Pneumonia Prevention to Decrease Mortality in Intensive Care Unit: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: To determine the strategies of prevention of hospital-acquired pneumonia that reduce mortality in intensive care unit (ICU). METHODS: We followed PRISMA (Preferred Reported Items for Systemic Reviews and Meta-Analyses) guidelines. We searched MEDLINE and the Cochrane Controlled Trials Register (through 10 June 2014) as well as reference lists of articles. We included all randomized controlled trials conducted in critically ill adult patients hospitalized in ICUs and evaluating digestive prophylactic methods (selective digestive decontamination [SDD], acidification of gastric content, early enteral feeding, prevention of microinhalation); circuit prophylactic methods (closed suctioning systems, early tracheotomy, aerosolized antibiotics, humidification, lung secretion drainage, silver-coated endotracheal tubes) or oropharyngeal prophylactic methods (selective oropharyngeal decontamination, patient position, sinusitis prophylaxis, subglottic secretion drainage, tracheal cuff monitoring). One reviewer extracted data that were checked by 3 others. The primary outcome was the mortality rate in the ICU. RESULTS: We identified 157 randomized trials to pool in a meta-analysis. The primary outcome was available in 145 studies (n = 37 156). The risk ratio (RR) for death was 0.95 (95% confidence interval [CI], .92-.99; P = .02) in the intervention groups. In subgroup analysis, only SDD significantly decreased mortality compared with control (n = 10 227; RR, 0.84 [95% CI, .76-.92; P < .001]). The RR for in-ICU death was 0.78 (95% CI, .69-.89; P < .001; I(2) = 33%) in trials investigating SDD with systemic antimicrobial therapy and 1.00 (.84-1.21; P = .96; I(2) = 0%) without systemic antimicrobial therapy. CONCLUSIONS: Selective digestive decontamination with systemic antimicrobial therapy reduced mortality and should be considered in critically ill patients at high risk for death.
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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 | 0.020 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.051 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".