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Record W3160853723 · doi:10.1177/20420986211011345

Renin–angiotensin–aldosterone system blockers and region-specific variations in COVID-19 outcomes: findings from a systematic review and meta-analysis

2021· review· en· W3160853723 on OpenAlexaboutno aff
Upinder Kaur, Sankha Shubhra Chakrabarti, Tejas Patel

Bibliographic record

VenueTherapeutic Advances in Drug Safety · 2021
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOdds ratioMeta-analysisInternal medicineIntensive care unitConfidence intervalIntensive care medicine

Abstract

fetched live from OpenAlex

Background and aims: Coronavirus disease 2019 (COVID-19) has been observed to cause a high mortality in people with cardiometabolic diseases. Renin–angiotensin–aldosterone system (RAAS) blockers enhance the expression of ACE2, the binding receptor of SARS-CoV-2, and can enhance viral infectivity. We aim to provide a pooled estimate of the effect of RAAS blockers on COVID-19 outcomes. Methods: A literature search was performed using MEDLINE/PubMed, Google Scholar and preprint servers. All clinical studies analyzing the effect of RAAS blockers on clinical outcomes in COVID-19 patients were included in this study. Newcastle–Ottawa scale was used for quality assessment of studies. MOOSE checklist was followed. Mortality and severity outcomes were recorded as pooled odds ratio (OR) with 95% Confidence Intervals (CIs) and level of heterogeneity ( I 2 ). Odds of mortality was the primary outcome. Odds of severity, hospitalization, intensive care unit (ICU) admission, mechanical ventilation (MV), steroid use and acute kidney injury were the secondary outcomes. Severity outcomes were chosen depending upon the definition used by respective authors. Country-specific variations and effects of individual class of RAAS blockers were also explored. Results: In total 47 published studies were included in the final analysis, with a total of 26,432 patients from 31 studies in mortality analysis and 20,127 patients from 23 studies in severity analysis. No increased risk of mortality [Pooled OR 0.91 (0.65–1.26), I 2 = 89%] or severity [Pooled OR 1.08 (0.79–1.46), I 2 = 88%] was seen with RAAS blockers. The drug class was protective in hypertension [pooled OR 0.63 (0.46–0.86), I 2 = 58%]. Severity of COVID-19 outcomes was high for Europeans [Pooled OR 2.08 (1.52–2.85), I 2 = 77%] and US patients [Pooled OR 1.87 (1.62–2.17)]. Nearly 4 times higher risk of hospitalization and 2 times higher risk of ICU admission and MV were observed in US patients. Class-wise, angiotensin receptor blocker use was associated with 1.6 times higher odds of severity, mainly in Europeans. Conclusion: RAAS blockers are not associated with increased mortality in COVID-19 patients and should be continued in hypertensives. US and European patients are at higher risk of severe outcomes. Pharmacogenetic differences may explain the ethnicity-related variations. Plain language summary Effect of RAAS-blocking medicines on COVID-19 Background and aims: Higher deaths have been observed in COVID-19 patients who have other long-term diseases such as heart disease, diabetes, and high blood pressure. Many of these patients are prescribed a class of medicines called RAAS blockers (ramipril, telmisartan, etc). We studied whether the use of these medicines worsens the course of COVID-19 disease in these patients or causes excess deaths. Methods: We conducted a pooled analysis of 47 observational studies on the use of RAAS blocker drugs in COVID-19 patients. Results: We found that RAAS blockers do not cause excess deaths in patients with COVID-19. On the contrary, they have benefits if prescribed to those with high blood pressure. We also found that whereas European and US patients of COVID-19 taking these medicines had higher disease severity, this was not the case for Chinese patients. Conclusion: Theremay be some genetic and other factors responsible for differences by ethnicity.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0180.002
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.145
GPT teacher head0.461
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2021
Admission routes1
Has abstractyes

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