Incidence and risk factors of ventilator-associated pneumonia in the intensive care unit: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Ventilator-associated pneumonia (VAP) is a serious complication occurring in critically ill patients receiving mechanical ventilation in the intensive care unit (ICU). This study attempted to analyze VAP incidence in the ICU using a meta-analysis, investigate risk factors for VAP occurrence, and examine influence of VAP on outcomes. Methods: A search was carried out in the Web of Science, PubMed, Embase, and The Cochrane Library databases to identify studies on incidence and risk factors of VAP in ICU patients. Study quality was tested by the Newcastle-Ottawa Scale. Data related to risk factors, incidence, and outcomes were utilized for meta-analysis. Meta-analysis was conducted using Stata 18 and Review Manager 5.4. Results: Seventeen articles were included, comprising 6,222 patients, and incidence of VAP was 30% [95% confidence interval (CI): 24-37%]. Risk factor analysis showed that males [odds ratio (OR): 1.50; 95% CI: 1.29-1.75; P<0.001], smoking (OR: 1.30; 95% CI: 1.08-1.57; P=0.007) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score [weighted mean difference (WMD): 1.30; 95% CI: 0.31-2.30; P=0.01] were risk factors for VAP. Antibiotic prophylaxis (OR: 0.79; 95% CI: 0.63-0.99; P=0.04) was a protect factor for VAP. Compared with non-VAP patients, VAP patients had a prolonged duration of mechanical ventilation (WMD: 6.96; 95% CI: 5.42-8.50; P<0.001), ICU length of stay (WMD: 7.91; 95% CI: 5.43-10.39; P<0.001) and total length of hospital stay (WMD: 8.09; 95% CI: 3.70-12.48; P=0.0003). There was no significant difference in mortality rate between VAP and non-VAP patients (OR: 1.13; 95% CI: 0.79-1.63; P=0.50). Conclusions: VAP incidence in the ICU was around 30%. Male, smoking, and high APACHE II score were risk factors for VAP, while antibiotic prophylaxis was a protective factor for VAP. VAP could lead to prolonged mechanical ventilation, ICU stay, and hospital stay, but it did not influence mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".