SARS-CoV-2 infection and adverse outcomes in users of ACE ...

Original research

SARS- CoV-2 infection and adverse outcomes in users of ACE inhibitors and angiotensin- receptor blockers: a nationwide case- control and cohort analysisChristian Fynbo Christiansen ,1 Anton Pottegård,2 Uffe Heide- Jørgensen,1 Jacob Bodilsen ,3 Ole Schmeltz Søgaard,4 Michael Maeng,5 Simon Tilma Vistisen,6,7 Morten Schmidt,1,5,8 Lars Christian Lund,2 Mette Reilev ,2 Jesper Hallas,2 Marianne Voldstedlund,9 Anders Husby,10 Marianne Kragh Thomsen,11 Nanna Borup Johansen,12 Nikolai Constantin Brun,12 Reimar Wernich Thomsen ,1 Hans Erik Bøtker,5 Henrik Toft Sørensen1,13

Respiratory infection

To cite: Christiansen CF, Pottegård A, Heide- Jørgensen U, et al. Thorax 2021;76:370–379.

► Additional material is published online only. To view please visit the journal online (http:// dx. doi. org/ 10. 1136/ thoraxjnl- 2020- 215768).

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Correspondence toDr Christian Fynbo Christiansen, Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark; cfc@ clin. au. dk

Received 12 July 2020Revised 14 October 2020Accepted 3 November 2020Published Online First 8 December 2020

© Author(s) (or their employer(s)) 2021. No commercial re- use. See rights and permissions. Published by BMJ.

ABSTRACTObjective To examine the impact of ACE inhibitor (ACE- I)/angiotensin receptor blocker (ARB) use on rate of SARS- CoV-2 infection and adverse outcomes.Methods This nationwide case- control and cohort study included all individuals in Denmark tested for SARS- CoV-2 RNA with PCR from 27 February 2020 to 26 July 2020. We estimated confounder- adjusted ORs for a positive test among all SARS- CoV-2 tested, and inverse probability of treatment weighted 30- day risk and risk ratios (RRs) of hospitalisation, intensive care unit (ICU) admission and mortality comparing current ACE- I/ARB use with calcium channel blocker (CCB) use and with non- use.Results The study included 13 501 SARS- CoV-2 PCR- positive and 1 088 695 PCR- negative individuals. Users of ACE- I/ARB had a marginally increased rate of a positive PCR when compared with CCB users (aOR 1.17, 95% CI 1.00 to 1.37), but not when compared with non- users (aOR 1.00 95% CI 0.92 to 1.09).Among PCR- positive individuals, 1466 (11%) were ACE- I/ARB users. The weighted risk of hospitalisation was 36.5% in ACE- I/ARB users and 43.3% in CCB users (RR 0.84, 95% CI 0.70 to 1.02). The risk of ICU admission was 6.3% in ACE- I/ARB users and 5.4% in CCB users (RR 1.17, 95% CI 0.64 to 2.16), while the 30- day mortality was 12.3% in ACE- I/ARB users and 13.9% in CCB users (RR 0.89, 95% CI 0.61 to 1.30). The associations were similar when ACE- I/ARB users were compared with non- users.Conclusions ACE- I/ARB use was associated neither with a consistently increased rate nor with adverse outcomes of SARS- CoV-2 infection. Our findings support the current recommendation of continuing use of ACE- Is/ARBs during the SARS- CoV-2 pandemic.Trial registration number EUPAS34887

INTRODUCTIONThe use of renin–angiotensin system inhibitors, including ACE inhibitors (ACE- Is) and angiotensin receptor blockers (ARBs), has been suggested to increase the risk of being infected by SARS- CoV-2 and of adverse outcomes of coronavirus disease

2019 (COVID-19) caused by SARS- CoV-2. ACE- Is/ARBs upregulates the human ACE2 receptor, which facilitates entry of SARS- CoV-2 into cells.1–5 The initially published studies of ACE- I/ARB users and SARS- CoV-2 infection reported no increased risk or worsened outcome after a positive SARS- CoV-2 test or a diagnosis of COVID-19.6–16 However, available studies are limited by incomplete data on recent ACE- I/ARB use and preexisting comorbidi-ties,6 7 9 by restriction to hospitalised or hospital- diagnosed COVID-19 patients,9 10 12–15 or by incomplete follow- up.6 Other limitations have included immortal time bias from inclusion of in- hospital ACE- I/ARB use after COVID-19 diag-nosis,10 11 15 16 which may lead to apparently bene-ficial effects, because ACE- I/ARBs would only be prescribed if patients are haemodynamically stable

Key messages

What is the key question? ► Does use of ACE inhibitors (ACE- I) and angiotensin receptor blockers (ARBs) increase the rate or worsen the outcome of SARS- CoV-2 infection?

What is the bottom line? ► Use of ACE- I/ARB was associated neither with a consistently increased rate nor with adverse outcomes of SARS- CoV-2 infection, compared with ACE- I/ARB non- use or calcium channel blocker use.

Why read on? ► This population- based study, including all individuals PCR tested for SARS- CoV-2 in Denmark, used extensive confounder adjustment and an active comparator design to examine the association between ACE- I/ARB use and the rate of microbiologically verified SARS- CoV-2 infection as well as the associated outcomes including hospitalisation, intensive care unit admission, mechanical ventilation and death.

370 Christiansen CF, et al. Thorax 2021;76:370–379. doi:10.1136/thoraxjnl-2020-215768

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and have survived until drug initiation. Only few studies on risk of SARS- CoV-2 infection included an active comparator.12 13

Major professional societies have called for further high- quality research and issued warnings against ACE- I/ARB discon-tinuation in patients with SARS- CoV-2 infection,1 17 to avoid worsening of underlying cardiometabolic conditions.18

As ACE- Is/ARBs are widely used drugs, any association with rate of infection or adverse outcomes of SARS- CoV-2 infection may have an important public health impact. Thus, there is an urgent need to examine the hypotheses of increased rate of SARS- CoV-2 infection and worsened outcome, among users of ACE- Is/ARBs.

METHODSDesign and settingWe conducted this nationwide combined case- control and cohort study in Denmark (population ~5.8 million persons) to study the rate (case- control design) and the prognosis (cohort design) of SARS- CoV-2. Denmark has a uniform tax- supported healthcare system responsible for all acute care in Denmark. The unique personal identification number assigned at birth or on immigration allows individual- level linkage of data and complete follow- up.19

As previously described,20 data on all individuals tested for SARS- CoV-2 RNA by reverse transcriptase PCR (RT- PCR) were obtained from the Danish Microbiology Database21 and linked to regularly updated data from the Danish National Patient Registry,22 the Civil Registration System,23 the National Prescrip-tion Database24 and the Danish Register of Causes of Deaths.25

ParticipantsThe study included prospectively collected data on all individ-uals tested for SARS- CoV-2 RNA from 27 February 2020 (the date when the first patient tested positive for SARS- CoV-2 in Denmark) to 26 July 2020, allowing complete 30- day follow- up through 26 August 2020.

The study population for the analysis of the rate of acquiring a positive SARS- CoV-2 test (the case- control analysis) included all patients tested for SARS- CoV-2, while the analysis of the outcome (the cohort analysis) only included patients who tested positive for SARS- CoV-2. The first date of a positive test was defined as the index date.

Medication exposuresCurrent use of ACE- Is and ARBs was ascertained from prescrip-tions filled within 90 days before testing (online supplemental eFigure 1). Former use was defined as a prescription filled within 91–365 days before testing, while non- use was defined as no prescriptions filled during 1 year before testing. Prescription data included complete and valid information on all prescrip-tions filled at community pharmacies in Denmark since 1995.24 Registry data include date of dispensing, Anatomical Thera-peutic Chemical code and drug quantity. In addition to prescrip-tions for ACE- I/ARBs, we obtained data on prescriptions for other antihypertensive medications, including calcium channel blockers (CCBs), beta blockers and thiazides.

The main exposure comparisons were current use of ACE- Is/ARBs versus current use of CCBs, and current use of ACE- Is/ARBs versus no ACE- Is/ARB use. The first comparison allowed us to reduce confounding by indication, as CCB is an active drug with medical indications similar to those for ACE- Is/ARBs and with no known effects on the renin–angiotensin system.

SARS-CoV-2 infection and adverse outcomesCases in the case- control analysis were individuals acquiring a positive SARS- CoV-2 PCR test, and controls were individuals with a negative PCR test. The primary outcome in the cohort analysis of outcome was death within 30 days following a posi-tive SARS- CoV-2 test. Secondary outcomes included hospital admission (hospital stay lasting >12 hours) within 30 days after index date, among patients who were not already hospitalised. Additional secondary outcomes included intensive care unit (ICU) admission, ICU admission with mechanical ventilation (MV) and dialysis within 30 days after index date. Secondary outcomes were obtained from the Danish National Patient Registry, which is also the platform for mandatory reporting to the national database for quality of ICU, and earlier assess-ments of the accuracy of its data on ICU admissions, ICU admis-sion with MV and dialysis yielded positive predictive values of 96%–100%.26 27

Potential confoundersWe included a wide range of potential confounders that may be associated with both ACE- I/ARB use and the risk and outcome of SARS- CoV-2 infection (table 1). Data on age, sex, marital status, ethnicity and urban residence were obtained from the Civil Registration System.23 We also obtained information on comorbidities associated with an inpatient stay or an outpatient hospital clinic diagnosis or with treatment by prescribed medi-cations within 10 years before the index date (codes provided in online supplemental eTable 1).22 24 Prescriptions for concurrent medications filled within 90 days before the index date were also included.24

Statistical methodsIn the test- negative case- control analysis, the association between ACE- I/ARB use and a positive SARS- CoV-2 test was examined using a logistic regression model to compute ORs with 95% CIs adjusted for all covariates in table 1 and test date in 3- day inter-vals. In post hoc analyses, we tabulated patient characteristics in all tested patients by exposure group (current ACE- I/ARB use, no ACE- I/ARB use and current CCB use) and described posi-tive:negative ratio, both overall and stratified by age group.

In the cohort analyses of outcome, we computed a propensity score (PS) for each individual, that is, the probability of being exposed in each comparison (eg, current ACE- I/ARB use vs current CCB use), using a logistic regression model including all covariates in table 1. We used the PS for inverse probability of treatment weighting (IPTW) with stabilised weights to esti-mate the average treatment effect in the population.28 Covariate balance before and after IPTW was described using standardised mean differences.

We restricted the comparison of current vs no ACE- I/ARB use to patients aged 50 years or older as there were only few ACE- I/ARB users, but many non- users, under age 50 leading to imbal-ance before restriction.

The cohort analysis of adverse outcomes followed patients from the day of their first positive test result to the date of the outcome of interest, that is, hospital admission, ICU admission (with or without need for MV), dialysis, date of death, emigra-tion, or for up to 30 days. Patients were excluded in the anal-ysis of each non- fatal outcome if they experienced that outcome from seven to 1 day before the test date.

Patient characteristics were tabulated according to each expo-sure group before and after weighting. For each exposure group, we estimated the 30- day weighted risks and risk differences with

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robust 95% CIs using generalised linear models with a binomial distribution and an identity link. Risk ratios (RRs) were esti-mated similarly but using a log link.

A subgroup analysis was conducted to address potential effect modification by age group (≤65 years, >65 years). A second subgroup analysis was conducted in patients with assumed uncomplicated hypertension as the primary indication for treat-ment (defined as patients without a history of diabetes, renal disease, angina pectoris, myocardial infarction or heart failure). A third subgroup analysis was restricted to patients tested after the test strategy changed in Denmark and the country was locked down on 13 March 2020.

In a sensitivity analysis, we explored the robustness of our find-ings by repeating the analyses for patients who filled a prescrip-tion within 120 days before a positive test. We also conducted a sensitivity analysis stratified by calendar time to address changes in testing and hospitalisation strategy. We followed the protocol registered in the European Union electronic Register of Post- Authorisation Studies (EU PAS Register) (record number: EUPAS34887), with two exemptions. First, standardised mortality rate weighting was replaced with IPTW with stabilised weights to better handle the low number of current CCB users in the comparison group. Second, the comparison with non- users of ace- i/ARB was restricted to patients aged 50 years and older due to the imbalance mentioned above.

All data management and statistical analyses were performed using STATA V.16 MP.

RESULTSThe study included 13 501 test- positive and 1 088 695 test- negative individuals (table 1). Among test- positive cases, there were 1466 current ACE- I/ARB users (11%) (587 ACE- I users, 887 ARB users and 8 using both) of whom 1336 were 50 years or above and included in the comparison between current ACE- I/ARB use with no ACE- I/ARB use. Among the 1466 current ACE- I/ARB users, 1065 did not receive concurrent CCBs and could therefore be included in the comparison between current ACE- I/ARB use and current CCB use.

Table 1 Characteristics of patients with positive and negative tests for SARS- CoV-2

Test- positive cases(n=13 501)

Test- negative controls(n=1 088 695)

Age, median (IQR) 47 (31–61) 43 (26–59)

Sex (male) 5763 (42.7) 474 335 (43.6)

Status as healthcare professional

Physician 423 (3.1) 10 247 (0.9)

Nurse 1351 (10.0) 31 520 (2.9)

Care assistant 607 (4.5) 24 211 (2.2)

Use of antihypertensives (within prior 90 days)

ACE inhibitors 587 (4.3) 46 195 (4.2)

Angiotensin receptor blockers 887 (6.6) 63 467 (5.8)

Calcium channel blockers 690 (5.1) 55 901 (5.1)

Thiazides 646 (4.8) 47 627 (4.4)

Beta blockers 833 (6.2) 60 685 (5.6)

Other antihypertensives 47 (0.3) 3336 (0.3)

Diagnoses (within prior 10 years)

Hypertension 1416 (10.5) 99 572 (9.1)

Atrial fibrillation 652 (4.8) 40 165 (3.7)

Hospital- diagnosed obesity 931 (6.9) 71 682 (6.6)

Angina 610 (4.5) 42 965 (3.9)

Heart valve disease 272 (2.0) 18 917 (1.7)

Alcohol abuse 224 (1.7) 27 855 (2.6)

Diabetes 1162 (8.6) 69 796 (6.4)

Venous thromboembolism 296 (2.2) 16 947 (1.6)

Dementia 384 (2.8) 9980 (0.9)

Myocardial infarction 211 (1.6) 14 487 (1.3)

Liver disease 124 (0.9) 10 449 (1.0)

Kidney disease 291 (2.2) 15 955 (1.5)

Chronic pulmonary disease 908 (6.7) 73 435 (6.7)

End- stage renal disease 21 (0.2) 1215 (0.1)

Heart failure 292 (2.2) 17 515 (1.6)

Cancer 737 (5.5) 61 394 (5.6)

Stroke 413 (3.1) 23 500 (2.2)

Markers of smoking 3293 (24.4) 296 588 (27.2)

Medications (within prior 90 days)

Statins 1244 (9.2) 94 770 (8.7)

Antivirals 193 (1.4) 12 171 (1.1)

Low- dose aspirin 476 (3.5) 36 812 (3.4)

Vitamin K- antagonists 106 (0.8) 8138 (0.7)

Opioids 778 (5.8) 51 647 (4.7)

Antidepressants 934 (6.9) 74 239 (6.8)

Immunosuppressants 47 (0.3) 4207 (0.4)

Antipsychotics 262 (1.9) 22 504 (2.1)

Glucocorticoids 278 (2.1) 19 675 (1.8)

Hypnotics 430 (3.2) 29 887 (2.7)

Loop diuretics 524 (3.9) 29 630 (2.7)

Antibiotics 2042 (15.1) 111 921 (10.3)

Continued

Test- positive cases(n=13 501)

Test- negative controls(n=1 088 695)

Socioeconomic factors

Marital status

Widowed 1005 (7.4) 53 203 (4.9)

Divorced 1568 (11.6) 121 025 (11.1)

Married 6205 (46.0) 429 375 (39.4)

Unmarried 4653 (34.5) 483 512 (44.4)

Unknown 70 (0.5) 1580 (0.1)

Ethnicity

Non- immigrant 10 329 (76.5) 935 629 (85.9)

First- generation or second- generation immigrant

3172 (23.5) 153 066 (14.1)

Residence

Non- urban 6539 (48.4) 648 923 (59.6)

Urban 6962 (51.6) 439 772 (40.4)

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Rate of acquiring a positive SARS-CoV-2 testThere were no major differences in characteristics of test- positive and test- negative individuals with regard to age, sex, comor-bidity and medication use (table 1). There were, however, more healthcare professionals, more living in urban areas, but fewer non- immigrants among the test- positive cases. After adjusting, ACE- I/ARB users had a slightly increased rate of a positive test compared with current CCB users (adjusted OR 1.17, 95% CI 1.00 to 1.37) (figure 1). ACE- I/ARB users had a similar rate of a positive test compared with ACE- I/ARB non- users (adjusted OR 1.00, 95% CI 0.92 to 1.09) (figure 1).

Outcomes of SARS-CoV-2 infectionPatient characteristics of current ACE- I/ARB users are compared with CCB users in table 2 and with non- users in table 3.

After excluding patients both on ACE- I/ARB and CCB from the SARS- CoV-2 positive cohort, 1065 ACE- I/ARB users and 289 current CCB users remained. The characteristics of patients in the two groups were well balanced after weighting (table 2).

The risk of hospital admission was 36.5% in ACE- I/ARB users and 43.3% in CCB users (RR 0.84, 95% CI 0.70 to 1.02) after weighting (table 4). The risk of ICU admission was 6.3% in ACE- I/ARB users and 5.4% in CCB users (RR 1.17, 95% CI 0.64 to 2.16), while the risk of death within 30 days was 12.3% in ACE- I/ARB users and 13.9% in CCB users (RR 0.89, 95% CI 0.61 to 1.30).

Among SARS- CoV-2 positive patients aged 50 years or above, 1336 were current ace- i/ARB users and 4326 were non- users. Characteristics of patients in the two groups were well balanced after weighting (table 3). The weighted risk of hospital admis-sion was 32.3% in ACE- I/ARB users and 33.1% in non- users (RR 0.98, 95% CI 0.84 to 1.14) (table 4). The risk of ICU admis-sion was 6.4% in ACE- I/ARB users and 5.1% in non- users (RR 1.25, 95% CI 0.66 to 2.36), while the risk of death within 30 days was 9.5% in ACE- I/ARB users and 10.8% in non- users (RR 0.88, 95% CI 0.68 to 1.14).

Subgroup analysesResults were confirmed in subgroup analyses stratified by age, no cardiovascular disease other than hypertension, and period of testing (online supplemental eTable 2).

Results for various exposure definitions are shown in online supplemental eTable 3. Results remained robust when the expo-sure window was changed to 120 days and when current ACE- I/ARB use was compared with current thiazide and beta- blocker use. There was no conclusive difference in the associations when analysing current ACE- I and ARB use separately, although point estimates differed.

Post hoc analysesAmong all tested individuals, patient characteristics were similar for current ACE- I/ARB users compared with current CCB users, while ACE- I/ARB non- users were younger and had less comor-bidity (online supplemental eTable 4). The overall positive:nega-tive ratios were similar for current ACE- I/ARB users, ACE- I/ARB non- users and current CCB users (online supplemental eTable 5). When stratified by age, the positive:negative ratio differed slightly between the exposure groups among young adults only.

DISCUSSIONIn this large nationwide study of prospectively collected data, current ACE- I/ARB use was associated with a marginally increased rate of testing positive compared with CCB use but not when compared with ACE- I/ARB non- use. Moreover, we showed that among individuals who tested positive for SARS- CoV-2, current use of ACE- Is/ARBs was not associated with increased risk of hospitalisation, ICU admission or 30- day mortality.

Strengths and limitations of the studyStrengths of the current study include its nationwide population- based design, including all individuals tested for SARS- CoV-2 in Denmark, with linkage to validated medical registries and complete follow- up for censoring of all Danish residents.19 20 23–25 ICU admissions and treatments also are recorded accurately, as the Danish National Patient Registry is used for financial reim-bursements to hospitals and for mandatory reporting to national quality of care databases.26 27 The RT- PCR test for presence of SARS- CoV-2 has high sensitivity and predictive value,29 and registration of the tests are complete and accurately recorded in the Danish Microbiology Database.21 Despite these strengths, the study had several limitations. The threshold for SARS- CoV-2

Figure 1 OR for a positive test among ACE- I/ARB users compared with CCB users and non- users tested for SARS- CoV2. ACE- I, ACE inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.




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Table 2 Characteristics of current ACE- I/ARB users and current CCB users before and after inverse probability of treatment weighting

Unweighted cohort IPTW cohort

Current ACE- I/ARB users Current CCB users

SMD


SMD(n=1065) (n=289) (n=1065) (n=285)

Age, median (IQR) 68 (58–79) 72 (60–82) 0.20 69 (58–80) 68 (57–80) 0.02

Sex (male) 519 (48.7) 133 (46.0) 0.05 511 (48.0) 139 (48.9) 0.02


Physician 20 (1.9) (n<5) 0.07 18 (1.7) (n<5) 0.00

Nurse 46 (4.3) 5 (1.7) 0.15 40 (3.8) 10 (3.3) 0.02

Care assistant 43 (4.0) 9 (3.1) 0.05 41 (3.9) 11 (4.0) 0.01


ACE inhibitors 426 (40.0) 0 1.15 426 (40.1) 0 1.16

Angiotensin receptor blockers 645 (60.6) 0 1.75 644 (60.5) 0 1.75

Calcium channel blockers 0 289 (100.0) . 0 285 (100.0) .

Thiazides 316 (29.7) 34 (11.8) 0.45 275 (25.9) 72 (25.3) 0.01

Beta blockers 234 (22.0) 70 (24.2) 0.05 239 (22.4) 65 (22.6) 0.01

Other antihypertensives 16 (1.5) 11 (3.8) 0.14 22 (2.1) 6 (2.2) 0.01


Hypertension 425 (39.9) 137 (47.4) 0.15 440 (41.3) 122 (42.6) 0.03

Atrial fibrillation 138 (13.0) 37 (12.8) 0.00 138 (13.0) 38 (13.4) 0.01

Hospital- diagnosed obesity 112 (10.5) 23 (8.0) 0.09 106 (10.0) 26 (9.1) 0.03

Angina 146 (13.7) 33 (11.4) 0.07 142 (13.3) 41 (14.2) 0.03

Heart valve disease 69 (6.5) 13 (4.5) 0.09 64 (6.0) 13 (4.5) 0.07

Alcohol abuse 35 (3.3) 12 (4.2) 0.05 37 (3.5) 11 (3.8) 0.02

Diabetes 291 (27.3) 59 (20.4) 0.16 276 (26.0) 78 (27.3) 0.03

Venous thromboembolism 45 (4.2) 22 (7.6) 0.14 52 (4.8) 13 (4.4) 0.02

Dementia 66 (6.2) 20 (6.9) 0.03 67 (6.3) 16 (5.7) 0.03

Myocardial infarction 60 (5.6) 8 (2.8) 0.14 53 (5.0) 11 (4.0) 0.05

Liver disease 10 (0.9) 5 (1.7) 0.07 13 (1.2) (n<5) 0.00

Kidney disease 66 (6.2) 37 (12.8) 0.23 81 (7.6) 22 (7.6) 0.00

Chronic pulmonary disease 128 (12.0) 34 (11.8) 0.01 127 (11.9) 34 (11.9) 0.00

End- stage renal disease (n<5) 6 (2.1) 0.18 6 (0.5) (n<5) 0.01

Heart failure 111 (10.4) 15 (5.2) 0.20 99 (9.3) 24 (8.6) 0.03

Cancer 136 (12.8) 32 (11.1) 0.05 132 (12.4) 33 (11.6) 0.02

Stroke 98 (9.2) 35 (12.1) 0.09 104 (9.8) 26 (9.1) 0.02

Markers of smoking 354 (33.2) 93 (32.2) 0.02 351 (33.0) 88 (30.7) 0.05


Statins 381 (35.8) 95 (32.9) 0.06 373 (35.1) 108 (37.7) 0.06

Antiviral 14 (1.3) (n<5) 0.11 12 (1.1) (n<5) 0.05

Low- dose aspirin 141 (13.2) 37 (12.8) 0.01 140 (13.1) 37 (12.8) 0.01

Vitamin K- antagonists 23 (2.2) 9 (3.1) 0.06 25 (2.4) 6 (2.0) 0.03

Opioids 131 (12.3) 46 (15.9) 0.10 141 (13.3) 45 (15.7) 0.07

Antidepressants 152 (14.3) 47 (16.3) 0.06 156 (14.6) 42 (14.6) 0.00

Immunosuppressants 8 (0.8) (n<5) 0.06 9 (0.9) (n<5) 0.02

Antipsychotics 42 (3.9) 10 (3.5) 0.03 41 (3.8) 12 (4.1) 0.01

Glucocorticoids 45 (4.2) 11 (3.8) 0.02 43 (4.1) 9 (3.0) 0.06

Hypnotics 71 (6.7) 20 (6.9) 0.01 75 (7.1) 26 (9.1) 0.08

Loop diuretics 157 (14.7) 42 (14.5) 0.01 158 (14.9) 45 (15.7) 0.02

Antibiotics 282 (26.5) 80 (27.7) 0.03 283 (26.6) 77 (27.1) 0.01


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testing was lowered as the pandemic progressed and testing capacity has increased steadily since March 2020.20 Importantly, our results did not change after restriction to patients tested after the policy guidelines changed and the country was locked down on 13 March 2020. Any bias should be minimal as use of ACE- I/ARB was not expected to influence the threshold for testing, which followed national guidelines. This was confirmed by the lack of major difference in positive:negative ratios between exposure groups.

Medication use was assessed using complete and valid data on prescriptions prior to testing in a time window corresponding to the typical interval between medication refills. Still, misclas-sification could have occurred if some patients had sporadic use of drugs filled more than 90 days before testing. Given the chronic use of the drugs included in the study, such misclassi-fication should be minor and not associated with the outcome of interest. The direction of any information bias is therefore expected to be towards the null. It is likely to be minimal as no change in estimates was observed after the time window was extended from 90–120 days before testing in a sensitivity anal-ysis. A related concern is that we lacked in- hospital medication data to examine the impact of continued and discontinued use of prescribed drugs during follow- up, which may be relevant, since 50% of hospitalised COVID-19 patients may discontinue ACE- I/ARB.30

The use of ICU admission as an outcome in observational prog-nostic studies is challenging.31 In clinical practice, ICU admission is offered to patients who are expected to have a clear prog-nostic benefit from invasive monitoring and treatment.32 This is the case particularly in countries with limited ICU capacity, which are not able to accommodate the level of need during the COVID-19 pandemic. In Denmark, ICU capacity was more than sufficient during the study period. In addition, patients’ quality of life, functional level at home and hospital capacity may influ-ence the decision to admit a patient to the ICU. This may explain why ICU and mortality outcomes tended to go in opposite direc-tions for some associations examined in our study.

Potential confounding by medical indication for drug treat-ment was handled by use of an active comparator in the main analysis, by implementing IPTW that included a large number of

potential confounders, and by restricting analyses to subgroups according to indication for treatment. Although cardiovascular and other diagnoses used in the study have documented high positive predictive values,20 33 we cannot entirely rule out that our findings were influenced by unmeasured confounding by indication and contraindication for treatments and by severity of underlying comorbidity. A final concern is that precision of risk estimates was limited in some subgroups.

Comparison with other studiesOur results on risk of acquiring a positive SARS- CoV-2 test are consistent with the few published studies on risk of ACE- I/ARB users compared with non- users,6–8 12 13 16 and to other antihy-pertensives.12 13 The earlier studies, which used hospital based rather than population based data or were limited by incomplete data on recent ACE- I/ARB exposure, reported ORs ranging from 0.94 to 1.23 associated with ACE- I/ARB use.6–8 12 13 16 A Danish study limited to hospital- diagnosed COVID-19 cases and popu-lation controls found similar association between ACE- I/ARB use and non- use (HR 1.05, 95% CI 0.80 to 1.36) and CCB use (HR 1.23, 95% CI 0.89 to 1.70), respectively.13

Thus, our study has confirmed and extended the previous findings in a large nationwide cohort of all individuals with microbiologically confirmed SARS- CoV-2 infection comparing ACE- I/ARB users to a specific active comparator group of users of another antihypertensive, CCB, corroborating no major association.

In our cohort analysis of patients with positive SARS- CoV-2 test, we found that ACE- I/ARB users had no increased risk of an ICU admission, confirming previous hospital- based studies.9–11 13–15 More importantly, our findings qualified that ACE- I/ARB use was not associated with increased risk of hospi-talisation when accounting for confounding factors. Our adverse outcome findings remained robust across varying exposure defi-nitions, subgroups and also in comparison with CCB use.

Our observed associations were more precise and closer to the null than reported in a recent systematic review.34 The few larger studies had some limitations. Reynolds et al conducted a study of 12 594 patients tested for SARS- CoV-2 in emergency



SMD


SMD(n=1065) (n=289) (n=1065) (n=285)

Marital status

Widowed 207 (19.4) 72 (24.9) 0.13 221 (20.8) 63 (22.1) 0.03

Divorced 156 (14.6) 34 (11.8) 0.09 149 (14.0) 35 (12.2) 0.05

Married 589 (55.3) 156 (54.0) 0.03 584 (54.9) 158 (55.2) 0.01

Unmarried 102 (9.6) 24 (8.3) 0.04 100 (9.4) 28 (9.8) 0.01

Unknown 11 (1.0) (n<5) 0.00 11 (1.0) (n<5) 0.02

Ethnicity

Non- immigrant 902 (84.7) 251 (86.9) 0.06 908 (85.3) 240 (84.1) 0.03

First- or second- generation immigrant 163 (15.3) 38 (13.1) 0.06 156 (14.7) 45 (15.9) 0.03

Residence

Non- urban 581 (54.6) 160 (55.4) 0.02 584 (54.9) 155 (54.4) 0.01

Urban 484 (45.4) 129 (44.6) 0.02 480 (45.1) 130 (45.6) 0.01

ACE- I, ACE inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker; IPTW, inverse probability of treatment weighting; SMD, standardised mean difference.

Table 2 Continued




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Table 3 Characteristics of current ACE- I/ARB users and non- users aged 50 years or above, before and after inverse probability of treatment weighting


Current ACE- I/ARB use No ACE- I/ARB use

SMD


SMD(n=1336) (n=4326) (n=1179) (n=4738)

Age, median (IQR) 70 (60–79) 61 (55–73) 0.50 66 (58–77) 64 (56–78) 0.09

Sex (male) 685 (51.3) 1830 (42.3) 0.18 525 (44.5) 2164 (45.7) 0.02


Physician 20 (1.5) 99 (2.3) 0.06 21 (1.8) 87 (1.8) 0.01

Nurse 38 (2.8) 352 (8.1) 0.23 56 (4.7) 291 (6.1) 0.06

Care assistent 39 (2.9) 223 (5.2) 0.11 39 (3.3) 193 (4.1) 0.04


ACE inhibitors 544 (40.7) 0 1.17 443 (37.6) 0 1.10

Angiotensin receptor blockers 800 (59.9) 0 1.73 741 (62.9) 0 1.84

Calcium channel blockers 376 (28.1) 213 (4.9) 0.66 157 (13.3) 771 (16.3) 0.08

Thiazides 434 (32.5) 143 (3.3) 0.82 142 (12.0) 744 (15.7) 0.11

Beta blockers 345 (25.8) 345 (8.0) 0.49 197 (16.7) 866 (18.3) 0.04

Other antihypertensives 25 (1.9) 13 (0.3) 0.15 12 (1.1) 50 (1.1) 0.00


Hypertension 603 (45.1) 496 (11.5) 0.81 299 (25.4) 1277 (26.9) 0.04

Atrial fibrillation 182 (13.6) 353 (8.2) 0.18 158 (13.4) 544 (11.5) 0.06

Hospital- diagnosed obesity 134 (10.0) 256 (5.9) 0.15 91 (7.8) 436 (9.2) 0.05

Angina 205 (15.3) 288 (6.7) 0.28 138 (11.7) 565 (11.9) 0.01

Heart valve disease 90 (6.7) 113 (2.6) 0.20 51 (4.3) 176 (3.7) 0.03

Alcohol abuse 47 (3.5) 125 (2.9) 0.04 47 (4.0) 211 (4.4) 0.02

Diabetes 390 (29.2) 379 (8.8) 0.54 195 (16.6) 760 (16.0) 0.01

Venous thromboembolism 57 (4.3) 171 (4.0) 0.02 56 (4.8) 192 (4.1) 0.04

Dementia 89 (6.7) 263 (6.1) 0.02 91 (7.7) 285 (6.0) 0.07

Myocardial infarction 73 (5.5) 99 (2.3) 0.17 45 (3.9) 147 (3.1) 0.04

Liver disease 10 (0.7) 63 (1.5) 0.07 18 (1.6) 57 (1.2) 0.03

Kidney disease 94 (7.0) 112 (2.6) 0.21 67 (5.7) 227 (4.8) 0.04

Chronic pulmonary disease 158 (11.8) 391 (9.0) 0.09 145 (12.3) 488 (10.3) 0.06

End- stage renal disease (n<5) 11 (0.3) 0.02 13 (1.1) 11 (0.2) 0.10

Heart failure 119 (8.9) 99 (2.3) 0.29 63 (5.4) 331 (7.0) 0.07

Cancer 177 (13.2) 428 (9.9) 0.11 141 (12.0) 568 (12.0) 0.00

Stroke 138 (10.3) 215 (5.0) 0.20 93 (7.9) 328 (6.9) 0.04

Markers of smoking 430 (32.2) 1170 (27.0) 0.11 362 (30.7) 1321 (27.9) 0.06


Statins 545 (40.8) 504 (11.7) 0.70 263 (22.3) 1145 (24.2) 0.04

Antivirals 16 (1.2) 57 (1.3) 0.01 17 (1.4) 54 (1.1) 0.03

Low- dose acetylsalicylic acid 208 (15.6) 199 (4.6) 0.37 112 (9.5) 395 (8.3) 0.04

Vitamin K- antagonists 32 (2.4) 50 (1.2) 0.09 29 (2.4) 69 (1.4) 0.07

Opioids 176 (13.2) 426 (9.8) 0.10 173 (14.7) 701 (14.8) 0.00

Antidepressants 199 (14.9) 472 (10.9) 0.12 167 (14.1) 609 (12.9) 0.04

Immunosuppresants 8 (0.6) 20 (0.5) 0.02 (n<5) 28 (0.6) 0.04

Antipsychotics 52 (3.9) 138 (3.2) 0.04 40 (3.4) 169 (3.6) 0.01

Glucocorticoids 55 (4.1) 150 (3.5) 0.03 61 (5.2) 168 (3.5) 0.08

Hypnotics 89 (6.7) 218 (5.0) 0.07 95 (8.1) 359 (7.6) 0.02

Loop diuretics 212 (15.9) 220 (5.1) 0.36 121 (10.3) 535 (11.3) 0.03

Antibiotics 361 (27.0) 843 (19.5) 0.18 291 (24.7) 1106 (23.3) 0.03

Continued




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SMD


SMD(n=1336) (n=4326) (n=1179) (n=4738)


Marital status

Widowed 286 (21.4) 591 (13.7) 0.20 226 (19.1) 801 (16.9) 0.06

Divorced 195 (14.6) 745 (17.2) 0.07 194 (16.5) 734 (15.5) 0.03

Married 743 (55.6) 2519 (58.2) 0.05 641 (54.4) 2748 (58.0) 0.07

Unmarried 95 (7.1) 429 (9.9) 0.10 102 (8.7) 408 (8.6) 0.00

Unknown 17 (1.3) 42 (1.0) 0.03 15 (1.3) 46 (1.0) 0.03

Ethnicity

Non- immigrant 1159 (86.8) 3665 (84.7) 0.06 1013 (86.0) 4008 (84.6) 0.04

First- generation or second- generation immigrant

177 (13.2) 661 (15.3) 0.06 166 (14.0) 730 (15.4) 0.04

Residence

Non- urban 747 (55.9) 2397 (55.4) 0.01 644 (54.6) 2685 (56.7) 0.04

Urban 589 (44.1) 1929 (44.6) 0.01 535 (45.4) 2052 (43.3) 0.04

ACE- I, ACE inhibitors; ARB, angiotensin receptor blocker; SMD, standardised mean difference.

Table 3 Continued

Table 4 Outcomes in current ACE- I/ARB users compared with ACE- I/ARB non- users aged 50+ years and compared with CCB users

Outcome

Exposed Unexposed Comparison

Events Risk (%) Events Risk (%) Risk difference (%) Relative risk

Current ACE- I/ARB users compared with current CCB users

Unweighted cohort

Death 126/1065 11.8 (9.9–13.8) 43/289 14.9 (10.8–19.0) −3.0 (−7.6–1.5) 0.80 (0.58–1.10)

ICU admission 66/1059 6.2 (4.8–7.7) 16/288 5.6 (2.9–8.2) 0.7 (−2.3–3.7) 1.12 (0.66–1.91)

Mechanical ventilation 51/1065 4.8 (3.5–6.1) 16/289 5.5 (2.9–8.2) −0.7 (−3.7–2.2) 0.86 (0.50–1.49)

Hospital admission 361/1001 36.1 (33.1–39.0) 125/273 45.8 (39.9–51.7) −9.7 (−16.3–-3.1) 0.79 (0.68–0.92)

Acute dialysis NA NA NA NA 0.2 (−1.4–1.8) 1.13 (0.38–3.35)

IPTW cohort

Death 131/1065 12.3 (10.3–14.4) 40/285 13.9 (9.2–18.6) −1.5 (−6.7–3.6) 0.89 (0.61–1.30)

ICU admission 66/1058 6.3 (4.8–7.8) 15/283 5.4 (2.3–8.4) 0.9 (−2.4–4.3) 1.17 (0.64–2.16)

Mechanical ventilation 52/1065 4.8 (3.5–6.2) 17/285 5.9 (2.6–9.2) −1.1 (−4.6–2.5) 0.82 (0.44–1.53)

Hospital admission 366/1001 36.5 (33.5–39.6) 118/274 43.3 (36.0–50.6) −6.7 (−14.7–1.2) 0.84 (0.70–1.02)

Acute dialysis NA NA NA NA 0.7 (−0.7–2.0) 1.62 (0.53–4.92)

Current ace- i/ARB users compared with ace- i/ARB non- users aged 50 years or older

Unweighted cohort

Death 166/1336 12.4 (10.7–14.2) 367/4326 8.5 (7.7–9.3) 3.9 (2.0–5.9) 1.46 (1.23–1.74)

ICU admission 104/1329 7.8 (6.4–9.3) 166/4321 3.8 (3.3–4.4) 4.0 (2.4–5.5) 2.04 (1.61–2.58)

Mechanical ventilation 81/1336 6.1 (4.8–7.3) 121/4326 2.8 (2.3–3.3) 3.3 (1.9–4.6) 2.17 (1.65–2.85)

Hospital admission 507/1258 40.3 (37.6–43.0) 1097/4192 26.2 (24.8–27.5) 14.1 (11.1–17.2) 1.54 (1.42–1.68)

Acute dialysis 27/1325 2.0 (1.3–2.8) 37/4309 0.9 (0.6–1.1) 1.2 (0.4–2.0) 2.37 (1.45–3.88)

IPTW cohort

Death 112/1179 9.5 (7.5–11.5) 512/4738 10.8 (9.1–12.5) −1.3 (−3.9–1.3) 0.88 (0.68–1.14)

ICU admission 75/1173 6.4 (4.7–8.1) 243/4733 5.1 (2.2–8.1) 1.3 (−2.1–4.7) 1.25 (0.66–2.36)

Mechanical ventilation 62/1179 5.3 (3.7–6.9) 201/4738 4.2 (1.3–7.2) 1.0 (−2.3–4.4) 1.24 (0.58–2.66)

Hospital admission 362/1118 32.3 (28.8–35.9) 1505/4546 33.1 (29.5–36.7) −0.8 (−5.8–4.3) 0.98 (0.84–1.14)

Acute dialysis 27/1172 2.3 (1.1–3.5) 36/4710 0.8 (0.5–1.0) 1.6 (0.3–2.8) 3.04 (1.64–5.65)

ACE- I, ACE inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker; ICU, intensive care unit; IPTW, inverse probability of treatment weighting; NA, not available.




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departments or during hospitalisation at New York University Langone Health.6 They examined use of ACE- Is/ARBs and other antihypertensive medications and a positive SARS- CoV-2 test result, as well as severity of COVID-19, and found no substan-tial association. The study was limited by its inclusion of only 18 months of chronic disease history, as well as by defining ACE- I/ARB exposure as any treatment yes/no within 18 months before the SARS- CoV-2 tests without evidence of discontinuation in the previous 30 days. In addition, severity of illness (defined by ICU admission, MV or death) was assessed only at one time point at the end of the study period, that is, length of follow- up differed by date of inclusion.6 An Italian case- control study included 6272 patients diagnosed with COVID-19 matched to 30 759 controls. The authors found that neither ACE- I nor ARB use was associated with risk of and severity of COVID-19.7 Expo-sure was defined as redemption of any prescription in 2019. A Danish study of 4480 patients with hospital- diagnosed COVID-19, found no clear association between ACE- I/ARB use and 30- day mortality (HR 0.83, 95% CI 0.67 to 1.03).13

Potential mechanismsWe have no data to examine whether conflicting mechanisms produced the neutral association with SARS- CoV-2 infection and outcomes that we observed. Cell- surface ACE2 expression, which is likely increased in patients treated with ACE- Is/ARBs, may facilitate SARS- CoV-2 entry into cells.5 However, ACE2 expression also has been shown to protect against development of severe acute lung injury in other infectious diseases.1 4 35 The null findings of our case- control risk analyses argue against any clinically relevant effect of ACE- I/ARB- mediated ACE2 upreg-ulation in increasing SARS- CoV-2 risk in general. These issues will be addressed in several planned trials on the impact of losartan on organ dysfunction and mortality in patients hospi-talised with SARS- CoV-2 infection ( ClinicalTrials. gov Identifier: NCT04312009 and NCT04328012).

CONCLUSIONOur study showed that ACE- I/ARB use was not associated with a consistently higher rate of acquiring a positive SARS- CoV-2 test among tested individuals. Further, ACE- I/ARB use was not associated with increased mortality and other adverse outcomes among patients with microbiologically confirmed SARS- CoV-2 infection. These results support the recommendations of continuing treatment with ACE- Is/ARBs during the COVID-19 pandemic.

Author affiliations1Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark2Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense C, Denmark3Department of Infectious Diseases, Aalborg University Hospital, Aalborg, Denmark4Department of Infectious Diseases, Aarhus University Hospital, Aarhus N, Denmark5Department of Cardiology, Aarhus University Hospital, Aarhus N, Denmark6Department of Clinical Medicine, Aarhus University, Aarhus N, Denmark7Department of Intensive Care, Aarhus University Hospital, Aarhus N, Denmark8Department of Cardiology, Regional Hospital West Jutland, Herning, Denmark9Department of Data Integration and Analysis, Statens Serum Institut, Copenhagen S, Denmark10Department of Epidemiology Research, Statens Serum Institut, Copenhagen S, Denmark11Department of Clinical Microbiology, Aarhus University Hospital, Aarhus N, Denmark12Department of Medical Evaluation and Biostatistics, Danish Medicines Agency, Copenhagen S, Denmark13Center for Population Health Sciences, Stanford University, Stanford, California, USA

Correction notice This article has been corrected since it was published Online First. An author first name and last name were interchanged.

Twitter Christian Fynbo Christiansen @ChristianFynbo and Reimar Wernich Thomsen @dr_rwt

Acknowledgements The Danish Departments of Clinical Microbiology are acknowledged for contributing to the national infectious disease surveillance. The Danish Health Data Authority and Statens Serum Institut are acknowledged for valuable support with preparation and linkage of data.

Contributors CFC, UH- J, AP, RWT and HTS planned and designed the study. All authors contributed with input to the design and participated in the interpretation of the data. CFC reviewed the literature, organised the writing and wrote the initial manuscript. All authors critically reviewed the manuscript and approved the final version for submission. AP and LCL conducted the statistical analyses. AP and HTS obtained funding. NCB, HTS, RWT supervised the study. AP and HTS are the guarantors. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding The study was funded by Aarhus University and the University of Southern Denmark.

Competing interests CFC, UH- J, RWT and HTS have not received any personal fees, grants, travel grants or teaching grants from companies, but the Department of Clinical Epidemiology is involved in studies with funding from various companies as research grants to (and administered by) Aarhus University. MR, LCL, AP and JH have participated in industry- funded projects with money paid to their employer, the University of Southern Denmark. MM has received speaker or advisory board fees from AstraZeneca, Bayer, Boston Scientific, Boehringer- Ingelheim, Bristol- Myers Squibb, and Novo Nordisk.

Patient consent for publication Not required.

Ethics approval The study was registered at the University of Southern Denmark (record no. 10.960) and approved by the Danish Health Data Authority (FSEID-00004874). According to Danish law, registry- based studies do not require approval from ethics committees or informed consent from participants.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement Data may be obtained from a third party and are not publicly available. No additional data available. Because of the sensitive nature of the data collected for this study, requests to access the databases used in this study from researchers at certified Danish research institutions may be sent to the Danish Health Data Authority by email to forskerservice@ sundhedsdata. dk.

This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non- commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

ORCID iDsChristian Fynbo Christiansen http:// orcid. org/ 0000- 0002- 0727- 953XJacob Bodilsen http:// orcid. org/ 0000- 0002- 7398- 814XMette Reilev http:// orcid. org/ 0000- 0003- 1241- 4385Reimar Wernich Thomsen http:// orcid. org/ 0000- 0001- 9135- 3474

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31 Pottegård A, Kurz X, Moore N, et al. Considerations for pharmacoepidemiological analyses in the SARS- CoV-2 pandemic. Pharmacoepidemiol Drug Saf 2020;29:825–31.

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35 Vaduganathan M, Vardeny O, Michel T, et al. Renin- Angiotensin- Aldosterone system inhibitors in patients with Covid-19. N Engl J Med 2020;382:1653–9.




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BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any relianceSupplemental material placed on this supplemental material which has been supplied by the author(s) Thorax

doi: 10.1136/thoraxjnl-2020-215768–10.:10 2020;Thorax, et al. Christiansen CF

2

eTable 1. Medication, diagnosis and treatment codes used in the study.

Source/ coding

Look-back

Inclusion codes Exclusion codes

Exposures (ATC codes)

Number of antihypertensives NPD/ATC 90d 0-5 (see below: ACEI/ARB, CCB, Thiazides/diuretics, BB, other antihypertensives)

ACEI NPD/ATC 90d C09A, C09B

ARB NPD/ATC 90d C09C, C09D

Calcium channel blockers (CCB) NPD/ATC 90d C07FB, C08CA, C09BB, C09DB, C09DX01

Thiazides/diuretics NPD/ATC 90d C03AA01, C03AA03, C03AB01, C03AB03, C03AX01, C03EA, C07B, C09BA, C09DA, C09DX01, C09DX03, C09XA52, C09XA54

C07BA06 C09BA04

Beta-blockers (BB) NPD/ATC 90d C07

Other antihypertensives NPD/ATC 90d C02AC, C02CA, C03BA11, C09XA C02AB01

C09XA54

Outcomes

ICU admission (procedure code) DNPR/Procedure

NABE, NABB

Mechanical ventilation (procedure code)

DNPR/Procedure

BGDA0

Acute renal replacement therapy (dialysis) (in patients without chronic dialysis)

DNPR/Procedure

BJFD0 BJFD2 (any codes within prior 12 months)

Treatment with inotropes/vasopressors

DNPR/Procedure

BFHC92A, BFHC92B, BFHC92C, BFHC92D, BFHC92E, BFHC93A, BFHC93B, BFHC93C, BFHC95

Covariates

Age CPR

Sex CPR

Marital status CPR (Widowed, divorced, married, unmarried, or unknown)

Rural/urban place of residence CPR (Urban = Living in the cities of Copenhagen, Aarhus, Odense, or Aalborg)

Ethnicity CPR (First-/ second-generation immigrant or non-immigrant)

Calendar time (before / after lockdown was instituted March 13, 2020)

DNPR

Hospital-diagnosed hypertension DNPR/ICD-10 10y I10, I15

Stable angina pectoris (without procedures)

DNPR/ICD-10 10y I20, I251, I259 I21, I22, I23, I200

Stable angina pectoris or CABG/PCI procedures


DNPR/Procedure

10y KFNA, KFNB, KFNC, KFND, KFNE, KFNF, KFNG, KFNH20

I21, I22, I23, I200



3

(any diagnosis during hospital contact with the procedure or within 10 years before)

Myocardial infarction DNPR/ICD-10 10y I21, I22, I23

Heart failure DNPR/ICD-10 10y I50

Stroke DNPR/ICD-10 10y I60, I61, I63, I64

Atrial fibrillation/flutter DNPR/ICD-10 10y I48

Heart valve disease DNPR/ICD-10 10y I05, I06, I07, I08, I09.8, I34-I37, I39, I51.1A, Q22, Q23

Venous thromboembolism DNPR/ICD-10 10y I26, I801, I802, I803

Diabetes DNPR/ICD-10 10y E10, E11, E12, E13, E14, O24, G63.2, H360, N083

O24.4

NPD/ATC 10y A10A, A10B

Chronic pulmonary disease DNPR/ICD-10 10y J40, J41-J44, J45−J47, J60−J67, J68.4, J70.1, J70.3, J84.1, J92.0, J96.1, J98.2, J98.3

Markers of smoking (diagnoses or medications for tobacco smoking or chronic obstructive pulmonary disease)

DNPR/ICD-10

10y J41-J44, F17, Z716, Z720

NPD/ATC 10y R03, N07BA

Obesity diagnoses or medications

DNPR/ICD-10 10y E66

NPD/ATC 10y A08

Alcoholism-related diagnoses or medication for alcohol deterrent

DNPR/ICD-10 10y DF10, DE244, DG312, DG621, DG721, DI426, DK292, DK70, DK852, DK860, DQ860, DZ502, DZ714, DZ721

F100

NPD/ATC 10y V03AA, N07BB

Kidney disease diagnosis DNPR/ICD-10 10y I12, I13, N00−N05, N07, N11, N14, N18−N19, Q61, N08, E102, E112, E142

End-stage renal disease (kidney transplant or dialysis)

DNPR/Procedure

10y BJFD2

DNPR/Surgery

10y KKAS

DNPR/ICD-10 10y T861, Z940

Liver disease DNPR/ICD-10 10y B18, B150, B160, B162, B190, I85, K70, K71, K72, K73, K74, K760, K76.6

Dementia DNPR/ICD-10 10y DF00, DF01, DF02, DF03, DG30, DG310B, DG311, DG318, DG319



4

NPD/ATC 10y N06D

Cancer (including metastatic cancer)

DNPR/ICD-10 10y C00−C96, D459, D46, D471, D473, D474, D475, CxxxM

C44

Concurrent antihypertensive medication (see exposures)

NPD/ATC

Statins NPD/ATC 90d C10AA, C10B

Aspirin NPD/ATC 90d B01AC06, N02BA01, N02BA51

Opioid use NPD/ATC 90d N02A, N07BC02

Immunosuppressant use NPD/ATC 90d L04

Glucocorticoids NPD/ATC 90d H02AB

Loop diuretics NPD/ATC 90d C03C

Antibiotics NPD/ATC 10d J01

Antivirals NPD/ATC 10d J05

Vitamin K antagonists NPD/ATC 90d B01AA

Antidepressants NPD/ATC 90d N06A

Antipsychotics NPD/ATC 90d N05A

Hypnotics/sedatives NPD/ATC 90d N05C

Abbreviations: ATC, Anatomical Therapeutic Chemical Classification System; CPR, Danish Civil Registration System; DNPR, Danish National

Patient Registry; ICD-10, International Classification of Diseases, Tenth Revision; NPD, National Prescription Database.



5

eTable 2. Outcomes (death and ICU admission) among current ACEI/ARB users compared with CCB users after propensity-

score weighting. Stratified by subgroups.


Death Events Risk (%) Events Risk (%) Risk difference (%) Relative risk

Overall 131/1,065 12.3 (10.3-14.4) 40/285 13.9 (9.2-18.6) -1.5 (-6.7-3.6) 0.89 (0.61-1.30)

Subgroups:

Age >65 years 122/573 21.2 (17.7-24.7) 45/190 23.5 (15.2-31.8) -2.3 (-11.3-6.7) 0.90 (0.61-1.33)

Hypertension (no other cardiovascular disease)

55/616 9.0 (6.7-11.3) 17/179 9.7 (5.0-14.4) -0.7 (-5.9-4.5) 0.93 (0.54-1.60)

After lock-down 124/1,022 12.1 (10.0-14.2) 39/276 14.0 (9.0-19.0) -1.9 (-7.2-3.5) 0.87 (0.58-1.29)

ICU admission

Overall 66/1,058 6.3 (4.8-7.8) 15/283 5.4 (2.3-8.4) 0.9 (-2.4-4.3) 1.17 (0.64-2.16)

Subgroups:

Age >65 years 53/567 9.3 (6.9-11.7) 14/188 7.4 (0.9-14.0) 1.9 (-5.1-8.8) 1.25 (0.50-3.14)


39/613 6.3 (4.3-8.4) 7/179 3.9 (0.7-7.0) 2.5 (-1.3-6.2) 1.64 (0.68-3.97)

After lock-down 64/1,016 6.3 (4.8-7.8) 16/273 5.7 (2.0-9.4) 0.6 (-3.4-4.5) 1.10 (0.55-2.18)

Abbreviations: ACEI, Angiotensin converting enzyme inhibitors; ARB, Angiotensin receptor blockers; CCB, Calcium channel blockers; ICU,

Intensive care unit



6

eTable 3. Outcomes (death and ICU admission) by different exposure definitions after inverse probability of treatment weighting.



cACEI/ARB vs. cCCB 131/1,065 12.3 (10.3-14.4) 40/285 13.9 (9.2-18.6) -1.5 (-6.7-3.6) 0.89 (0.61-1.30)

cACEI/ARB vs. no ACEI/ARB (50+) 112/1,179 9.5 (7.5-11.5) 512/4,738 10.8 (9.1-12.5) -1.3 (-3.9-1.3) 0.88 (0.68-1.14)

Other exposures: Former vs. no ACEI/ARB (50+) 41/464 8.8 (6.2-11.4) 420/4,343 9.7 (8.7-10.6) -0.9 (-3.6-1.9) 0.91 (0.67-1.24)

cACEI/ARB vs. cCCB with current use defined as 120 days

145/1,194 12.2 (10.2-14.1) 41/319 12.9 (9.0-16.9) -0.7 (-5.1-3.6) 0.94 (0.67-1.33)

cACEI/ARB vs. no ACEI/ARB (50+) with current use defined as 120 days

124/1,354 9.1 (7.4-10.8) 522/4,713 11.1 (9.4-12.8) -2.0 (-4.3-0.4) 0.82 (0.65-1.05)

cACEI vs. cCCB 66/425 15.6 (11.3-20.0) 43/285 14.9 (9.8-20.0) 0.7 (-6.0-7.4) 1.05 (0.68-1.62) cARB vs. cCCB 72/636 11.3 (8.6-14.0) 41/288 14.1 (9.5-18.8) -2.8 (-8.2-2.5) 0.80 (0.53-1.20) cACEI/ARB vs. thiazide 120/1,001 12.0 (9.9-14.1) 19/202 9.5 (3.7-15.2) 2.5 (-3.6-8.6) 1.27 (0.67-2.38) cACEI/ARB vs. beta blocker 165/1,182 14.0 (9.4-18.5) 60/456 13.2 (10.0-16.5) 0.7 (-4.9-6.3) 1.06 (0.70-1.59)

ICU admission cACEI/ARB vs. cCCB 66/1,058 6.3 (4.8-7.8) 15/283 5.4 (2.3-8.4) 0.9 (-2.4-4.3) 1.17 (0.64-2.16)

cACEI/ARB vs. no ACEI/ARB (50+) 75/1,173 6.4 (4.7-8.1) 243/4,733 5.1 (2.2-8.1) 1.3 (-2.1-4.7) 1.25 (0.66-2.36)

Other exposures: Former vs. no ACEI/ARB (50+) 32/463 6.9 (4.4-9.5) 172/4,338 4.0 (3.4-4.6) 3.0 (0.3-5.6) 1.74 (1.17-2.59)


84/1,188 7.0 (5.6-8.5) 15/316 4.7 (2.3-7.1) 2.4 (-0.5-5.2) 1.50 (0.86-2.63)


103/1,349 7.6 (5.8-9.4) 239/4,708 5.1 (2.3-7.8) 2.5 (-0.7-5.8) 1.50 (0.83-2.69)

cACEI vs. cCCB 28/418 6.8 (4.2-9.4) 20/283 7.0 (2.5-11.4) -0.2 (-5.3-4.9) 0.98 (0.47-2.05) cARB vs. cCCB 40/634 6.3 (4.3-8.3) 14/286 4.8 (2.3-7.2) 1.5 (-1.6-4.7) 1.32 (0.72-2.42) cACEI/ARB vs. thiazide NA NA NA NA 5.7 (2.6-8.9) 4.24 (0.93-19.40) cACEI/ARB vs. beta blocker 87/1,175 7.4 (3.8-11.1) 33/452 7.3 (4.0-10.5) 0.2 (-4.7-5.1) 1.02 (0.53-1.99)

Abbreviations: ACEI, Angiotensin converting enzyme inhibitors; ARB, Angiotensin receptor blockers; c, Current; CCB, Calcium channel blockers;

NA, not available (masked to prevent identification of individuals when n<5)



7

eTable 4. Characteristics by exposure group (current ACEI/ARB, no ACEI/ARB, current CCB) regardless of test result

Current ACEI/ARB users No ACEI/ARB use Current CCB users

(n=110,330) (n=952,875) (n=56,591)

Age, median (IQR) 67 (58-76) 38 (24-54) 68 (59-77)

Sex (male) 55,846 (50.6) 404,285 (42.4) 28,864 (51.0)

Marital status

Widowed 16,449 (14.9) 32,025 (3.4) 9,313 (16.5)

Divorced 18,459 (16.7) 97,169 (10.2) 9,494 (16.8)

Married 62,299 (56.5) 351,872 (36.9) 31,511 (55.7)

Unmarried 12,783 (11.6) 470,651 (49.4) 6,096 (10.8)

Unknown 340 (0.3) 1,158 (0.1) 177 (0.3)

Ethnicity

Non-immigrant 102,792 (93.2) 807,456 (84.7) 52,765 (93.2)

First- or second-generation immigrant 7,538 (6.8) 145,419 (15.3) 3,826 (6.8)

Residence

Non-urban 76,907 (69.7) 551,966 (57.9) 40,045 (70.8)

Urban 33,423 (30.3) 400,909 (42.1) 16,546 (29.2)

Health care professional

Physician 455 (0.4) 9,961 (1.0) 217 (0.4)

Nurse 1,771 (1.6) 30,429 (3.2) 729 (1.3)

Care assistant 2,037 (1.8) 22,091 (2.3) 947 (1.7)

Use of antihypertensives

Angiotensin converting enzyme inhibitors 46,782 (42.4) - 12,532 (22.1)

Angiotensin receptor blockers 64,354 (58.3) - 18,289 (32.3)

Calcium channel blockers 30,604 (27.7) 19,850 (2.1) 56,591 (100.0)

Thiazides 33,622 (30.5) 11,409 (1.2) 14,031 (24.8)

Beta blockers 28,483 (25.8) 26,275 (2.8) 14,370 (25.4)

Other antihypertensives 1,919 (1.7) 1,000 (0.1) 1,566 (2.8)

Diagnoses

Hypertension 48,937 (44.4) 34,836 (3.7) 27,620 (48.8)

Atrial fibrillation 14,370 (13.0) 21,345 (2.2) 6,135 (10.8)

Obesity 12,019 (10.9) 56,152 (5.9) 5,500 (9.7)

Angina 16,843 (15.3) 21,063 (2.2) 8,505 (15.0)

Heart valve disease 6,605 (6.0) 10,172 (1.1) 3,362 (5.9)



8

Alcohol abuse 4,804 (4.4) 21,345 (2.2) 2,546 (4.5)

Diabetes 27,006 (24.5) 34,298 (3.6) 12,452 (22.0)

Venous thromboembolism 3,837 (3.5) 11,906 (1.2) 1,917 (3.4)

Dementia 2,576 (2.3) 6,887 (0.7) 1,485 (2.6)

Myocardial infarction 6,082 (5.5) 6,637 (0.7) 2,600 (4.6)

Liver disease 1,689 (1.5) 8,155 (0.9) 879 (1.6)

Kidney disease 5,888 (5.3) 7,720 (0.8) 4,073 (7.2)

Chronic obstructive pulmonary disease 13,410 (12.2) 56,044 (5.9) 6,894 (12.2)

End-stage renal disease 352 (0.3) 714 (0.1) 437 (0.8)

Heart failure 9,786 (8.9) 5,122 (0.5) 2,012 (3.6)

Cancer 14,748 (13.4) 41,817 (4.4) 8,032 (14.2)

Stroke 8,264 (7.5) 12,739 (1.3) 5,004 (8.8)

Markers of smoking 39,884 (36.1) 245,705 (25.8) 20,330 (35.9)

Medication

Statins 43,769 (39.7) 42,956 (4.5) 22,058 (39.0)

Antiviral 1,117 (1.0) 10,877 (1.1) 553 (1.0)

Low-dose acetylsalicylic acid 16,737 (15.2) 16,868 (1.8) 9,111 (16.1)

Vitamin K-antagonists 3,259 (3.0) 4,048 (0.4) 1,375 (2.4)

Opioids 12,914 (11.7) 34,683 (3.6) 7,119 (12.6)

Antidepressants 15,166 (13.7) 55,507 (5.8) 8,243 (14.6)

Immunosuppresants 822 (0.7) 3,183 (0.3) 405 (0.7)

Antipsychotics 3,270 (3.0) 18,408 (1.9) 1,791 (3.2)

Glucocorticoids 4,669 (4.2) 13,543 (1.4) 2,534 (4.5)

Hypnotics 6,395 (5.8) 21,623 (2.3) 3,554 (6.3)

Loop diuretics 12,532 (11.4) 13,744 (1.4) 6,003 (10.6)

Antibiotics 18,183 (16.5) 89,109 (9.4) 9,589 (16.9) Abbreviations: ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.



9

eTable 5. Positive:negative ratio of SARS-CoV-2 test in exposure groups overall and stratified by age groups.


Overall 0.0135 0.0122 0.0123

Age group (years)

18-29 0.0078 0.0112 0.0164

30-44 0.0124 0.0129 0.0108

45-65 0.0137 0.0147 0.0116

>65 0.0134 0.0140 0.0129 Abbreviations: ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.





2

eTable 1. Medication, diagnosis and treatment codes used in the study.

Source/ coding

Look-back

Inclusion codes Exclusion codes

Exposures (ATC codes)

Number of antihypertensives NPD/ATC 90d 0-5 (see below: ACEI/ARB, CCB, Thiazides/diuretics, BB, other antihypertensives)

ACEI NPD/ATC 90d C09A, C09B

ARB NPD/ATC 90d C09C, C09D

Calcium channel blockers (CCB) NPD/ATC 90d C07FB, C08CA, C09BB, C09DB, C09DX01

Thiazides/diuretics NPD/ATC 90d C03AA01, C03AA03, C03AB01, C03AB03, C03AX01, C03EA, C07B, C09BA, C09DA, C09DX01, C09DX03, C09XA52, C09XA54

C07BA06 C09BA04

Beta-blockers (BB) NPD/ATC 90d C07

Other antihypertensives NPD/ATC 90d C02AC, C02CA, C03BA11, C09XA C02AB01

C09XA54

Outcomes

ICU admission (procedure code) DNPR/Procedure

NABE, NABB

Mechanical ventilation (procedure code)

DNPR/Procedure

BGDA0

Acute renal replacement therapy (dialysis) (in patients without chronic dialysis)

DNPR/Procedure

BJFD0 BJFD2 (any codes within prior 12 months)

Treatment with inotropes/vasopressors

DNPR/Procedure

BFHC92A, BFHC92B, BFHC92C, BFHC92D, BFHC92E, BFHC93A, BFHC93B, BFHC93C, BFHC95

Covariates

Age CPR

Sex CPR

Marital status CPR (Widowed, divorced, married, unmarried, or unknown)

Rural/urban place of residence CPR (Urban = Living in the cities of Copenhagen, Aarhus, Odense, or Aalborg)

Ethnicity CPR (First-/ second-generation immigrant or non-immigrant)

Calendar time (before / after lockdown was instituted March 13, 2020)

DNPR

Hospital-diagnosed hypertension DNPR/ICD-10 10y I10, I15

Stable angina pectoris (without procedures)


Stable angina pectoris or CABG/PCI procedures


DNPR/Procedure

10y KFNA, KFNB, KFNC, KFND, KFNE, KFNF, KFNG, KFNH20

I21, I22, I23, I200



3

(any diagnosis during hospital contact with the procedure or within 10 years before)

Myocardial infarction DNPR/ICD-10 10y I21, I22, I23

Heart failure DNPR/ICD-10 10y I50

Stroke DNPR/ICD-10 10y I60, I61, I63, I64

Atrial fibrillation/flutter DNPR/ICD-10 10y I48

Heart valve disease DNPR/ICD-10 10y I05, I06, I07, I08, I09.8, I34-I37, I39, I51.1A, Q22, Q23

Venous thromboembolism DNPR/ICD-10 10y I26, I801, I802, I803

Diabetes DNPR/ICD-10 10y E10, E11, E12, E13, E14, O24, G63.2, H360, N083

O24.4

NPD/ATC 10y A10A, A10B

Chronic pulmonary disease DNPR/ICD-10 10y J40, J41-J44, J45−J47, J60−J67, J68.4, J70.1, J70.3, J84.1, J92.0, J96.1, J98.2, J98.3

Markers of smoking (diagnoses or medications for tobacco smoking or chronic obstructive pulmonary disease)

DNPR/ICD-10

10y J41-J44, F17, Z716, Z720

NPD/ATC 10y R03, N07BA

Obesity diagnoses or medications

DNPR/ICD-10 10y E66

NPD/ATC 10y A08

Alcoholism-related diagnoses or medication for alcohol deterrent

DNPR/ICD-10 10y DF10, DE244, DG312, DG621, DG721, DI426, DK292, DK70, DK852, DK860, DQ860, DZ502, DZ714, DZ721

F100

NPD/ATC 10y V03AA, N07BB

Kidney disease diagnosis DNPR/ICD-10 10y I12, I13, N00−N05, N07, N11, N14, N18−N19, Q61, N08, E102, E112, E142

End-stage renal disease (kidney transplant or dialysis)

DNPR/Procedure

10y BJFD2

DNPR/Surgery

10y KKAS

DNPR/ICD-10 10y T861, Z940

Liver disease DNPR/ICD-10 10y B18, B150, B160, B162, B190, I85, K70, K71, K72, K73, K74, K760, K76.6

Dementia DNPR/ICD-10 10y DF00, DF01, DF02, DF03, DG30, DG310B, DG311, DG318, DG319



4

NPD/ATC 10y N06D

Cancer (including metastatic cancer)

DNPR/ICD-10 10y C00−C96, D459, D46, D471, D473, D474, D475, CxxxM

C44

Concurrent antihypertensive medication (see exposures)

NPD/ATC

Statins NPD/ATC 90d C10AA, C10B

Aspirin NPD/ATC 90d B01AC06, N02BA01, N02BA51

Opioid use NPD/ATC 90d N02A, N07BC02

Immunosuppressant use NPD/ATC 90d L04

Glucocorticoids NPD/ATC 90d H02AB

Loop diuretics NPD/ATC 90d C03C

Antibiotics NPD/ATC 10d J01

Antivirals NPD/ATC 10d J05

Vitamin K antagonists NPD/ATC 90d B01AA

Antidepressants NPD/ATC 90d N06A

Antipsychotics NPD/ATC 90d N05A

Hypnotics/sedatives NPD/ATC 90d N05C

Abbreviations: ATC, Anatomical Therapeutic Chemical Classification System; CPR, Danish Civil Registration System; DNPR, Danish National

Patient Registry; ICD-10, International Classification of Diseases, Tenth Revision; NPD, National Prescription Database.



5

eTable 2. Outcomes (death and ICU admission) among current ACEI/ARB users compared with CCB users after propensity-

score weighting. Stratified by subgroups.



Overall 131/1,065 12.3 (10.3-14.4) 40/285 13.9 (9.2-18.6) -1.5 (-6.7-3.6) 0.89 (0.61-1.30)

Subgroups:

Age >65 years 122/573 21.2 (17.7-24.7) 45/190 23.5 (15.2-31.8) -2.3 (-11.3-6.7) 0.90 (0.61-1.33)


55/616 9.0 (6.7-11.3) 17/179 9.7 (5.0-14.4) -0.7 (-5.9-4.5) 0.93 (0.54-1.60)

After lock-down 124/1,022 12.1 (10.0-14.2) 39/276 14.0 (9.0-19.0) -1.9 (-7.2-3.5) 0.87 (0.58-1.29)

ICU admission

Overall 66/1,058 6.3 (4.8-7.8) 15/283 5.4 (2.3-8.4) 0.9 (-2.4-4.3) 1.17 (0.64-2.16)

Subgroups:

Age >65 years 53/567 9.3 (6.9-11.7) 14/188 7.4 (0.9-14.0) 1.9 (-5.1-8.8) 1.25 (0.50-3.14)


39/613 6.3 (4.3-8.4) 7/179 3.9 (0.7-7.0) 2.5 (-1.3-6.2) 1.64 (0.68-3.97)

After lock-down 64/1,016 6.3 (4.8-7.8) 16/273 5.7 (2.0-9.4) 0.6 (-3.4-4.5) 1.10 (0.55-2.18)

Abbreviations: ACEI, Angiotensin converting enzyme inhibitors; ARB, Angiotensin receptor blockers; CCB, Calcium channel blockers; ICU,

Intensive care unit



6

eTable 3. Outcomes (death and ICU admission) by different exposure definitions after inverse probability of treatment weighting.



cACEI/ARB vs. cCCB 131/1,065 12.3 (10.3-14.4) 40/285 13.9 (9.2-18.6) -1.5 (-6.7-3.6) 0.89 (0.61-1.30)

cACEI/ARB vs. no ACEI/ARB (50+) 112/1,179 9.5 (7.5-11.5) 512/4,738 10.8 (9.1-12.5) -1.3 (-3.9-1.3) 0.88 (0.68-1.14)

Other exposures: Former vs. no ACEI/ARB (50+) 41/464 8.8 (6.2-11.4) 420/4,343 9.7 (8.7-10.6) -0.9 (-3.6-1.9) 0.91 (0.67-1.24)


145/1,194 12.2 (10.2-14.1) 41/319 12.9 (9.0-16.9) -0.7 (-5.1-3.6) 0.94 (0.67-1.33)


124/1,354 9.1 (7.4-10.8) 522/4,713 11.1 (9.4-12.8) -2.0 (-4.3-0.4) 0.82 (0.65-1.05)

cACEI vs. cCCB 66/425 15.6 (11.3-20.0) 43/285 14.9 (9.8-20.0) 0.7 (-6.0-7.4) 1.05 (0.68-1.62) cARB vs. cCCB 72/636 11.3 (8.6-14.0) 41/288 14.1 (9.5-18.8) -2.8 (-8.2-2.5) 0.80 (0.53-1.20) cACEI/ARB vs. thiazide 120/1,001 12.0 (9.9-14.1) 19/202 9.5 (3.7-15.2) 2.5 (-3.6-8.6) 1.27 (0.67-2.38) cACEI/ARB vs. beta blocker 165/1,182 14.0 (9.4-18.5) 60/456 13.2 (10.0-16.5) 0.7 (-4.9-6.3) 1.06 (0.70-1.59)

ICU admission cACEI/ARB vs. cCCB 66/1,058 6.3 (4.8-7.8) 15/283 5.4 (2.3-8.4) 0.9 (-2.4-4.3) 1.17 (0.64-2.16)

cACEI/ARB vs. no ACEI/ARB (50+) 75/1,173 6.4 (4.7-8.1) 243/4,733 5.1 (2.2-8.1) 1.3 (-2.1-4.7) 1.25 (0.66-2.36)

Other exposures: Former vs. no ACEI/ARB (50+) 32/463 6.9 (4.4-9.5) 172/4,338 4.0 (3.4-4.6) 3.0 (0.3-5.6) 1.74 (1.17-2.59)


84/1,188 7.0 (5.6-8.5) 15/316 4.7 (2.3-7.1) 2.4 (-0.5-5.2) 1.50 (0.86-2.63)


103/1,349 7.6 (5.8-9.4) 239/4,708 5.1 (2.3-7.8) 2.5 (-0.7-5.8) 1.50 (0.83-2.69)

cACEI vs. cCCB 28/418 6.8 (4.2-9.4) 20/283 7.0 (2.5-11.4) -0.2 (-5.3-4.9) 0.98 (0.47-2.05) cARB vs. cCCB 40/634 6.3 (4.3-8.3) 14/286 4.8 (2.3-7.2) 1.5 (-1.6-4.7) 1.32 (0.72-2.42) cACEI/ARB vs. thiazide NA NA NA NA 5.7 (2.6-8.9) 4.24 (0.93-19.40) cACEI/ARB vs. beta blocker 87/1,175 7.4 (3.8-11.1) 33/452 7.3 (4.0-10.5) 0.2 (-4.7-5.1) 1.02 (0.53-1.99)

Abbreviations: ACEI, Angiotensin converting enzyme inhibitors; ARB, Angiotensin receptor blockers; c, Current; CCB, Calcium channel blockers;

NA, not available (masked to prevent identification of individuals when n<5)



7

eTable 4. Characteristics by exposure group (current ACEI/ARB, no ACEI/ARB, current CCB) regardless of test result


(n=110,330) (n=952,875) (n=56,591)

Age, median (IQR) 67 (58-76) 38 (24-54) 68 (59-77)

Sex (male) 55,846 (50.6) 404,285 (42.4) 28,864 (51.0)

Marital status

Widowed 16,449 (14.9) 32,025 (3.4) 9,313 (16.5)

Divorced 18,459 (16.7) 97,169 (10.2) 9,494 (16.8)

Married 62,299 (56.5) 351,872 (36.9) 31,511 (55.7)

Unmarried 12,783 (11.6) 470,651 (49.4) 6,096 (10.8)

Unknown 340 (0.3) 1,158 (0.1) 177 (0.3)

Ethnicity

Non-immigrant 102,792 (93.2) 807,456 (84.7) 52,765 (93.2)

First- or second-generation immigrant 7,538 (6.8) 145,419 (15.3) 3,826 (6.8)

Residence

Non-urban 76,907 (69.7) 551,966 (57.9) 40,045 (70.8)

Urban 33,423 (30.3) 400,909 (42.1) 16,546 (29.2)

Health care professional

Physician 455 (0.4) 9,961 (1.0) 217 (0.4)

Nurse 1,771 (1.6) 30,429 (3.2) 729 (1.3)

Care assistant 2,037 (1.8) 22,091 (2.3) 947 (1.7)

Use of antihypertensives

Angiotensin converting enzyme inhibitors 46,782 (42.4) - 12,532 (22.1)

Angiotensin receptor blockers 64,354 (58.3) - 18,289 (32.3)

Calcium channel blockers 30,604 (27.7) 19,850 (2.1) 56,591 (100.0)

Thiazides 33,622 (30.5) 11,409 (1.2) 14,031 (24.8)

Beta blockers 28,483 (25.8) 26,275 (2.8) 14,370 (25.4)

Other antihypertensives 1,919 (1.7) 1,000 (0.1) 1,566 (2.8)

Diagnoses

Hypertension 48,937 (44.4) 34,836 (3.7) 27,620 (48.8)

Atrial fibrillation 14,370 (13.0) 21,345 (2.2) 6,135 (10.8)

Obesity 12,019 (10.9) 56,152 (5.9) 5,500 (9.7)

Angina 16,843 (15.3) 21,063 (2.2) 8,505 (15.0)

Heart valve disease 6,605 (6.0) 10,172 (1.1) 3,362 (5.9)



8

Alcohol abuse 4,804 (4.4) 21,345 (2.2) 2,546 (4.5)

Diabetes 27,006 (24.5) 34,298 (3.6) 12,452 (22.0)

Venous thromboembolism 3,837 (3.5) 11,906 (1.2) 1,917 (3.4)

Dementia 2,576 (2.3) 6,887 (0.7) 1,485 (2.6)

Myocardial infarction 6,082 (5.5) 6,637 (0.7) 2,600 (4.6)

Liver disease 1,689 (1.5) 8,155 (0.9) 879 (1.6)

Kidney disease 5,888 (5.3) 7,720 (0.8) 4,073 (7.2)

Chronic obstructive pulmonary disease 13,410 (12.2) 56,044 (5.9) 6,894 (12.2)

End-stage renal disease 352 (0.3) 714 (0.1) 437 (0.8)

Heart failure 9,786 (8.9) 5,122 (0.5) 2,012 (3.6)

Cancer 14,748 (13.4) 41,817 (4.4) 8,032 (14.2)

Stroke 8,264 (7.5) 12,739 (1.3) 5,004 (8.8)

Markers of smoking 39,884 (36.1) 245,705 (25.8) 20,330 (35.9)

Medication

Statins 43,769 (39.7) 42,956 (4.5) 22,058 (39.0)

Antiviral 1,117 (1.0) 10,877 (1.1) 553 (1.0)

Low-dose acetylsalicylic acid 16,737 (15.2) 16,868 (1.8) 9,111 (16.1)

Vitamin K-antagonists 3,259 (3.0) 4,048 (0.4) 1,375 (2.4)

Opioids 12,914 (11.7) 34,683 (3.6) 7,119 (12.6)

Antidepressants 15,166 (13.7) 55,507 (5.8) 8,243 (14.6)

Immunosuppresants 822 (0.7) 3,183 (0.3) 405 (0.7)

Antipsychotics 3,270 (3.0) 18,408 (1.9) 1,791 (3.2)

Glucocorticoids 4,669 (4.2) 13,543 (1.4) 2,534 (4.5)

Hypnotics 6,395 (5.8) 21,623 (2.3) 3,554 (6.3)

Loop diuretics 12,532 (11.4) 13,744 (1.4) 6,003 (10.6)

Antibiotics 18,183 (16.5) 89,109 (9.4) 9,589 (16.9) Abbreviations: ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.



9

eTable 5. Positive:negative ratio of SARS-CoV-2 test in exposure groups overall and stratified by age groups.


Overall 0.0135 0.0122 0.0123

Age group (years)

18-29 0.0078 0.0112 0.0164

30-44 0.0124 0.0129 0.0108

45-65 0.0137 0.0147 0.0116

>65 0.0134 0.0140 0.0129 Abbreviations: ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.



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