Association Between Angiotensin Converting Enzyme Inhibitor or Angiotensin Receptor Blocker Use and COVID-19 Severity and Mortality Among US Veterans
Conditions: Hypertension, COVID
Sponsor: University of Utah

1 
 
WORK PLAN – DATA EXTRACTION AND DATA ANALYSIS  
Project: Association between angiotensin converting enzyme inhibitor or angiotensin receptor 
blocker use and COVID-19 severity and mortality among US Veterans 
NCT number: Not yet assigned 
Date of document: June 17, 2020 
Authors: 
Catherine G. Derington, PharmD, MS;a Jordana B. Cohen, MD, MSCE;b,c Tom H. Greene, 
PhD;a Jennifer S. Herrick, MS;a,d James Cook, MS;a,d Vanessa W. Stevens, PhD;a,d Barbara 
E. Jones, MD, MS;d,e Libo Wang, MD;e  April F. Mohanty, MPH, PhD;d,e Alexander Zheutlin, 
MD, MS;e Andrew M. South, MD, MS;f Thomas C. Hanff, MD, MPH;g Steven M. Smith, 
PharmD, MPH;h Rhonda M. Cooper-DeHoff, PharmD, MS;h Jordan B. King, PharmD, MS;a,d,i 
G. Caleb Alexander, MD;j Dan R. Berlowitz, MD, MPH;k Faraz S. Ahmad, MD, MS;l M. Jason 
Penrod, MD;e Rachel Hess, MD, MS;a,e Molly B. Conroy, MD, MPH;a,e James Fang, MD;e 
Michael A. Rubin, MD, PhD, MS;e Srinivasan Beddhu, MD;e Alfred K. Cheung, MD;e Weiming 
Xia, PhD;m,n Lewis Kazis, ScD;k  Andrew E. Moran, MD, MPH;o  William S. Weintraub, MD;p  
Adam P. Bress, PharmD, MSa,d,e 
 
a) Department of Population Health Sciences, Division of Health System Innovation and 
Research, University of Utah School of Medicine, Salt Lake City, UT 
b) Department of Medicine, Renal-Electrolyte and Hypertension Division, Perelman School 
of Medicine at the University of Pennsylvania, Philadelphia, PA 
c) Department of Biostatistics, Epidemiology, and Informatics, Perelman School of 
Medicine, University of Pennsylvania, Philadelphia, PA 
d) George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT 
e) Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, 
UT 
f) Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC 
g) Department of Medicine, Division of Cardiology, Perelman School of Medicine, 
University of Pennsylvania, Philadelphia, PA 
h) Department of Pharmacotherapy and Translational Research, University of Florida 
College of Pharmacy, Gainesville, FL 
i) Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO 
j) Department of Epidemiology, Division of General Epidemiology and Methodology, Johns 
Hopkins Bloomberg School of Public Health, Baltimore, MD 
k) Department of Health Law, Policy and Management, Boston University School of Public 
Health, Boston, MA 
l) Department of Cardiology, Northwestern University Feinberg School of Medicine, 
Chicago, IL 
m) Department of Pharmacology and Experimental Therapeutics, Boston University School 
of Medicine, Boston, MA 
n) Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA 
o) Department of Medicine, Division of General Medicine, Columbia University, New York, 
NY 
p) MedStar Washington Hospital Center, Washington, DC 

2 
 
AIM 1 
Study Schema 
Aim 1.1: Among Veterans with treated hypertension and without compelling indications* 
who test positive for SARS-CoV-2, compare all-cause hospitalization and all-cause 
mortality rates between current users of a range of doses of ACEI/ARB- vs. non-
ACEI/ARB-based regimens. 
 
*Diabetes, chronic kidney disease, heart failure, coronary heart disease, and history of stroke. 
 
 
Time
Index date: positive 
outpatient SARS-CoV-2 test
Index date identification period: 
January 19, 2020 to present day
Outcome assessment window: 
Time to all-cause hospitalization, all-
cause mortality, or administrative 
end of follow-up (June 1, 2020)
Days [1, event]
Exposure assessment
window:
≥ 1 fill for an ACEI/ARB-
vs. non-ACEI/ARB-
based regimen
Days [-90,0] 
Covariate assessment window
Days [-365,0] for demographics, medication use; all available claims for 
comorbidities
Exclusion assessment window
No hypertension diagnosis, untreated hypertension, presence of compelling 
indications
Days [-365,0] for medication use; all available claims for comorbidities

3 
 
Aim 1.2: Among Veterans with treated hypertension who test positive for SARS-CoV-2, 
compare all-cause hospitalization and all-cause mortality rates between current users of 
a range of doses of ACEI- vs. ARB-based regimens. 
 
 
Time
Index date: positive 
outpatient SARS-CoV-2 test
Index date identification period: 
January 19, 2020 to present day
Outcome assessment window: 
Time to all-cause hospitalization, all-
cause mortality, or administrative 
end of follow-up (June 1, 2020)
Days [1, event]
Exposure assessment
window:
≥ 1 fill for an ACEI vs. 
ARB-based regimen
Days [-90,0] 
Covariate assessment window
Days [-365,0] for demographics, medication use; all available claims for 
comorbidities
Exclusion assessment window
No hypertension diagnosis, untreated hypertension
Days [-365,0] for medication use; all available claims for comorbidities

4 
 
Cohort Creation 
We will create two separate, analysis-ready datasets to carry out the analyses for Aims 1.1 and 
1.2. 
 
1. Aim 1 Cohort Creation 
1.1. Please identify all Veterans who have a positive laboratory test for severe acute 
respiratory syndrome coronavirus 2 (SARS-CoV-2) between January 19, 2020 to 
present-day using the official VA definition in the COVID-19 domain (see Appendix A). 
The date of the positive test will be denoted as the index date. 
1.2. Restrict the cohort to Veterans without a hospitalization in the 7 days prior to the index 
date to narrow the cohort to Veterans who were tested in the outpatient setting. 
1.3. Restrict the cohort to Veterans who had ≥1 inpatient or any outpatient encounter in 
each of the two, six-month periods during the 365 days prior to the index date.  
1.4. Restrict the cohort to Veterans without data inconsistencies (test patients, not Veterans, 
multiple death dates in data, or not alive on index date).  
1.5. Restrict the cohort to Veterans with a diagnosis of hypertension at any point prior to 
their index date (see Appendix B for definition of hypertension). 
1.6. Restrict the cohort to Veterans who have an outpatient pharmacy fill in 90 days prior to 
the index date for any antihypertensive medication (see Appendix E). 
1.7. Cohort creation specific for Aim 1.1  
1.7.1. Follow steps 1.1 through 1.6 above. 
1.7.2. Restrict the analysis to Veterans who do not have a history of diabetes, stroke, 
chronic kidney disease, heart failure with reduced ejection fraction, or coronary 
heart disease (see Appendix B for definitions of these conditions). 
1.7.3. Categorize Veterans according to current antihypertensive medication use as in 
steps 1.7.3.1 and 1.7.3.2 below. The groups should be mutually exclusive. 
1.7.3.1. 
Identify and categorize Veterans who have a pharmacy fill for an 
angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor 
blocker (ARB; see Appendix E) within the 90 days prior to the index date. 
These Veterans will be categorized as Veterans with current use of 
“ACEI/ARB-based regimens”. Veterans included in this group may have fills 
for non-ACEI/ARB medications but must also have a fill for an ACEI or an 
ARB. For each Veteran, please create variables to indicate the use of these 
non-ACEI/ARB medication classes in the dataset. 

5 
 
1.7.3.2. 
Identify Veterans who have a pharmacy fill an antihypertensive 
medication class other than an ACEI or an ARB AND do not have a fill for an 
ACEI or an ARB (see Appendix E) within the 90 days prior to the index date. 
These Veterans will be categorized as Veterans with current use of “non-
ACEI/ARB-based regimens”. Veterans included in this group may have fills for 
multiple non-ACEI/ARB medications. For each Veteran’s regimen, please 
create variables to indicate the use of all medication classes in the dataset. 
1.7.4. Please provide a flow chart with the number of Veterans retained and excluded 
during steps 1.1 through 1.7.3.2. See Figure 1. 
1.8. Cohort creation specific for Aim 1.2  
1.8.1. Follow steps 1.1 through 1.6 above. 
1.8.2. Exclude Veterans who do not have a pharmacy fill for an ACEI or ARB within the 
90 days prior to the index date (see Appendix E). 
1.8.3. Exclude Veterans who have a pharmacy fill for both an ACEI and an ARB within 
the 90 days prior to the index date. 
1.8.4. Identify and categorize Veterans who have a pharmacy fill for ACEI within the 90 
days prior to the index date. These Veterans will be categorized as “ACEI users”. 
Veterans included in this group may have fills for non-ACEI medications (other than 
ACEIs) but must also have a fill for an ACEI. For each Veteran, please create 
variables to indicate the use of these non-ACEI medication classes in the dataset. 
1.8.5. Identify and categorize Veterans who have a pharmacy fill for an ARB within the 
90 days prior to the index date. These Veterans will be categorized as “ARB users”. 
Veterans included in this group may have fills for non-ARB medications (other than 
ARBs) but must also have a fill for an ARB. For each Veteran, please create 
variables to indicate the use of these non-ARB medication classes in the dataset. 
1.8.6. Please provide a flow chart with the number of Veterans retained and excluded 
during steps 1.1 through 1.6, then 1.8.1 through 1.8.5. See Figure 3. 

6 
 
Data Management  
1. The data management will be conducted using VINCI. Consistency will be followed for the 
name and levels for variables created for Veterans in each data set. The steps below 
describe the data management for Veterans who are included in the aim 1.1 cohort 
(ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen) and the aim 1.2 cohort 
(ACEI users vs. ARB users). Baseline covariates will be created as listed in Appendix B. 
Please produce separate analyses ready datasets for aims 1.1 and 1.2. 
2. Please report the percent missingness of each variable in each cohort, separately. 
3. For each cohort, create a single variable indicating to which medication exposure group the 
Veteran has been assigned. 
a. Aim 1.1: “ACEI/ARB-based regimen cohort” and “non-ACEI/ARB-based regimen cohort” 
b. Aim 1.2: “ACEI user cohort” and “ARB user cohort”. 
4. For each Veteran, identify the occurrence of the primary and secondary outcomes. 
5. For each observation, identify the time to occurrence or censoring of the primary and 
secondary outcomes in days, separately. 
6. For secondary analyses within each cohort (see statistical analysis section): 
a. The main exposure will be re-defined using alternative exposure definitions, and patients 
will be re-categorized according to these new definitions (see Appendix C). The primary 
analysis will be repeated.  
b. A variable identifying the occurrence of negative control outcomes will be created. 
c. A variable identifying the time to occurrence or censoring of negative control outcomes 
in days will be created. 

7 
 
Statistical analysis 
Aim 1.1 
1. Calculate baseline patient characteristics (Appendix B) for users of ACEI/ARB-based 
regimens and non-ACEI/ARB-based regimens, separately. Populate Table 1, left panel 
(“before weighting”).  
2. Generate propensity scores (PS) for being a user of an ACEI/ARB-based regimen vs. a 
non-ACEI/ARB-based regimen using generalized boosted regression models as a 
function of all baseline covariates.1,2 The algorithm should minimize standardized mean 
differences in covariates between exposure groups in the PS-weighted population.3  
Generate Supplemental Figure S1, which shows the distribution of PSs among Veterans 
who are hospitalized for COVID-19 between the ACEI/ARB-based regimen vs. non-
ACEI/ARB-based regimen cohorts. 
3. Use the final PS generated in step 2 to calculate each study-eligible Veteran’s matching 
weight.  
4. Verify covariate balance in the matching weighted population using the Kolmogorov-
Smirnov metric4,5 and calculate absolute standardized mean differences. Populate Table 
1, right panel (“after weighting”). Generate Supplemental Figure S2. 
5. Primary analysis: Apply matching-weighted Cox regression with Poissonization6 to 
estimate the causal marginal hazard ratio comparing the primary outcome (time to all-
cause hospitalization or all-cause mortality) and secondary outcomes as appropriate 
between medication exposure groups (ACEI/ARB-based regimens vs. non-ACEI/ARB-
based regimens). Populate Table 2 and generate Figure 2. 
6. Perform bootstrap resampling7 to generate 95% confidence intervals using 2-sided alpha 
= 0.025 for the primary outcome and 2-sided alpha = 0.05 for the secondary outcomes.  
7. Secondary analyses: 
a. Re-run steps 5 and 6 as follows and populate Supplemental Table S1:  
i. Unadjusted (i.e., “Crude” analysis, Cox regression with no covariate 
adjustment)  
ii. Multivariable-adjusted (Cox regression with Poissonization with 
adjustment for all covariates included in the estimation of the PS),  
iii. PS adjusted (Cox regression with Poissonization with PS used as a 
covariate in the model, adjusted for deciles of the PS),  
iv. PS stratification (Cox regression with Poissonization within strata of 
deciles of the PS to estimate stratum-specific estimates of treatment 

8 
 
effect. Produce and report a pooled estimate [not stratum-specific] across 
stratum to estimate an overall treatment effect via the method of 
Imbens8).  
v. PS matching (Cox regression with Poissonization within a 1:1 PS 
matched (greedy algorithm, nearest neighbor matching with a caliper size 
equal to 0.2 of the standard deviation of the logit of the PS without 
replacement).  
vi. Inverse probability of treatment weighting (IPTW) (Weighted Cox 
regression with Poissonization using stabilized, traditional IPTW with 
truncation at 99th percentile). 
vii. Subgroup analyses. The PS and matching weights will need to be 
reproduced within each subgroup for each subgroup analysis. Populate 
Supplemental Table S2 with results of all subgroup analyses. 
1. Stratify the population by the total number of antihypertensive 
medications in the regimen (i.e., 1, 2, 3, ≥4). Repeat primary 
analysis within these strata (i.e., Steps 5 and 6 above only). 
2. Create subgroups of the population by age (<40, 40 to <50, 50 to 
<60, 60 to <70 and ≥70 years), sex (male and female), race-
ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, 
Asian), and body mass index (<18.5 kg/m2, 18.5-<25 kg/m2 , 25-
<30 kg/m2 , and ≥30 kg/m2). Repeat primary analysis within each 
subgroup (i.e., Steps 5 and 6 above only). 
3. Stratify the population by tertiles of Modified Therapeutic Intensity 
Score of the medication defining the main exposure. Repeat the 
primary analysis within each tertile (i.e., Steps 5 and 6 above 
only). 
viii. Sensitivity analysis varying the exposure definition. The PS and matching 
weights will need to be reproduced within each group under each 
alternative definition. Populate Supplemental Table S3 with results. 
1. Re-define the primary exposure according to the alterative 
definitions listed in Appendix C. The alternative definition will only 
apply to the primary exposure of interest. For example, if a patient 
is taking an ACEI and a calcium channel blocker, the definition will 
only be applied to the ACEI. For the non-ACEI/ARB-based 

9 
 
regimen group, the alternative definition must hold true for at least 
one of the medications in the regimen.  
2. Re-categorize Veterans into exposure groups based on each 
definition. 
3. Recalculate primary and secondary outcomes under each 
alternative exposure definition (i.e., Steps 5 and 6 above only). 
8. Secondary analyses: 
a. Repeat the primary analysis (i.e., Step 5 only) for all negative control outcomes, 
separately. See Appendix D for definitions of negative control outcomes. 
Populate Supplemental Table S4. 
b. Perform methods described by Vanderweele9 to describe the value of the joint 
minimum strength of association on the risk ratio scale that an unmeasured 
confounder must have with the treatment and outcome to fully explain away the 
observed treatment-outcome association and generate Supplemental Figure S3. 
c. Perform negative control calibration on the estimates generated in the primary 
analysis to adjust for residual bias using the control outcome calibration 
approach by Tchetgen Tchetgen.10 
 
Aim 1.2 
1. Calculate baseline patient characteristics (Appendix B) for ACEI users and ARB users, 
separately. Populate Table 3, left panel (“before weighting”).  
2. Generate PS for being a user of an ACEI vs. an ARB using generalized boosted 
regression models as a function of baseline covariates.1,2 The algorithm should minimize 
standardized mean differences in covariates between exposure groups in the PS-
weighted population.3 Generate Supplemental Figure S4, which shows the distribution of 
PSs among outpatient Veterans who are hospitalized for COVID-19 between the ACEI 
users vs. ARB users. 
3. Use the final PS generated in step 2 to calculate each study-eligible Veteran’s matching 
weight.  
4. Verify covariate balance in the matching weighted population using the Kolmogorov-
Smirnov metric4,5 and calculate absolute standardized mean differences. Populate Table 
3, right panel (“after weighting”). Generate Supplemental Figure S5. 
5. Primary analysis: Apply matching-weighted Cox regression with Poissonization6 to 
estimate the causal marginal hazard ratio comparing the primary outcome (time to all-

10 
 
cause hospitalization or all-cause mortality) and secondary outcomes as appropriate 
between medication exposure groups (ACEI users vs. ARB users). Populate Table 4 
and generate Figure 4. 
6. Perform bootstrap resampling7 to generate 95% confidence intervals using 2-sided alpha 
= 0.025 for the primary outcome and 2-sided alpha = 0.05 for the secondary outcomes.  
7. Secondary analyses: 
a. Re-run steps 5 and 6 as follows and populate Supplemental Table S5:  
i. Unadjusted (i.e., “Crude” analysis, Poisson regression with no covariate 
adjustment)  
ii. Multivariable-adjusted (Cox regression with Poissonization with 
adjustment for all covariates included in the estimation of the PS),  
iii. PS adjusted (Cox regression with Poissonization with PS used as a 
covariate in the model, adjusted for deciles of the PS),  
iv. PS stratification (Cox regression with Poissonization within strata of PS to 
estimate stratum-specific estimates of treatment effect. Produce and 
report a pooled estimate [not stratum-specific] across stratum to estimate 
an overall treatment effect via the method of Imbens8).  
v. PS matching (Cox regression with Poissonization within a 1:1 PS 
matched (greedy algorithm, nearest neighbor matching with a caliper size 
equal to 0.2 of the standard deviation of the logit of the PS without 
replacement).  
vi. Inverse propensity treatment weighting (IPTW) (Weighted Cox regression 
with Poissonization using stabilized, traditional IPTW with truncation at 
99th percentile). 
vii. Subgroup analyses. The PS and matching weights will need to be 
reproduced within each subgroup for each subgroup analysis. Populate 
Supplemental Table S6 with results of all subgroup analyses. 
1. Stratify the population by the total number of antihypertensive 
medications in the regimen (i.e., 1, 2, 3, ≥4). Repeat primary 
analysis within these strata (i.e., Steps 5 and 6 above only). 
2. Create subgroups of the population by age (<40, 40 to <50, 50 to 
<60, 60 to <70 and ≥70 years), sex (male and female), race-
ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, 
Asian), and body mass index (<18.5 kg/m2, 18.5-<25 kg/m2 , 25-

11 
 
<30 kg/m2 , and ≥30 kg/m2). Repeat primary analysis within each 
subgroup (i.e., Steps 5 and 6 above only). 
3. Stratify the population by tertiles of Modified Therapeutic Intensity 
Score of the medication defining the main exposure. Repeat the 
primary analysis within each tertile (i.e., Steps 5 and 6 above 
only). 
viii. Sensitivity analysis varying the exposure definition. The PS and matching 
weights will need to be reproduced within each group under each 
alternative definition. Populate Supplemental Table S7 with results. 
1. Re-define the primary exposure according to the alterative 
definitions listed in Appendix C. The alternative definition will only 
apply to the primary exposure of interest. For example, if a patient 
is taking an ACEI and a calcium channel blocker, the definition will 
only be applied to the ACEI. For the non-ACEI/ARB-based 
regimen group, the alternative definition must hold true for at least 
one of the medications in the regimen.  
2. Re-categorize Veterans into exposure groups based on each 
definition. 
3. Recalculate primary and secondary outcomes under each 
alternative exposure definition (i.e., Steps 5 and 6 above only). 
8. Secondary analyses: 
a. Repeat the primary analysis for all negative control outcomes, separately. See 
Appendix D for definitions of negative control outcomes. Populate Supplemental 
Table S8. 
b. Perform methods described by Vanderweele9 to describe the value of the joint 
minimum strength of association on the risk ratio scale that an unmeasured 
confounder must have with the treatment and outcome to fully explain away the 
observed treatment-outcome association and generate Supplemental Figure S6. 
c. Perform negative control calibration on the estimates generated in the primary 
analysis to adjust for residual bias using the control outcome calibration 
approach by Tchetgen Tchetgen.10 
 

12 
 
AIM 2  
Study Schema: 
Aim 2.1: Among Veterans with treated hypertension and without compelling indications* 
who are hospitalized for COVID-19, compare all-cause mortality rates between current 
users of a range of doses of ACEI/ARB- vs. non-ACEI/ARB-based regimens. 
 
 
*Diabetes, chronic kidney disease, heart failure, coronary heart disease, and history of stroke. 
 
 
Secondary analyses: time-varying 
treatment, confounder assessment window 
(e.g., kidney function)
Days [1, event]
Time
Index date: COVID-19 
hospitalization
Index date identification period: 
January 19, 2020 to present day
Outcome assessment window: Time to 
all-cause mortality or administrative end of 
follow-up (June 1, 2020)
Days [1, event]
Exposure assessment
window:
≥ 1 fill for an ACEI/ARB-
vs. non-ACEI/ARB-
based regimen
Days [-90,0] 
Covariate assessment window
Days [-365,0] for demographics, medication use; all available claims for 
comorbidities
Exclusion assessment window
No hypertension diagnosis, untreated hypertension, presence of compelling 
indications
Days [-365,0] for medication use; all available claims for comorbidities

13 
 
Aim 2.2: Among Veterans with treated hypertension who are hospitalized for COVID-19, 
compare all-cause mortality rates between current users of a range of doses of ACEI- vs. 
ARB-based regimens. 
 
 
 
Secondary analyses: time-varying 
treatment, confounder assessment window 
(e.g., kidney function)
Days [1, event]
Time
Index date: COVID-19 
hospitalization
Index date identification period: 
January 19, 2020 to present day
Outcome assessment window: Time to 
all-cause mortality or administrative end of 
follow-up (June 1, 2020)
Days [1, event]
Exposure assessment
window:
≥ 1 fill for an ACEI vs. 
ARB-based regimen
Days [-90,0] 
Covariate assessment window
Days [-365,0] for demographics, medication use; all available claims for 
comorbidities
Exclusion assessment window
No hypertension diagnosis, untreated hypertension
Days [-365,0] for medication use; all available claims for comorbidities

14 
 
Cohort Creation 
We will create two separate, analysis-ready datasets to carry out the analyses for Aims 2.1 and 
2.2. 
 
2. Aim 2 Cohort Creation  
2.1. Please identify all Veterans who have a hospitalization for COVID-19 between January 
19, 2020 to present-day (see Appendix G for definition of COVID-19-related 
hospitalization). The admit date of hospitalization will be denoted as the index date. 
2.2. Restrict the cohort to Veterans who had ≥1 inpatient or any outpatient encounter in 
each of the two, six-month periods during the 365 days prior to the index date.  
2.3. Restrict the cohort to Veterans without data inconsistencies (test patients, not Veterans, 
multiple death dates in data, or not alive on index date).  
2.4. Restrict the cohort to Veterans with a diagnosis of hypertension at any point prior to 
their index date (see Appendix B for definition of hypertension). 
2.5. Restrict the cohort to Veterans who have an outpatient pharmacy fill in 90 days prior to 
the index date for any antihypertensive medication (see Appendix F). 
2.6. Cohort creation specific for Aim 2.1 
2.6.1. Follow steps 2.1 through 2.5 above. 
2.6.2. Restrict the analysis to Veterans who do not have a history of diabetes, stroke, 
chronic kidney disease, heart failure with reduced ejection fraction, or coronary 
heart disease (see Appendix B for definitions of these conditions). 
2.6.3. Categorize Veterans according to antihypertensive medication use as in steps 
2.6.3.1 and 2.6.3.2 below. The groups should be mutually exclusive. 
2.6.3.1. Identify and categorize Veterans who have a pharmacy fill for an angiotensin 
converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB; 
see Appendix F) within the 90 days prior to the index date. These Veterans 
will be categorized as Veterans with current use of “ACEI/ARB-based 
regimens”. Veterans included in this group may have fills for non-ACEI/ARB 
medications but must also have a fill for an ACEI or an ARB. For each 
Veteran, please create variables to indicate the use of these non-ACEI/ARB 
medication classes in the dataset. 
2.6.3.2. Identify Veterans who have a pharmacy fill an antihypertensive medication 
class other than an ACEI or an ARB AND do not have a fill for an ACEI or an 
ARB (see Appendix F) within the 90 days prior to the index date. These 

15 
 
Veterans will be categorized as Veterans with current use of “non-
ACEI/ARB-based regimens”. Veterans included in this group may have fills 
for multiple non-ACEI/ARB medications. For each Veteran’s regimen, please 
create variables to indicate the use of all medication classes in the dataset. 
2.6.4. Please provide a flow chart with the number of Veterans retained and excluded 
during steps 2.1 through 2.6.3.2. See Figure 5. 
2.7. Cohort creation specific for Aim 2.2  
2.7.1. Follow steps 2.1 through 2.5 above. 
2.7.2. Exclude Veterans who do not have a pharmacy fill for an ACEI or ARB within the 
90 days prior to the index date (see Appendix F). 
2.7.3. Exclude Veterans who have a pharmacy fill for both an ACEI and an ARB within 
the 90 days prior to the index date. 
2.7.4. Identify and categorize Veterans who have a pharmacy fill for ACEI within the 90 
days prior to the index date. These Veterans will be categorized as “ACEI users”. 
Veterans included in this group may have fills for non-ACEI medications (other than 
ACEIs) but must also have a fill for an ACEI. For each Veteran, please create 
variables to indicate the use of these non-ACEI medication classes in the dataset. 
2.7.5. Identify and categorize Veterans who have a pharmacy fill for an ARB within the 
90 days prior to the index date. These Veterans will be categorized as “ARB 
users”. Veterans included in this group may have fills for non-ARB medications 
(other than ARBs) but must also have a fill for an ARB. For each Veteran, please 
create variables to indicate the use of these non-ARB medication classes in the 
dataset. 
2.7.6. Please provide a flow chart with the number of Veterans retained and excluded 
during steps 2.1 through 2.5, then 2.7.1 through 2.7.5. See Figure 7. 

16 
 
Data Management  
7. The data management will be conducted using VINCI. Consistency will be followed for the 
name and levels for variables created for Veterans in each data set. The steps below 
describe the data management for Veterans who are included in the aim 1.1 cohort 
(ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen) and the aim 1.2 cohort 
(ACEI users vs. ARB users). Baseline covariates will be created as listed in Appendix B. 
Please produce separate analyses ready datasets for aims 2.1 and 2.2. 
8. Separate analyses ready datasets for aims 2.1 and 2.2 will be created. 
9. The percent missingness of each variable will be reported in each cohort, separately. 
10. For each cohort, a single variable indicating to which medication exposure group the 
Veteran has been assigned will be created. 
a. Aim 2.1: “ACEI/ARB-based regimen cohort” and “non-ACEI/ARB-based regimen cohort” 
b. Aim 2.2: “ACEI user cohort” and “ARB user cohort”. 
11. For each Veteran, the occurrence of the primary and secondary outcomes will be identified. 
12. For each observation, the time to occurrence or censoring of the primary and secondary 
outcomes in days will be identified, separately. 
13. For secondary analyses within each cohort (see statistical analysis section): 
a. The main exposure will be re-defined using alternative exposure definitions, and patients 
will be re-categorized according to these new definitions (see Appendix H).The primary 
analysis will be repeated. 
b. A variable identifying the occurrence of negative control outcomes will be created. 
c. A variable identifying the time to occurrence or censoring of negative control outcomes 
in days will be created. 
d. A variable for each time-varying covariate as listed in Appendix J will be created. 
14. For the “leave-out-an-essential-ingredient” negative control sensitivity analysis, a separate 
cohort Aims 2.1 and 2.2 will be created with the following modifications: 
a. Change the index-date identification period from “January 19, 2020 to present-day” to 
January 1, 2016, to December 31, 2018. 
b. Change step 1.1 to: All Veterans who have a hospitalization for bacterial pneumonia will 
be identified (see Appendix H for definition of pneumonia hospitalization). The admit 
date of the hospitalization will be denoted as the index date. 
i. For Veterans with more than one eligible bacterial pneumonia hospitalization, the 
first hospitalization will be used. 
c. Label this cohort: “leave-out-an-essential-ingredient negative control sensitivity analysis”

17 
 
Statistical analysis 
 
Aim 2.1 
1. Calculate baseline patient characteristics (Appendix B) for users of ACEI/ARB-based 
regimens and non-ACEI/ARB-based regimens, separately. Populate Table 5, left panel 
(“before weighting”). 
2. Generate propensity scores (PS) for being a user of an ACEI/ARB-based regimen vs. a 
non-ACEI/ARB-based regimen using generalized boosted regression models as a 
function of all baseline covariates.1,2 The algorithm should minimize standardized mean 
differences in covariates between exposure groups in the PS-weighted population.3 
Generate Supplemental Figure S7, which shows the distribution of PSs among Veterans 
who are hospitalized for COVID-19 between the ACEI/ARB-based regimen vs. non-
ACEI/ARB-based regimen cohorts. 
3. Use the final PS generated in step 2 to calculate each study-eligible Veteran’s matching 
weight.  
4. Verify covariate balance in the matching weighted population using the Kolmogorov-
Smirnov metric4,5 and calculate absolute standardized mean differences. Populate Table 
5, right panel (“after weighting”). Generate Supplemental Figure S8. 
5. Primary analysis: Apply matching-weighted Cox regression with Poissonization6 to 
estimate the causal marginal hazard ratio comparing the primary outcome (time to all-
cause mortality) and secondary outcomes as appropriate between medication exposure 
groups (ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens). Populate 
Table 6 and generate Figure 6. 
6. Perform bootstrap resampling7 to generate 95% confidence intervals using 2-sided alpha 
= 0.05 for the primary and secondary outcomes.  
7. Secondary analyses: 
a. Re-run steps 5 and 6 as follows and populate Supplemental Table S9:  
i. Unadjusted (i.e., “Crude” analysis, Poisson regression with no covariate 
adjustment)  
ii. Multivariable-adjusted (Cox regression with Poissonization with 
adjustment for all covariates included in the estimation of the PS),  
iii. PS adjusted (Cox regression with Poissonization with PS used as a 
covariate in the model, adjusted for deciles of the PS),  

18 
 
iv. PS stratification (Cox regression with Poissonization within strata of 
deciles of the PS to estimate stratum-specific estimates of treatment 
effect. Produce and report a pooled estimate [not stratum-specific] across 
stratum to estimate an overall treatment effect via the method of 
Imbens8).  
v. PS matching (Cox regression with Poissonization within a 1:1 PS 
matched (greedy algorithm, nearest neighbor matching with a caliper size 
equal to 0.2 of the standard deviation of the logit of the PS without 
replacement).  
vi. Inverse probability of treatment weighting (IPTW) (Weighted cox 
regression with Poissonization using stabilized, traditional IPTW with 
truncation at 99th percentile) 
vii. Subgroup analyses. The PS and matching weights will need to be 
reproduced within each subgroup for each subgroup analysis. Populate 
Supplemental Table S10 with results of all subgroup analyses. 
1. Stratify the population by the total number of antihypertensive 
medications in the regimen (i.e., 1, 2, 3, ≥4). Repeat primary 
analysis within these strata (i.e., Steps 5 and 6 above only). 
2. Create subgroups of the population by age (<40, 40 to <50, 50 to 
<60, 60 to <70 and ≥70 years), sex (male and female), race-
ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, 
Asian), and body mass index (<18.5 kg/m2, 18.5-<25 kg/m2 , 25-
<30 kg/m2 , and ≥30 kg/m2). Repeat primary analysis within each 
subgroup (i.e., Steps 5 and 6 above only). 
3. Stratify the population by tertiles of Modified Therapeutic Intensity 
Score of the medication defining the main exposure. Repeat the 
primary analysis within each tertile (i.e., Steps 5 and 6 above 
only). 
viii. Sensitivity analysis varying the exposure definition. The PS and matching 
weights will need to be reproduced within each group under each 
alternative definition. Populate Supplemental Table S11 with results. 
1. Re-define the primary exposure according to the alterative 
definitions listed in Appendix H. The alternative definition will only 
apply to the primary exposure of interest. For example, if a patient 

19 
 
is taking an ACEI and a calcium channel blocker, the definition will 
only be applied to the ACEI. For the non-ACEI/ARB-based 
regimen group, the alternative definition must hold true for at least 
one of the medications in the regimen.  
2. Re-categorize Veterans into exposure groups based on each 
definition. 
3. Recalculate primary and secondary outcomes under each 
alternative exposure definition (i.e., Steps 5 and 6 above only). 
8. Secondary analyses: 
a. Repeat the primary analysis for all negative control outcomes, separately. See 
Appendix I for definitions of negative control outcomes. Populate Supplemental 
Table S12. 
b. Perform methods described by Vanderweele9 to describe the value of the joint 
minimum strength of association on the risk ratio scale that an unmeasured 
confounder must have with the treatment and outcome to fully explain away the 
observed treatment-outcome association and generate Supplemental Figure S9. 
c. Perform negative control calibration on the estimates generated in the primary 
analysis to adjust for residual bias using the control outcome calibration 
approach by Tchetgen Tchetgen.10 
d. Leave-out-an-essential-ingredient negative control sensitivity analysis:  
i. This analysis will require one additional step.  
ii. First, generate a PS for being in the COVID-19 cohort vs. non-COVID-19 
cohort.  
iii. Perform PS matching to match each COVID-19 veteran with a non-
COVID-19 Veteran using a 1:1 PS matching (greedy algorithm, nearest 
neighbor matching with a caliper size equal to 0.2 of the standard 
deviation of the logit of the PS without replacement).  
iv. Next, repeat steps 2-6 above to estimate the association of the main 
medication exposure with the study outcomes. Repeat the primary 
analysis in this matching weighted cohort. Populate Supplemental Table 
S13. 
 

20 
 
Aim 2.2 
1. Calculate baseline patient characteristics (Appendix B) for ACEI users and ARB users, 
separately. Populate Table 7, left panel (“before weighting”).  
2. Generate PS for being a user of an ACEI vs. an ARB using generalized boosted 
regression models as a function of baseline covariates.1,2 The algorithm should minimize 
standardized mean differences in covariates between exposure groups in the PS-
weighted population.3 Generate Supplemental Figure S10, which shows the distribution 
of PSs among outpatient Veterans who are hospitalized for COVID-19 between the 
ACEI users vs. ARB users. 
3. Use the final PS generated in step 2 to calculate each study-eligible Veteran’s matching 
weight.  
4. Verify covariate Verify covariate balance in the matching weighted population using the 
Kolmogorov-Smirnov metric4,5 and calculate absolute standardized mean differences. 
Populate Table 7, right panel (“after weighting”). Generate Supplemental Figure S11. 
5. Primary analysis: Apply matching-weighted Cox regression with Poissonization6 to 
estimate the causal marginal hazard ratio comparing the primary outcome (time to all-
cause mortality) and secondary outcomes as appropriate between medication exposure 
groups (ACEI users vs. ARB users). Populate Table 8 and generate Figure 8. 
6. Perform bootstrap resampling7 to generate 95% confidence intervals using 2-sided alpha 
= 0.05 for the primary and secondary outcomes.  
7. Secondary analyses: 
a. Re-run steps 5 and 6 as follows and populate Supplemental Table S14:  
i. Unadjusted (i.e., “Crude” analysis, Cox regression with Poissonization6 
with no covariate adjustment)  
ii. Multivariable-adjusted (Cox regression with Poissonization6 with 
adjustment for all covariates included in the estimation of the PS),  
iii. Propensity-score adjusted (Cox regression with Poissonization6 with PS 
used as a covariate in the model, adjusted for deciles of the PS),  
iv. PS stratification (Cox regression with Poissonization6 within strata of PS 
to estimate stratum-specific estimates of treatment effect. Produce and 
report a pooled estimate [not stratum-specific] across stratum to estimate 
an overall treatment effect via the method of Imbens8).  
v. PS matching (Cox regression with Poissonization6 within a 1:1 PS 
matched (greedy algorithm, nearest neighbor matching with a caliper size 

21 
 
equal to 0.2 of the standard deviation of the logit of the PS without 
replacement).  
vi. IPTW (Weighted Cox regression with Poissonization6 using stabilized, 
traditional IPTW with truncation at 99th percentile) 
vii. Subgroup analyses. The PS and matching weights will need to be 
reproduced within each subgroup for each subgroup analysis. Populate 
Supplemental Table S15 with results of all subgroup analyses. 
1. Stratify the population by the total number of antihypertensive 
medications in the regimen (i.e., 1, 2, 3, ≥4). Repeat primary 
analysis within these strata (i.e., Steps 5 and 6 above only). 
2. Create subgroups of the population by age (<40, 40 to <50, 50 to 
<60, 60 to <70 and ≥70 years), sex (male and female), race-
ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, 
Asian), and body mass index (<18.5 kg/m2, 18.5-<25 kg/m2 , 25-
<30 kg/m2 , and ≥30 kg/m2). Repeat primary analysis within each 
subgroup (i.e., Steps 5 and 6 above only). 
3. Stratify the population by tertiles of Modified Therapeutic Intensity 
Score of the medication defining the main exposure. Repeat the 
primary analysis within each tertile (i.e., Steps 5 and 6 above 
only). 
viii. Sensitivity analysis varying the exposure definition. The PS and matching 
weights will need to be reproduced within each group under each 
alternative definition. Populate Supplemental Table S16 with results. 
1. Re-define the primary exposure according to the alterative 
definitions listed in Appendix H. The alternative definition will only 
apply to the primary exposure of interest. For example, if a patient 
is taking an ACEI and a calcium channel blocker, the definition will 
only be applied to the ACEI. For the non-ACEI/ARB-based 
regimen group, the alternative definition must hold true for at least 
one of the medications in the regimen.  
2. Re-categorize Veterans into exposure groups based on each 
definition. 
3. Recalculate primary and secondary outcomes under each 
alternative exposure definition (i.e., Steps 5 and 6 above only). 

22 
 
8. Secondary analyses: 
a. Repeat the primary analysis for all negative control outcomes, separately. See 
Appendix I for definitions of negative control outcomes. Populate Supplemental 
Table S17. 
b. Perform methods described by Vanderweele9 to describe the value of the joint 
minimum strength of association on the risk ratio scale that an unmeasured 
confounder must have with the treatment and outcome to fully explain away the 
observed treatment-outcome association and generate Supplemental Figure 
S12. 
c. Perform negative control calibration on the estimates generated in the primary 
analysis to adjust for residual bias using the control outcome calibration 
approach by Tchetgen Tchetgen.10 
d. Leave-out-an-essential-ingredient negative control sensitivity analysis: 
i. This analysis will require one additional step.  
ii. First, generate a PS for being in the COVID-19 cohort vs. non-COVID-19 
cohort.  
iii. Perform PS matching to match each COVID-19 veteran with a non-
COVID-19 Veteran using a 1:1 PS matching (greedy algorithm, nearest 
neighbor matching with a caliper size equal to 0.2 of the standard 
deviation of the logit of the PS without replacement).  
iv. Next, repeat steps 2-6 above to estimate the association of the main 
mediation exposure with the study outcomes. Repeat the primary analysis 
in this matching weighted cohort. Populate Supplemental Table S18. 

23 
 
Proposed Tables and Figures 
 

24 
 
Aim 1.1 Main Tables................................................................................................................................. 28 
Table 1: Baseline characteristics of Veterans with treated hypertension without compelling indications 
for an ACEI or ARB who have a positive outpatient SARS-CoV-2 test and are taking ACEI/ARB-based 
regimens vs. non-ACEI/ARB-based regimens (Aim 1.1), before and after propensity score weighting. 28 
Table 2: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among 
SARS-CoV-2 positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based 
regimens (Aim 1.1) overall, matching weight adjusted. ......................................................................... 31 
Aim 1.1 Supplemental Tables ................................................................................................................. 32 
Supplemental Table S1: Incidence rates and hazard ratios for all-cause hospitalization and all-cause 
mortality among SARS-CoV-2 positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens (Aim 1.1) overall, by covariate adjustment strategy. ................................. 32 
Supplemental Table S2: Incidence rates and hazard ratios for all-cause hospitalization and all-cause 
mortality among SARS-CoV-2 positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens (Aim 1.1) in subgroups, matching weight adjusted. ................................... 34 
Supplemental Table S3: Incidence rates and hazard ratios for the primary and secondary outcomes 
among SARS-CoV-2 positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens (Aim 1.1) overall, by varying the definition of the primary medication 
exposure. ............................................................................................................................................... 36 
Supplemental Table S4: One or more inpatient encounter for negative control outcomes among SARS-
CoV-2 positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based 
regimens (Aim 1.1) overall, matching weight adjusted. ......................................................................... 38 
Aim 1.2 Main Tables................................................................................................................................. 39 
Table 3: Baseline characteristics of Veterans with treated hypertension who have a positive outpatient 
SARS-CoV-2 test and are taking ACEI vs. ARB based regimens (Aim 1.2), before and after propensity 
score weighting. ..................................................................................................................................... 39 
Table 4: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among 
SARS-CoV-2 positive outpatient Veterans taking an ACEI vs. ARB based regimens (Aim 1.2) overall, 
matching weight adjusted. ..................................................................................................................... 42 
Aim 1.2 Supplemental Tables ................................................................................................................. 43 
Supplemental Table S5: Incidence rates and hazard ratios for all-cause hospitalization and all-cause 
mortality among SARS-CoV-2 positive outpatient Veterans taking an ACEI vs. ARB based regimens 
(Aim 1.2) overall, by covariate adjustment strategy. .............................................................................. 43 
Supplemental Table S6: Incidence rates and hazard ratios for all-cause hospitalization and all-cause 
mortality among SARS-CoV-2 positive outpatient Veterans taking an ACEI vs. ARB based regimens 
(Aim 1.2) in subgroups, matching weight adjusted. ............................................................................... 45 
Supplemental Table S7: Incidence rates and hazard ratios for the primary and secondary outcomes 
among SARS-CoV-2 positive outpatient Veterans taking an ACEI vs. ARB based regimens (Aim 1.2)  
overall, by varying the definition of the primary medication exposure. .................................................. 47 
Supplemental Table S8: One or more inpatient encounter for negative control outcomes among SARS-
CoV-2 positive outpatient Veterans taking an ACEI vs. an ARB based regimen (Aim 1.2) overall, 
matching weight adjusted. ..................................................................................................................... 49 
Aim 1.1 Main Figures ............................................................................................................................... 50 
Figure 1: Flowchart ................................................................................................................................ 50 

25 
 
Figure 2: Matching weight-adjusted cumulative hazard curves (ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens) for experiencing all-cause hospitalization or mortality among outpatient 
Veterans who are SARS-CoV-2 positive. .............................................................................................. 51 
Aim 1.1 Supplemental Figures ................................................................................................................ 52 
Supplemental Figure S1: Distribution of propensity scores among outpatient Veterans who are SARS-
CoV-2 positive between the ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen cohorts. . 52 
Supplemental Figure S2: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are SARS-CoV-2 positive between the ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens cohorts. ...................................................................................................... 53 
Supplemental Figure S3: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 1.1) ............................................................... 54 
Aim 1.2 Main Figures ............................................................................................................................... 55 
Figure 3: Flowchart ................................................................................................................................ 55 
Figure 4: Matching weight-adjusted cumulative hazard curves (ACEI users vs. ARB users) for 
experiencing all-cause hospitalization or all-cause mortality among outpatient Veterans who are SARS-
CoV-2 positive. ....................................................................................................................................... 56 
Aim 1.2 Supplemental Figures ................................................................................................................ 57 
Supplemental Figure S4: Distribution of propensity scores among outpatient Veterans who are SARS-
CoV-2 positive between ACEI users vs. ARB users. ............................................................................. 57 
Supplemental Figure S5: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are SARS-CoV-2 positive between the ACEI users vs. ARB users. .............. 58 
Supplemental Figure S6: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 1.2) ............................................................... 59 
Aim 2.1 Main Tables................................................................................................................................. 60 
Table 5: Baseline characteristics of Veterans with hypertension without compelling indications for an 
ACEI or ARB hospitalized with COVID-19 and are taking ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens (Aim 2.1), before and after propensity score weighting. ............................ 60 
Table 6: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans 
hospitalized for COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 
2.1) overall, matching weight adjusted. .................................................................................................. 63 
Aim 2.1 Supplemental Tables ................................................................................................................. 64 
Supplemental Table S9: Incidence rates and hazard ratios for the primary and secondary outcomes 
among Veterans hospitalized for COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-
based regimens (Aim 2.1) overall, by covariate adjustment strategy .................................................... 64 
Supplemental Table S10: Incidence rates and hazard ratios for all-cause mortality among Veterans 
hospitalized for COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 
2.1) in subgroups, matching weight adjusted. ........................................................................................ 66 
Supplemental Table S11: Incidence rates and hazard ratios for the primary and secondary outcomes 
among Veterans hospitalized for COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-
based regimens (Aim 2.1) overall, by varying the definition of the primary medication exposure. ........ 68 
Supplemental Table S12: One or more inpatient encounter negative control outcomes among Veterans 
hospitalized for COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 
2.1) overall, matching weight adjusted. .................................................................................................. 71 

26 
 
Supplemental Table S13: All-cause mortality among Veterans hospitalized for bacterial pneumonia vs. 
COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, 
propensity matching weight adjusted. [Leave-out-essential ingredient negative control analysis] ........ 72 
Aim 2.2 Main Tables................................................................................................................................. 73 
Table 7: Baseline characteristics of Veterans with treated hypertension who are hospitalized for 
COVID-19 and taking ACEI vs. ARB-based regimens (Aim 2.2), before and after propensity score 
weighting. ............................................................................................................................................... 73 
Table 8: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans 
hospitalized for COVID-19 taking an ACEI vs. an ARB based regimen (Aim 2.2) overall, matching 
weight adjusted. ..................................................................................................................................... 76 
Aim 2.2 Supplemental Tables ................................................................................................................. 77 
Supplemental Table S14: Incidence rates and hazard ratios for the primary and secondary outcomes 
among Veterans hospitalized for COVID-19 taking an ACEI vs. an ARB based regimen (Aim 2.2) 
overall, by covariate adjustment strategy ............................................................................................... 77 
Supplemental Table S15: Incidence rates and hazard ratios for all-cause hospitalization Veterans 
hospitalized for COVID-19 taking an ACEI vs. ARB based regimens (Aim 1.2) in subgroups, matching 
weight adjusted. ..................................................................................................................................... 79 
Supplemental Table S16: Incidence rates and hazard ratios for the primary and secondary outcomes 
among Veterans hospitalized for COVID-19 taking an ACEI vs. ARB (Aim 2.2) overall, by varying the 
definition of the primary medication exposure. ...................................................................................... 81 
Supplemental Table S17: One or more inpatient encounter for negative control outcomes among 
Veterans hospitalized for COVID-19 taking an ACEI vs. an ARB based regimen (Aim 2.2) overall, 
matching weight adjusted. ..................................................................................................................... 83 
Supplemental Table S18: All-cause mortality among Veterans hospitalized for bacterial pneumonia vs. 
COVID-19 taking ACEI vs. ARB (Aim 2.2) overall, propensity matching weight adjusted. [Leave-out-
essential ingredient negative control analysis] ....................................................................................... 84 
Aim 2.1 Main Figures ............................................................................................................................... 85 
Figure 5: Flowchart ................................................................................................................................ 85 
Figure 6: Matching weight-adjusted cumulative hazard curves (ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens) for experiencing all-cause mortality among outpatient Veterans who are 
hospitalized for COVID-19. .................................................................................................................... 86 
Aim 2.1 Supplemental Figures ................................................................................................................ 87 
Supplemental Figure S7: Distribution of propensity scores among outpatient Veterans who are 
hospitalized for COVID-19 between the ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen 
cohorts. .................................................................................................................................................. 87 
Supplemental Figure S8: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are hospitalized for COVID-19  between the ACEI/ARB-based regimens vs. 
non-ACEI/ARB-based regimens cohorts. .............................................................................................. 88 
Supplemental Figure S9: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 2.1) ............................................................... 89 
Aim 2.2 Main Figures ............................................................................................................................... 90 
Figure 7: Flowchart ................................................................................................................................ 90 
Figure 8: Matching weight-adjusted cumulative hazard curves (ACEI users vs. ARB users) for 
experiencing all-cause mortality among outpatient Veterans who are hospitalized for COVID-19. ....... 91 

27 
 
Aim 2.2 Supplemental Figures ................................................................................................................ 92 
Supplemental Figure S10: Distribution of propensity scores among outpatient Veterans who are 
hospitalized for COVID-19 between ACEI users vs. ARB users. ........................................................... 92 
Supplemental Figure S11: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are hospitalized for COVID-19 between the ACEI users vs. ARB users. ...... 93 
Supplemental Figure S12: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 2.2) ............................................................... 94 
Appendix A: Variables used to define study population (Aim 1). ....................................................... 95 
Appendix B. Variables used to define baseline covariates (Aim 1). ................................................... 96 
Appendix C: Variables used to define main exposures (Aim 1). ....................................................... 103 
Appendix D: Variables used to define outcomes (Aim 1). ................................................................. 104 
Appendix E: List of Antihypertensive Medications by Class ............................................................ 105 
Appendix F: Calculation of Modified Therapeutic Intensity Score ................................................... 108 
Appendix G: Variables used to define study population (Aim 2). ..................................................... 111 
Appendix H. Variables used to define baseline covariates (Aim 2). ......... Error! Bookmark not defined. 
Appendix I: Variables used to define main exposures (Aim 2). ........................................................ 112 
Appendix J: Variables used to define outcomes (Aim 2). .................................................................. 113 
Appendix K: Variables used to define time-varying covariates (Aim 2). .......................................... 114 

28 
 
Aim 1.1 Main Tables 
Table 1: Baseline characteristics of Veterans with treated hypertension without compelling indications for an ACEI or ARB who have a positive 
outpatient SARS-CoV-2 test and are taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1), before and after propensity score 
weighting. 
Patient characteristics 
Before weighting 
After weighting 
Total 
ACEI/ARB-
based regimen 
Non-
ACEI/ARB-
based regimen 
ASMD 
ACEI/ARB-
based regimen 
Non-
ACEI/ARB-
based regimen 
ASMD 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
Demographics 
 
 
 
 
 
 
 
Age (years) 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
<40  
 
 
 
 
 
 
 
40 to <50  
 
 
 
 
 
 
 
50 to <60 
 
 
 
 
 
 
 
60 to <70 
 
 
 
 
 
 
 
≥70 
 
 
 
 
 
 
 
Female sex 
 
 
 
 
 
 
 
Race-ethnicity/ethnicity 
 
 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
 
 
Hispanic 
 
 
 
 
 
 
 
Asian American 
 
 
 
 
 
 
 
Other 
 
 
 
 
 
 
 
Median area-level income 
 
 
 
 
 
 
 
<$25,000  
 
 
 
 
 
 
 
$25,000 - $49,999  
 
 
 
 
 
 
 
$50,000 - $74,999  
 
 
 
 
 
 
 
≥$75,000  
 
 
 
 
 
 
 
Commercial health insurance 
 
 
 
 
 
 
 
Priority group status 
 
 
 
 
 
 
 
1 
 
 
 
 
 
 
 
2 through 8 
 
 
 
 
 
 
 
VISN Region 
 
 
 
 
 
 
 
Northeast  
 
 
 
 
 
 
 
Southeast  
 
 
 
 
 
 
 

29 
 
Continental  
 
 
 
 
 
 
 
Pacific  
 
 
 
 
 
 
 
Current smoker 
 
 
 
 
 
 
 
Vitals and laboratory 
measurements 
 
 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
 
 
Systolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 130 
 
 
 
 
 
 
 
130 - 139 
 
 
 
 
 
 
 
140 - 159 
 
 
 
 
 
 
 
≥ 160 
 
 
 
 
 
 
 
Diastolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 80 
 
 
 
 
 
 
 
80 - 89 
 
 
 
 
 
 
 
90 - 99 
 
 
 
 
 
 
 
≥ 100 
 
 
 
 
 
 
 
Total cholesterol, mg/dL 
 
 
 
 
 
 
 
LDL-C, mg/dL 
 
 
 
 
 
 
 
HDL-C, mg/dL 
 
 
 
 
 
 
 
Triglycerides, mg/dL 
 
 
 
 
 
 
 
Hemoglobin A1c, % 
 
 
 
 
 
 
 
Serum potassium, mEq/L 
 
 
 
 
 
 
 
Serum creatinine, mg/dL 
 
 
 
 
 
 
 
eGFR, mL/min/1.73m2 
 
 
 
 
 
 
 
Comorbidities 
 
 
 
 
 
 
 
Peripheral artery disease 
 
 
 
 
 
 
 
History of renal transplant 
 
 
 
 
 
 
 
Atrial fibrillation 
 
 
 
 
 
 
 
Chronic obstructive pulmonary 
disease 
 
 
 
 
 
 
 

30 
 
Asthma 
 
 
 
 
 
 
 
Depression 
 
 
 
 
 
 
 
Charlson Comorbidity Index, 
mean (SD) 
 
 
 
 
 
 
 
Antihypertensive Medication 
 
 
 
 
 
 
 
ACEI 
 
 
 
 
 
 
 
ARB 
 
 
 
 
 
 
 
CCB 
 
 
 
 
 
 
 
Thiazide diuretic 
 
 
 
 
 
 
 
Alpha-blocker 
 
 
 
 
 
 
 
Beta-blocker 
 
 
 
 
 
 
 
Centrally-acting 
 
 
 
 
 
 
 
Direct vasodilator 
 
 
 
 
 
 
 
Direct renin inhibitor 
 
 
 
 
 
 
 
Aldosterone receptor 
antagonist 
 
 
 
 
 
 
 
Loop diuretic 
 
 
 
 
 
 
 
Potassium-sparing diuretic 
 
 
 
 
 
 
 
Total number of 
antihypertensive medications in 
regimen, median (IQR) 
 
 
 
 
 
 
 
One 
 
 
 
 
 
 
 
Two 
 
 
 
 
 
 
 
Three 
 
 
 
 
 
 
 
Four or more 
 
 
 
 
 
 
 
mTIS of antihypertensive 
regimen, median (IQR) 
 
 
 
 
 
 
 
Other medication use 
 
 
 
 
 
 
 
Current statin use 
 
 
 
 
 
 
 
Current aspirin use 
 
 
 
 
 
 
 
Numbers in table are number (column %) or mean (standard deviation) unless otherwise specified. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; ASMD: absolute standardized mean difference; BP: blood pressure; CCB: 
calcium channel blocker; eGFR: estimated glomerular filtration rate; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; SD: 
standard deviation 
Modified Therapeutic Intensity Score is a standardized measure to measure regimen intensity calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 

31 
 
Table 2: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 positive outpatient 
Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-
based regimen 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Primary Outcome 
 
 
 
 
All-cause hospitalization or all-cause 
mortality  
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
All-cause mortality 
 
 
 
 
ICU admission 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IQR: interquartile range; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2 

32 
 
Aim 1.1 Supplemental Tables 
Supplemental Table S1: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 
positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1) overall, by covariate 
adjustment strategy. 
Outcome 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
All-cause hospitalization or all-
cause mortality 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
All-cause mortality 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ICU admission 
 
 
 
 
Crude 
 
 
 
 

33 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

34 
 
Supplemental Table S2: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 
positive outpatient Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1) in subgroups, matching 
weight adjusted. 
Subgroup 
Matching weight adjusted 
 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-
based regimen 
Hazard Ratio 
 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Pinteraction 
Age, years 
 
 
 
 
 
<40  
 
 
 
 
 
40 to <50  
 
 
 
 
 
50 to <60 
 
 
 
 
 
60 to <70 
 
 
 
 
 
≥70 
 
 
 
 
 
Sex 
 
 
 
 
 
Male 
 
 
 
 
 
Female 
 
 
 
 
 
Race-ethnicity 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
Hispanic 
 
 
 
 
 
Asian American 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
Antihypertensive medications being 
taken 
 
 
 
 
 
One  
 
 
 
 
 
Two  
 
 
 
 
 
Three  
 
 
 
 
 
Four or more  
 
 
 
 
 
Tertile of mTIS 
 
 
 
 
 
T1 (mTIS x-x) 
 
 
 
 
 
T2 (mTIS x-x) 
 
 
 
 
 

35 
 
T3 (mTIS x-x) 
 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; 
Modified Therapeutic Intensity Score is a standardized measure calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 For the purposes of this table, the mTIS represents the Modified Therapeutic Intensity Score of the specified 
drug in the regimen, not the patients entire medication regimen. For example, a patient on lisinopril 20 mg daily would have a mTIS for lisinopril of 
20/40 = 0.5. 

36 
 
Supplemental Table S3: Incidence rates and hazard ratios for the primary and secondary outcomes among SARS-CoV-2 positive 
outpatient Veterans taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1) overall, by varying the definition of 
the primary medication exposure. 
Outcome 
Matching weight adjusted 
 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
N event/N exposed 
(Rate per 100 person 
years) 
N event/N exposed 
(Rate per 100 person 
years) 
(95% CI) 
p-value 
All-cause hospitalization or all-
cause mortality 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
All-cause mortality 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 

37 
 
ICU admission 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
* Defined as: prescription dispensed before the index date with a days’ supply that met or exceeded the index date. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; EHR: electronic health record; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

38 
 
Supplemental Table S4: One or more inpatient encounter for negative control outcomes among SARS-CoV-2 positive outpatient Veterans 
taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 1.1) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI/ARB-based regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
(n = xxxx)  
N (Rate per 100 person 
years) 
(n = xxxx) 
N (Rate per 100 person 
years) 
(95% CI) 
p-value 
Severe gastrointestinal 
bleeding 
 
 
 
 
Urinary tract infection 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 2019 

39 
 
Aim 1.2 Main Tables 
Table 3: Baseline characteristics of Veterans with treated hypertension who have a positive outpatient SARS-CoV-2 test and are taking ACEI vs. ARB 
based regimens (Aim 1.2), before and after propensity score weighting. 
Patient characteristics 
Before weighting 
After weighting 
Total 
ACEI users 
ARB users 
ASMD 
ACEI users 
ARB users 
ASMD 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
Demographics 
 
 
 
 
 
 
 
Age (years) 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
<40  
 
 
 
 
 
 
 
40 to <50  
 
 
 
 
 
 
 
50 to <60 
 
 
 
 
 
 
 
60 to <70 
 
 
 
 
 
 
 
≥70 
 
 
 
 
 
 
 
Female sex 
 
 
 
 
 
 
 
Race-ethnicity/ethnicity 
 
 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
 
 
Hispanic 
 
 
 
 
 
 
 
Asian American 
 
 
 
 
 
 
 
Other 
 
 
 
 
 
 
 
Median area-level income 
 
 
 
 
 
 
 
<$25,000  
 
 
 
 
 
 
 
$25,000 - $49,999  
 
 
 
 
 
 
 
$50,000 - $74,999  
 
 
 
 
 
 
 
≥$75,000  
 
 
 
 
 
 
 
Commercial health insurance 
 
 
 
 
 
 
 
Priority group status 
 
 
 
 
 
 
 
1 
 
 
 
 
 
 
 
2 through 8 
 
 
 
 
 
 
 
VISN Region 
 
 
 
 
 
 
 
Northeast  
 
 
 
 
 
 
 
Southeast  
 
 
 
 
 
 
 
Continental  
 
 
 
 
 
 
 
Pacific  
 
 
 
 
 
 
 

40 
 
Current smoker 
 
 
 
 
 
 
 
Vitals and laboratory 
measurements 
 
 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
 
 
Systolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 130 
 
 
 
 
 
 
 
130 - 139 
 
 
 
 
 
 
 
140 - 159 
 
 
 
 
 
 
 
≥ 160 
 
 
 
 
 
 
 
Diastolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 80 
 
 
 
 
 
 
 
80 - 89 
 
 
 
 
 
 
 
90 - 99 
 
 
 
 
 
 
 
≥ 100 
 
 
 
 
 
 
 
Total cholesterol, mg/dL 
 
 
 
 
 
 
 
LDL-C, mg/dL 
 
 
 
 
 
 
 
HDL-C, mg/dL 
 
 
 
 
 
 
 
Triglycerides, mg/dL 
 
 
 
 
 
 
 
Hemoglobin A1c, % 
 
 
 
 
 
 
 
Serum potassium, mEq/L 
 
 
 
 
 
 
 
Serum creatinine, mg/dL 
 
 
 
 
 
 
 
eGFR, mL/min/1.73m2 
 
 
 
 
 
 
 
Comorbidities 
 
 
 
 
 
 
 
Diabetes 
 
 
 
 
 
 
 
Chronic kidney disease 
 
 
 
 
 
 
 
Heart failure with reduced 
ejection fraction 
 
 
 
 
 
 
 
Coronary heart disease 
 
 
 
 
 
 
 
History of stroke 
 
 
 
 
 
 
 
Peripheral artery disease 
 
 
 
 
 
 
 

41 
 
History of renal transplant 
 
 
 
 
 
 
 
Atrial fibrillation 
 
 
 
 
 
 
 
Chronic obstructive pulmonary 
disease 
 
 
 
 
 
 
 
Asthma 
 
 
 
 
 
 
 
Depression 
 
 
 
 
 
 
 
Charlson Comorbidity Index 
 
 
 
 
 
 
 
Antihypertensive Medication 
 
 
 
 
 
 
 
ACEI 
 
 
 
 
 
 
 
ARB 
 
 
 
 
 
 
 
CCB 
 
 
 
 
 
 
 
Thiazide diuretic 
 
 
 
 
 
 
 
Alpha-blocker 
 
 
 
 
 
 
 
Beta-blocker 
 
 
 
 
 
 
 
Centrally-acting 
 
 
 
 
 
 
 
Direct vasodilator 
 
 
 
 
 
 
 
Direct renin inhibitor 
 
 
 
 
 
 
 
Aldosterone receptor 
antagonist 
 
 
 
 
 
 
 
Loop diuretic 
 
 
 
 
 
 
 
Potassium-sparing diuretic 
 
 
 
 
 
 
 
Total number of 
antihypertensive medications in 
regimen 
 
 
 
 
 
 
 
One 
 
 
 
 
 
 
 
Two 
 
 
 
 
 
 
 
Three 
 
 
 
 
 
 
 
Four or more 
 
 
 
 
 
 
 
mTIS of antihypertensive 
regimen, median (IQR) 
 
 
 
 
 
 
 
Other medication use 
 
 
 
 
 
 
 
Current statin use 
 
 
 
 
 
 
 
Current aspirin use 
 
 
 
 
 
 
 
Numbers in table are number (column %) or mean (standard deviation) unless otherwise specified. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; ASMD: absolute standardized mean difference; BP: blood pressure; CCB: 
calcium channel blocker; eGFR: estimated glomerular filtration rate; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; SD: 
standard deviation 

42 
 
Table 4: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 positive outpatient 
Veterans taking an ACEI vs. ARB based regimens (Aim 1.2) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI users 
ARB users 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Primary Outcome 
 
 
 
 
All-cause hospitalization or all-cause 
mortality  
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
All-cause mortality 
 
 
 
 
ICU admission 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IQR: interquartile range;  

43 
 
Aim 1.2 Supplemental Tables 
Supplemental Table S5: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 
positive outpatient Veterans taking an ACEI vs. ARB based regimens (Aim 1.2) overall, by covariate adjustment strategy. 
Outcome 
ACEI user 
ARB user 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
All-cause hospitalization or all-
cause mortality  
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
All-cause mortality 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ICU admission 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 

44 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

45 
 
Supplemental Table S6: Incidence rates and hazard ratios for all-cause hospitalization and all-cause mortality among SARS-CoV-2 
positive outpatient Veterans taking an ACEI vs. ARB based regimens (Aim 1.2) in subgroups, matching weight adjusted. 
Subgroup 
Matching weight adjusted 
 
ACEI user 
ARB user 
Hazard Ratio 
 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Pinteraction 
Age, years 
 
 
 
 
 
<40  
 
 
 
 
 
40 to <50  
 
 
 
 
 
50 to <60 
 
 
 
 
 
60 to <70 
 
 
 
 
 
≥70 
 
 
 
 
 
Sex 
 
 
 
 
 
Male 
 
 
 
 
 
Female 
 
 
 
 
 
Race-ethnicity 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
Hispanic 
 
 
 
 
 
Asian American 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
Antihypertensive medications being 
taken 
 
 
 
 
 
One  
 
 
 
 
 
Two  
 
 
 
 
 
Three  
 
 
 
 
 
Four or more  
 
 
 
 
 
Tertile of mTIS 
 
 
 
 
 
T1 (mTIS x-x) 
 
 
 
 
 
T2 (mTIS x-x) 
 
 
 
 
 
T3 (mTIS x-x) 
 
 
 
 
 

46 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2 
Modified Therapeutic Intensity Score is a standardized measure calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 For the purposes of this table, the mTIS represents the Modified Therapeutic Intensity Score of the specified 
drug in the regimen, not the patients entire medication regimen. For example, a patient on lisinopril 20 mg daily would have a mTIS for lisinopril of 
20/40 = 0.5. 

47 
 
Supplemental Table S7: Incidence rates and hazard ratios for the primary and secondary outcomes among SARS-CoV-2 positive 
outpatient Veterans taking an ACEI vs. ARB based regimens (Aim 1.2)  overall, by varying the definition of the primary medication 
exposure. 
Outcome 
Matching weight adjusted 
 
ACEI user 
ARB user 
Hazard Ratio 
 
N event/N exposed 
(Rate per 100 person 
years) 
N event/N exposed 
(Rate per 100 person 
years) 
(95% CI) 
p-value 
All-cause hospitalization or all-
cause mortality  
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
Secondary Outcomes 
 
 
 
 
All-cause hospitalization 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
All-cause mortality 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 

48 
 
ICU admission 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
* Defined as: prescription dispensed before the index date with a days’ supply that met or exceeded the index date. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; EHR: electronic health record; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

49 
 
Supplemental Table S8: One or more inpatient encounter for negative control outcomes among SARS-CoV-2 positive outpatient Veterans 
taking an ACEI vs. an ARB based regimen (Aim 1.2) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI users 
ARB users 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 person 
years) 
(n = xxxx) 
N (Rate per 100 person 
years) 
(95% CI) 
p-value 
Severe gastrointestinal 
bleeding 
 
 
 
 
Urinary tract infection 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 2019 

50 
 
Aim 1.1 Main Figures 
Figure 1: Flowchart 
Editable from: https://drive.google.com/file/d/1DHhWPAe9VxUXFrSbvQjbtoFxdarIlmv4/view?usp=sharing   
VeWeUaQV ZiWh SRViWiYe SARS-CRV-2 WeVW
beWZeeQ JaQXaU\ 19, 2020 WR SUeVeQW-da\ (iQde[
daWe)
N = [[[[[
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cUiWeUia
Q = [[[[[
E[cOXded: VeWeUaQV ZhR dR QRW PeeW cRQWiQXRXV
eQUROOPeQW cUiWeUia
Q = [[[[[
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Q = [[[[[
E[cOXded: VeWeUaQV ZiWh daWa iQcRQViVWeQcieV¬
Q = [[[[[
VeWeUaQV ZiWh h\SeUWeQViRQ diagQRViV
Q = [[[[[
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diagQRViV
Q = [[[[[
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aQWih\SeUWeQViYe PedicaWiRQ iQ Whe 90 da\V SUiRU
WR Whe iQde[ daWe
Q = [[[[[
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Q = [[[[[
VeWeUaQV ZiWhRXW cRPSeOOiQg
cRPRUbid cRQdiWiRQV fRU ACEI/ARB
Q = [[[[[
VeWeUaQV WaNiQg ACEI- RU
ARB-baVed
aQWih\SeUWeQViYe
UegiPeQV
Q = [[[[[
VeWeUaQV WaNiQg QRQ-
ACEI- RU ARB-baVed
aQWih\SeUWeQViYe
UegiPeQV
Q = [[[[[
E[cOXded: VeWeUaQV ZhR haYe cRPSeOOiQg
iQdicaWiRQV fRU aQ ACEI RU ARB
Q = [[[[[
VeWeUaQV ZhR WeVW SRViWiYe fRU SARS-CRV-2 iQ
Whe RXWSaWieQW VeWWiQg
Q = [[[[[
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Whe 7 da\V befRUe Whe daWe Rf Whe SRViWiYe SARS-
CRV-2 WeVW
Q = [[[[[

51 
 
Figure 2: Matching weight-adjusted cumulative hazard curves (ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens) for 
experiencing all-cause hospitalization or mortality among outpatient Veterans who are SARS-CoV-2 positive. 
ACEI/ARB-based regimens
Non-ACEI/ARB-based regimens
Days
0         5          10        15       20        25         30
A. Primary Outcome
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
B. All-cause hospitalization
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
C. All-cause mortality
HR: x.xx
(95% CI x.xx, x.xx)
Cumulative Hazard
Cumulative Hazard
Cumulative Hazard
No. at Risk
ACEI/ARB
n
n
n
n
n
n
n
Non-
ACEI/ARB
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
ACEI/ARB-based regimens
Non-ACEI/ARB-based regimens
ACEI/ARB-based regimens
Non-ACEI/ARB-based regimens

52 
 
Aim 1.1 Supplemental Figures 
Supplemental Figure S1: Distribution of propensity scores among outpatient Veterans who are SARS-
CoV-2 positive between the ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen cohorts. 
ACEI/ARB-based regimens
Non-ACEI/ARB-based regimens

53 
 
Supplemental Figure S2: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are SARS-CoV-2 positive between the ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens cohorts. 
 
 
 
*Figure will be updated with covariates on left using the same list from Table 1.

54 
 
Supplemental Figure S3: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 1.1) 

55 
 
Aim 1.2 Main Figures 
Figure 3: Flowchart 
Editable from: https://drive.google.com/file/d/1qGpyHEy9x1Uc0EbrJdi5VXkSL37Jx2Ng/view?usp=sharing  
VeWeUaQV ZiWh SRViWiYe SARS-CRV-2 WeVW
beWZeeQ JaQXaU\ 19, 2020 WR SUeVeQW-da\ (iQde[
daWe)
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cUiWeUia
Q = [[[[[
E[clXded: VeWeUaQV ZhR dR QRW PeeW cRQWiQXRXV
eQURllPeQW cUiWeUia
Q = [[[[[
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Q = [[[[[
E[clXded: VeWeUaQV ZiWh daWa iQcRQViVWeQcieV¬
Q = [[[[[
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Q = [[[[[
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Q = [[[[[
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Q = [[[[[
VeWeUaQV ZhR aUe ACEI RU ARB
XVeUV¬
Q = [[[[[
VeWeUaQV ZhR aUe ACEI
XVeUV
Q = [[[[[
VeWeUaQV ZhR aUe ARB
XVeUV
Q = [[[[[
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aQ ACEI RU ARB iQ Whe 90 da\V SUiRU WR Whe iQde[
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Q = [[[[[
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Whe RXWSaWieQW VeWWiQg
Q = [[[[[
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Whe 7 da\V befRUe Whe daWe Rf Whe SRViWiYe SARS-
CRV-2 WeVW
Q = [[[[[
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aQ ACEI aQd aQ ARB iQ Whe 90 da\V SUiRU WR Whe
iQde[ daWe
Q = [[[[[

56 
 
Figure 4: Matching weight-adjusted cumulative hazard curves (ACEI users vs. ARB users) for experiencing all-cause hospitalization or 
all-cause mortality among outpatient Veterans who are SARS-CoV-2 positive. 
ACEI users
ARB users
Days
0         5          10        15       20        25         30
A. Primary Outcome
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
B. All-cause hospitalization
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
C. All-cause mortality
HR: x.xx
(95% CI x.xx, x.xx)
Cumulative Hazard
Cumulative Hazard
Cumulative Hazard
No. at Risk
ACEI
n
n
n
n
n
n
n
ARB
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
ACEI users
ARB users
ACEI users
ARB users

57 
 
Aim 1.2 Supplemental Figures 
Supplemental Figure S4: Distribution of propensity scores among outpatient Veterans who are SARS-
CoV-2 positive between ACEI users vs. ARB users. 
ACEI users
ARB users

58 
 
Supplemental Figure S5: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are SARS-CoV-2 positive between the ACEI users vs. ARB users. 
 
 
 
*Figure will be updated with covariates on left using the same list from Table 1.

59 
 
Supplemental Figure S6: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 1.2) 

60 
 
Aim 2.1 Main Tables 
Table 5: Baseline characteristics of Veterans with hypertension without compelling indications for an ACEI or ARB hospitalized with COVID-19 and are 
taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1), before and after propensity score weighting. 
Patient characteristics 
Before weighting 
After weighting 
Total 
ACEI/ARB-
based regimen 
Non-
ACEI/ARB-
based regimen 
ASMD 
ACEI/ARB-
based regimen 
Non-
ACEI/ARB-
based regimen 
ASMD 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
Demographics 
 
 
 
 
 
 
 
Age (years) 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
<40  
 
 
 
 
 
 
 
40 to <50  
 
 
 
 
 
 
 
50 to <60 
 
 
 
 
 
 
 
60 to <70 
 
 
 
 
 
 
 
≥70 
 
 
 
 
 
 
 
Female sex 
 
 
 
 
 
 
 
Race-ethnicity/ethnicity 
 
 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
 
 
Hispanic 
 
 
 
 
 
 
 
Asian American 
 
 
 
 
 
 
 
Other 
 
 
 
 
 
 
 
Current smoker 
 
 
 
 
 
 
 
Vitals and laboratory 
measurements 
 
 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
 
 
Systolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 130 
 
 
 
 
 
 
 
130 - 139 
 
 
 
 
 
 
 

61 
 
140 - 159 
 
 
 
 
 
 
 
≥ 160 
 
 
 
 
 
 
 
Diastolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 80 
 
 
 
 
 
 
 
80 - 89 
 
 
 
 
 
 
 
90 - 99 
 
 
 
 
 
 
 
≥ 100 
 
 
 
 
 
 
 
Total cholesterol, mg/dL 
 
 
 
 
 
 
 
LDL-C, mg/dL 
 
 
 
 
 
 
 
HDL-C, mg/dL 
 
 
 
 
 
 
 
Triglycerides, mg/dL 
 
 
 
 
 
 
 
Hemoglobin A1c, % 
 
 
 
 
 
 
 
Serum potassium, mEq/L 
 
 
 
 
 
 
 
Serum creatinine, mg/dL 
 
 
 
 
 
 
 
eGFR, mL/min/1.73m2 
 
 
 
 
 
 
 
Comorbidities 
 
 
 
 
 
 
 
Peripheral artery disease 
 
 
 
 
 
 
 
History of renal transplant 
 
 
 
 
 
 
 
Atrial fibrillation 
 
 
 
 
 
 
 
Chronic obstructive pulmonary 
disease 
 
 
 
 
 
 
 
Asthma 
 
 
 
 
 
 
 
Depression 
 
 
 
 
 
 
 
Charlson Comorbidity Index, 
mean (SD) 
 
 
 
 
 
 
 
Antihypertensive Medication 
 
 
 
 
 
 
 
ACEI 
 
 
 
 
 
 
 
ARB 
 
 
 
 
 
 
 
CCB 
 
 
 
 
 
 
 
Thiazide diuretic 
 
 
 
 
 
 
 
Alpha-blocker 
 
 
 
 
 
 
 
Beta-blocker 
 
 
 
 
 
 
 
Centrally-acting 
 
 
 
 
 
 
 
Direct vasodilator 
 
 
 
 
 
 
 
Direct renin inhibitor 
 
 
 
 
 
 
 

62 
 
Aldosterone receptor 
antagonist 
 
 
 
 
 
 
 
Loop diuretic 
 
 
 
 
 
 
 
Potassium-sparing diuretic 
 
 
 
 
 
 
 
Total number of 
antihypertensive medications in 
regimen, median (IQR) 
 
 
 
 
 
 
 
One 
 
 
 
 
 
 
 
Two 
 
 
 
 
 
 
 
Three 
 
 
 
 
 
 
 
Four or more 
 
 
 
 
 
 
 
mTIS of antihypertensive 
regimen, median (IQR) 
 
 
 
 
 
 
 
Other medication use 
 
 
 
 
 
 
 
Current statin use 
 
 
 
 
 
 
 
Current aspirin use 
 
 
 
 
 
 
 
Numbers in table are number (column %) or mean (standard deviation) unless otherwise specified. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; ASMD: absolute standardized mean difference; BP: blood pressure; CCB: 
calcium channel blocker; eGFR: estimated glomerular filtration rate; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; SD: 
standard deviation 
Modified Therapeutic Intensity Score is a standardized measure to measure regimen intensity calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 

63 
 
Table 6: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for COVID-19 taking 
ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-
based regimen 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Primary Outcome 
 
 
 
 
All-cause mortality  
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, median 
(IQR) 
 
 
 
 
ICU admission 
 
 
 
 
Dialysis 
 
 
 
 
Mechanical ventilation 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IQR: interquartile range; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2 

64 
 
Aim 2.1 Supplemental Tables 
Supplemental Table S9: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for 
COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, by covariate adjustment strategy 
Outcome 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
All-cause mortality  
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, 
median (IQR) 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ICU admission 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Dialysis 
 
 
 
 
Crude 
 
 
 
 

65 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Mechanical ventilation 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

66 
 
Supplemental Table S10: Incidence rates and hazard ratios for all-cause mortality among Veterans hospitalized for COVID-19 taking 
ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) in subgroups, matching weight adjusted. 
Subgroup 
Matching weight adjusted 
 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-
based regimen 
Hazard Ratio 
 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Pinteraction 
Age, years 
 
 
 
 
 
<40  
 
 
 
 
 
40 to <50  
 
 
 
 
 
50 to <60 
 
 
 
 
 
60 to <70 
 
 
 
 
 
≥70 
 
 
 
 
 
Sex 
 
 
 
 
 
Male 
 
 
 
 
 
Female 
 
 
 
 
 
Race-ethnicity 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
Hispanic 
 
 
 
 
 
Asian American 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
Antihypertensive medications being 
taken 
 
 
 
 
 
One  
 
 
 
 
 
Two  
 
 
 
 
 
Three  
 
 
 
 
 
Four or more  
 
 
 
 
 
Tertile of mTIS 
 
 
 
 
 
T1 (mTIS x-x) 
 
 
 
 
 
T2 (mTIS x-x) 
 
 
 
 
 
T3 (mTIS x-x) 
 
 
 
 
 

67 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; 
Modified Therapeutic Intensity Score is a standardized measure calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 For the purposes of this table, the mTIS represents the Modified Therapeutic Intensity Score of the specified 
drug in the regimen, not the patients entire medication regimen. For example, a patient on lisinopril 20 mg daily would have a mTIS for lisinopril of 
20/40 = 0.5. 

68 
 
Supplemental Table S11: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for 
COVID-19 taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, by varying the definition of the 
primary medication exposure. 
Outcome 
Matching weight adjusted 
 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
N event/N exposed 
(Rate per 100 person 
years) 
N event/N exposed 
(Rate per 100 person 
years) 
(95% CI) 
p-value 
All-cause mortality  
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, 
median (IQR) 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
ICU admission 
 
 
 
 

69 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Dialysis 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Mechanical ventilation 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
* Defined as: prescription dispensed before the index date with a days’ supply that met or exceeded the index date. 

70 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; EHR: electronic health record; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

71 
 
Supplemental Table S12: One or more inpatient encounter negative control outcomes among Veterans hospitalized for COVID-19 taking 
ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI/ARB-based regimen 
Non-ACEI/ARB-based 
regimen 
Hazard Ratio 
 
(n = xxxx)  
N (Rate per 100 person 
years) 
(n = xxxx) 
N (Rate per 100 person 
years) 
(95% CI) 
p-value 
Severe gastrointestinal 
bleeding 
 
 
 
 
Urinary tract infection 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 2019 

72 
 
Supplemental Table S13: All-cause mortality among Veterans hospitalized for bacterial pneumonia vs. COVID-19 
taking ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens (Aim 2.1) overall, propensity matching weight 
adjusted. [Leave-out-essential ingredient negative control analysis] 
Cohort 
Matching weight adjusted 
 
ACEI/ARB-based regimen 
 
Non-ACEI/ARB-based 
regimen 
 
HR (95% CI) for 
treatment arm 
within hospitalized 
cohort 
N event/no 
event 
Hazard Ratio 
 
N event/no 
event 
Hazard Ratio 
  
(95% CI) 
(95% CI) 
Hospitalized for bacterial 
pneumonia 
xx/xxxx 
 
 
xx/xxxx 
 
 
 
 
1.0 (reference) 
 
 
HR (95% CI) 
 
HR (95% CI) 
 
 
 
 
p=0.xx 
 
p=0.xx 
Hospitalized for COVID-
19 
xx/xxxx 
 
 
xx/xxxx 
 
 
 
 
HR (95% CI) 
 
 
HR (95% CI) 
 
HR (95% CI) 
 
p=0.xx 
 
 
p=0.xx 
 
p=0.xx 
Measure of interaction on additive scale: Relative excess risk due to interaction (RERI) (95% CI): x.xx (x.xx to x.xx), p=0.xx 
Measure of interaction on multiplicative scale: ratio of hazard ratios (95% CI) = x.xx (x.xx to x.xx), p=0.xx 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: 
Coronavirus Disease 2019; HR: hazard ratio 

73 
 
Aim 2.2 Main Tables 
Table 7: Baseline characteristics of Veterans with treated hypertension who are hospitalized for COVID-19 and taking ACEI vs. ARB-based regimens 
(Aim 2.2), before and after propensity score weighting. 
Patient characteristics 
Before weighting 
After weighting 
Total 
ACEI users 
ARB users 
ASMD 
ACEI users 
ARB users 
ASMD 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
(n = xxxx) 
Demographics 
 
 
 
 
 
 
 
Age (years) 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
<40  
 
 
 
 
 
 
 
40 to <50  
 
 
 
 
 
 
 
50 to <60 
 
 
 
 
 
 
 
60 to <70 
 
 
 
 
 
 
 
≥70 
 
 
 
 
 
 
 
Female sex 
 
 
 
 
 
 
 
Race-ethnicity/ethnicity 
 
 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
 
 
Hispanic 
 
 
 
 
 
 
 
Asian American 
 
 
 
 
 
 
 
Other 
 
 
 
 
 
 
 
Median area-level income 
 
 
 
 
 
 
 
<$25,000  
 
 
 
 
 
 
 
$25,000 - $49,999  
 
 
 
 
 
 
 
$50,000 - $74,999  
 
 
 
 
 
 
 
≥$75,000  
 
 
 
 
 
 
 
Commercial health insurance 
 
 
 
 
 
 
 
Priority group status 
 
 
 
 
 
 
 
1 
 
 
 
 
 
 
 
2 through 8 
 
 
 
 
 
 
 
VISN Region 
 
 
 
 
 
 
 
Northeast  
 
 
 
 
 
 
 
Southeast  
 
 
 
 
 
 
 
Continental  
 
 
 
 
 
 
 
Pacific  
 
 
 
 
 
 
 

74 
 
Current smoker 
 
 
 
 
 
 
 
Vitals and laboratory 
measurements 
 
 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
 
 
Systolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 130 
 
 
 
 
 
 
 
130 - 139 
 
 
 
 
 
 
 
140 - 159 
 
 
 
 
 
 
 
≥ 160 
 
 
 
 
 
 
 
Diastolic BP, mm Hg 
 
 
 
 
 
 
 
Mean (SD) 
 
 
 
 
 
 
 
< 80 
 
 
 
 
 
 
 
80 - 89 
 
 
 
 
 
 
 
90 - 99 
 
 
 
 
 
 
 
≥ 100 
 
 
 
 
 
 
 
Total cholesterol, mg/dL 
 
 
 
 
 
 
 
LDL-C, mg/dL 
 
 
 
 
 
 
 
HDL-C, mg/dL 
 
 
 
 
 
 
 
Triglycerides, mg/dL 
 
 
 
 
 
 
 
Hemoglobin A1c, % 
 
 
 
 
 
 
 
Serum potassium, mEq/L 
 
 
 
 
 
 
 
Serum creatinine, mg/dL 
 
 
 
 
 
 
 
eGFR, mL/min/1.73m2 
 
 
 
 
 
 
 
Comorbidities 
 
 
 
 
 
 
 
Diabetes 
 
 
 
 
 
 
 
Chronic kidney disease 
 
 
 
 
 
 
 
Heart failure with reduced 
ejection fraction 
 
 
 
 
 
 
 
Coronary heart disease 
 
 
 
 
 
 
 
History of stroke 
 
 
 
 
 
 
 
Peripheral artery disease 
 
 
 
 
 
 
 

75 
 
History of renal transplant 
 
 
 
 
 
 
 
Atrial fibrillation 
 
 
 
 
 
 
 
Chronic obstructive pulmonary 
disease 
 
 
 
 
 
 
 
Asthma 
 
 
 
 
 
 
 
Depression 
 
 
 
 
 
 
 
Charlson Comorbidity Index 
 
 
 
 
 
 
 
Antihypertensive Medication 
 
 
 
 
 
 
 
ACEI 
 
 
 
 
 
 
 
ARB 
 
 
 
 
 
 
 
CCB 
 
 
 
 
 
 
 
Thiazide diuretic 
 
 
 
 
 
 
 
Alpha-blocker 
 
 
 
 
 
 
 
Beta-blocker 
 
 
 
 
 
 
 
Centrally-acting 
 
 
 
 
 
 
 
Direct vasodilator 
 
 
 
 
 
 
 
Direct renin inhibitor 
 
 
 
 
 
 
 
Aldosterone receptor 
antagonist 
 
 
 
 
 
 
 
Loop diuretic 
 
 
 
 
 
 
 
Potassium-sparing diuretic 
 
 
 
 
 
 
 
Total number of 
antihypertensive medications in 
regimen 
 
 
 
 
 
 
 
One 
 
 
 
 
 
 
 
Two 
 
 
 
 
 
 
 
Three 
 
 
 
 
 
 
 
Four or more 
 
 
 
 
 
 
 
mTIS of antihypertensive 
regimen, median (IQR) 
 
 
 
 
 
 
 
Other medication use 
 
 
 
 
 
 
 
Current statin use 
 
 
 
 
 
 
 
Current aspirin use 
 
 
 
 
 
 
 
Numbers in table are number (column %) or mean (standard deviation) unless otherwise specified. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; ASMD: absolute standardized mean difference; BP: blood pressure; CCB: 
calcium channel blocker; eGFR: estimated glomerular filtration rate; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; SD: 
standard deviation 

76 
 
Table 8: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for COVID-19 taking 
an ACEI vs. an ARB based regimen (Aim 2.2) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI users 
ARB users 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Primary Outcome 
 
 
 
 
All-cause mortality  
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, median 
(IQR) 
 
 
 
 
ICU admission 
 
 
 
 
Dialysis 
 
 
 
 
Mechanical ventilation 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IQR: interquartile range;  

77 
 
Aim 2.2 Supplemental Tables 
Supplemental Table S14: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for 
COVID-19 taking an ACEI vs. an ARB based regimen (Aim 2.2) overall, by covariate adjustment strategy 
Outcome 
ACEI user 
ARB user 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
All-cause mortality  
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, 
median (IQR) 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ICU admission 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Dialysis 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 

78 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
Mechanical ventilation 
 
 
 
 
Crude 
 
 
 
 
Multivariable-adjusted 
 
 
 
 
Propensity score as covariate 
 
 
 
 
Propensity score stratification 
 
 
 
 
Propensity score matching 
 
 
 
 
IPTW 
 
 
 
 
Matching weight adjusted 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

79 
 
Supplemental Table S15: Incidence rates and hazard ratios for all-cause hospitalization Veterans hospitalized for COVID-19 taking an 
ACEI vs. ARB based regimens (Aim 1.2) in subgroups, matching weight adjusted. 
Subgroup 
Matching weight adjusted 
 
ACEI/ARB-based 
regimen 
Non-ACEI/ARB-
based regimen 
Hazard Ratio 
 
 
(n = xxxx) 
N (Rate per 100 
person years) 
(n = xxxx) 
N (Rate per 100 
person years) 
(95% CI) 
p-value 
Pinteraction 
Age, years 
 
 
 
 
 
<40  
 
 
 
 
 
40 to <50  
 
 
 
 
 
50 to <60 
 
 
 
 
 
60 to <70 
 
 
 
 
 
≥70 
 
 
 
 
 
Sex 
 
 
 
 
 
Male 
 
 
 
 
 
Female 
 
 
 
 
 
Race-ethnicity 
 
 
 
 
 
Non-Hispanic White 
 
 
 
 
 
Non-Hispanic Black 
 
 
 
 
 
Hispanic 
 
 
 
 
 
Asian American 
 
 
 
 
 
Body mass index, kg/m2 
 
 
 
 
 
Underweight (<18.5) 
 
 
 
 
 
Normal weight (18.5 - <25) 
 
 
 
 
 
Overweight (25 - <30) 
 
 
 
 
 
Obese (≥30) 
 
 
 
 
 
Antihypertensive medications being 
taken 
 
 
 
 
 
One  
 
 
 
 
 
Two  
 
 
 
 
 
Three  
 
 
 
 
 
Four or more  
 
 
 
 
 
Tertile of mTIS 
 
 
 
 
 
T1 (mTIS x-x) 
 
 
 
 
 
T2 (mTIS x-x) 
 
 
 
 
 
T3 (mTIS x-x) 
 
 
 
 
 

80 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; ICU: intensive care unit; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2 
Modified Therapeutic Intensity Score is a standardized measure calculated as !!
"
#$%&'$()%* ,-&%
.///.1. 23!4 567(898 ,-&% where n is the number of 
antihypertensive medications.11,12 For the purposes of this table, the mTIS represents the Modified Therapeutic Intensity Score of the specified 
drug in the regimen, not the patients entire medication regimen. For example, a patient on lisinopril 20 mg daily would have a mTIS for lisinopril of 
20/40 = 0.5. 

81 
 
Supplemental Table S16: Incidence rates and hazard ratios for the primary and secondary outcomes among Veterans hospitalized for 
COVID-19 taking an ACEI vs. ARB (Aim 2.2) overall, by varying the definition of the primary medication exposure. 
Outcome 
Matching weight adjusted 
 
ACEI users 
ARB users 
Hazard Ratio 
 
N event/N exposed 
(Rate per 100 person 
years) 
N event/N exposed 
(Rate per 100 person 
years) 
(95% CI) 
p-value 
All-cause mortality  
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Secondary Outcomes 
 
 
 
 
Duration of hospitalization, days, 
median (IQR) 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
ICU admission 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 

82 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Dialysis 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
Mechanical ventilation 
 
 
 
 
1 pharmacy fill in previous 90 days 
(primary analysis) 
 
 
 
 
2 pharmacy fills in the previous 180 
days  
 
 
 
 
1 pharmacy fill in the previous 90 
days and 3 consecutive pharmacy 
fills in the previous 365 days 
 
 
 
 
Medication on-hand at index date* 
 
 
 
 
1 pharmacy fill in the previous 90 
days and medication continued 
during hospitalization 
 
 
 
 
* Defined as: prescription dispensed before the index date with a days’ supply that met or exceeded the index date. 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 
2019; EHR: electronic health record; ICU: intensive care unit; IPTW: inverse propensity treatment weighting; IQR: interquartile range 

83 
 
Supplemental Table S17: One or more inpatient encounter for negative control outcomes among Veterans hospitalized for COVID-19 taking 
an ACEI vs. an ARB based regimen (Aim 2.2) overall, matching weight adjusted. 
Outcome 
Matching weight adjusted 
ACEI users 
ARB users 
Hazard Ratio 
 
(n = xxxx) 
N (Rate per 100 person 
years) 
(n = xxxx) 
N (Rate per 100 person 
years) 
(95% CI) 
p-value 
Severe gastrointestinal 
bleeding 
 
 
 
 
Urinary tract infection 
 
 
 
 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: Coronavirus Disease 2019 

84 
 
Supplemental Table S18: All-cause mortality among Veterans hospitalized for bacterial pneumonia vs. COVID-19 
taking ACEI vs. ARB (Aim 2.2) overall, propensity matching weight adjusted. [Leave-out-essential ingredient negative 
control analysis] 
Cohort 
Matching weight adjusted 
 
ACEI users 
 
ARB users 
 
HR (95% CI) for 
treatment arm 
within hospitalized 
cohort 
N event/no 
event 
Hazard Ratio 
 
N event/no 
event 
Hazard Ratio 
  
(95% CI) 
(95% CI) 
Hospitalized for bacterial 
pneumonia 
xx/xxxx 
 
 
xx/xxxx 
 
 
 
 
1.0 (reference) 
 
 
HR (95% CI) 
 
HR (95% CI) 
 
 
 
 
p=0.xx 
 
p=0.xx 
Hospitalized for COVID-
19 
xx/xxxx 
 
 
xx/xxxx 
 
 
 
 
HR (95% CI) 
 
 
HR (95% CI) 
 
HR (95% CI) 
 
p=0.xx 
 
 
p=0.xx 
 
p=0.xx 
Measure of interaction on additive scale: Relative excess risk due to interaction (RERI) (95% CI): x.xx (x.xx to x.xx), p=0.xx 
Measure of interaction on multiplicative scale: ratio of hazard ratios (95% CI) = x.xx (x.xx to x.xx), p=0.xx 
ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin-II receptor blocker; CI: confidence interval; COVID-19: 
Coronavirus Disease 2019; HR: hazard ratio 

85 
 
Aim 2.1 Main Figures 
Figure 5: Flowchart 
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86 
 
Figure 6: Matching weight-adjusted cumulative hazard curves (ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimens) for 
experiencing all-cause mortality among outpatient Veterans who are hospitalized for COVID-19. 
ACEI/ARB regimens
Non-ACEI/ARB regimens
Days
0         5          10        15       20        25         30
A. All-cause mortality
HR: x.xx
(95% CI x.xx, x.xx)
ACEI/ARB regimens
Non-ACEI/ARB regimens
Days
0         5          10        15       20        25         30
B. ICU admission
HR: x.xx
(95% CI x.xx, x.xx)
ACEI/ARB regimens
Non-ACEI/ARB regimens
Days
0         5          10        15       20        25         30
C. Mechanical Ventilation
HR: x.xx
(95% CI x.xx, x.xx)
Cumulative Hazard
Cumulative Hazard
Cumulative Hazard
No. at Risk
ACEI/ARB
n
n
n
n
n
n
n
Non-
ACEI/ARB
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n

87 
 
Aim 2.1 Supplemental Figures 
Supplemental Figure S7: Distribution of propensity scores among outpatient Veterans who are 
hospitalized for COVID-19 between the ACEI/ARB-based regimens vs. non-ACEI/ARB-based regimen 
cohorts. 
ACEI/ARB-based regimens
Non-ACEI/ARB-based regimens

88 
 
Supplemental Figure S8: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are hospitalized for COVID-19  between the ACEI/ARB-based regimens vs. non-
ACEI/ARB-based regimens cohorts. 
 
 
 
*Figure will be updated with covariates on left using the same list from Table 1.

89 
 
Supplemental Figure S9: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 2.1) 

90 
 
Aim 2.2 Main Figures 
Figure 7: Flowchart 
Editable from: https://drive.google.com/file/d/12g7r7OEd6vecy5NzUFUB4eSD73JAeOEA/view?usp=sharing  
VeWeUaQV hRVSiWaOi]ed fRU COVID-19 beWZeeQ
JaQXaU\ 19, 2020 WR SUeVeQW-da\ (iQde[ daWe)
N = [[[[[
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cUiWeUia
Q = [[[[[
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eQUROOPeQW cUiWeUia
Q = [[[[[
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Q = [[[[[
E[cOXded: VeWeUaQV ZiWh daWa iQcRQViVWeQcieV¬
Q = [[[[[
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Q = [[[[[
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diagQRViV
Q = [[[[[
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aQWih\SeUWeQViYe PedicaWiRQ iQ Whe 90 da\V SUiRU
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Q = [[[[[
VeWeUaQV WaNiQg ACEI-
baVed aQWih\SeUWeQViYe
UegiPeQV
Q = [[[[[
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Q = [[[[[
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aQWih\SeUWeQViYe UegiPeQV
Q = [[[[[

91 
 
Figure 8: Matching weight-adjusted cumulative hazard curves (ACEI users vs. ARB users) for experiencing all-cause mortality among 
outpatient Veterans who are hospitalized for COVID-19. 
ACEI users
ARB users
Days
0         5          10        15       20        25         30
A. All-cause mortality
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
B. ICU Admission
HR: x.xx
(95% CI x.xx, x.xx)
Days
0         5          10        15       20        25         30
C. Mechanical Ventilation
HR: x.xx
(95% CI x.xx, x.xx)
Cumulative Hazard
Cumulative Hazard
Cumulative Hazard
No. at Risk
ACEI
n
n
n
n
n
n
n
ARB
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
n
ACEI users
ARB users
ACEI users
ARB users

92 
 
Aim 2.2 Supplemental Figures 
Supplemental Figure S10: Distribution of propensity scores among outpatient Veterans who are 
hospitalized for COVID-19 between ACEI users vs. ARB users. 
ACEI users
ARB users

93 
 
Supplemental Figure S11: Characteristic balance before and after propensity score weighting among 
outpatient Veterans who are hospitalized for COVID-19 between the ACEI users vs. ARB users. 
 
 
 
*Figure will be updated with covariates on left using the same list from Table 1.

94 
 
Supplemental Figure S12: Value of the joint minimum strength of association on the risk ratio scale that 
an unmeasured confounder must have with the treatment and outcome to fully explain away an 
observed treatment-outcome risk ratio of RR = x.x. (Aim 2.2) 

95 
 
Appendix A: Variables used to define study population (Aim 1). 
Variable 
Definition 
Index date 
Date of the positive SARS-CoV-2 test. 
SARS-CoV-2 positive test 
Veterans with a positive SARS-CoV-2 test between January 19, 2020, to present-day will be identified using the VA’s official 
SARS-CoV-2 phenotype definition, which incorporates testing external to the VA. Patients identified as “VA confirmed” and “VA 
probable” will be categorized as SARS-CoV-2 positive.  
SARS-CoV-2 positive 
outpatients 
Veterans with a positive SARS-CoV-2 test will be identified as above. Then, to capture outpatients who have been tested, 
patients will be excluded if they have been hospitalized within the 7 days before the date of the positive test.  
Hypertension 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. At least 1 inpatient claim with a discharge ICD-9 diagnosis (any position) of 401.x, 403.0x, 403.1x, 403.9x. 
b. ≥2 outpatient claims with an ICD-9 diagnosis code of 401.x, 403.0x, 403.1x, 403.9x in any position at least 30 
days apart 
(b) ICD-10 codes: 
a. 1 inpatient claim with an ICD-10 discharge diagnosis code of I10, I12.0, I12.9 in any discharge diagnosis position 
b. ≥2 outpatient claims with an ICD-10 diagnosis code of I10, I12.0, I12.9 in any position at least 30 days apart 
Treated hypertension 
Having hypertension, as defined above, and currently taking antihypertensive medication, as defined as a pharmacy fill for an 
antihypertensive medication within 90 days prior to the index date (see Appendix E for list of medication classes). 
Compelling indication for ACEI 
or ARB 
Individuals with diabetes, stroke, chronic kidney disease, heart failure with reduced ejection fraction, or coronary heart disease 
as defined in Appendix B will be excluded from the population for Aim 1.1.  

96 
 
Appendix B. Variables used to define baseline covariates (Aim 1).  
Variable 
Definition 
Age 
Age of Veterans calculated on the index date based on the date of birth. 
Sex 
Male or female 
Race-ethnicity 
Non-Hispanic Black, Non-Hispanic White, Hispanic, Asian, and Other/Missing 
Area level income 
Using ZIP and FIPS codes based on data obtained from the American Community Survey. The variable ZCTA was matched to 
ZIP code in the American Community Survey. If ZCTA and ZIP did not match, then FIPS code (county level) from the American 
Community Survey was used. 
Veterans Integrated Service 
Network  
Defined by receipt of care in one of the 23 VISNs. Will be categorized into 4 regions after data query: Northeast, Southeast, 
Continental, and Pacific according to the VA regional offices map.13 The Northeast region is comprised of VISNs 1, 2, 4, 5, 10, 
and 12. The Southeast region is comprised of VISNs 5, 6, 7, 8, 9, and 16. The Continental region is comprised of VISNs 15, 17, 
18, 19, and 23. Finally, the Pacific region is comprised of VISNs 20, 21, and 22. 
Current Smoking 
Any of the following within one year prior to the index date: 
(a) ICD-9 codes: 
a. ≥1 hospitalization with a discharge diagnosis code of tobacco use (ICD-9 CM diagnosis code of 305.1, 649.0x, 
989.84, or V15.82) in any discharge position 
b. ≥1 physician evaluation and management visit with a diagnosis code of tobacco use (ICD-9-CM diagnosis code 
of 305.1, 649.0x, 989.84, or V15.82) in any discharge position 
(b) ICD-19 codes: 
a. ≥1 hospitalization with a discharge diagnosis code of tobacco use (ICD-10 CM diagnosis code of F17.200, 
F17.201, F17.210, F17.211, F17.220, F17.221, F17.290, F17.291, or Z87.891) in any discharge position 
b.  ≥1 outpatient visit with a diagnosis code of tobacco use (ICD-10 CM diagnosis code of F17.200, F17.201, 
F17.210, F17.211, F17.220, F17.221, F17.290, F17.291, or Z87.891) in any discharge position 
(c) ≥1 hospitalization with a discharge diagnosis code or physician evaluation and management visit of tobacco use with a 
CPT code of 99406, 99407, G0436, G0437, G9016, S9453, S4995, G9276, G9458, 1034F, 4004F, 4001F 
(d) ≥1 pharmacy claim for nicotine or varenicline. 
Insurance type 
Coded as government (Medicare, Medicaid), private (all insurance external to Medicare/Medicaid), none, and unknown. 
Priority group status 
Coded as 1 through 9 or multiple. 
Height  
Veteran's height (in m) on the index date or the date closest to the index date during the one-year pre-index period. Retain 
values that are within 3 standard deviations of the mean of all heights for the cohort. For Veterans without observations within 3 
standard deviations of the mean, other values will be accepted as valid if for height, there are at least 2 identical observations. 
Otherwise, code as missing. 
Weight 
Veteran's weight (in kg) on the index date or the date closest to the index date during the one-year pre-index period. Retain 
values that are within 3 standard deviations of the mean of all weights for the cohort. For Veterans without observations within 3 
standard deviations of the mean, other values will be accepted as valid if for weight, there are at least 2 observations within 5 
pounds. Otherwise, code as missing. 
Body mass index 
The patient’s body mass index on or closest to the index date during the one-year pre-index period. Height and weight 
measurements do not need to be on the same day. This variable will be calculated from height and weight observations as 
weight (in kilograms) divided by height (in meters, squared). 

97 
 
Systolic blood pressure 
Most recent proximal SBP value corresponding to an outpatient encounter in cardiology, renal, and primary care settings in the 
one-year pre-index period (including the index date). SBP values will be dropped if any of the following was true: Missing value 
(either SBP or DBP), systolic less than diastolic, systolic >300 mm Hg, and systolic <60 mm Hg. 
Diastolic blood pressure 
Most recent proximal DBP value corresponding to an outpatient encounter in cardiology, renal, and primary care settings in the 
one-year pre-index period (including the index date). DBP values will be dropped if any of the following was true: Missing value 
(either SBP or DBP), diastolic greater than systolic, diastolic <30 mm Hg, and or diastolic >180 mm Hg. 
Heart rate 
Most recent proximal heart rate/pulse value corresponding to an outpatient encounter in the one-year pre-index period (including 
the index date). 
Total cholesterol 
The total cholesterol value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where 
LOINC is '2093-3'. 
HDL-C level 
The HDL-C value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where LOINC is 
'2085-9'. 
LDL-C level 
The LDL-C value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where LOINC is 
'13457-7','18262-6','2089-1','2574-2','9346-8'. 
Triglyceride level 
The triglyceride value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where LOINC 
is '2571-8'. 
Hemoglobin A1c 
The glycated hemoglobin (i.e., “hemoglobin A1c”) value closest to the index date in the one-year pre-index period. Defined using 
OMOP’s mapping where LOINC is '4548-4'. 
Serum creatinine 
The serum creatinine value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where 
LOINC is '33914-3'. 
Estimated glomerular filtration 
rate 
The estimated glomerular filtration rate closest to the index date in the one-year pre-index period. The VA calculates eGFR using 
the Modified Diet in Renal Disease equation.14  
Serum potassium 
The serum potassium value closest to the index date in the one-year pre-index period. Defined using OMOP’s mapping where 
LOINC is '6298-4', '2823-3'. 
Diabetes  
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. At least 1 inpatient claim with a discharge ICD-9 diagnosis (any position) of 250.xx, 357.2, 362.0x, or 366.41. 
b. At least 2 carrier claims, carrier line or outpatient claims with ICD-9 diagnoses (any position) of 250.xx, 357.2, 
362.0x, or 366.41, linked to an ambulatory physician evaluation and management claim, with the 2 claims 
occurring at least 7 days apart. 
(b) ICD-10 codes: 
a. At least 1 inpatient claim with a discharge ICD-10 diagnosis (any position) of 'E0836', 'E08.42', 'E09.36', 'E09.42', 
'E10.10', 'E10.11', 'E10.29', 'E10.311', 'E10.319', 'E10.36', 'E10.39', 'E10.40', 'E10.42', 'E10.51', 'E10.618', 
'E10.620', 'E10.621', 'E10.622', 'E10.628', 'E10.630', 'E10.638', 'E10.641', 'E10.649', 'E10.65', 'E10.69', 'E10.8', 
'E10.9', 'E11.00', 'E11.01', 'E11.29', 'E11.311', 'E11.319', 'E11.329', 'E11.339', 'E11.349', 'E11.359', 'E11.36', 
'E11.39', 'E11.40', 'E11.42', 'E11.51', 'E11.618', 'E11.620', 'E11.621', 'E11.622', 'E11.628', 'E11.630', 'E11.638', 
'E11.641', 'E11.649', 'E11.65', 'E11.69', 'E11.8', 'E11.9', 'E13.10', 'E13.36', 'E13.42'. 

98 
 
b. At least 2 carrier claims, carrier line or outpatient claims with ICD-10 diagnoses (any position) of 'E0836', 'E08.42', 
'E09.36', 'E09.42', 'E10.10', 'E10.11', 'E10.29', 'E10.311', 'E10.319', 'E10.36', 'E10.39', 'E10.40', 'E10.42', 'E10.51', 
'E10.618', 'E10.620', 'E10.621', 'E10.622', 'E10.628', 'E10.630', 'E10.638', 'E10.641', 'E10.649', 'E10.65', 'E10.69', 
'E10.8', 'E10.9', 'E11.00', 'E11.01', 'E11.29', 'E11.311', 'E11.319', 'E11.329', 'E11.339', 'E11.349', 'E11.359', 
'E11.36', 'E11.39', 'E11.40', 'E11.42', 'E11.51', 'E11.618', 'E11.620', 'E11.621', 'E11.622', 'E11.628', 'E11.630', 
'E11.638', 'E11.641', 'E11.649', 'E11.65', 'E11.69', 'E11.8', 'E11.9', 'E13.10', 'E13.36', 'E13.42', linked to an 
ambulatory physician evaluation and management claim, with the 2 claims occurring at least 7 days apart. 
(c) At least 1 pharmacy claim for an oral antidiabetic drug fill or insulin. 
Chronic kidney disease 15,16 
Any of the following using all available claims prior to the index date: 
(c) ICD-9 codes: 
a. At least 1 inpatient claim with a discharge ICD-9 diagnosis (any position) of 250.xx, 357.2, 362.0x, or 366.41. 
b. At least 2 carrier claims, carrier line or outpatient claims with ICD-9 diagnoses (any position) of 250.xx, 357.2, 
362.0x, or 366.41, linked to an ambulatory physician evaluation and management claim, with the 2 claims 
occurring at least 7 days apart. 
(d) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of chronic kidney disease (ICD-10 diagnosis code of ‘A18.11', 
'A52.75', 'C6.49', 'C6.89', 'D30.00', 'D41.00', 'D41.20', 'D59.3', 'E10.21’,  'E10.29', 'E11.21’, 'E11.29', 'E74.8', 'I12.0', 
'I129', 'I13.0', 'I13.10', 'I13.11', 'I13.2', I70.1', 'I72.2', 'K76.7', 'M10.30', 'N00.3', 'N00.8', 'N00.9', 'N01.3', 'N02.2', 
'N03.2', 'N03.3', 'N03.5', 'N03.8', 'N03.9', 'N04.0', 'N04.3', 'N04.4', 'N04.8', 'N04.9', 'N05.2', 'N05.5', 'N05.8', 'N05.9', 
'N08.x', 'N13.30', 'N17.0', 'N17.1', 'N17.2', 'N17.8', 'N17.9', 'N18.1', 'N18.2', 'N18.3', 'N18.4', 'N18.5', 'N18.6', 'N18.9', 
'N19.x', 'N25.0', 'N25.1', 'N25.81', 'N25.89', 'N25.9', 'N26.9','Q61.02', 'Q61.19', 'Q61.2', 'Q61.3', 'Q61.4', 'Q61.5', 
'Q61.8', 'Q62.10', 'Q62.11', 'Q62.12', 'Q62.31', 'Q62.39', 'R94.4') in any discharge diagnosis position.  
b. ≥1 physician evaluation and management visit with a diagnosis code of chronic kidney disease (ICD-10-CM 
diagnosis code of ‘A18.11', 'A52.75', 'C6.49', 'C6.89', 'D30.00', 'D41.00', 'D41.20', 'D59.3', 'E10.21’,  'E10.29', 
'E11.21’, 'E11.29', 'E74.8', 'I12.0', 'I129', 'I13.0', 'I13.10', 'I13.11', 'I13.2', I70.1', 'I72.2', 'K76.7', 'M10.30', 'N00.3', 
'N00.8', 'N00.9', 'N01.3', 'N02.2', 'N03.2', 'N03.3', 'N03.5', 'N03.8', 'N03.9', 'N04.0', 'N04.3', 'N04.4', 'N04.8', 'N04.9', 
'N05.2', 'N05.5', 'N05.8', 'N05.9', 'N08.x', 'N13.30', 'N17.0', 'N17.1', 'N17.2', 'N17.8', 'N17.9', 'N18.1', 'N18.2', 'N18.3', 
'N18.4', 'N18.5', 'N18.6', 'N18.9', 'N19.x', 'N25.0', 'N25.1', 'N25.81', 'N25.89', 'N25.9', 'N26.9','Q61.02', 'Q61.19', 
'Q61.2', 'Q61.3', 'Q61.4', 'Q61.5', 'Q61.8', 'Q62.10', 'Q62.11', 'Q62.12', 'Q62.31', 'Q62.39', 'R94.4') in any position. 
(e) Estimated glomerular filtration rate of <60 mL/min/1.73m2. The eGFR reading used is the most recent within the one-
year pre-index period. To account for data/reading errors, only eGFR values between 0 and 250 will be considered. 
Heart failure with reduced 
ejection fraction 
Defined as left ventricular ejection fraction (LVEF) value <=40% in the one-year pre-index period. If no LVEF measurement is 
available, then we will look for the presence of one of the following using all available claims before the index date: 
 following ICD-10 codes indicating systolic heart failure using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. ≥ 1 inpatient claim with ICD-10 diagnoses (any position) of '428.0x', '428.1x', '428.2x', '428.4x' or 

99 
 
b. ≥ 2 outpatient or carrier claims on separate calendar days with ICD-10 diagnoses (any position) of '428.0x', 
'428.1x', '428.2x', '428.4x' 
(b) ICD-10 codes: 
a. ≥ 1 inpatient claim with ICD-10 diagnoses (any position) of 'I50.1', 'I50.2x', 'I50.4x', 'I50.9', or 
b. ≥ 2 outpatient or carrier claims on separate calendar days with ICD-10 diagnoses (any position) of 'I50.1', 'I50.2x', 
'I50.4x', 'I50.9' 
(c) At least one prescription for Entresto® (sacubitril/valsartan) in the prior 90 days. 
History of CHD 17 
 
 
 
 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. At least 1 inpatient claim with a discharge ICD-9 diagnosis (any position) of 410.xx-414.xx, V45.81 or V45.82. 
b. At least 2 carrier claims, carrier line or outpatient claims with ICD-9 diagnoses (any position) of 410.xx-414.xx, 
V45.81 or V45.82. 
(b) ICD-10 codes: 
a. An inpatient claim diagnosis codes of I20.0, I21.xx, I22.xx, I24.0, I24.8, I24.9, I25.10, I25.110, I25.700, I25.710, 
I25.720, I25.730, I25.750, I25.760, I25.790, I25.810, I25.811, I25.812, I25.3, I25.41, I25.42, Z95.1 or Z9861. 
b. An outpatient or carrier file claim, linked to E&M code, with diagnosis codes of codes I20.0, I21.xx, I22.xx, I24.0, 
I24.8, I24.9, I25.10, I25.110, I25.700, I25.710, I25.720, I25.730, I25.750, I25.760, I25.790, I25.810, I25.811, 
I25.812, I25.3, I25.41, I25.42, Z95.1 or Z98.61. 
 
Veterans who met the definition of a prior coronary revascularization, as defined below, will be also considered to have a history 
of CHD. 
Prior coronary 
revascularization  
Defined by ≥ 1 inpatient or outpatient procedure with a current procedure terminology (CPT) code for coronary revascularization 
(33510-33519, 33521-33523, 33530, 33533-33536, 92920, 92921, 92924, 92925, 92928, 92929, 92933, 92934, 92937, 92938, 
92941, 92943, and 92944), an ICD-9 procedure code of 00.66, 36.0, 36.01-36.19, 36.2, or an ICD-10 procedure code starting 
with any of the following 4 digits: 0210, 0211, 0212, 0213, 0270, 0271, 0272, 0273, 02C0, 02C1, 02C2, 02C3, 3E07 using all 
available claims prior to the index date. In addition to having 1 inpatient or outpatient procedure, Veterans are required to meet 
at least 1 of the following criteria: 
a) Have no inpatient claims with a diagnosis code for acute myocardial infarction (ICD9 codes 410.x0 or 410.x1 or ICD10 
codes I21.xx or I22.xx) within 60 days prior to the procedure. 
b) Have primary discharge diagnosis code for non-elective CHD-related hospitalization prior to the index date (arrhythmia 
[ICD-9 diagnosis code of 427.xx, except 427.5 or ICD-10 diagnosis code of I47.1, I47.2, I47.9, I48.91, I48.92, I49.01, 
I49.02, I49.1, I49.3, I49.40, I49.49, I49.5, I49.8, I49.9, R00.1], cardiac arrest [ICD-9 diagnosis code of 427.5 or ICD-10 
diagnosis code of I46.9], heart failure [ICD-9 diagnosis code of 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 
404.91, 404.93, 428.x or ICD-10 diagnosis code of I11.0, I13.0, I13.2, I50.1, I50.20, I50.21, I50.22, I50.23, I50.30, 
I50.31, I50.32, I50.33, I50.40, I50.41, I50.42, I50.43, I50.9], and unstable angina [ICD-9 diagnosis code of 411.xx or ICD-
10 diagnosis code of I20.0, I24.0, I24.1, I24.8]). 
History of Stroke18 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 

100 
 
a. ≥1 inpatient claim with a discharge ICD-9 diagnosis (primary or secondary position) of 433.x1 or 434.x1. 
b. ≥1 outpatient or carrier claim with ICD-9 diagnoses (any position) of 433.x1 or 434.x1, linked by CLAIM_ID to an 
ambulatory physician evaluation and management claim. 
c. ≥1 claim with ICD-9 diagnoses (any position) of 433.x1 or 434.x1 in other file types (Home Health Agency [HHA], 
durable medical equipment [DME], Hospice, SNF). 
(b) ICD-10 codes: 
a. ≥1 inpatient ICD-10 diagnosis (primary or secondary position) I63.xx 
b. ≥1 outpatient or carrier claim with ICD-10 diagnoses (any position) of I63.xx linked by CLAIM_ID to an ambulatory 
physician evaluation and management claim 
c. ≥1 claim with ICD-10 diagnoses (any position) of I63.xx in other file types (Home Health Agency [HHA], durable 
medical equipment [DME], Hospice, SNF). 
d. ≥ 1 inpatient ICD-10 procedure code in ('03CH0ZZ', '03CH4ZZ', '03CJ0ZZ', '03CJ4ZZ', '03CK0ZZ', '03CK4ZZ', 
'03CL0ZZ', '03CL4ZZ', '03CM0ZZ', '03CM4ZZ', '03CN0ZZ', '03CN4ZZ', '03RH07Z', '03RH0JZ', '03RH0KZ', 
'03RH47Z', '03RH4JZ', '03RH4KZ', '03RJ07Z', '03RJ0JZ', '03RJ0KZ', '03RJ47Z', '03RJ4JZ', '03RJ4KZ',  
'03RK07Z', '03RK0JZ', '03RK0KZ', '03RK47Z', '03RK4JZ', '03RK4KZ', '03RL07Z', '03RL0JZ', '03RL0KZ', 
'03RL47Z', '03RL4JZ', '03RL4KZ', '03RM07Z', '03RM0JZ', '03RM0KZ', '03RM47Z', '03RM4JZ', '03RM4KZ', 
'03RN07Z', '03RN0JZ', '03RN0KZ', '03RN47Z', '03RN4JZ', '03RN4KZ') 
(c) CPT codes: 
a. ≥1 inpatient or outpatient claim with a CPT code for carotid revascularization (35301, 35390, 37215, 37216, 
0005T, 0075T, or 0076). 
History of PAD 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of peripheral vascular disease (ICD-9-CM diagnosis codes 
440.20-440.24, 440.31, 444.2, 443.9, or 444.81) in any position, or  
b. ≥2 physician evaluation and management outpatient or carrier claims with an ICD-9-CM diagnosis code of 
peripheral vascular disease on separate days, or 
c. ≥1 inpatient, outpatient or carrier claim with a CPT code 37205 or 75962.  
(b) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of peripheral vascular disease (ICD-10-CM diagnosis codes 
‘I70.209’, ‘I70.219, ‘I70.229’, ‘I70.25’, ‘I70.269’, ‘I70.499’, ‘I73.9’) or  
b. ≥2 physician evaluation and management outpatient or carrier claims with an ICD-10-CM diagnosis code of 
peripheral vascular disease on separate days, or 
(c) ≥1 inpatient, outpatient or carrier claim with a CPT code 37205 or 75962. 
History of ASCVD 
Defined by a history of CHD, cerebrovascular disease, or peripheral artery disease, as defined above. 
History of renal transplant 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code V42.0 in any position, or  

101 
 
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code V42.0 
(b) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code Z94.0 in any position, or 
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code Z94.0. 
Atrial fibrillation19 
Any of the following using all available claims prior to the index date: 
(c) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code 427.31 in any position, or  
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code 427.31 
(d) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of I48.0, I48.2, I48.91 in any position, or 
≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code I48.0, I48.2, I48.91. 
Chronic obstructive pulmonary 
disease20 
Any of the following using all available claims prior to the index date: 
(e) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code 491-492 or 496 in any position, or  
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code 491-492 or 496 
(f) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of J41-J44 in any position, or 
(a) ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code J41-J44 
Asthma21 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code 493 in any position, or  
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code 493 
(b) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of J45 in any position, or 
(a) ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code J45 
History of depression22 
Any of the following using all available claims prior to the index date: 
(a) ICD-9 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code 296.2, 296.3, 296.5, 300.4, 309.x, 311 in any position, or  
b. ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code 296.2, 296.3, 296.5, 
300.4, 309.x, 311 
(b) ICD-10 codes: 
a. ≥1 inpatient claim with a discharge diagnosis code of F20.4, F31.3-F31.5, F32.x, F33.x, F34.1, F41.2, F43.2in any 
position, or 
(a) ≥2 physician evaluation and management outpatient or carrier claims with a diagnosis code F20.4, F31.3-F31.5, F32.x, 
F33.x, F34.1, F41.2, F43.2 

102 
 
Charlson Comorbidity Index23 
Continuous variable to represent chronic disease burden. Calculated according to methods described in Quan et al (incorporates 
Elixhauser and Deyo comorbidities). 
Current statin use 
Defined as one or more pharmacy fills for a statin in the 90 days prior to each Veteran’s index date (atorvastatin, rosuvastatin, 
simvastatin, fluvastatin, pitavastatin, pravastatin, or lovastatin). 
Current aspirin use 
Defined as one or more pharmacy fills for aspirin in the 90 days prior to each Veteran’s index date.   
Antihypertensive medication 
daily dose 
Calculated for each antihypertensive medication being taken. Described as milligrams of drug taken per day. We will first parse 
the dosage value then use the quantity and days supplied variables to inform the parsed dose value (if partial or multiple pills are 
being taken per day, for example).  
Antihypertensive Modified 
Therapeutic Intensity Score 
Continuous variable calculated for each antihypertensive medication being taken. Calculated using the most proximal 
prescription dispensed in the pre-index period using the daily dose as calculated above, divided by the maximum daily dose per 
the 2017 ACC/AHA blood pressure guideline. See Appendix F. 

103 
 
Appendix C: Variables used to define main exposures (Aim 1). 
Variable 
Definition 
Antihypertensive – non-ACEI 
or ARB-based regimen (Aim 
1.1) 
Defined as one or more pharmacy fills for an oral non-ACEI or ARB medications in the 90 days (± 14 days) prior to each 
Veteran’s index date and categorized by class as aldosterone receptor antagonist, beta-blocker, calcium channel blocker, 
centrally-acting drug, direct arterial vasodilator, direct renin inhibitor, thiazide diuretic, loop diuretic, and potassium sparing 
diuretic. See Appendix E for specific drug names within each class. Exclude non-oral products. 
Antihypertensive – ACEI/ARB-
based regimen (Aim 1.1) 
Defined as one or more pharmacy fills for an oral ACEI or an ARB in the 90 days (± 14 days) prior to each Veteran’s index date. 
See Appendix E for specific drug names within each class. Exclude non-oral products. Exclude sacubitril/valsartan (Brand name: 
Entresto®) from ARB exposures. 
Antihypertensive – ACEI (Aim 
1.2) 
Defined as one or more pharmacy fills for an oral ACEI in the 90 days (± 14 days) prior to each Veteran’s index date. See 
Appendix E for specific drug names within each class. Exclude non-oral products. 
Antihypertensive – ARB (Aim 
1.2) 
Defined as one or more pharmacy fills for an oral ARB in the 90 days (± 14 days) prior to each Veteran’s index date. See 
Appendix E for specific drug names within each class. Exclude non-oral products. Exclude sacubitril/valsartan (Brand name: 
Entresto®) from ARB exposures. 
Antihypertensive medication 
daily dose 
Calculated for each antihypertensive medication being taken. Described as milligrams of drug taken per day. We will first parse 
the dosage value then use the quantity and days supplied variables to inform the parsed dose value (if partial or multiple pills are 
being taken per day, for example). 
Antihypertensive Modified 
Therapeutic Intensity Score 
Continuous variable calculated for each antihypertensive medication being taken. Calculated using the most proximal 
prescription dispensed in the pre-index period using the daily dose as calculated above, divided by the maximum daily dose per 
the 2017 ACC/AHA blood pressure guideline. See Appendix F. 
Number of antihypertensive 
medication fills  
Calculated for each antihypertensive medication being taken. Number of antihypertensive medication fills in the most proximal 
12 months prior each Veteran’s index date. Used only in a sensitivity analysis. 
Alternative exposure definition 
1 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if the patient had two 
pharmacy fills for the primary exposure of interest in the 180 (± 14 days) days prior to the index date. The pharmacy fills do not 
have to be consecutive.  
Alternative exposure definition 
2 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if the patient had 1 
pharmacy fill in the 90 days (± 14 days) prior to the index date for the primary exposure of interest and 3 consecutive pharmacy 
fills for the primary exposure of interest in the one year (± 14 days) prior to the index date. A “consecutive” fill is defined as 
pharmacy fills with less than 30 days of gap in days’ supply between the fills. 
Alternative exposure definition 
3 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if a prescription for the 
primary exposure of interest was dispensed before the index date with a days’ supply that met or exceeded the index date. 
Calculated as “no” if prescription was dispensed before the index date with a days’ supply that did not meet or exceed the index 
date. 

104 
 
Appendix D: Variables used to define outcomes (Aim 1).  
Variable 
Definition 
Primary Outcomes 
 
All-cause hospitalization 
A binary variable indicating the occurrence of one or more all-cause hospitalization(s) during the post index period. 
Time to all-cause 
hospitalization 
Integer number of days from index date to first all-cause hospitalization (inpatient claim/encounter) post the index date.  
All-cause mortality 
A binary variable indicating all-cause mortality during the post index period.  
Time to all-cause mortality 
Integer number of days from index date to all-cause mortality post the index date.  
Primary composite outcome 
Composite of time to all-cause hospitalization or all-cause mortality. 
Secondary Outcomes 
 
ICU admission 
A binary variable indicating admission to an intensive care unit during the first hospitalization post-index date. 
Negative Control Outcomes 
 
Severe gastrointestinal 
bleeding24 
Occurrence of any of the following codes associated with a hospital (inpatient) encounter post-index date: 
(a) ICD-10 code in any position for K25-K28, K92.2, AND 
(b) CPT code 78278, 7424.x, 7425.x, 74260, 435.xx, 436.xx, 440.xx, 44120, 446.xx 
Urinary tract infection 
Presence of a positive urine culture, defined as urine culture with at least one organism with a quantitative count of >105 CFU/mL 
of any of the following uropathogens: Escherichia coli, Pseudomonas aeruginosa, Enterococcus spp., Klebsiella spp., 
Enterobacter spp., Proteus spp., Citrobacter spp., Providentia spp., Morganella spp., Serratia spp., Candida spp. during the 
hospitalization post-index date (including the index date) OR 
Presence of the ICD10 codes N10, N30, N39, A41.9 using all available claims post the index date. 
 
 
 
 
 

105 
 
Appendix E: List of Antihypertensive Medications by Class 
 
Antihypertensive medication class 
Medication Name 
Angiotensin converting enzyme inhibitor 
benazepril 
captopril 
enalapril 
fosinopril 
lisinopril 
moexipril 
perindopril 
quinapril 
ramipril 
trandolapril 
Angiotensin-II receptor blocker 
azilsartan 
candesartan 
eprosartan 
irbesartan 
losartan 
olmesartan 
telmisartan 
valsartan* 
Alpha-blocker 
doxazosin 
prazosin 
terazosin 
Beta-blocker 
acebutolol 
nebivolol 
atenolol 
betaxolol 
bisoprolol 
metoprolol 
pindolol 

106 
 
penbutolol 
carvedilol 
labetalol 
nadolol 
propranolol 
timolol 
Calcium channel blocker 
amlodipine 
felodipine 
isradipine 
nicardipine 
nifedipine 
nisoldipine 
diltiazem 
verapamil 
Centrally-acting 
clonidine 
guanabenz 
guanfacine 
methyldopa 
reserpine 
Direct vasodilators 
hydralazine 
minoxidil 
Direct renin inhibitor 
aliskiren 
Aldosterone receptor antagonist 
spironolactone 
eplerenone 
Loop diuretic 
bumetanide 
ethacrynic acid 
furosemide 
torsemide 
Potassium-sparing diuretic 
amiloride 
triamterene 
Thiazide diuretic 
bendroflumethiazide 

107 
 
chlorothiazide 
chlorthalidone 
hydrochlorothiazide 
indapamide 
metolazone 
*Excluding sacubitril/valsartan products. 

108 
 
Appendix F: Calculation of Modified Therapeutic Intensity Score 
For each antihypertensive medication being taken for each patient, a Modified Therapeutic 
Intensity Score will be calculated as the 
!"#$%"&'#( *+$#
,--/,/, 0123 456&787 *+$#.11,12 The maximum dose will 
be defined using the table below based on the 2017 ACC/AHA blood pressure guideline.25 If a 
drug was not listed in the 2017 ACC/AHA guideline, then the max dose as listed in the Food and 
Drug Administration-approved manufacturer labeling will be used. 
Each medication’s mTIS can be summed for a total regimen mTIS score, calculated as 
!2
9
!"#$%"&'#( *+$#
,--/,/, 0123 456&787 *+$# where n is the number of antihypertensive medications.  
Example: a patient on lisinopril 20 mg daily would have a mTIS for lisinopril of 20/40 = 0.5. 
 
Table. Complete List of Antihypertensive Medications Used During SPRINT 
Medication Name  
Medication Class 
Maximum Daily Dose 
benazepril 
ACEI 
40 
captopril 
ACEI 
150 
enalapril 
ACEI 
40 
fosinopril 
ACEI 
40 
lisinopril 
ACEI 
40 
moexipril 
ACEI 
30 
perindopril 
ACEI 
16 
quinapril 
ACEI 
80 
ramipril 
ACEI 
20 
trandolapril 
ACEI 
4 
doxazosin 
Alpha Blocker  
16 
prazosin 
Alpha Blocker  
20 
terazosin 
Alpha Blocker  
20 
azilsartan 
Angiotensin II Receptor 
Blocker  
80 
candesartan 
Angiotensin II Receptor 
Blocker  
32 
eprosartan 
Angiotensin II Receptor 
Blocker  
800 
irbesartan 
Angiotensin II Receptor 
Blocker  
300 
losartan 
Angiotensin II Receptor 
Blocker  
100 
olmesartan 
Angiotensin II Receptor 
Blocker  
40 
telmisartan 
Angiotensin II Receptor 
Blocker  
80 
valsartan 
Angiotensin II Receptor 
Blocker  
320 
acebutolol 
Beta Blocker  
800 
nebivolol 
Beta Blocker  
40 
atenolol 
Beta Blocker  
100 

109 
 
betaxolol 
Beta Blocker  
20 
bisoprolol 
Beta Blocker  
10 
metoprolol 
Beta Blocker  
200 
pindolol 
Beta Blocker  
60 
penbutolol 
Beta Blocker  
40 
carvedilol 
Beta Blocker  
50 
labetalol 
Beta Blocker  
800 
nadolol 
Beta Blocker  
120 
propranolol 
Beta Blocker  
160 
timolol 
Beta Blocker  
60 
amlodipine 
Calcium Channel Blocker  
10 
felodipine 
Calcium Channel Blocker  
10 
isradipine 
Calcium Channel Blocker  
10 
nicardipine 
Calcium Channel Blocker  
120 
nifedipine 
Calcium Channel Blocker  
90 
nisoldipine 
Calcium Channel Blocker  
34 
diltiazem 
Calcium Channel Blocker  
360 
verapamil 
Calcium Channel Blocker  
360 
clonidine 
Central Alpha-2 Agonists and 
Other Centrally Acting Drugs  
Oral 0.8 
Patch 0.3/wk 
guanabenz 
Central Alpha-2 Agonists and 
Other Centrally Acting Drugs 
64 
guanfacine 
Central Alpha-2 Agonists and 
Other Centrally Acting Drugs  2 
methyldopa 
Central Alpha-2 Agonists and 
Other Centrally Acting Drugs  1000 
reserpine 
Central Alpha-2 Agonists and 
Other Centrally Acting Drugs  .25 
hydralazine 
Direct Arterial Vasodilators  
200 
minoxidil 
Direct Arterial Vasodilators  
100 
aliskiren 
Direct Renin Inhibitor  
300 
eplerenone 
Aldosterone receptor 
antagonist  
100 
spironolactone 
Aldosterone receptor 
antagonist 
100 
bumetanide 
Loop diuretic 
2 
ethacrynic acid 
Loop diuretic 
100 
furosemide 
Loop diuretic 
80 
torsemide 
Loop diuretic 
10 
amiloride 
Potassium-sparing diuretic  
10 
triamterene 
Potassium-sparing diuretic 
100 
bendroflumethiazide 
Thiazide diuretic 
5 
chlorothiazide 
Thiazide diuretic  
2000 
chlorthalidone 
Thiazide diuretic  
25 
hctz 
Thiazide diuretic  
50 
indapamide 
Thiazide diuretic  
2.5 

110 
 
metolazone 
Thiazide diuretic  
5 

111 
 
Appendix G: Variables used to define study population (Aim 2). 
Variable 
Definition 
Index date 
Admit date of the COVID-19 related hospitalization. 
SARS-CoV-2 positive test 
Veterans with a positive SARS-CoV-2 test between January 19, 2020, to present-day will be identified using the VA’s official 
SARS-CoV-2 phenotype definition, which incorporates testing external to the VA. Patients identified as “VA confirmed” and “VA 
probable” will be categorized as SARS-CoV-2 positive.  
COVID-19 related 
hospitalization 
Hospitalization within 7 days before or 14 days after SARS-CoV-2 positive test (defined above). If a patient has more than one 
hospitalization in this timeframe, the one closest to the SARS-CoV-2 positive test will be selected as the index date. 
Hypertension 
Any of the following using all available claims prior to the index date: 
(f) ICD-9 codes: 
a. At least 1 inpatient claim with a discharge ICD-9 diagnosis (any position) of 401.x, 403.0x, 403.1x, 403.9x. 
b. ≥2 outpatient claims with an ICD-9 diagnosis code of 401.x, 403.0x, 403.1x, 403.9x in any position at least 30 
days apart 
(g) ICD-10 codes: 
a. 1 inpatient claim with an ICD-10 discharge diagnosis code of I10, I12.0, I12.9 in any discharge diagnosis position 
b. ≥2 outpatient claims with an ICD-10 diagnosis code of I10, I12.0, I12.9 in any position at least 30 days apart 
Treated hypertension 
Having hypertension, as defined above, and currently taking antihypertensive medication, as defined as a pharmacy fill for an 
antihypertensive medication within 90 days prior to the index date (see Appendix E for list of medication classes). 
Compelling indication for ACEI 
or ARB 
Individuals with diabetes, stroke, chronic kidney disease, heart failure with reduced ejection fraction, or coronary heart disease 
as defined in Appendix B will be excluded from the population for Aim 2.1.  
Hospitalized for pneumonia 
not due to COVID-19 
Patients will be identified who are hospitalized (i.e., an inpatient encounter) with an ICD-10 code of J13-J18 in any position. Used 
for a sensitivity analysis only. 

112 
 
Appendix H: Variables used to define main exposures (Aim 2). 
Variable 
Definition 
Antihypertensive – non-ACEI or 
ARB-based regimen (Aim 2.1) 
Defined as one or more pharmacy fills for an oral non-ACEI or ARB medications in the 90 days (± 14 days) prior to each 
Veteran’s index date and categorized by class as aldosterone receptor antagonist, beta-blocker, calcium channel blocker, 
centrally-acting drug, direct arterial vasodilator, direct renin inhibitor, thiazide diuretic, loop diuretic, and potassium sparing 
diuretic. See Appendix E for specific drug names within each class. Exclude non-oral products. 
Antihypertensive – ACEI/ARB-
based regimen (Aim 2.1) 
Defined as one or more pharmacy fills for an oral ACEI or an ARB in the 90 days (± 14 days) prior to each Veteran’s index 
date. See Appendix E for specific drug names within each class. Exclude non-oral products. Exclude sacubitril/valsartan 
(Brand name: Entresto®) from ARB exposures. 
Antihypertensive – ACEI- based 
regimen (Aim 2.2) 
Defined as one or more pharmacy fills for an oral ACEI in the 90 days (± 14 days) prior to each Veteran’s index date. See 
Appendix E for specific drug names within each class. Exclude non-oral products. 
Antihypertensive – ARB-based 
regimen (Aim 2.2)  
Defined as one or more pharmacy fills for an oral ARB in the 90 days (± 14 days) prior to each Veteran’s index date. See 
Appendix E for specific drug names within each class. Exclude non-oral products. Exclude sacubitril/valsartan (Brand name: 
Entresto®) from ARB exposures. 
Antihypertensive medication 
daily dose 
Calculated for each antihypertensive medication being taken. Described as milligrams of drug taken per day. We will first parse 
the dosage value then use the quantity and days supplied variables to inform the parsed dose value (if partial or multiple pills 
are being taken per day, for example). 
Antihypertensive Modified 
Therapeutic Intensity Score 
Continuous variable calculated for each antihypertensive medication being taken. Calculated using the most proximal 
prescription dispensed in the pre-index period using the daily dose as calculated above, divided by the maximum daily dose 
per the 2017 ACC/AHA blood pressure guideline. See Appendix F. 
Number of antihypertensive 
medication fills  
Calculated for each antihypertensive medication being taken. Number of antihypertensive medication fills in the most proximal 
12 months prior each Veteran’s index date. Used only in a sensitivity analysis. 
Alternative exposure definition 1 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if the patient had two 
pharmacy fills for the primary exposure of interest in the 180 (± 14 days) days prior to the index date. The pharmacy fills do not 
have to be consecutive.  
Alternative exposure definition 2 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if the patient had 1 
pharmacy fill in the 90 days (± 14 days) prior to the index date for the primary exposure of interest and 3 consecutive 
pharmacy fills for the primary exposure of interest in the one year (± 14 days) prior to the index date. A “consecutive” fill is 
defined as pharmacy fills with less than 30 days of gap in days’ supply between the fills. 
Alternative exposure definition 3 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if a prescription for the 
primary exposure of interest was dispensed before the index date with a days’ supply that met or exceeded the index date. 
Calculated as “no” if prescription was dispensed before the index date with a days’ supply that did not meet or exceed the 
index date. 
Alternative exposure definition 4 
Used for a sensitivity analysis. Described as a dichotomous variable (yes=1; no=0). Calculated as “yes” if the patient had 1 
pharmacy fill in the 90 days prior to the index date and at least one medication administration for the same antihypertensive 
medication post the index date (including the index date). 

113 
 
Appendix I: Variables used to define outcomes (Aim 2).  
Variable 
Definition 
Primary Outcomes 
 
All-cause mortality 
A binary variable indicating all-cause mortality during the post index period.  
Time to all-cause mortality 
Integer number of days from index date to all-cause mortality post the index date.  
Secondary Outcomes 
 
Duration of hospitalization 
Integer number of days of the inpatient claim post-index date, inclusive of admit and discharge dates. 
ICU admission 
A binary variable indicating admission to an intensive care unit during the first hospitalization post-index date. 
Dialysis 
A binary variable indicating occurrence of dialysis post-index date, inclusive of admit and discharge dates.  
Mechanical ventilation 
Occurrence of any of the following codes associated with a hospital (inpatient) encounter post-index date (including the index 
date): 
(a) ICD-10 codes: J95.850, Z99.1x, T88.4x  
(b) Current Procedural Terminology: 31500 
(c) ICD-10 procedure codes: 5A19054, 5A0945Z, 5A1935Z, 5A1955Z, 5A0935Z 
(d) Order for intubation placed in the electronic health record 
(e) Inpatient medication administration of a paralytic agent (succinylcholine, cisatracurium, or rocuronium) 
Negative Control Outcomes 
 
Severe gastrointestinal 
bleeding24 
Occurrence of any of the following codes associated with a hospital (inpatient) encounter post-index date: 
(c) ICD-10 code in any position for K25-K28, K92.2, AND 
(d) CPT code 78278, 7424.x, 7425.x, 74260, 435.xx, 436.xx, 440.xx, 44120, 446.xx 
Urinary tract infection 
Presence of a positive urine culture, defined as urine culture with at least one organism with a quantitative count of >105 CFU/mL 
of any of the following uropathogens: Escherichia coli, Pseudomonas aeruginosa, Enterococcus spp., Klebsiella spp., 
Enterobacter spp., Proteus spp., Citrobacter spp., Providentia spp., Morganella spp., Serratia spp., Candida spp. during the 
hospitalization post-index date (including the index date) OR 
Presence of the ICD10 codes N10, N30, N39, A41.9 using all available claims post the index date. 

114 
 
Appendix J: Variables used to define time-varying covariates (Aim 2). 
Variable 
Definition 
Systolic blood pressure 
Each systolic blood pressure value post-index date (including the index date) will be collected where the measure date falls 
between the admit and discharge dates (admit and discharge dates included). SBP values will be dropped if any of the following 
was true: Missing value, systolic less than diastolic, systolic >300 mm Hg, and systolic <60 mm Hg. 
Heart rate 
Each heart rate measurement value post-index date (including the index date) will be collected where the measure date falls 
between the admit and discharge dates (admit and discharge dates included). HR values will be dropped if missing. 
Estimated glomerular filtration 
rate 
Each eGFR recorded where the measure date falls between the admit and discharge dates (admit and discharge dates 
included). If multiple values for 1 day exist, they will be averaged to create 1 value for that day. If no value exists for a day, use 
last observation measured. The VA calculates eGFR using the Modified Diet in Renal Disease equation.14 
Serum potassium 
Each daily serum potassium value where the measure date falls between the admit and discharge dates (admit and discharge 
dates included) will be collected and reported as daily values. If multiple values for 1 day exist, they will be averaged to create 1 
value for that day. If no value exists for a day, use the last observation measured. Defined using OMOP’s mapping where LOINC 
is '6298-4', '2823-3'. 
Daily administration of 
antihypertensive medication 
regimen 
Calculated for each antihypertensive medication from the baseline regimen. Described as a dichotomous variable (yes=1; no=0) 
for each day. Calculated as “yes” if at least one medication administration for the antihypertensive medication occurred during 
the hospitalization day (including the index date). Calculated as “no” if no medication administration occurred for the 
antihypertensive medication during the hospitalization day (including the index date). 
Daily administration of 
pressor/inotrope  
Daily administration of norepinephrine, phenylephrine, dopamine, vasopressin, epinephrine, milrinone, dobutamine, angiotensin 
II, or midodrine. Described as a dichotomous variable (yes=1; no=0) for each day. Calculated as “yes” if at least one medication 
administration for the medication occurred during the hospitalization day (including the index date). Calculated as “no” if no 
medication administration occurred for the antihypertensive medication during the hospitalization day (including the index date).  

115 
 
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