 ABC DI ABG01 1 DEVTYPE Device Type Blood Gas Analyzer
2 ABC DI ABG01 2 MANUF Manufacturer CheckURBreathing
3 ABC DI ABG01 4 MODEL Model PO277
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The following table shows common lab test names and test codes.
LB Test Name - LBTEST LB Test Code - LBTESTCD
Activated partial thromboplastin time APTT
Alanine aminotransferase AST
Aspartate aminotransferase ALT
Bilirubin BILI
C reactive protein CRP
Creatinine CREAT
Glucose GLUC
Hemoglobin HGB
Hematocrit HCT
Lactic acid LACTICAC
Leukocytes WBC
Lymphocytes LYM
Neutrophils NEUT
Platelets PLAT
Potassium K
Procalcitonin PCT
Prothrombin time PT
Prothrombin international normalized ratio INR
Sodium SODIUM
Urea Nitrogen UREAN
Controlled terminology can be found in the Lab Test Name and Lab Test Code codelists at https://www.cdisc.org/standards/terminology. Sponsors may request new terms as needed. A link to applicable codelists is
included in the SDTMIG domain specification tables.
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6 Diagnostics and Virology
6.1 Virus Identification
Identification of viruses from a collected sample is represented in the Microbiology Specimen (MB) domain.
Example 1
This example shows the results of tests to detect SARS-CoV-2, the virus that causes COVID-19, in 2 different subjects.
Row 1: Shows a subject who tested positive for SARS-CoV-2 by quantitative reverse transcriptase polymerase chain reaction (PCR) of an endotracheal fluid specimen.
Row 2: Shows a subject who tested negative for SARS-CoV-2 by quantitative reverse transcriptase PCR of a throat swab specimen.
mb.xpt
Row STUDYID DOMAIN USUBJID MBSEQ MBREFID MBGPRID MBTESTCD MBTEST MBTSTDTL MBORRES MBSTRESC MBSPEC MBLOC MBMETHOD VISITNUM VISIT MBDTC
1 ABC MB ABC-01-601
1 60101 1 SARSCOV2 Severe Acute Resp Syndrome Coronavirus 2
DETECTION POSITIVE POSITIVE ENDOTRACHEAL FLUID
QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
1 SCREENING 2020-03-27T14:15
2 ABC MB ABC-01-722
2 72201 1 SARSCOV2 Severe Acute Resp Syndrome Coronavirus 2
DETECTION NEGATIVE NEGATIVE SWABBED MATERIAL
THROAT QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
1 SCREENING 2011-04-01T10:00
6.2 Antibody Testing
Antibody testing provides a more rapid indication of current or past infection than testing for viral RNA by PCR-based methods.
Example 1
This example demonstrates the testing of immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies to the SARS-CoV-2 virus in subject serum samples. The example does not cover quantification of
antibodies. Such tests would be handled using the same MBTESTCD/MBTEST terminology, and with MBTSTDTL= QUANTIFICATION.
Rows 1-2: Show the screening of subject 011 for the separate detection of IgM and IgG antibodies to the SARS-CoV-2 virus, performed at the baseline visit. The subject tested positive for IgM and negative for
IgG.
Row 3: Shows the screening of subject 022 for the detection of IgG and/or IgM antibodies to the SARS-CoV-2 virus, performed at the baseline visit. The subject tested positive for this combined test, indicating
that the presence of 1 or both of these antibodies. This test does not differentiate between the presence of IgG and IgM; the presence of either will give a positive result.
mb.xpt
Row STUDYID DOMAIN USUBJID MBSEQ MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBSTRESC MBSPEC MBMETHOD VISITNUM VISIT MBDTC
1 COVID-ABC MB COVID-ABC-011 1 13668 SAR2IGM SARS-CoV-2 IgM Antibody DETECTION POSITIVE POSITIVE SERUM ELISA 1 BASELINE 2020-04-27
2 COVID-ABC MB COVID-ABC-011 2 13668 SAR2IGG SARS-CoV-2 IgG Antibody DETECTION NEGATIVE NEGATIVE SERUM ELISA 1 BASELINE 2020-04-27
3 COVID-ABC MB COVID-ABC-022 1 23433 SAR2IGGM SARS-CoV-2 IgG/IgM Antibody DETECTION POSITIVE POSITIVE SERUM ELISA 1 BASELINE 2020-04-29
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6.3 SARS-CoV-2 Viral Load
Quantification of viral shedding in SARS-CoV-2 infection is an evolving science. The following example uses data from a published source in the primary literature[4] as a starting point, where the results were
expressed in units of log 10 copies/ml. Units of copies/ml may also be used at the implementer's discretion.
Example 1
This example follows 1 subject through a series of viral load assessments over the course of a 10-day period.
The testing process took place in 2 parts: determination of threshold cycle and conversion of the threshold cycle readout to a viral load readout (i.e., copies/mL). The threshold cycle (Ct) represents the number of
cycles the PCR completed before the signal generated by amplification of viral RNA rose above the threshold set as a parameter of the experiment. In this example, records indicating the threshold cycle are grouped
with the preceding records of viral load using MBGRPID.
For the qRT-PCR assay illustrated in this example, conversion from the Ct readout to a viral load readout requires the use of a known concentration of reference standard sample of the target RNA to be run parallel
with the subject sample. It is important to note that in the case of emerging pathogens like SARS-CoV-2 such reference standards may not be available. In such cases only the Ct value will be available and a
quantitative viral load expressed as number of copies per unit volume will not be reported.
Rows 1-6: Show the subject's viral load expressed as log 10 copies/mL of SARS-CoV-2 RNA and the associated threshold cycle value over the course of days 3, 5, and 6.
Rows 7-9: Show the subject's viral load became undetectable at day 8, and remained undetectable on days 10 and 12. MBTSTDTL is not populated because there is nothing to quantify.
mb.xpt
Row STUDYID DOMAIN USUBJID SPDEVID MBSEQ MBGRPID MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBORRESU MBSTRESC MBSTRESN MBSTRESU MBSPEC MBMETHOD MBLOBXFL VISITNUM VISIT MBDTC
1 ABC MB ABC-001 PCR01 1 1 001-02 SAR2RNA SARS-
CoV-2 RNA
VIRAL LOAD 3.9 log 10
copies/mL
3.9 3.9 log 10
copies/mL
SPUTUM QUANTITATIVE REVERSE
TRANSCRIPTASE POLYMERASE CHAIN REACTION
Y 3 DAY
3
2020-
03-19
2 ABC MB ABC-001 PCR01 2 1 001-02 SAR2RNA SARS-CoV-2 RNA
THRESHOLD CYCLE
27.43 27.43 27.43 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN
REACTION
Y 3 DAY 3
2020-03-19
3 ABC MB ABC-001 PCR01 3 2 001-03 SAR2RNA SARS-CoV-2 RNA
VIRAL LOAD 4.7 log 10 copies/mL
4.7 4.7 log 10 copies/mL
SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
5 DAY 5
2020-03-21
4 ABC MB ABC-001 PCR01 4 2 001-03 SAR2RNA SARS-CoV-2 RNA
THRESHOLD CYCLE
23.11 23.11 23.11 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
5 DAY 5
2020-03-21
5 ABC MB ABC-001 PCR02 5 3 001-04 SAR2RNA SARS-
CoV-2 RNA
VIRAL LOAD 4.5 log 10
copies/mL
4.5 4.5 log 10
copies/mL
SPUTUM QUANTITATIVE REVERSE
TRANSCRIPTASE POLYMERASE CHAIN REACTION
6 DAY
6
2020-
03-22
6 ABC MB ABC-001 PCR02 6 3 001-04 SAR2RNA SARS-CoV-2
RNA
THRESHOLD CYCLE
23.22 23.22 23.22 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE
POLYMERASE CHAIN REACTION
6 DAY 6
2020-03-22
7 ABC MB ABC-001 PCR02 7 001-05 SAR2RNA SARS-CoV-2 RNA
TARGET NOT DETECTED
TARGET NOT DETECTED
SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE
8 DAY 8
2020-03-24
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Row STUDYID DOMAIN USUBJID SPDEVID MBSEQ MBGRPID MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBORRESU MBSTRESC MBSTRESN MBSTRESU MBSPEC MBMETHOD MBLOBXFL VISITNUM VISIT MBDTC
POLYMERASE CHAIN REACTION
8 ABC MB ABC-001 PCR01 8 001-06 SAR2RNA SARS-CoV-2 RNA
TARGET NOT DETECTED
TARGET NOT DETECTED
SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
10 DAY 10
2020-03-26
9 ABC MB ABC-001 PCR02 9 001-07 SAR2RNA SARS-
CoV-2 RNA
TARGET
NOT DETECTED
TARGET NOT
DETECTED
SPUTUM QUANTITATIVE REVERSE
TRANSCRIPTASE POLYMERASE CHAIN REACTION
12 DAY
12
2020-
03-28
Properties of the assays used to determine viral load are represented in the Device domains. In this example, the lot numbers of the assays used changed, and the sponsor chose to keep track of this parameter. Had the
lot number not changed or were it not of interest, a single SPDEVID could have been used to link to a single set of parameters in the Device Identifiers (DI) dataset.
Rows 1-4: Show the device type, manufacturer, trade name, and lot number for the RT-qPCR kit identifed by SPDEVID="PCR01".
Rows 5-8: Show the device type, manufacturer, trade name, and lot number for the RT-qPCR kit identifed by SPDEVID="PCR02".
di.xpt
Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL
1 ABC DI PCR01 1 DEVTYPE Device Type RT-qPCR kit
2 ABC DI PCR01 2 MANUF Manufacturer Acme
3 ABC DI PCR01 3 TRADENAM Trade Name DetectPRO
4 ABC DI PCR01 4 LOTNUM Lot Number 20160202013
5 ABC DI PCR02 1 DEVTYPE Device Type RT-qPCR kit
6 ABC DI PCR02 2 MANUF Manufacturer Acme
7 ABC DI PCR02 3 TRADENAM Trade Name DetectPRO
8 ABC DI PCR02 4 LOTNUM Lot Number 20161101004
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7 Vital Signs and Urine Output Example 1
The following example represents collection of baseline vital signs upon admission and summary daily assessments thereafter. The daily assessment shows abnormal values and rates them as "LOWEST" or
"HIGHEST" for each 24-hour period. The value of "HIGHEST" or "LOWEST" is dependent upon the range of normal limits and the direction of the abnormal values. The value is stored in the VSCOLSRT variable.
Rows 1-6: Show baseline vital signs upon admission (i.e., systolic and diastolic blood pressure, heart rate, respiratory rate, temperature, oxygen saturation). The non-standard variable VSN2SCAL reflects that the
"SpO2 Scale 1" from the National Early Warning Score 2 (NEWS2) Scale was the appropriate scale to be used in scoring this result in calculating the subject's NEWS2 total score.
Rows 7-13: Show the most abnormal vital signs for the 24-hour period of 2020-03-10, day 4 in this study. The subject was in prone position at the time of the measurement. The lowest blood pressure for the 24-
hour period occurred at 08:15; it was 70/36 with an MAP 47 mmHg. The highest temperature, highest heart rate, highest respiratory rate and lowest saturation also occurred at different times throughout
the 24-hour period. The LNKID variable is used to show the connection of LOWEST urine output that occurred at 0800.
vs.xpt Row STUDYID DOMAIN USUBJID VSSEQ VSLNKID VSTESTCD VSTEST VSCAT VSSCAT VSPOS VSORRES VSORRESU VSSTRESC VSSTRESN VSSTRESU VSLOC VSCSTATE VSBLFL VISITNUM VISIT VISITDY VSDTC VSDY VSEVLINT VSCOLSRT VSO2SRC VSN2SCAL
1 CVD-2 VS 200 1 SYSBP Systolic Blood Pressure
ADMISSION SITTING 120 mmHg 120 120 mmHg CONSCIOUS Y 1 1 1 2020-03-07T08:00
1
2 CVD-2 VS 200 2 DIABP Diastolic Blood
Pressure
ADMISSION SITTING 80 mmHg 80 80 mmHg CONSCIOUS Y 1 1 1 2020-03-
07T08:00
1
3 CVD-2 VS 200 3 HR Heart Rate ADMISSION SITTING 72 beats/min 72 72 beats/min CONSCIOUS Y 1 1 1 2020-03-07T08:00
1
4 CVD-2 VS 200 4 RESP Respiratory Rate ADMISSION SITTING 26 breaths/min 26 26 breaths/min CONSCIOUS Y 1 1 1 2020-03-07T08:00
1
5 CVD-2 VS 200 5 TEMP Temperature ADMISSION SITTING 41.0 C 41.0 41.0 C CONSCIOUS Y 1 1 1 2020-03-07T08:00
1
6 CVD-2 VS 200 6 OXYSAT Oxygen Saturation ADMISSION SITTING 93 % 93 93 % CONSCIOUS Y 1 1 1 2020-03-07T08:00
1 ROOM AIR SPO2 SCALE 1
7 CVD-2 VS 200 7 CPLRFLT Capillary Refill Time ADMISSION SITTING 1 sec 1 1 sec FINGERNAIL CONSCIOUS Y 1 1 1 2020-03-
07T08:00
1
8 CVD-2 VS 200 8 A SYSBP Systolic Blood Pressure
DAILY PRONE 70 mmHg 70 70 mmHg UNCONSCIOUS 4 4 4 2020-03-10T08:15
4 -PT24H LOWEST
9 CVD-2 VS 200 9 A DIABP Diastolic Blood Pressure
DAILY PRONE 36 mmHg 36 36 mmHg UNCONSCIOUS 4 4 4 2020-03-10T08:15
4 -PT24H LOWEST
10 CVD-2 VS 200 10 A MAP Mean Arterial Pressure
DAILY PRONE 47 mmHg 47 47 mmHg UNCONSCIOUS 4 4 4 2020-03-10T08:15
4 -PT24H LOWEST
11 CVD-2 VS 200 11 A HR Heart Rate DAILY PRONE 126 beats/min 126 126 beats/min UNCONSCIOUS 4 4 4 2020-03-10T22:18
4 -PT24H HIGHEST
12 CVD-2 VS 200 12 A RESP Respiratory Rate DAILY PRONE 28 breaths/min 28 28 breaths/min UNCONSCIOUS 4 4 4 2020-03-
10T17:00
4 -PT24H HIGHEST
13 CVD-2 VS 200 13 A TEMP Temperature DAILY PRONE 38.6 C 38.6 38.6 C UNCONSCIOUS 4 4 4 2020-03-10T05:14
4 -PT24H HIGHEST
14 CVD-2 VS 200 14 A OXYSAT Oxygen Saturation DAILY PRONE 88 % 88 88 % UNCONSCIOUS 4 4 4 2020-03-10T13:05
4 -PT24H LOWEST OXYGEN THERAPY
15 CVD-2 VS 200 15 A CPLRFLT Capillary Refill Time DAILY PRONE 4 sec 4 4 sec STERNUM UNCONSCIOUS 4 4 4 2020-03-07T21:00
4 -PT24H HIGHEST
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VS NSV Metadata
Variable Label Type Role Codelist Origin
VSCOLSRT Collected Summary Result Type text Non-standard Record Qualifier CRF
VSO2SRC Oxygen Source text Non-standard Record Qualifier CRF
VSN2SCAL NEWS2 Oxygen Saturation Scale Used text Non-standard Record Qualifier SPO2 SCALE 1, SPO2 SCALE 2 CRF
The Laboratory Test Results (LB) domain was used to show the urine output.
Row 1: Shows the amount of urine collected for the 24-hour period for day 4 of the study (2020-03-10T11:59).
Row 2: Shows the lowest hourly urine output in the 24-hour period for day 4 of the study. LBCOLSRT was used to denote the urine output was the LOWEST in the 24-hour period.
lb.xpt
Row STUDYID DOMAIN USUBJID LBSEQ LBLNKID LBTESTCD LBTEST LBORRES LBORRESU LBORNRLO LBORNRHI LBSTRESC LBSTRESN LBSTRESU LBLOINC LBSPEC VISITNUM VISIT VISITDY LBDTC LBDY LBCOLSRT
1 CVD-2 LB 200 1 A FLUIDOUT Fluid Output
150 mL/day 150 150 mL/day 9192-6 URINE 1 1 4 2020-03-10T11:59
4
2 CVD-2 LB 200 2 A FLUIDOUT Fluid Output
10 mL/h 10 10 mL/h 9188-4 URINE 1 1 4 2020-03-10T08:00
4 LOWEST
LB NSV Metadata
Variable Label Type Role Codelist Origin
LBCOLSRT Collected Summary Result Type text Non-standard Record Qualifier CRF
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8 Concomitant Medications Example 1
In COVID-19 studies, sponsors may be interested in collecting data on medication use, such as anti-malarial medications. This example shows data for subjects who were asked about their medication
use. CMEVLINT is used to indicate that only medications in the last 7 days were of interest.
Rows 1-2: Show the subject took an "ANTI-MALARIA MEDICATION" within 7 days before the study start.
Row 3: Shows the subject did not use an "ANTIVIRAL AGENT" within 7 days before the study start.
Rows 4-5: Show the subject took a "CORTICOSTEROID" within 7 days before the study start.
Row 6: Shows the subject did not take an "ANTIBIOTIC" within 7 days before the study start.
Row 7: Shows the subject did not use an "ANTIFUNGAL AGENT" within 7 days before the study start.
cm.xpt
Row STUDYID DOMAIN USUBJID CMSEQ CMTRT CMCAT CMPRESP CMOCCUR CMDOSE CMDOSU CMDOSFRQ CMROUTE CMDTC CMSTDTC CMENDTC CMSTRF CMEVLINT
1 CVD-18 CM 180 1 ANTI-MALARIA MEDICATION
ANTI-MALARIA MEDICATION
Y Y 2020-04-08
BEFORE -P7D
2 CVD-18 CM 180 2 HYDROXYCHLOROQUINE ANTI-MALARIA MEDICATION
400 mg QD ORAL 2020-04-02
2020-04-06
3 CVD-18 CM 180 3 ANTIVIRAL AGENT ANTIVIRAL AGENT Y N 2020-04-08
BEFORE -P7D
4 CVD-18 CM 180 4 CORTICOSTEROID CORTICOSTEROID Y Y 2020-04-08
BEFORE -P7D
5 CVD-18 CM 180 5 PREDNISONE CORTICOSTEROID 125 mg Q6H INTRAVENOUS 2020-04-07
2020-04-07
6 CVD-18 CM 180 6 ANTIBIOTIC ANTIBIOTIC Y N 2020-04-08
BEFORE -P7D
7 CVD-18 CM 180 7 ANTIFUNGAL AGENT ANTIFUNGAL AGENT Y N 2020-04-08
BEFORE -P7D
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9 Respiratory Findings
9.1 Imaging
In some instances, imaging (chest radiographs, computed tomography (CT) scans) may be performed on suspected COVID-19 subjects for screening, diagnosis,
and management of the virus.[5]
Example 1
This example illustrates pre-specified procedures for chest x-rays and chest CT scans collected for 2 subjects in the Procedures (PR) domain. Findings from these
imaging procedures are represented in the Respiratory System Findings (RE) domain.
Rows 1-2: Show that pre-specified procedures for chest x-ray and chest CT scan were collected for the subject. The subject had a chest x-ray but not a CT
scan.
Rows 3-4: Show pre-specified procedures for chest x-ray and chest CT scan were collected for the subject. This subject had both a chest x-ray and a CT scan
of the chest performed.
pr.xpt
Row STUDYID DOMAIN USUBJID PRSEQ PRTRT PRPRESP PROCCUR PRLOC VISITNUM VISIT PRDTC PRSTDTC
1 COVID1901 PR COVID1901-01 1 X-RAY Y Y CHEST 5 DAY 5 2020-04-07 2020-04-07
2 COVID1901 PR COVID1901-01 2 CT SCAN Y N CHEST 5 DAY 5 2020-04-07
3 COVID1901 PR COVID1901-02 1 X-RAY Y Y CHEST 7 DAY 7 2020-04-09 2020-04-09
4 COVID1901 PR COVID1901-02 2 CT SCAN Y Y CHEST 7 DAY 7 2020-04-09 2020-04-09
As noted, these imaging findings are shown in the RE domain. In this study, the sponsor was interested in whether the findings were normal or abnormal, so a
test of "Interpretation" was used. The non-standard variable (NSV) RECLSIG was used to note whether the findings were clinically significant.
Row 1: Shows the chest x-ray was normal for subject COVID1901-01.
Row 2: Shows the chest x-ray performed on subject COVID1901-02 was not evaluable.
Row 3: Shows that subject COVID1901-02 had an abnormal chest CT, and the imaging reviewer deemed this to be a clinically significant finding (as
indicated in the NSV RECLSIG).
re.xpt
Row STUDYID DOMAIN USUBJID SPDEVID RESEQ RETESTCD RETEST REORRES RESTRESC RELOC REMETHOD VISITNUM VISIT REDTC RECLSIG
1 COVID1901 RE COVID1901-01
ABC006 1 INTP Interpretation Normal NORMAL LUNG X-RAY 5 DAY 5
2020-04-07
N
2 COVID1901 RE COVID1901-02
ABC010 1 INTP Interpretation Not evaluable
NOT EVALUABLE
LUNG X-RAY 7 DAY 7
2020-04-09
3 COVID1901 RE COVID1901-02
ABC010 2 INTP Interpretation Abnormal ABNORMAL LUNG CT SCAN 7 DAY 7
2020-04-09
Y
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RE NSV Metadata
Variable Label Type Role Origin
RECLSIG Clinically Significant text Non-standard Result Qualifier CRF
Example 2
This example illustrates 2 pre-specified imaging findings (i.e., infiltrates, pneumonia) in the RE domain, collected for 1 subject on 2 different visits.
Rows 1-2: Show that there was no sign of pneumonia or infiltrates on day 3 by imaging.
Rows 3-4: Show that by day 7 the subject had developed signs of both pneumonia and infiltrates on imaging.
re.xpt
Row STUDYID DOMAIN USUBJID RESEQ RETESTCD RETEST REORRES RESTRESC RELOC REMETHOD VISITNUM VISIT REDTC
1 ABC001 RE ABC001-01 1 PNEUMIND Pneumonia Indicator N N CHEST X-RAY 2 DAY 3 2020-03-21
2 ABC001 RE ABC001-01 2 INFLTIND Infiltrates Indicator N N CHEST CT SCAN 2 DAY 3 2020-03-21
3 ABC001 RE ABC001-01 3 PNEUMIND Pneumonia Indicator Y Y CHEST X-RAY 3 DAY 7 2020-03-25
4 ABC001 RE ABC001-01 4 INFLTIND Infiltrates Indicator Y Y CHEST CT SCAN 3 DAY 7 2020-03-25
9.2 Pulmonary Function Tests
Pulmonary function tests will probably not be planned assessments for acute phases of COVID-19, but may be useful in studies to assess possible long-term
after-effects of infection. Pulmonary function tests are discussed in the Asthma Therapeutic Area User Guide (TAUG-Asthma;
https://www.cdisc.org/standards/therapeutic-areas/asthma) and the Chronic Obstructive Pulmonary Disease Therapeutic Area User Guide (TAUG-COPD;
https://www.cdisc.org/standards/therapeutic-areas/copd). Pulmonary function tests are represented in the RE domain; CDISC controlled terminology includes
codelists for multiple test names and codes.
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10 Cardiac Events/Findings The topic of electrocardiograms (EKGs) and measuring QT intervals may be of interest in some treatments currently
under study for COVID-19.[6] Drug-induced QT prolongation has long served as a surrogate indicator for increased
risk of drug-associated arrhythmia. However, the relationship between QT prolongation and risk of arrhythmia is
imperfect and complex.[7] Refer to the QT Studies Therapeutic Area User Guide
(https://www.cdisc.org/standards/therapeutic-areas/qt-studies) if this aspect is of interest for the study requirements.
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11 Hospitalization Information about hospitalization events is represented in the Healthcare Encounters (HO) domain.
Example 1
This example includes the HODECOD variable. An extensible codelist has been developed for HODECOD. The
indication for hospitalization and discharge outcome are shown in the NSVs INDC and DISOUT, respectively. The
NSV DISOUT uses the published DISCHDX codelist.
Row 1: Shows the subject was hospitalized due to COVID-19 and was discharged to self-care at home.
Row 2: Shows the subject was admitted to an intensive care unit due to COVID-19 and did not survive.
ho.xpt
Row STUDYID DOMAIN USUBJID HOSEQ HOTERM HODECOD HOSTDTC HOENDTC HOINDC HODISOUT
1 CVD-20 HO 200 1 HOSPITAL HOSPITAL STAY 2020-04-01
2020-04-08
COVID-19
HOME, SELF CARE
2 CVD-20 HO 201 1 INTENSIVE CARE UNIT
INTENSIVE CARE UNIT STAY
2020-04-02
2020-04-14
COVID-19
EXPIRED
HO NSV Metadata
Variable Label Type Codelist Role Origin
HOINDC Indication text Non-standard Record Qualifier CRF
HODISOUT Discharge Outcome text DISCHDX Non-standard Record Qualifier CRF
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12 Procedures Some COVID-19 patients may require assisted ventilation therapy (also known as mechanical ventilation therapy)
or renal treatment. These treatments—along with underlying comorbidities such as older age, hypertension, diabetes,
cardiovascular disease, chronic lung disease, and cancer—may play a role in the survival of patients with COVID-
19. Understanding the treatments used may provide insight into future treatment. In their 2020 article, Vincent and
Taccone[8] provided a decision tree for the possible paths to death and recovery in patients who require respiratory
support.
A focus of interest is the different types of assistance for oxygen therapy. Non-invasive ventilation (NIV) such as
continuous positive airway pressure (CPAP) and bilevel positive airway pressure (BIPAP) helps the patient breathe by taking in pressurized air through a mask attached to a small machine. The use of NIV treatments may reduce the
need for invasive treatments such as mechanical ventilation. As respiratory decompensation progresses, the patient
may require intubation, in which an endotracheal tube (ETT) is inserted through the mouth into the airway so the
patient can be placed on a ventilator to help with breathing. Some studies have shown that, for patients with severe
respiratory illness, prone positioning treatments while on mechanical ventilation when applied for at least 12 hours
daily is likely to reduce mortality.[9] Extracorporeal membrane oxygenation (ECMO) has been shown in some
studies of severe acute respiratory failure to rescue lung injury, improve oxygen levels, and reduce kidney
damage.[10] The ECMO machine pumps blood from the patient's body through tubes to an artificial lung, which
adds oxygen to it and removes carbon dioxide and then sends the blood back to the patient with the same force as
the heart. These treatments have been used for patients with COVID-19.[10]
12.1 Assisted Ventilation and Oxygen Treatments
Oxygen therapy treatments provide respiratory assistance and include invasive and non-invasive mechanical
ventilation. When required for the treatment of COVID-19, this is represented in the Procedures (PR) domain.
Example 1
The following example shows how to represent this information for a subject receiving these treatments in a
hospital. For this study, the sponsor was only interested in whether these procedures occurred during hospitalization
and the length of time a subject was on mechanical ventilation, not other treatments. If the start and end date of the
invasive mechanical ventilation was not available, the PRDUR variable would be used and could be populated with
count of DAYS (example not shown). This could be linked to the hospitalization record via RELREC (example not
shown). The Sponsor Device Identifier (SPDEVID) is used in the Procedures (PR) and Concomitant Medication
(CM) examples to link to the Device Identifiers (DI) dataset. MedDRA was used as the coding list for the
PRDECOD variable.
Row 1: Shows a pre-specified question asking whether the subject has received high-flow nasal cannula
oxygen therapy during hospitalization.
Rows 2-4: Show pre-specified questions asking whether the subject has received non-invasive mechanical
ventilation during hospitalization (includes oxygen therapy). If the answer is yes, the next 2 pre-
specified questions specify what types of non-invasive mechanical ventilation treatments were used:
CPAP ventilation and/or BIPAP ventilation.
Rows 5-6: Show pre-specified questions asking whether the subject has received invasive mechanical ventilation
during the hospitalization (includes oxygen therapy). If the answer is yes, the start and end date of the
mechanical ventilation is collected, and whether the subject received the treatment using "Prone"
positioning (a treatment called prone mechanical ventilation). The PRPOS variable for body position
was not used because the positioning is part of the treatment aim for prone mechanical ventilation.
Row 7: Shows a pre-specified question asking whether the subject has had a tracheostomy procedure during
hospitalization.
Row 8: Shows a pre-specified question asking whether the subject has received ECMO treatment during
hospitalization.
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pr.xpt
Row STUDYID DOMAIN USUBJID SPDEVID PRSEQ PRTRT PRDECOD PRCAT PRPRESP PROCCUR PRSTDTC PRENDTC PREVINTX
1 CVD-12 PR 201 HFNC 1 High-flow Nasal Cannula Oxygen Therapy
HIGH-FLOW NASAL CANNULA OXYGEN THERAPY
Y Y DURING HOSPITALIZATION
2 CVD-12 PR 201 2 Non-Invasive Ventilation NON-INVASIVE MECHANICAL VENTILATION
NON-INVASIVE MECHANICAL VENTILATION
Y Y DURING HOSPITALIZATION
3 CVD-12 PR 201 CPAP 3 Continuous Positive Airway pressure
CONTINUOUS POSITIVE AIRWAY PRESSURE VENTILATION
NON-INVASIVE MECHANICAL VENTILATION
Y Y DURING HOSPITALIZATION
4 CVD-12 PR 201 BIPAP 4 Bilevel Positive Airway Pressure
BILEVEL POSITIVE AIRWAY PRESSURE VENTILATION
NON-INVASIVE MECHANICAL VENTILATION
Y N DURING HOSPITALIZATION
5 CVD-12 PR 201 VENTDV 5 Mechanical Ventilation MECHANICAL VENTILATION INVASIVE MECHANICAL VENTILATION
Y Y 2020-03-07T23:45
2020-03-12T09:15
DURING HOSPITALIZATION
6 CVD-12 PR 201 VENTDV 6 Prone Ventilation MECHANICAL VENTILATION INVASIVE MECHANICAL VENTILATION
Y Y DURING HOSPITALIZATION
7 CVD-12 PR 201 7 Tracheostomy TRACHEOSTOMY Y N DURING HOSPITALIZATION
8 CVD-12 PR 201 ECMODV 8 Extracoroporeal Membrane Oxygenation
EXTRACORPOREAL MEMBRANE OXYGENATION
LIFE SUPPORT/HEMODYNAMIC SUPPORT
Y Y DURING HOSPITALIZATION
Details for the 3 subjects who received oxygen therapy are shown in the following table. The device used to deliver the oxygen therapy is represented in the DI domain. SPDEVID was included because the sponsor
was interested in the device used for administering oxygen.
cm.xpt
Row STUDYID DOMAIN SPDEVID USUBJID CMSEQ CMTRT CMINDC CMDOSE CMDOSU CMDOSFRQ CMROUTE CMSTDTC CMENDTC
1 CVD-12 CM NC 201 1 OXYGEN THERAPY SHORTNESS OF BREATH 2 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T17:45 2020-03-07T18:45
2 CVD-12 CM MASK 201 2 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T21:16 2020-03-07T22:30
3 CVD-12 CM HFOM 201 3 OXYGEN THERAPY SHORTNESS OF BREATH 12 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T22:31 2020-03-07T23:45
4 CVD-12 CM VENTDV 201 4 OXYGEN THERAPY HYPOXIA 100 % CONTINUOUS ENDOTRACHEAL 2020-03-07T23:45 2020-03-15T09:19
5 CVD-12 CM VENTDV 201 5 OXYGEN THERAPY HYPOXIA 50 % CONTINUOUS TRANSTRACHEAL 2020-03-15T09:20
6 CVD-12 CM MASK 202 1 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-21T09:20 2020-03-24T17:20
7 CVD-12 CM HFOM 203 1 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-22T09:20 2020-03-26T07:20
In this particular study, the sponsor was interested in the model for the non-invasive ventilation devices, the ventilator, and the ECMO device. The DI domain provides a mechanism for identifying devices that appear
in other domains.
di.xpt
Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL
1 CVD-12 DI NC 1 DEVTYPE Device Type NASAL CANNULA
2 CVD-12 DI HFNC 1 DEVTYPE Device Type HIGH FLOW NASAL CANNULA
3 CVD-12 DI HFNC 2 MODEL Model FLOWRITENC
4 CVD-12 DI FM 1 DEVTYPE Device Type OXYGEN DELIVERY FACE MASK
5 CVD-12 DI HFOM 1 DEVTYPE Device Type HIGH FLOW OXYGEN MASK DELIVERY SYSTEM
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Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL
6 CVD-12 DI CPAP 1 DEVTYPE Device Type CPAP MACHINE
7 CVD-12 DI CPAP 2 MODEL Device Type BREATHWELL CPAP MACHINE
8 CVD-12 DI BIPAP 1 DEVTYPE Device Type BIPAP MACHINE
9 CVD-12 DI BIPAP 2 MODEL Device Type TWICETHEBREATH BIPAP MACHINE
10 CVD-12 DI VENTDV 1 DEVTYPE Device Type VENTILATOR MACHINE
11 CVD-12 DI VENTDV 2 MODEL Model WEHELPYOUBREATHE
12 CVD-12 DI ECMODV 1 DEVTYPE Device Type ECMO - EXTRACORPOREAL MEMBRANE OXYGENATION MACHINE
13 CVD-12 DI ECMODV 2 MODEL Model PERFUSEBETTER
12.2 Renal Treatment
Example 1
In this example, all subjects were asked whether they received renal treatment during hospitalization for COVID-19.
Row 1: Shows the subject underwent renal treatment during hospitalization, which was ongoing.
Row 2: Shows the subject did not undergo renal treatment during hospitalization.
pr.xpt
Row STUDYID DOMAIN USUBJID PRSEQ PRTRT PRPRESP PROCCUR PRDTC PRSTDTC PRENDTC PRENRTPT PREVINTX
1 CVD-12 PR 120 1 RENAL TREATMENT Y Y 2020-03-15 2020-03-15 ONGOING DURING HOSPITALIZATION
2 CVD-12 PR 121 1 RENAL TREATMENT Y N 2020-03-15 DURING HOSPITALIZATION
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13 Vaccines The CDISC Vaccines Therapeutic Area User Guide (TAUG-Vax; https://www.cdisc.org/standards/therapeutic-
areas/vaccines/) was developed with FDA participation. The FDA technical specification Submitting Study Datasets
for Vaccines to the Office of Vaccines Research and Review[11] refers to the TAUG-Vaccines.
The TAUG-Vaccines includes a number of known issues. Some information which has become available since
publication is relevant in resolving some of those known issues and other points.
• One known issue discusses the appropriateness of the value "TREATMENT" in the epoch codelist for
vaccine studies. The definition of this term has been updated as suggested in the known issue to read, "A
period in a clinical study during which subjects receive investigational product." This means that
"TREATMENT" is an appropriate value in the EPOCH variable for vaccine studies.
• Some of the known issues refer to the supplemental qualifier --COLSRT (Collected Summary Result
Type). This variable is included as a standard variable in the drafts of the SDTM v2.0 and the SDTMIG
v3.4 developed for release in November 2020. This variable would still be represented as a supplemental
qualifier in submissions based on currently published versions of the standards, but can be used with
increased confidence because it is very likely to become a standard variable.
• One known issue is whether reactogenicity events that meet criteria for reporting as adverse events should
be reported in both the Clinical Events (CE) and Adverse Events (AE) domains. The FDA technical
specification[11] says (p. 3) that "if a reactogenicity event should happen to continue beyond the
assessment interval, it should also be represented in the AE domain," which seems to answer this question
for submissions to the FDA.
• One known issue discusses CESTDTC and CEENDTC in global Clinical Events (CE) reactogenicity
records; examples in the TAUG-Vaccines assume that these dates are collected. The FDA technical
specification (p. 2) says that "if an event occurred, the clinical event start day/date (CESTDY/CESTDTC)
and end day/date (CEENDY/CEENDTC) of the reactogenicity event should be collected and included in
the dataset."
• The TAUG-Vaccines discusses data collection approaches for reactogenicity data (i.e., flat model, nested
model, highly nested model). The FDA expresses a preference for the flat model in the technical
specification:[11]
We prefer that the Vaccine TAUG “flat model” be utilized, i.e., that data for each day be included,
even if a subject never experienced a particular event. However, the “nested model,” which
includes only a summary record for a particular event if a subject never experienced that event,
may be necessary for large trials with significant amounts of data. Sponsors should discuss which
model is appropriate with their review team prior to beginning their clinical trial. (p. 2)
• One of the known issues in the TAUG-Vaccines concerns cases where an investigator's assessment of
severity is different from a subject's. Although the known issue says there is no agreed-upon solution, there
are in fact solutions described within the SDTMIG, as illustrated in the following examples.
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Example 1
In this example, symptom severity is assessed for events as a whole. In this record, severity is recorded as "MILD". The variable --EVAL is a findings domain variable so is not present in this events domain. All data
in an events record is assumed to be provided by the investigator.
ce.xpt
Row STUDYID DOMAIN USUBJID CESEQ CETERM CEDECOD CECAT CESCAT CEPRESP CEOCCUR CESTAT CEREASND CESEV CESTDTC CEENDTC CESTDY CEENDY
1 ABC123 CE 101 1 VOMITING Vomiting REACTOGENICITY SYSTEMIC Y Y MILD 2020-04-01 2020-04-02 1 2
The subject also provided an evaluation of severity of the event, and the investigator provided the reason why their evaluations of severity differed. Both of these items were recorded as supplemental qualifiers.
This example represents non-standard variables (NSVs) in a separate supplemental qualifiers domain since the QEVAL variable is needed.
Row 1: Shows the assessment of severity by the study subject.
Row 2: Shows the reason the investigator's assessment of severity differed from the study subject's.
suppce.xpt
Row STUDYID RDOMAIN USUBJID IDVAR IDVARVAL QNAM QLABEL QVAL QORIG QEVAL
1 ABC123 CE 101 CESEQ 1 CESEV1 Severity/Intensity 1 MODERATE CRF STUDY SUBJECT
2 ABC123 CE 101 CESEQ 1 CEDIFFRS Reason Investigator Changed Assessment Subject's verbal description was of mild vomiting. CRF INVESTIGATOR
Example 2
In the study in this example, subjects kept a diary assessing the severity of symptoms. The diary results were discussed with the investigator, who could agree or disagree with the subject's assessment of symptom
severity. Because these assessments were for time periods within the event rather than for the event as a whole, they were represented as findings about the event. In this example, assessments by the investigator and
the subject differed, so were represented in 2 different evaluators as 2 separate FA records.
Row 1: Shows the investigator's evaluation of vomiting severity. The NSV FADIFFRS was used for the reason the investigator's assessment was different from the subject's assessment.
Row 2: Shows the study subject's evaluation of vomiting severity.
face.xpt
Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FASCAT FAORRES FASTRESC FASTAT FAREASND FABLFL FAEVAL FADTC FADY FADIFFRS
1 COVIDABC FA 101 1 SEV Severity/Intensity VOMITING REACTOGENICITY SYSTEMIC MILD MILD INVESTIGATOR 20200-04-01
1 Subject's verbal description was of mild vomiting
2 COVIDABC FA 101 2 SEV Severity/Intensity VOMITING REACTOGENICITY SYSTEMIC MODERATE MODERATE STUDY SUBJECT
20200-04-01
1
FACE NSV Metadata
Variable Label Type Codelist Role Origin
FADIFFRS Reason Investigator Changed Assessment text Non-standard Record Qualifier CRF
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14 Questionnaires, Ratings, and Scales Questionnaires, ratings, and scales (QRS) are maintained as stand-alone guides on the CDISC website
at https://www.cdisc.org/foundational/qrs. Supplements may or may not be finalized at the time of publication of
this interim user guide, and depend on copyright approval where applicable. CDISC cannot produce supplements for
copyrighted instruments without the express permission of the copyright holder.
New measurement tools are implemented on an ongoing basis by the CDISC QRS Terminology and Standards
Development subteams. The following table lists the instruments that are being pursued as potential supplements as
part of the development work for this interim user guide. Sponsors should refer to the the CDISC website
(https://www.cdisc.org/foundational/qrs) if an instrument of interest in COVID-19 research studies is not included, as it may have been developed for another therapeutic area. See CDISC COP 001
(at https://www.cdisc.org/about/bylaws) for details on implementing or requesting development of standards for
SDTM-based submissions.
Full Name and Abbreviation
Copyright Permission Status
Supplement Status
RSCAT RSTESTCD/RSTEST
National Early Warning Score 2 (NEWS2)
Granted Supplement in progress
NEWS2 NEWS109/NEWS1-NEWS Total (see supplement for additional RSTESTCD/RSTEST terminology)
Richmond Agitation-Sedation Scale (RASS)
To be requested RASS RASS0101/RASS01-Score
Riker Sedation-Agitation Scale (SAS)
To be requested SAS SAS0101/SAS01-Score
Some sponsors may calculate the scores for the individual items as well as the total score for the NEWS2 instrument
in ADaM. There are some items that may need to be collected and represented in SDTM.
The NEWS2 consciousness score can be represented in SDTM using RSTESTCD = "NEWS107"/RSTEST =
"NEWS1-Consciousness". The possible responses on the CRF include "Alert", "Confusion", "V", "P", or "U". After
consulting with subject matter experts and the NEWS2 phone application, it was determined that the most
meaningful data would be to represent these as "Alert", "New Confusion", "Verbal Responsive", "Pain Responsive",
or "Unresponsive". The mapping strategy is included in the following tables.
RSTESTCD RSTEST
NEWS107 NEWS1-Consciousness
RSORRES RSSTRESC RSSTRESN
Alert 0 0
New Confusion 3 3
Verbal Responsive
3 3
Pain Responsive
3 3
Unresponsive 3 3
Sponsors may also wish to collect information on the oxygen saturation scale used; see Vital Signs and Urine Output
for an example representing this information as an NSV in VS.
14.1 Clinical Global Impression and Sponsor-created
Instruments
The Clinical Global Impression (CGI)—sometimes also called the Clinical Global Assessment (CGA)—and the
Patient Global Impression (PGI) are scales used to assess the severity, change, or improvement of a disease
condition. CDISC supplements for both CGI and PGI are available at https://www.cdisc.org/foundational/qrs.
As with any standard instruments, the CGI and PGI should be used as intended and not adapted. Some sponsors'
disease-specific assessment instruments may be thought to apply to CGI or PGI concepts. However, when these
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require different item terminology or detailed disease-specific responses they may represent substantially different
scientific concepts than those in the CGI and PGI standard instruments.
For sponsor-developed scales, the best practice is to follow the guidance provided in the QRS Naming Rules
document (available at https://www.cdisc.org/foundational/qrs) for the values of --TESTCD, --TEST, and --CAT.
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15 Appendices
Appendix A: Non-standard Variables (NSVs)
The following table lists the non-standard variables (NSVs) used in this document and provides their parent domain
and variable-level metadata.
Parent Domain
Variable Label SAS Data Type
XML Data Type
Codelist/Controlled Terms
Role
ER ERCNTRY Country Char text ISO 3166-1 alpha-3 Non-Standard Record Qualifier
ER ERREGION Geographical Region Char text ISO 3166-2 Non-Standard Record Qualifier
FA FADIFFRS Reason Investigator Changed Assessment
Char text Non-Standard Record Qualifier
FA RNGVALLO Range Value Low Num float Non-Standard Record Qualifier
FA RNGTXTLO Range Text Low Char text Non-Standard Record Qualifier
FA RNGVALHI Range Value High Num float Non-Standard Record Qualifier
FA RNGTXTHI Range Text High Char text Non-Standard Record Qualifier
HO HOINDC Indication Char text Non-Standard Record Qualifier
HO HODISOUT Discharge Outcome Char text DISCHDX Non-Standard Record Qualifier
LB LBCOLSRT Collected Summary Result Type
Char text Non-Standard Record Qualifier
RE RECLSIG Clinically Significant Char text Non-Standard Record Qualifier
VS VSCOLSRT Collected Summary Result Type
Char text Non-Standard Record Qualifier
VS VSN2SCAL NEWS2 Oxygen Saturation Scale Used
Char text SPO2 SCALE 1, SPO2 SCALE 2
Non-Standard Record Qualifier
VS VSO2SRC Oxygen Source Char text Non-Standard Record Qualifier
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Appendix B: Glossary and Abbreviations
aCRF Annotated case report form
ADaM Analysis Data Model
ADaMIG ADaM Implementation Guide
BPAP Bilevel positive airway pressure
CDASH Clinical Data Acquisition Standards Harmonization Project
CDASHIG CDASH Implementation Guide
CDISC Clinical Data Interchange Standards Consortium
CGA Clinical Global Assessment (scale)
CGI Clinical Global Impression (scale)
Controlled Terminology A finite set of values that represent the only allowed values for a data item. These values may be codes, text, or numeric. A codelist is one type of controlled terminology.
CPAP Continuous positive airway pressure
CRF Case report form (sometimes called a case record form). A printed, optical, or electronic document designed to record all required information to be reported to the sponsor for each trial subject.
CSR Clinical study report
CT Computed tomography (scan)
Domain A collection of observations with a topic-specific commonality about a subject.
ECMO Extracorporeal membrane oxygenation
EDC Electronic data collection
EKG Electrocardiogram
ETT Endotracheal tube
FDA (US) Food & Drug Administration
FiO2 Fraction of inspired oxygen
Foundational Standards Used to refer to the suite of CDISC standards that describe the clinical study protocol (Protocol), design (Study Design), data collection (CDASH), laboratory work (Lab), analysis (ADaM), and data tabulation (SDTM and SEND). See http://www.cdisc.org/ for more information on each of these clinical data standards.
GI Gastrointestinal
HIV Human immunodeficiency virus
IgG Immunoglobulin G
IgM Immunoglobulin M
MedDRA Medical Dictionary for Regulatory Activities
MERS Middle East respiratory syndrome
NIH (US) National Institutes of Health
NIV Non-invasive ventilation
NSV Non-standard variable
Oxygen therapy Respiratory assistance treatments, including invasive and non-invasive mechanical ventilation
PCR Polymerase chain reaction
PGI Patient Global Impression (scale)
PPE Personal protective equipment
Prone mechanical ventilation
Mechanical ventilation using prone positioning; the positioning is a part of the treatment
QRS Questionnaires, ratings, and scales
RNA Ribonucleic acid
SARS Severe acute respiratory syndrome
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SDTM Study Data Tabulation Model
SDTMIG SDTM Implementation Guide
Slice Data about an event that represents assessment at a period of time within an event
Snapshot Data about an event that represents assessment at a point in time
Subject A participant in a study
TAUG Therapeutic area user guide
VAS Visual analog scale(s)
WHO World Health Organization
Zoonotic transmission Transmission of a disease from infected animals to humans
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Appendix C: References
1. Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19): people who are at higher
risk for severe illness. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-higher-
risk.html. Accessed April 17, 2020.
2. Johns Hopkins Medicine. Coronavirus and COVID-19: who is at higher risk?
https://www.hopkinsmedicine.org/health/conditions-and-diseases/coronavirus/coronavirus-and-covid19-who-is-
at-higher-risk. Accessed April 17, 2020.
3. Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19): if you have animals.
https://www.cdc.gov/coronavirus/2019-ncov/daily-life-
coping/animals.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fcoronavirus%2F2019-
ncov%2Fprepare%2Fanimals.html. Accessed April 7, 2020.
4. Pan X, Chen D, Xia Y, et al. Viral load of SARS-CoV-2 in clinical samples. Lancet, 2020;20(4):411-412.
doi:10.1016/ S1473-3099(20)30113-4
5. American College of Radiology. ACR recommendations for the use of chest radiography and computed
tomography (CT) for suspected COVID-19 infection. https://www.acr.org/Advocacy-and-Economics/ACR-
Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection.
Accessed April 17, 2020.
6. Guatret P, Lagier J, Parola P, et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results
of an open-label non-randomized clinical trial. Int J Antimicrob Agents. 2020.
doi:10.1016/j.ijantimicag.2020.105949. Published March 20, 2020. Accessed April 2, 2020.
7. Simpson TF, Kovacs RJ, Stecker EC. Ventricular arrhythmia risk due to hydroxychloroquine-azithromycin
treatment for COVID-19. Cardiology Magazine. https://www.acc.org/latest-in-
cardiology/articles/2020/03/27/14/00/ventricular-arrhythmia-risk-due-to-hydroxychloroquine-azithromycin-
treatment-for-covid-19. Published March 29, 2020. Accessed April 2, 2020.
8. Vincent JL, Taccone FS. Understanding pathways to death in patients with COVID-19. Lancent Respir Med.
2020. doi:10.1016/S2213-2600(20)30165-X. Published April 6, 2020. Accessed April 8, 2020.
9. Munshi L, Del Sorbo L, Adhikari NKJ, et al. Prone position for acute respiratory distress syndrome. A
systematic review and meta-analysis. Ann Am Thorac Soc. 2017;14(suppl 4):S280-S288.
doi:10.1513/AnnalsATS.201704-343OT
10. Phua J, Weng L, Ling L, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges
and recommendations. Lancet Respir Med. 2020. doi:10.1016/S2213-2600(20)30161-2. Published April 6,
2020. Accessed April 8, 2020.
11. US Department of Health and Human Services, Food and Drug Administration. Submitting study datasets for
vaccines to the Office of Vaccine Research and Review. Guidance for industry. Technical specifications
document. https://www.fda.gov/media/112581/download. Revised December 2019. Accessed April 6, 2020.
CDISC Interim User Guide for COVID-19 Version 1.0
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Appendix D: Representations and Warranties, Limitations of
Liability, and Disclaimers
CDISC Patent Disclaimers
It is possible that implementation of and compliance with this standard may require use of subject matter covered by
patent rights. By publication of this standard, no position is taken with respect to the existence or validity of any
claim or of any patent rights in connection therewith. CDISC, including the CDISC Board of Directors, shall not be
responsible for identifying patent claims for which a license may be required in order to implement this standard or
for conducting inquiries into the legal validity or scope of those patents or patent claims that are brought to its
attention.
Representations and Warranties
“CDISC grants open public use of this User Guide (or Final Standards) under CDISC’s copyright.”
Each Participant in the development of this standard shall be deemed to represent, warrant, and covenant, at the time
of a Contribution by such Participant (or by its Representative), that to the best of its knowledge and ability: (a) it
holds or has the right to grant all relevant licenses to any of its Contributions in all jurisdictions or territories in
which it holds relevant intellectual property rights; (b) there are no limits to the Participant’s ability to make the
grants, acknowledgments, and agreements herein; and (c) the Contribution does not subject any Contribution, Draft
Standard, Final Standard, or implementations thereof, in whole or in part, to licensing obligations with additional
restrictions or requirements inconsistent with those set forth in this Policy, or that would require any such
Contribution, Final Standard, or implementation, in whole or in part, to be either: (i) disclosed or distributed in
source code form; (ii) licensed for the purpose of making derivative works (other than as set forth in Section 4.2 of
the CDISC Intellectual Property Policy (“the Policy”)); or (iii) distributed at no charge, except as set forth in
Sections 3, 5.1, and 4.2 of the Policy. If a Participant has knowledge that a Contribution made by any Participant or
any other party may subject any Contribution, Draft Standard, Final Standard, or implementation, in whole or in
part, to one or more of the licensing obligations listed in Section 9.3, such Participant shall give prompt notice of the
same to the CDISC President who shall promptly notify all Participants.
No Other Warranties/Disclaimers. ALL PARTICIPANTS ACKNOWLEDGE THAT, EXCEPT AS PROVIDED
UNDER SECTION 9.3 OF THE CDISC INTELLECTUAL PROPERTY POLICY, ALL DRAFT STANDARDS
AND FINAL STANDARDS, AND ALL CONTRIBUTIONS TO FINAL STANDARDS AND DRAFT
STANDARDS, ARE PROVIDED “AS IS” WITH NO WARRANTIES WHATSOEVER, WHETHER EXPRESS,
IMPLIED, STATUTORY, OR OTHERWISE, AND THE PARTICIPANTS, REPRESENTATIVES, THE CDISC
PRESIDENT, THE CDISC BOARD OF DIRECTORS, AND CDISC EXPRESSLY DISCLAIM ANY
WARRANTY OF MERCHANTABILITY, NONINFRINGEMENT, FITNESS FOR ANY PARTICULAR OR
INTENDED PURPOSE, OR ANY OTHER WARRANTY OTHERWISE ARISING OUT OF ANY PROPOSAL,
FINAL STANDARDS OR DRAFT STANDARDS, OR CONTRIBUTION.
Limitation of Liability
IN NO EVENT WILL CDISC OR ANY OF ITS CONSTITUENT PARTS (INCLUDING, BUT NOT LIMITED
TO, THE CDISC BOARD OF DIRECTORS, THE CDISC PRESIDENT, CDISC STAFF, AND CDISC
MEMBERS) BE LIABLE TO ANY OTHER PERSON OR ENTITY FOR ANY LOSS OF PROFITS, LOSS OF
USE, DIRECT, INDIRECT, INCIDENTAL, CONSEQUENTIAL, OR SPECIAL DAMAGES, WHETHER
UNDER CONTRACT, TORT, WARRANTY, OR OTHERWISE, ARISING IN ANY WAY OUT OF THIS
POLICY OR ANY RELATED AGREEMENT, WHETHER OR NOT SUCH PARTY HAD ADVANCE NOTICE
OF THE POSSIBILITY OF SUCH DAMAGES.
Note: The CDISC Intellectual Property Policy can be found at:
http://www.cdisc.org/system/files/all/article/application/pdf/cdisc_20ip_20policy_final.pdf.