The Effect of Prior Use of Statins on the Severity of COVID-19 Disease
Bibliographic record
Abstract
It has been suggested that the use of statin pills beforehand could potentially influence the outcomes when individuals are hospitalized with COVID-19. In this study, we investigated how the prior use of statin medication could influence the COVID-19 severity parameters. In this retrospective cohort study, we categorized COVID-19 patients into 2 groups: statin users and non-users. Then, various data including age, gender, the patient's need for ventilation support, the lowest oxygen blood saturation level, the length of hospitalization, receiving remdesivir treatment, and their COVID-19 vaccination status were collected. Out of 168 patients, 62 had taken statin medication before being admitted. Using statins decreased the patient's need for ventilation support, length of hospitalization, ventilation duration, and oxygen saturation level (P < .001). Interaction effect analysis showed that receiving remdesivir statically affected the length of hospitalization, ventilation duration, and oxygen saturation level but did not significantly affect the association between statins and needing to ventilator. The use of statin pills before COVID-19 admission reduced the requirement for ventilator support.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".