Effect of Oral Care with Povidone-Iodine in the Prevention of Ventilator-Associated Pneumonia; a Systematic Review and Meta-Analysis.
Bibliographic record
Abstract
Introduction: Ventilator-associated pneumonia (VAP) is one of the most common nosocomial infections affecting one-third of patients with mechanical ventilation. This study aimed to synthesize available evidence regarding the effect of treatment with povidone-iodine (PI) among adult patients admitted to intensive care units (ICUs) for the prevention of VAP. Methods: An extensive search was conducted in online databases, including PubMed, Web of Science and Scopus, from the earliest records until January 1, 2023. STATA software v14 was used for statistical analysis. Publication bias was assessed via funnel plot, Begg's and Egger's tests. A P-value less than 0.1 was considered statistically significant for publication bias value. Results: Four studies were included in the meta-analysis. Three studies showed rhat PI decreased VAP compared to the placebo group, but it was not statistically significant (RR: 0.61, 95%CI: 0.25 to 1.47, Z=1.10, P=0.27, I2:71.5%). One study compared the effect of PI with chlorhexidine on the rate of VAP, the difference between which was not statistically significant (RR: 1.50, 95%CI: 0.46 to 4.87, Z=0.67, P=0.50, I2:0). Two studies demonstrated that the use of PI intervention compared to placebo decreased the average length of stay in ICU; however, it was not statistically significant (WMD: -0.35, 95%CI:-3.90 to 3.20, Z=0.19, P=0.85, I2:0). Also, three studies showed that using PI had almost no effect on mortality rate compared to placebo (RR: 1.05, 95%CI: 0.66 to 1.53, Z=0.8, P=0.27, I2:29.0%). Conclusion: More rigorously designed randomized clinical trials and further evidence are required to make a better decision/comparison about using PI as a suitable choice for preventing VAP among adult patients admitted to the ICU.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.039 |
| Bibliometrics | 0.009 | 0.008 |
| 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) | 0.003 | 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".