The Association between Statins Intake and Risk of Post Stroke Pneumonia:A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Aim: This research aimed to examine the relationship between the intake of statins and the risk of post-stroke pneumonia in a systematic review and meta-analysis study. Methods: An extensive search of published articles on March 21st, 2023, was done in several databases, like Web of Science (ISI), PubMed, Cochrane Library, Embase, Scopus, and Google Scholar. The Newcastle Ottawa Scale (NOS) checklist was employed to evaluate the quality of observational studies. Statistical tests (Chi-square test and I2) and graphical techniques (Forest plot) were used to determine whether heterogeneity existed in the meta-analysis studies. Funnel plots and Begg and Egger's tests were used to assess the publication bias. Results: Seven studies (5 cohort and 2 case-control studies) were retrieved to examine the association between statins and post-stroke pneumonia. The sample size of the studies compiled in the meta- analysis was obtained to be 68,966 participants. Meta-analysis demonstrated that the overall odds of post-stroke pneumonia in the statin group was equal to 0.87 (95% CI: 0.67 – 1.13; p-value 0.458). Subgroup analysis indicated that the odds of post-stroke pneumonia in the statin group was equal to 0.93 (95% CI: 0.73-1.18; p-value = 0.558) in the cohort studies, and equal to 0.92 (95% CI: 0.37-2.26; p-value = 0.857) in the case-control studies. The examination of the association between the intake of statins and post-stroke pneumonia showed no evidence of publication bias (Begg's test, p-value = 0.368; Eggers test, p-value = 0.282). Conclusion: In this study, no relationship has been observed between receiving statins and the risk of post-stroke pneumonia.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.048 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".