What this study adds:
This observational study suggests that blocking of the
Renin–Angiotensin–Aldosterone System (RAAS) might lead to lower
Covid-19 hospitalization and mortality among patients with
pharmaceutically treated hypertension.
The best prognosis of Covid-19 patients with pharmaceutically treated
hypertension was observed if ACEIs instead of other anti-hypertensive
drugs were used.
Abstract
Aim: The risk-benefit profile of angiotensin-converting
enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) in
coronavirus disease 2019 (Covid-19) is still a matter of debate. With
growing evidence on the protective effect of this group of commonly used
antihypertensives in Covid-19, we aimed to thoroughly investigate the
association between the use of major classes of antihypertensive
medications and Covid-19 outcomes in comparison with the use of ACEIs
and ARBs.
Methods: We conducted a population-based study in
patients with pre-existing hypertension in the UK Biobank. Multivariable
logistic regression analysis was performed adjusting for a wide range of
confounders.
Results: The use of either beta-blockers (BBs),
calcium-channel blockers (CCBs), or diuretics was associated with a
higher risk of Covid-19 hospitalization compared to ACEI use (adjusted
OR, 1.63; 95% CI, 1.40 to 1.90) and ARB use (adjusted OR, 1.50; 95%
CI, 1.27 to 1.77). The risk of 28-day mortality among Covid-19 patients
was also increased among users of BBs, CCBs or diuretics when compared
to ACEI users (adjusted OR, 1.64; 95% CI, 1.23 to 2.19) but not when
compared to ARB users (adjusted OR, 1.18; 95% CI, 0.87 to 1.59).
However, no associations were observed when the same analysis was
conducted among hospitalized Covid-19 patients only.
Conclusion: Our results suggest protective effects of
blocking of the renin-angiotensin-aldosterone system on Covid-19
hospitalization and mortality among patients with pharmaceutically
treated hypertension, which should be addressed by randomized controlled
trials. If confirmed, this finding could have high clinical relevance
for treating hypertension during the SARS-CoV-2 pandemic.
Introduction
There has been a debate over the role of renin-angiotensin-aldosterone
system (RAAS) and RAAS blockers in coronavirus disease 2019 (Covid-19).
Angiotensin Converting Enzyme 2 (ACE2) is a transmembrane enzyme that
functions as receptor for severe acute respiratory syndrome coronavirus
2 (SARS-CoV-2) [1]. After SARS-CoV-2 binds to ACE2 receptor,
endocytosis of the viral complex results in ACE2 downregulation and
accumulation of angiotensin II (AngII) with pro-inflammatory,
vasoconstrictive, and pro-fibrotic effects. ACE2 is present in different
organs including heart, kidney, and lungs, the target organ for
SARS-CoV-2. ACE2 also counteracts the activation of RAAS via degrading
AngII to angiotensin (1-7) that exert their vasodilatory,
anti-inflammatory and antiproliferative effects through mitochondrial
assembly (MAS) receptor [2-4].
The controversy about the use of angiotensin-converting enzyme
inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) in patients
infected with SARS-CoV-2 started with findings that showed higher
prevalence and mortality of patients with cardiovascular diseases such
as hypertension among patients with Covid-19 [5]. Moreover, in an
animal study increased expression of ACE2 messenger RNA (mRNA) with the
use of RAAS inhibitors was observed suggesting higher susceptibility to
SARS-CoV-2 among the users of these medications and hence it was
hypothesized that their use might be related to Covid-19 severity and
mortality [6,7]. However, current findings do not support this
association [8-12] and evidence regarding beneficial effects of RAAS
blockers is growing, illustrating a potential protective effect of RAAS
inhibitors in relation to Covid-19 through the ACE2/angiotensin 1-7/MAS
axis and counteracting of the harmful effects of accumulated AngII
[13,14].
The favorable effect of RAAS inhibitors in Covid-19 needs investigation
in a large cohort study considering the inadequate and conflicting
evidence at hand. Therefore, we aimed to investigate the association of
ACEIs and ARBs with adverse Covid-19 outcomes in comparison with other
anti-hypertensive drugs in the large UK Biobank.
Methods
Study Population
The UK Biobank is a large population-based prospective cohort with about
500,000 participants living in the UK aged 40–69 years when recruited
in 2006–2010. The collection of data involved a self-completed
touch-screen questionnaire, a computer-assisted interview, physical and
functional measures, and the collection of biological samples, as
previously described in detail [15]. The data is also linked to
electronic health-related records, including death, cancer,
hospital admissions and primary care records. The UK Biobank study has
obtained ethical approval from regulatory authorities and all
participants provided signed electronic informed consent.
The UK Biobank has released Covid-19 data for its participants starting
from March 2020. The data comprises of diagnostic Covid-19 test data,
primary care data provided directly by the system suppliers, hospital
inpatient, critical care and death data that are being updated regularly
[16,17]. Currently, the primary care data are only available for
England and study participants from Scotland and Wales needed to be
excluded. A part of the primary care data are the prescription data of
general practitioners (GP). Participants from England with no recorded
GP prescription data and those who died before March 2020 were further
excluded from the analyses. Moreover, to account for the confounding by
indication bias, only patients with pharmaceutically treated
hypertension were included. Finally, among 149,962 English study
participants with recent use of antihypertensive medications, a total of
124,143 (82.8%) had diagnosed hypertension and could be included in the
analyses.
Ascertainment of
Outcomes
Our primary outcome of interest was hospitalization due to Covid-19 and
was identified from positive Covid-19 test results originated from a
hospital setting. The secondary outcomes were 28-day all-cause mortality
among: 1) Covid-19 patients and 2) Hospitalized Covid-19 patients.
We used the Covid-19 data release from June 2, 2021, which included
Covid-19 test data from March 16, 2020, onwards. However, we used only
Covid-19 test data up to February 23, 2021, to have at least 28 days of
mortality follow-up for all patients (the last date of death in the
death data set available in June 2021 was March 23, 2021). In addition,
we wanted to restrict the time of assessment of Covid-19 patients to
have not too many study participants with SARS-CoV-2 vaccination in our
study population. According to official statistics, on February 23,
2021, the prevalence of full SARS-CoV-2 vaccination in the UK was 1.2%
[18].
Exposures
Participants with recent use of antihypertensive medications as
combination or monotherapy were identified from the GP data, using the
ATC codes C02, C03, C07, C08 and C09. The antihypertensive treatment was
then categorized to the following drug classes: ACEI (C09A and C09B),
ARB (C09C and C09D), diuretic (C03, C02L, C07B, C07C, C07D, C08G, C09BA
and C09DA), beta-blocker (BB) (C07) and calcium-channel-blocker (CCB)
(C08, C07FB, C09BB and C09DB). Recent use was defined as six months
prior to Covid-19 test date for participants with Covid-19 positive test
result and six months prior to onset of the SARS-CoV-2 pandemic in March
2020 for those with no Covid-19 infection.
Covariates
Sociodemographic, lifestyle, and health-related data were taken from the
touchscreen interview conducted at the baseline examination of the UK
Biobank. Age at onset of the pandemic was calculated by adding the years
passed between date of attending assessment center for baseline
examination and March 1, 2020 to the baseline age. The ethnic background
was categorized as white, black, and other (all other ethnic groups
combined) and smoking status by never, former, or current smoker. The
Townsend deprivation index was calculated based on the participants
living areas defined by the corresponding postal codes [19]. The
intensity of physical activity (low, moderate, high) was based on the
international physical activity questionnaire (IPAQ). The grams of
ethanol consumed was estimated using the amount and type of beverages
used and classified in to the WHO drinking categories as follows:
abstainers, category I (mild) including women with an alcohol
consumption of < 20 g/day or men with < 40 g/day,
and category II (moderate) including women with an alcohol consumption
of 20-39.99 g/day or men with 40-59.99 g/day and category III (heavy)
including women with an alcohol consumption of ≥ 40 g/day or men with ≥
60 g/day.
Blood samples were donated and height, weight, systolic blood pressure
(SBP) and diastolic blood pressure (DBP) measures were taken as part of
the health assessments during the baseline examination in the recruiting
centers. An Omron automated device (range returned: 0-255 mmHg) or a
manual sphygmometer as an alternative were used for blood pressure
measurements. High-density lipoprotein (HDL) cholesterol (mmol/L),
low-density lipoprotein (LDL) cholesterol (mmol/L) and creatinine
(µmol/L) were measured using enzyme immunoinhibition analysis, enzymatic
protective selection analysis and enzymatic analysis on a Beckman
Coulter AU5800, respectively. The estimated glomerular filtration rate
(eGFR) was calculated based on the CKD-Epi equation [20] using serum
creatinine and categorized to three levels: ≥ 90 (mL/min/1.73m²), ≥ 60 -
< 90 (mL/min/1.73m²), and < 60 (mL/min/1.73m²).
In addition to self-reported chronic diseases and major cardiovascular
events in the touchscreen interview at baseline, GP diagnosis data were
used to complete diagnoses as good as possible up to the baseline date
for this analysis, which was March 16, 2020 (first recorded positive
SARS-CoV-2 test in the UK Biobank study population). The comorbid
conditions assessed were chronic obstructive pulmonary disease (COPD),
diabetes mellitus, heart failure, coronary heart disease (CHD), history
of myocardial infarction (MI) and history of stroke.
To specify the use of low-dose aspirin, lipid-lowering drugs, and number
of drugs concurrently used in participants only the GP data were used.
The time window to find users of low-dose aspirin and lipid-lowering
drugs was defined as six months prior to March 2020. For the total
number of drugs used by each participant, a shorter, three-month period
prior to March 2020 was considered. Prescriptions with the same ATC code
in this interval were only counted once.
In summary, age, all co-morbidity, and drug utilization information were
up to date on the state of the onset of the SARS-CoV-2 pandemic (March
2020), while life-style-factors, physical health assessment measurements
and biomarkers were on the state of the UK Biobank’s baseline
examination from 2006–2010.
Statistical Analysis
Multivariable logistic regression models were fitted and odds ratios
(OR) and corresponding 95% confidence intervals (CI) were estimated for
the risk of Covid-19 hospitalization and 28-day all-cause mortality
associated with drug exposures of interest. Covid-19 hospitalization was
addressed in the total population of patients with hypertension and
28-day all-cause mortality was evaluated in two subpopulations of
hypertensive patients: 1) Those who tested positive for SARS-CoV-2 and
2) those who were hospitalized due to Covid-19.
In a first round of analyses, ARB, CCB, BB and diuretics users were
directly compared to ACEI users and in a second round of analyses the
latter three were directly compared to ARB users as the reference group.
To increase the statistical power, in the third round of analyses, we
combined users of either CCBs, BBs and diuretics as one exposure group
and compared it first to ACEI users and second to ARB users. Moreover,
unadjusted Kaplan-Meier curves were generated for the third round of
analyses and log-rank tests were applied to test for different survival
probabilities between the patients who received different classes of
anti-hypertensives.
Patients receiving combinations of other antihypertensive drug classes
and ACEIs or ARBs were only assigned to the ACEIs or ARBs users’ group
respectively. In sensitivity analysis, we removed patients that used
drug combinations with ACEIs or ARBs from the respective analyses using
one of these drug groups as the reference.
All models were first adjusted for age, sex and ethnic background only
(“simple model”), and second for all potential confounders available
in the UK Biobank (“full model”), which included age, sex, ethnic
background, socio-economic deprivation, smoking status, physical
activity, alcohol consumption, body mass index (BMI), SBP, DBP, HDL
cholesterol, LDL cholesterol, eGFR, COPD, diabetes mellitus, heart
failure, CHD, history of MI, history of stroke, use of low-dose aspirin,
use of lipid-lowering drugs, and number of drugs concurrently used.
All the analyses were conducted with SAS software, version 9.4. The MCMC
algorithm of the SAS procedure PROC MI was utilized to impute missing
covariate values. Analyses of the five imputed datasets were combined
using the SAS procedure PROC MIANALYZE. Two-sided p values
<0.05 were considered significant.
Results
Characteristics of the Study
Population
A total of 124,143 patients with pharmaceutically treated hypertension
were included in this analysis, among whom 4,592 (3.7%) patients had
tested positive for Covid-19 and 1,015 (0.8%) got hospitalized due to
Covid-19 between March 16, 2020, and February 23, 2021. The baseline
characteristics of these three different populations are shown in Table
1. There are clear trends from the total population to all Covid-19
patients and to hospitalized Covid-19 patients with respect to a higher
percentage of males, a higher BMI, higher deprivation, less education,
higher prevalence of current smoking, abstinence from alcohol, and low
physical activity, higher prevalence of an eGFR < 60
mL/min/1.73 m² and all other assessed comorbidities and higher use of
lipid-lowering drugs and drugs in general. Hospitalized Covid-19
patients were older, but all Covid-19 patients combined were on average
younger than the total population. The use of ACEI was less frequent
among all Covid-19 patients (41.1%) and hospitalized Covid-19 patients
(38.1%) than among the total population (43.3%), but the prevalence of
ARB use did not differ much between the three groups (approx. 26%).
ACE inhibitors and Covid-19
Outcomes
In the total population, 1,015 (0.8%) got hospitalized due to Covid-19.
Of all Covid-19 patients, 346 (7.5%) and among Covid-19 inpatients, 225
(22.2%) died within 28 days after Covid-19 diagnosis. Table 2 shows the
associations of ARB, CCB, BB and diuretic use with these severe courses
of SARS-CoV-2 infection in comparison with ACEI use. Although there were
some differences in the results of the simple and full model, no pattern
of always stronger or weaker results was observed and the results of the
fully adjusted model are considered to be the main results and are being
referenced in the following text.
As summarized in Table 2, higher risk of Covid-19 hospitalization was
associated with the use of CCBs (adjusted OR, 1.37; 95% CI, 1.17 to
1.60), BBs (adjusted OR, 1.53; 95% CI, 1.29 to 1.80) and diuretics
(adjusted OR, 1.37; 95% CI, 1.16 to 1.63) compared to the use of ACEIs
in the total population with hypertension, whereas ARB use was not
significantly associated with this outcome in comparison to ACEIs
(adjusted OR, 1.10; 95% CI, 0.94 to 1.29).
For the outcome 28-day mortality in all Covid-19 patients and again in
comparison with ACEI use, the use of ARBs (adjusted OR, 1.49; 95% CI,
1.10 to 2.02), BBs (adjusted OR, 1.80; 95% CI, 1.33 to 2.46), diuretics
(adjusted OR, 1.81; 95% CI, 1.32 to 2.46) and CCBs (adjusted OR, 1.35;
95% CI, 0.99 to 1.84) was associated with increased mortality and only
the latter association scarcely missed statistical significance. No
statistically significant association was observed for ARB, CCB and BB
use for the outcome 28-day mortality in hospitalized Covid-
19 patients in comparison with the use of ACEIs but OR point estimates
were similar to those observed for the other two outcomes. For this
outcome, only the association of diuretic use compared to ACEI use was
statistically significant (adjusted OR, 1.54; 95% CI, 1.01 to 2.34).
The use of CCBs, BBs and diuretics, combined as one group compared to
the use of ACEIs, showed a significant association with hospitalization
due to Covid-19 (odds ratio, 1.63; 95% CI, 1.40 to 1.90) and 28-day
mortality among Covid-19 patients (odds ratio, 1.64; 95% CI, 1.23 to
2.19) whereas this association was not statistically significant in
hospitalized patients with Covid-19 (odds ratio, 1.37; 95% CI, 0.93 to
2.01). The unadjusted Kaplan-Meier curves for the latter two survival
analyses are shown in Figure 1 and log-rank tests came the same
conclusion as the logistic regression model: A significant association
with 28-day mortality among all Covid-19 patients (log-rank p=0.0002)
but not among hospitalized Covid-19 patients (log-rank
p=0.15).
ARBs and Covid-19
Outcomes
Table 3 shows the same analyses as Table 2 except that we used ARBs as
the reference group. Again, no pattern of always stronger or weaker
results was observed and the results of the fully adjusted model are
considered to be the main results and are being referenced in the
following text. Hypertensive patients who had been taking BBs and
diuretics had higher risk of Covid-19 hospitalization (adjusted OR,
1.26; 95% CI, 1.06 to 1.49 and adjusted OR, 1.28; 95% CI, 1.08 to
1.52), respectively. The use of CCBs was not significantly associated
with this outcome in comparison with the use of ARBs (adjusted OR, 1.09;
95% CI, 0.93 to 1.29). However, combining CCB, BB and diuretic users
into one group, the adjusted OR was statistically significant (1.50;
95% CI, 1.27 to 1.77). With respect to 28-day all-cause mortality in
all Covid-19 patients and hospitalized Covid-19 patients, no
associations were observed in the logistic regression model, and this
was further confirmed by the Kaplan-Meier curves and log-rank tests
(Figure 2, log rank p=0.36 for all Covid-19 patients and log rank p=0.46
for all Covid-19 inpatients).
Sensitivity Analysis
After removal of patients who used drug combinations with ACEIs or ARBs
from the respective analyses using one of these drug groups as the
reference, the results remained similar to the main analyses and showed
unchanged conclusions in every case (please see Supplemental Tables S1
and S2). The only exception was that the non-significant association of
the use of CCBs compared to ARBs with Covid-19 hospitalization in the
total hypertensive population became statistically significant (adjusted
OR, 1.23; 95% CI, 1.01 to 1.50).
Discussion
In this observational analysis in a large cohort of patients with
hypertension, we observed increased risk of hospitalization due to
Covid-19 among users of non-RAAS blocking anti-hypertensives compared to
ACEIs and ARBs. Furthermore, the risk of 28-day all-cause mortality
among hypertensive Covid-19 patients was increased if non-RAAS blocking
anti-hypertensives were compared to ACEIs. No association was observed
with 28-day all-cause mortality among hospitalized Covid-19 patients.
Our results are consistent with studies suggesting a better prognosis
for Covid-19 patients using RAAS inhibitors. A large cohort of 8.3
million people in the UK showed reduced risk of Covid-19 RT-PCR positive
disease in patients taking ACEIs (OR, 0.72; 95% CI, 0.68 – 0.76) and
ARBs (OR, 0.63; 95% CI, 0.59 – 0.67) [21]. A nation-wide registry
analysis of 1.4 million patients in Sweden also found a decreased risk
of hospitalization/mortality due to Covid-19 (OR, 0.86; 95% CI, 0.81 –
0.91) and lower all-cause mortality in outpatients with Covid-19 (hazard
ratio, 0.89; 95% CI, 0.82 – 0.96) among ACEI/ARB users [22]. These
observations are verified by the first systematic reviews and
meta-analyses specifically conducted for the hypertensive population
[23]. Ren et al. reported a lower disease severity and mortality of
Covid-19 in hypertensive patients with prior usage of ACEIs/ARBs (pooled
risk ratio, 0.81, 95% CI 0.66-0.99, and pooled risk ratio 0.77, 95% CI
0.66-0.91, respectively) [24]. Caldeira et al. observed a reduced
mortality among patients with Covid-19 and hypertension treated with
ACEIs/ARBs (pooled risk ratio 0.76, 95%CI 0.59–0.98) [25]. Our
findings are also in line with the French COVID cohort, a multicenter
prospective cohort, which observed no significant association between
the chronic use of RAAS blockers and mortality in hospitalized Covid-19
patients with hypertension [26].
Unlike previous studies, we compared the association of ACEIs and ARBs
with Covid-19 outcomes directly to other major antihypertensive drug
classes separately and all together, whereas most other studies have
only done the latter. Moreover, most of the previous studies have
considered ACEIs and ARBs as one class of antihypertensives, RAAS
agents, while comparing their association with Covid-19 outcomes to
other antihypertensive medications. We found a different behavior
between ACEIs and ARBs with ACEI use being associated with lower risks
of Covid-19 hospitalization and 28-day all-cause mortality. This is in
line with a meta-analysis conducted by Pirola and Sookoian, which
observed a reduced risk of death and critical disease among hypertensive
patients with Covid-19 only for ACEIs and not for ARBs or a combined
group of ACEIs/ARBs [27].
Different results for ACEIs and ARBs in adverse Covid-19 outcomes can be
explained by their different mode and mechanism of action in the RAAS
[28]. It is noteworthy that ACEIs bind to ACE, an enzyme homologous
to ACE2, yet with distinctly different binding sites. In other words,
ACE2 activity is not directly affected by ACEIs, and they primarily
exert their protective effect via decreasing Ang II levels by preventing
the conversion of Ang I to Ang II, whereas ARBs block angiotensin II
type 1 receptor (AT1 receptor), which results in an increase in Ang II
levels, the substrate for ACE2 and activates the protective axis in
RAAS. Furthermore, animal studies have shown increased expression of
ACE2 mRNA and protein in various tissues more consistently with ARBs
compared to ACEIs [29]. These differences might clarify the
inconsistent results between ACEIs and ARBs to some extent.
One strength of this study is that we used data from the UK Biobank with
extensive data collected on lifestyle and sociodemographic
characteristics of the participants and linked electronic health
records. On the one hand, this enabled us to adjust for many important
confounders not usually available in other studies using claims data. On
the other hand, a limitation is that life-style-factors, physical health
assessment measurements and biomarkers were assessed 10-14 years prior
to the Covid-19 pandemic and could have changed in that time. However,
the most important co-morbidity information could be updated until the
date of the onset of the pandemic by linked primary care records.
However, we cannot exclude that the combination of self-reported disease
from the cohort’s baseline and the primary care records to identify
co-morbidities has led to some misclassification and underreporting of
diagnoses in. In addition, despite extensive covariate adjustments,
there may be additional unmeasured confounders that could have affected
our results. Another limitation is that drug utilization was based on
prescribed medications and adherence to the drug treatment could not be
assessed.
Another strength of this study is that we included Covid-19 data in a
large time window, so that we covered the entire first and second
SARS-CoV-2 wave in UK, while most studies were limited to a shorter
period (usually the first wave of the pandemic in the respective
country). During the early stages of the pandemic, only symptomatic
patients were tested due to the limited testing capacity, which resulted
in patient populations with overrepresentation of severe Covid-19
disease cases.
By setting the cut-off date for extracting Covid-19 infection data to
February 23, 2021, we think that vaccination against Covid-19 did not
substantially influence our results because the vaccination campaign in
the UK started slowly in December 2020 and by the time of our cut-off
date, only 1.2% of the English population were fully vaccinated
[18]. Finally, our study population mainly consisted of the older
(50% of the participants were between 66 and 76 years old
(inter-quartile-range)), Caucasian, hypertensive population and hence
the results might not apply in other populations.
In summary, our findings suggest a better prognosis of Covid-19 patients
in pharmaceutically treated hypertension if RAAS blockers are being used
and the potential protective effects were stronger for ACEIs than ARBs.
However, results from randomized controlled trials (RCTs) are needed to
confirm this finding from an observational study because residual
confounding cannot be excluded. A RCT with 659 hospitalized patients
with mild to moderate Covid-19 and prior use of ACEIs or ARBs observed
no effect of continuation versus discontinuation of these medications on
the mean number of days alive and out of the hospital through 30 days
[30], which is in agreement with our results because it seems that
the potential protective effects are stronger in non-hospitalized than
hospitalized Covid-19 patients. As soon as Covid-19 patients develop a
severe course that requires inpatient care, the use of RAAS blockers may
be too late and ineffective. A phase II RCT, which tested the efficacy
of losartan on symptomatic outpatients with Covid-19 versus placebo
showed no significant difference in hospitalization rate between the two
arms [31]. However, the non-significant result should be interpreted
with caution due to low event rate (losartan arm: 3 events versus
placebo arm: 1 event) and short duration of follow-up of this phase II
trial. The results of more RCTs should help to elucidate the causality
of the observed protective associations of RAAS blockers on adverse
Covid-19 outcomes. If our results would be confirmed in RCTs, this could
have high clinical relevance for treating hypertension during the
SARS-CoV-2 pandemic.
Acknowledgements
This research has been conducted using the UK Biobank Resource under
Application Number “62848”.
Conflict of Interests
The authors have no conflict of interest to disclose.
Sources of Funding
No funding was obtained or used for the presented research project. The
UK Biobank was established by the Wellcome Trust medical charity,
Medical Research Council, Department of Health, Scottish Government and
the Northwest Regional Development Agency. It has also had funding from
the Welsh Government, British Heart Foundation, Cancer Research UK and
Diabetes UK. UK Biobank is supported by the National Health Service
(NHS).