De-adoption of oral chlorhexidine for mechanically ventilated patients: get thee to a conclusion
Bibliographic record
Abstract
Purpose: Oral chlorhexidine is used widely for mechanically ventilated patients to prevent pneumonia, but recent studies show an association with excess mortality.We examined whether de-adoption of chlorhexidine and parallel implementation of a standardized oral care bundle reduces intensive care unit (ICU) mortality in mechanically ventilated patients.Methods: A stepped wedge cluster-randomized controlled trial with concurrent process evaluation in 6 ICUs in Toronto, Canada.Clusters were randomized to de-adopt chlorhexidine and implement a standardized oral care bundle at 2-month intervals.The primary outcome was ICU mortality.Secondary outcomes were time to infection-related ventilator-associated complications (IVACs), oral procedural pain and oral health dysfunction.An exploratory post hoc analysis examined time to extubation in survivors.Results: A total of 3260 patients were enrolled; 1560 control, 1700 intervention.ICU mortality for the intervention and control periods were 399 (23.5%) and 330 (21.2%), respectively (adjusted odds ratio [aOR], 1.13; 95% confidence interval [CI] 0.82 to 1.54; P = 0.46).Time to IVACs (adjusted hazard ratio [aHR], 1.06; 95% CI 0.44 to 2.57; P = 0.90), time to extubation (aHR 1.03; 95% CI 0.85 to 1.23; P = 0.79) (survivors) and oral procedural pain (aOR, 0.62; 95% CI 0.34 to 1.10; P = 0.10) were similar between control and intervention periods.However, oral health dysfunction scores (-0.96; 95% CI -1.75 to -0.17; P = 0.02) improved in the intervention period.Conclusion: Among mechanically ventilated ICU patients, no benefit was observed for de-adoption of chlorhexidine and implementation of an oral care bundle on ICU mortality, IVACs, oral procedural pain, or time to extubation.The intervention may improve oral health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".