CSP #2030 - Observational Study of Convalescent Plasma for Treatment of Veterans With COVID-19
Conditions: Coronavirus Disease 2019 (COVID-19)
Sponsor: VA Office of Research and Development

CSP #2030: Observational Study of Convalescent Plasma for Treatment of Veterans with 
COVID-19 
 
Principal Investigators: 
J Michael Gaziano, MD, MPH, Director, Cooperative Studies Program Epidemiology Center, 
VA Boston Healthcare System, Boston, MA 
Nicholas L. Smith, PhD, Director, Seattle Cooperative Studies Program Epidemiology Center, 
VA Puget Sound Health Care System; Professor of Epidemiology, University of Washington, 
Seattle, WA 
 
Protocol Version Number: V 1.3 
Protocol Version Date:  May 25, 2021 
Funding Mechanism:  Unfunded  
NCT: NCT04545047 
 
Co-Investigators:  
Kelly Cho, PhD, MPH, Director of Data Science and Analytics, Division of Population Health 
and Data Science, Cooperative Studies Program Epidemiology Center, VA Boston Healthcare 
System, Boston MA; Assistant Professor of Medicine, Harvard Medical School, Boston, MA 
Juan P. Casas, MD, PhD, Executive Director Million Veteran Program and Senior Scientist,  
Cooperative Studies Program Epidemiology Center, VA Boston Healthcare System, Boston, MA 
David Gagnon, MD, MPH, PhD, Senior Biostatistician, VA Cooperative Studies Program 
Epidemiology Center, VA Boston Healthcare System; Research Professor of Biostatistics, 
Boston University School of Public Health, Boston, MA 
Sarah C. Keithly, MPH, Program Manager, Seattle Cooperative Studies Program Epidemiology 
Center, VA Puget Sound Health Care System, Seattle, WA 
Katherine Kurgansky, MPH, Senior Data Analyst, Cooperative Studies Program Epidemiology 
Center, VA Boston Healthcare System, Boston MA 
Jonathan D. Sugimoto, PhD, MHS, Epidemiologist, Seattle Cooperative Studies Program 
Epidemiology Center, VA Puget Sound Health Care System, Seattle, WA 

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Abstract 
Objectives: To determine if early treatment with convalescent plasma (CP) therapy reduces 30-
day mortality among Veterans hospitalized at a Department of Veterans Affairs (VA) facility with 
non-severe COVID-19. 
Research Design: This is a non-interventional, retrospective data collection study, designed to 
emulate a (hypothetical) target randomized trial using observational data from the VA electronic 
health record (EHR) database. Eligible patients will include Veterans admitted to a VA Medical 
Center with a SARS-CoV-2 positive test within 7 days of admission, had no prior plasma 
treatment, and non-severe disease. The intervention is CP administered within 2 days of 
hospitalization and SARS-CoV-2 positive test. The outcome is 30-day all-cause mortality.  
Methodology:  This project will access VA healthcare data in the EHR on a national basis. Data 
will be identified and captured using Computerized Patient Record System (CPRS), on VHA 
servers and the Corporate Data Warehouse (CDW) using the VA Informatics and Computing 
Infrastructure (VINCI) servers and non-identifiable data will be captured using the VA REDCap 
system. This will also include data from the VA Pathology & Laboratory Medicine Service. 
Additional data will be provided from the Mayo Clinic CP Registry to identify VA patients who 
have received CP. Death and morbidity, including intensive care unit (ICU) transition, intubation, 
extubation, and discharge, will be assessed using VHA data. We will fit inverse probability 
weighted pooled logistic models to estimate the observational analogue of the per-protocol 
effect of CP on 30-day mortality with cumulative incidence curves, risk differences, and hazard 
ratios. 
Clinical Implications: This project will allow a comprehensive assessment of the impact of 
convalescent plasma on morbidity and mortality among Veterans with COVID-19. This study 
aims to produce early evidence on the effectiveness of CP therapy, a promising approach to 
treating COVID-19. This evidence will help clinicians deliver better clinical care to critically-ill 
Veterans. In addition, it will set the stage for further research that informs the use of CP in 
patients with COVID-19.  
 
 

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Acronyms and Abbreviations 
CDW   
Corporate Data Warehouse 
COVID-19 
Coronavirus disease 2019 
CP 
 
Convalescent plasma 
CSP 
 
Cooperative Studies Program 
CPRS  
Computerized Patient Record System 
CSPCO 
Cooperative Studies Program Central Office 
CSPEC 
Cooperative Studies Program Epidemiology Center 
EHR  
Electronic health record 
ICU  
 
Intensive Care Unit 
III 
 
Individually-Identifiable Information 
PHI 
 
Protected Health Information  
R&D  
Research and Development  
SARS-CoV-2  Severe Acute Respiratory Syndrome Coronavirus 2 
SSN 
 
Social Security Number 
VA 
 
Department of Veterans Affairs  
VHA 
 
Veterans Health Administration 
VINCI  
VA Informatics and Computing Infrastructure  
VistA   
Veterans Health Information Systems and Technology Architecture  
 
 
 

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Contents 
Protocol Title: .................................................................................................................................. 5 
1.0 
Study Personnel................................................................................................................... 5 
1.1 
Principal Investigators ...................................................................................................... 5 
1.2 
Co-Investigators ............................................................................................................... 5 
2.0 
Introduction .......................................................................................................................... 5 
2.1 
Background ...................................................................................................................... 5 
2.2 
Rationale .......................................................................................................................... 5 
2.3  
Relevance to Veterans Health ......................................................................................... 6 
3.0 
Aims ..................................................................................................................................... 6 
4.0 
Resources and Personnel ................................................................................................... 6 
4.1 
Organizational Structure .................................................................................................. 6 
4.2 
Personnel, Location, VA Affiliation, and Role in Study.................................................... 6 
5.0 
Study Procedures ................................................................................................................ 7 
5.1 
Study Design .................................................................................................................... 7 
5.2 
Recruitment Methods ....................................................................................................... 8 
5.3 
Informed Consent Procedures ......................................................................................... 8 
5.4 
Inclusion/Exclusion Criteria .............................................................................................. 8 
5.5 
Study Evaluations............................................................................................................. 8 
5.6 
Data Analysis ................................................................................................................... 8 
5.7 
Withdrawal of Subjects................................................................................................... 11 
6.0 
Reporting............................................................................................................................ 11 
7.0 
Privacy and Confidentiality ................................................................................................ 11 
8.0 
Communication Plan .......................................................................................................... 12 
9.0 
References ......................................................................................................................... 12 
 
 
 

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Protocol Title:   
Observational Study of Convalescent Plasma for treatment of Veterans with COVID-19 
1.0 Study Personnel 
1.1 
Principal Investigators 
J. Michael Gaziano, MD, MPH, Director, Cooperative Studies Program Epidemiology Center, 
VA Boston Healthcare System, Boston, MA 
Nicholas L. Smith, PhD, Director, Seattle Cooperative Studies Program Epidemiology Center , 
VA Puget Sound Health Care System; Professor of Epidemiology, University of Washington, 
Seattle, WA 
1.2 
Co-Investigators 
Kelly Cho, PhD, MPH, Director of Data Science and Analytics, Division of Population Health and 
Data Science, CSP Epidemiology Center, VA Boston Healthcare System, Boston MA; Assistant 
Professor of Medicine, Harvard Medical School, Boston, MA 
Juan P. Casas, MD, PhD, Executive Director Million Veteran Program and Senior Scientist 
Boston CSP Epidemiology Center, Boston, MA 
David Gagnon, MD, MPH, PhD, Senior Biostatistician, VA CSP Epidemiology Center; Research 
Professor of Biostatistics, Boston University School of Public Health, Boston, MA 
Sarah C. Keithly, MPH, Program Manager, Seattle Cooperative Studies Program Epidemiology 
Center, VA Puget Sound Health Care System, Seattle, WA 
Katherine Kurgansky, MPH, Senior Data Analyst, Cooperative Studies Program Epidemiology 
Center, VA Boston Healthcare System, Boston MA 
Jonathan D. Sugimoto, PhD, MHS, Epidemiologist, Seattle Cooperative Studies Program 
Epidemiology Center, VA Puget Sound Health Care System, Seattle, WA 
2.0 Introduction 
2.1 
Background  
The epidemic of coronavirus disease 2019 (COVID-19) in Wuhan, China disproportionately 
infected persons who were older, male, and infirm. 1 Mortality risk and adverse outcomes 
followed the same pattern.2 Reports from United States have described a similar pattern of 
affected individuals.3 Many Veterans fit the vulnerable profile. As of June 15, 2020, 13,984 
Veterans have been tested or treated for known or probable COVID-19 at a Department of 
Veterans Affairs (VA) facility.4  
2.2 
Rationale  
The convalescent plasma (CP) collected from individuals who have recovered from a viral 
infection contain neutralizing antibodies. Administering CP to individuals who are infected by the 
virus may reduce symptoms and mortality. There is some evidence of benefit of CP treatment 
against respiratory illnesses during previous outbreaks, such as severe acute respiratory 
syndrome (SARS),5 novel influenza A subtype H1N1,6 and avian influenza virus subtype H5N1.7 
Recent data suggest that CP may improve outcomes in patients with COVID-19.8-12 Based on 
preliminary evidence of possible efficacy, this study will identify early signals of efficacy and 

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harm by evaluating key outcomes for Veterans with COVID-19 who have received and have not 
received CP treatment within the Veterans Health Administration (VHA) health care system.  
2.3  Relevance to Veterans Health 
Preliminary studies on the COVID-19 epidemic show that being male, of increased age, and 
those who are infirm are disproportionately infected with the disease.1-3 This population is also 
thought to have increased risk of mortality and adverse outcomes. Many Veterans fit this profile, 
and the electronic health record (EHR) used to care for Veterans provides a unique opportunity 
to assess the morbidity and mortality for Veterans with COVID-19. CP is one of several novel 
therapies being used in the VHA. Veterans being treated with CP in VHA are tracked by the VA 
Pathology & Laboratory Medicine Service and the Mayo Clinic CP Registry. This study will 
provide the opportunity to observationally assess the impact of CP for all Veterans with COVID-
19 using robust VHA data sources. 
3.0 Aims 
We will assess the effect of CP therapy on 30-day mortality in COVID-19 patients early 
in the hospital course. We will emulate a hypothetical randomized trial (target trial) using 
observational data from a large national sample of patients who received care within the  
VA. We will create a VA-based cohort using VA Corporate Data Warehouse (CDW) data 
and other VHA healthcare data sources, such as the VA Pathology & Laboratory 
Medicine Service, combined with Mayo Clinic CP Registry data to evaluate the impact of 
CP among Veterans with COVID-19 on mortality and morbidity.  
4.0 Resources and Personnel 
4.1 
Organizational Structure 
The project is a collaboration between the CSP Epidemiology Centers (CSPEC) in Boston, MA 
and Seattle, WA. The organizational and administrative structure of this study will include the 
following components: (1) CSP Central Office; and (2) the CSPECs, represented by Boston and 
Seattle.  
The Boston and Seattle CSPECs will share in the overall administrative coordination and 
oversight of the study. The Study Chairs, Drs. Gaziano and Smith, will perform the scientific 
coordination of the study in conjunction with the Co-Investigators and CSPEC leadership.  
4.2 
Personnel, Location, VA Affiliation, and Role in Study 
The effort is led by researchers with multidisciplinary expertise in medicine, population-based 
epidemiology, and biostatistics. All research activities are performed by VA employees or VA 
affiliates. 
● Kelly Cho, PhD, MPH, Director of Data Science and Analytics, VA Boston CSPEC: Co-
Investigator -  Dr. Cho has experience in advanced phenotyping methods and has been 
leading the development of the VA Phenomics Library in partnership with the VA 
research community. She will coordinate all phenotyping efforts using the VA CDW for 
the collection and classification of clinical data from the EHR. Dr. Cho will have access 
to individually-identifiable information (III) and protected health information (PHI).  
● Juan P Casas, MD, PhD, VA Boston CSPEC: Co-Investigator – Dr. Casas-Romero is a 
physician and epidemiologist with extensive experience on cohort studies using 
electronic medical records, genetics and other omics and innovative analytics. He has 
knowledge in the use of laboratory values from the EHR and the research laboratory. He 

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will work closely with the Co-Chairs and Co-Investigators on the data analyses for this 
study. Dr. Casas-Romero will have access to III and PHI. 
● David Gagnon, MD, PhD, MPH, VA Boston CSPEC: Co-Investigator – Dr. Gagnon has 
extensive experience in clinical research, beginning with his involvement in the 
Framingham Heart Study. His expertise extends to categorical data analysis, statistical 
computing, survival analysis, longitudinal analysis, clinical trials, and research study 
design. He will work closely with the Co-Chairs and Co-Investigators on the data 
analyses for this study. Dr. Gagnon will have access to III and PHI. 
● J. Michael Gaziano, MD, MPH, Director, VA Boston CSPEC: Chair – Dr. Gaziano is 
clinician and epidemiologist with extensive research experience working nationally and 
internationally on large data studies and biorepositories. He will work closely with his Co-
Chair, his team in Boston, and the CSPEC program to achieve the goals of this study. 
Dr. Gaziano will have access to III and PHI. 
● Sarah C. Keithly, MPH, Program Manager, Seattle CSPEC: Co-Investigator – Ms. 
Keithly is trained in epidemiology and biostatistics and has over 10 years of experience 
supporting a wide range of epidemiologic research projects, including large-scale 
surveys, program evaluations, and multi-site studies. She will work closely with the Co-
Chairs and Co-Investigators to achieve the goals of this study. She will have access to III 
and PHI. 
● Katherine Kurgansky, MPH, Senior Data Analyst, VA Boston CSPEC – Ms. Kurgansky 
has over 10 years of experience conducting innovative epidemiology, clinical, and 
laboratory research, with focus on study design, data analysis, and data interpretation. 
She will work closely with the Co-Chairs and Co-Investigators on the data analyses for 
this study. She will have access to III and PHI. 
● Nicholas L. Smith, PhD, Director, VA Seattle CSPEC: Chair - Dr. Smith is an 
experienced and collaborative epidemiologist who has successfully coordinated national 
and international observational studies among VA and non-VA researchers. He will work 
closely with his Co-Chair, his team in Seattle, and the CSPEC program to achieve the 
goals of this study. Dr. Smith will have access to III and PHI. 
● Jonathan D. Sugimoto, PhD, MHS, Epidemiologist, VA Seattle CSPEC: Co-Investigator - 
Dr. Sugimoto is a quantitative epidemiologist with expertise in the design, analysis, and 
implementation of vaccine trials and a wide range of infectious disease epidemiologic 
studies. He will work closely with the Chair on the scientific leadership of the study. Dr. 
Sugimoto will have access to III and PHI. 
Only individuals listed as study members on the sites’ approved Research and Development 
(R&D) Committee study staff forms will have access to identifiable data. No identifiable data will 
be transported or shared outside of the VA for the duration of the study. Analyses conducted on 
the study will receive internal quality control checks by an approved data analyst that was not 
involved in the data analysis. 
5.0 Study Procedures 
5.1 
Study Design 
This study is an observational study which emulates a hypothetical randomized trial (target 
trial)13,14 using observational data from the VHA EHR database. VA data will be used to emulate 
the eligibility criteria, treatment strategies, outcome, and follow-up of the target trial.  

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The specifications of the hypothetical trial are as follows. Patients would include Veterans 
hospitalized at a VA facility with a first-ever SARS-CoV-2 positive test within 7 days of 
admission, oxygen saturation of ≥90% within the past day, and non-severe COVID-19. Patients 
previously treated with convalescent plasma or residing in long-term care in the past 90 days 
would not be eligible. The patient would become eligible at the first SARS-CoV-2–positive test 
date (if the positive test occurred during hospitalization) or at the hospital admission date (if the 
positive test occurred before hospitalization). Eligible patients would be randomly assigned to 
either receive or not receive CP within 2 days of assignment. The primary outcome is 30-day 
mortality.  
This retrospective data collection study will be conducted at the CSPECs within the VA Boston 
and VA Puget Sound health care systems. This project will access VA healthcare data in the 
EHR at a national level. Data will be identified and captured using CPRS, on VHA servers and 
the CDW using VINCI servers. Approved study staff will have access to the VINCI data mart to 
identify Veterans with positive SARS-CoV-2 testing. 
If necessary, data can be extracted from medical records. In this case, data from VINCI/CDW 
will be reviewed by study staff and entered into a VA REDCap database. Each subject will be 
assigned a unique study ID and no PHI will be captured within VA REDCap. A crosswalk will be 
used to link the study ID to the Patient ICN. This document will be the only document to link 
study data and will be kept secure within the study’s VINCI workspace and will only be 
accessible to a limited number of study staff conducting data review. 
5.2 
Recruitment Methods 
This is non-interventional study that does not require contact with study subjects. All subjects 
will be identified from the Mayo Clinic CP Registry, the VA Pathology & Laboratory Medicine 
Service, and from the VA CDW.  
5.3 
Informed Consent Procedures 
There will not be any contact with subjects in the study and study subjects will not be consented 
into the study. We are requesting an Exemption Category 4.iii for secondary research use of 
identifiable private information or identifiable biospecimens.  
5.4 
Inclusion/Exclusion Criteria 
The population to study will include all Veterans who have tested positive for SARS-CoV-2 and 
treated for COVID-19 within the VHA healthcare system. Data available in the VA CDW will be 
utilized. Data analyses will assess multiple domains at the inpatient and outpatient level and 
obtained through the central VA COVID-19 Shared Data Resource. Domains for Data Analysis 
will include, but not limited to, Initial Presentation, Prior Medical Diagnoses, Health Limitations 
and Habits, Current Medications, Hospital Admission and Lab, Hospital Course, and Post 
Discharge Course. Data review will begin from date of diagnosis, short- and long-term outcomes 
will be assessed up to 1-year following diagnosis. There are no exclusion criteria for this study. 
5.5 
Study Evaluations 
This is non-interventional, retrospective data study, and therefore we will be using VA CDW 
data within the VA healthcare system. 
5.6 
Data Analysis  
Data Collection/Study Measures 
Data will be identified and captured using CPRS, on VHA servers and the CDW using the VINCI 
servers. Data captured will come from several VHA healthcare data sources and National 
Patient Care Databases (NPCDs), including: VA Pathology & Laboratory Medicine Service, 

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Veterans Health Information Systems and Technology Architecture (VistA) Medical SAS 
Outpatient Clinic and Patient Treatment File (PTF) datasets, Vital status crosswalk File with 
Real SSNs, Vital Status File with Scrambled SSNs, the Decision Support System (DSS) 
National Data Extract (NDE), Beneficiary Identification Records Locator (BIRLS) death file, 
Pharmacy files, and Pharmacy Benefit Management (PBM) system database. Data contain 
information on clinic visits, inpatient hospitalizations within VA, diagnosis, and procedure codes. 
Pharmacy data and laboratory data are available as well. All electronic databases related to the 
study will be stored on double password protected servers behind the VA firewall. Data 
accessed remotely via VINCI or in CDW will be accessible only by approved study personnel 
using strong IDs and passwords. 
As needed, data from VINCI/CDW will be reviewed by study staff and entered into a VA 
REDCap database. Each Veteran identified will be assigned a unique study ID. A crosswalk 
document will be kept within VINCI that will link the study ID to the Patient ICN. This document 
will be the only document to link study data and will be kept secure within on the study’s VINCI 
workspace and will only be accessible to a limited number of study staff conducting data review. 
The variables below represent a desirable list of information that will be captured using 
REDCap. We recognize that some of the information will not be available. Where feasible, we 
will make imputation for some information items.  
Analyses conducted on the study will receive internal quality control checks by an approved 
data analyst that was not involved in the data analysis. Below we describe the primary data and 
variables we will use to accomplish the aims of the proposal. The list of data and variables is not 
exhaustive but provides a detailed summary of the types of data will be using. 
Exposure: CP Treatment 
The primary exposure of interest is the use or the non-use of CP. These data are derived from 
multiple sources, including the VA Pathology and Laboratory Medicine Service, CDW, and the 
Mayo Clinic CP Registry. Data on CP recipients from the Mayo Clinic and VA Pathology and 
Laboratory Medicine Service will be matched to EHR data with unique identifiers, which include 
name, date of birth, VA patient identifiers (e.g., Patient ICN), date of hospitalization, and VA 
medical center or hospital. Other identifying information to match records may also be available, 
such as Social Security Numbers from the VA Pathology and Laboratory Medicine Service. 
Mayo Clinic data will not include Social Security numbers. 
Outcome variables 
The primary outcome is 30-day all-cause mortality.  
 
Other Covariates of Interest 
Initial Presentation: date of encounter, date of birth, sex, race, ethnicity, zip code of residence, 
date symptoms started. 
Prior Medical Diagnoses: chronic obstructive pulmonary disease, coronary heart disease, 
cardiac failure, diabetes mellitus, hypertension, cerebrovascular disease, chronic liver disease, 
cancer of solid organ, estimated glomerular filtration rate, immunodeficiency, autoimmune 
disorder [RA, IBD, lupus, etc.] 
Health Limitations and Habits: smoking (never, former, current). 
Current medications: diabetes oral medication, diabetes insulin used, immunosuppression 
therapy, blood pressure therapy, angiotensin converting enzyme angiotensin converting enzyme 

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(ACE) inhibitors, angiotensin-receptor blockers (ARBs), beta blockers, human 
immunodeficiency virus therapy.  
Outpatient Management Course: including symptoms at home, VA physician management, 
“progression of symptoms” and re-evaluation at the medical center, viral lab testing, and short- 
and long-term outcomes. 
Hospital Admission and Lab: VA Facility, admission date, Initial Admission to (ward, isolation, 
ICU, ICU on ventilator, other), chest x-ray lung findings at admission, PaO2,  admission and 
hospital course laboratory extremes (white blood cell count, lymphocyte count, platelet count, 
hemoglobin, CRP, procalcitonin, serum sodium, serum potassium, serum chloride) , and 
admission and hospital abnormal values (lactate dehydrogenase (LDH), aspartate transaminase 
(AST), alanine aminotransaminase (ALT), bilirubin total, creatine kinase (CK), dDimer), 
influenza vaccine in EHR over past 12 months, assay used to diagnose SARS-CoV-2 infection, 
and co-infection with other respiratory viruses.  
Hospital Course: ICU (start date and end date) complications (sepsis, acute kidney injury, 
rhabdomyolysis, ARDS, disseminated intravascular coagulation, pneumonia diagnosed by MD, 
hours to pneumonia from admission, hospital treatment (IV antibiotics, IV antifungal, IV antiviral 
(+name of antiviral), kidney dialysis, glucocorticoids, extra corporeal membrane oxygenation, IV 
immunoglobulin, IV hyperimmunoglobulin), other COVID-19 treatments, hospital discharge 
(date) and discharge facility or outcome (residence, nursing facility, death)   
Post Discharge:  COVID-19 antibody assay results and titer if available. Post discharge 
general medicine, cardiovascular care, and infectious disease follow up notes to estimate ability 
to perform activities of daily living. Use of VA medical care facilities and diagnoses in the 
recovery phase of the epidemic with focus on chronic disease complications with abstraction of 
information in outpatient encounters and communications with VA providers.  
Statistical Analysis Plan 
The target trial to emulate would include US Veterans hospitalized at a VA medical center 
where CP was a current practice. The patient would become eligible at the first SARS-CoV-2-
positive test date (if the positive test occurred during hospitalization) or at the hospital admission 
date (if the positive test occurred before hospitalization).  
Eligible patients would be randomly assigned to either receive or not receive CP. The exact 
timing of transfusion and determination of suitability for use (based on antibody levels or donor 
characteristics of the plasma units) would be left to the discretion of treating physicians. The 
primary outcome would be 30-day mortality. The causal contrasts of interest are the intention-to-
treat effect and the per-protocol effect. To estimate the intention-to-treat effect (the effect of 
assignment to CP on outcomes), estimate the risk difference and hazard ratio comparing 
patients in the CP and non-CP group. The risk (cumulative incidence) of outcomes could be 
estimated nonparametrically using the Kaplan-Meier method or under parametric smoothing 
assumptions via a pooled logistic regression model including a time-varying intercept, an 
indicator for treatment group, and a product (“interaction”) term between time and treatment 
group. The hazard ratio could be estimated from the pooled logistic regression model without 
the product term. In the case of a prespecified imbalance in baseline characteristics between 
intervention arms, relevant covariates could be added to the model. 
To estimate the per-protocol effect (the effect of treatment with CP on outcomes if all patients 
had adhered to the protocol), we would restrict the above intention-to-treat analysis to patients 
who adhered to their assigned treatment (CP or no CP) and adjust for the a priori baseline 
prognostic factors, as well as trial start day relative to first eligibility. The adjustment for these 
covariates would be carried out via inverse probability weighting, with all continuous variables 

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flexibly modeled using restricted cubic splines and estimated weights truncated at the 99.9th 
percentile to prevent extreme weights from affecting the analyses. In a secondary analysis, the 
adjustment for these covariates will instead be carried out via standardization. In all analyses, 
we use nonparametric bootstrapping, which yields unbiased estimates of standard error, to 
calculate percentile-based confidence intervals (CI) for survival difference and hazard ratio 
estimates. 
Combined analysis with other cohorts in the Mayo Clinic CP Registry: Other health systems in 
the registry will be performing similarly data analyses. Research groups are encouraged to 
share the same data analysis plan. Some will contribute summary statistics to a research 
collaboration.  
Sample Size/Power 
We present power calculations here for the mortality outcome. It is assumed that approximately 
500 subjects will receive CP in the course of this study, extrapolating from the 250 known 
recipients to date. We would then have 500 exposed and 2,500 unexposed subjects assuming a 
5:1 match. As of June 2020, nearly 4,000 COVID-19 patients have been admitted, making our 
sample viable. Current data shows an approximately 25% mortality rate, among those admitted 
who either have died or were discharged. Assuming independent observations, we would be 
able to detect a hazard ratio of 1.3 with 80% power and 1.35 with 90% power. Given the 
matched design, it is necessary to estimate a design effect due to the matching. A design effect 
of 2.0 would be considered extreme, assuming an intraclass correlation of 0.20 and cluster size 
of 6 [5:1]. This would result in an effective sample size of 1500 subjects. This would result in a 
detectable hazard ratio of 1.43 with 80% power and 1.50 with 90% power. These calculations 
assume alpha=0.05. 
5.7 
Withdrawal of Subjects 
We will not have contact with study subjects. We do not anticipate that Veterans will contact the 
study if they know that they received CP. If a study subject contacts the study and requests a 
withdrawal, we will not collect additional data from the subject. We will, however, continue to 
use data previously collected.  
6.0 Reporting 
The Co-Chairs will be jointly responsible for ensuring that the study adheres to the reporting 
requirements of the VA Central IRB, local R&D Committee(s), and VA/VHA requirements (e.g., 
VHA Handbook 1200.12 and VHA Handbook 1058.01). 
7.0 Privacy and Confidentiality 
All data will be stored in compliance with applicable VA policies. This study does not involve 
patient recruitment. All electronic databases related to the study will be stored on double-
password protected servers behind the VA firewall. Once uploaded to networked data servers, 
the data are maintained in a separate network system dedicated to databases containing PHI or 
sensitive data. There are multiple levels of security to ensure the integrity and confidentiality of 
all data stored on the system. The desktop computers and the data servers require 
authentication for access and these computers and servers are assigned to authorized staff 
only.  
Only personnel approved to be on the study by the R&D Committees will be allowed access to 
these files. Personnel that are removed from the study will have their access removed. To de-
identify and protect PHI, scrambled social security numbers and dates will be used in the 

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intermediate databases. De-identified information is provided to the PIs by the study team 
inclusive of the Biostatistician, and database programmer. The final analytic database will not 
have any PHI and will include aggregated data only. Since the data used is aggregate, this 
cannot be used to uniquely identify any patient. A crosswalk document linking the study ID to 
the Patient ICN will be kept within a VINCI workspace. No outside sources can access these 
data.  
Where applicable, we use encryption, physical security measures, restricted access, and locked 
file cabinets for paper records for data protection. VA study sites will utilize technologies that 
meet VA standards for data transfer to protect study data during transmission. For example, VA 
sensitive information will be transmitted using Federal Information Processing Standards (FIPS) 
140-2 compliant encryption tools or Secure File Transfer Protocol (SFTP). In accordance with 
VA policy, incident reporting of theft, loss of data, loss of storage media, unauthorized access to 
sensitive data or storage media and non-compliance with security controls will be reported 
promptly to the study PIs, Privacy Officer and Information Security Officer. 
Upon study completion, all research data will be maintained and/or destroyed, in accordance 
with the VHA Records Control Schedule (RCS 10-1) and VA Directive 6500. The study team will 
implement approved records dispositions, while ensuring that no records are destroyed without 
proper authorization. Decisions regarding disposal or disposition of the data, if necessitated, will 
be made with the approval of the appropriate oversight committees and VA regulations. 
8.0 Communication Plan  
This is an analysis-only protocol involving 2 CSPEC programs, Boston and Seattle. The Chairs 
and Co-investigators communicate on a regular basis. For this analysis, due to the urgency, we 
will have weekly analyses to produce results of the associations of interest. As follow-up of 
Veterans continues for 1 year, we will continue to meet regularly to complete the objectives of 
the study. 
The regulatory documents, including CIRB communications, will be maintained by Seattle and 
the protocol will be maintained by Boston. Seattle will also be monitoring serious adverse events 
related to study participation, which is limited to data security.  
9.0 References 
 
1. Guan WJ, Ni ZY, Hu Y, et al. Clinical Characteristics of Coronavirus Disease 2019 in 
China. The New England journal of medicine. 2020. 
2. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients 
with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 
2020;395(10229):1054-1062. 
3. Team CC-R. Severe outcomes among patients with coronavirus disease 2019 (COVID-
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