Risk of SARS-CoV-2 infection and COVID-19 prognosis with the use of renin–angiotensin–aldosterone system (RAAS) inhibitors: a systematic review
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting-enzyme-2, being the receptor for SARS-CoV-2, is increased in the use of RAAS inhibitors. Therefore, concerns have been raised over risks of SARS-CoV-2 infection and poor prognosis of COVID-19 in persons with prior exposure to these drugs. This study aimed to systematically review available evidence for associations between exposure to RAAS inhibitors with susceptibility to SARS-CoV-2 infection and clinical outcomes in infected persons. It hopes to address the question on the effects of RAAS inhibitors on the risk of COVID-19 and its prognosis. MAIN BODY: Search was conducted in the databases of PubMed, Scopus, Cochrane, Embase and MedRxiv.org from December 2019 to May 31, 2020, using relevant keywords. Additional articles were identified through hand-searching of reference lists. Studies that reported associations between positive tests to COVID-19 and use of RAAS inhibitors, and treatment outcomes of COVID-19 patients who had exposure to RAAS inhibitors were considered eligible. The Newcastle-Ottawa scale was used to assess risk of bias in individual studies. The review was conducted in line with Preferred Regulatory Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 2009. From the 952 studies screened and 2 studies from reference hand-searching, 18 were reviewed. Four studies evaluated the risks for SARS-CoV-2 infection among RAAS inhibitors users, and 16 (including 2 of the 4 studies) evaluated the clinical outcomes associated with previous exposure to RAAS inhibitors. CONCLUSION: Evidence does not suggest higher risks for SARS-CoV-2 infection or poor disease prognosis in the use of RAAS inhibitors. This suggests the continued use of RAAS inhibitors by patients with existing needs, which supports the position statements of American Heart Association and European societies for Cardiology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43094-021-00224-4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".