Association between smoking and risk of death in patientswith sepsis: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Although some research papers have suggested that smoking may increase mortality in patients with sepsis, no evidence has been produced in this regard. This systematic research evaluated the risk of death in patients with sepsis who were smokers to facilitate better clinical decision making. METHODS: This is a systematic review registered in PROPERO (CRD42022296654). Searches were conducted to identify suitable studies from the databases of PubMed, Embase, Web of Science and the Cochrane Controlled Register of Trials from January 1980 to June 2021. Two independent reviewers screened the articles using keywords and extracted the data. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of evidence. The primary endpoints included the mortality of patients with sepsis. RESULTS: Five studies involving 2694 participants were included in our study. Among the five included articles, three studies had an NOS score of 6, while the other two had an NOS score of 7. The results showed that a significantly higher risk of death was observed in smokers with sepsis compared with non-smokers with sepsis (hazard ratio, HR=1.62; 95% CI: 1.11-2.37, p=0.01). Among the patients followed for more than 2 months, the mortality rate of smokers was significantly higher (2.33 times) than that of non-smokers (HR=2.33; 95% CI: 1.83-2.96, p<0.01). The difference in mortality did not reach statistical significance when the follow-up period was shorter than 2 months (HR=1.22; 95% CI: 0.96-1.56, p=0.10). CONCLUSIONS: Smoking increased mortality in patients with sepsis when the follow-up period was longer than 2 months.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".