Association between Statin Use and Poor Outcomes in COVID-19 Patientswith Diabetes Mellitus: A Systematic Review
Bibliographic record
Abstract
BACKGROUND AND AIMS: Diabetes mellitus, cardiovascular diseases, obesity, and dyslipidaemia are considered risk factors for more severe forms of COVID-19 infection. Statins have been widely used in such patients to prevent the occurrence of cardiovascular events and the associated mortality. However, statin use has been suggested to promote a more severe form of infection. This review aims to investigate the association between statin use and poor outcomes in COVID-19 patients with diabetes. METHODS: Literature search was performed in PubMed, CENTRAL, Scopus, and pre-print databases (MedRxiv and BioRxiv), and studies published up to March 6th, 2021 have been reviewed. Selected studies were then assessed for risk of bias with the Newcastle Ottawa Scale. RESULT: Four studies were included in the final analysis; all were retrospective studies. Two studies reported a decreased risk of mortality with statin use, while one study reported opposite findings. The other one did not find a significant association between statin use and poor COVID-19 outcomes. CONCLUSION: Available data suggest that statins may be safely administered to diabetic COVID-19 patients as the majority of evidence signifies statins to confer benefits and improve clinical outcomes in COVID-19 patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".