Multidisciplinary Quality Improvement Initiative to Reduce Ventilator-Associated Tracheobronchitis in the PICU*
Bibliographic record
Abstract
OBJECTIVE: To test the hypothesis that successful implementation of a care bundle designed to prevent nosocomial airway infection will be associated with decreased incidence of ventilator-associated tracheobronchitis. DESIGN: Prospective pre- and post interventional. SETTING: PICU at an academic medical center PATIENTS: : All patients admitted to the PICU who received invasive mechanical ventilation for greater than or equal to 48 hours between March 1, 2009, and December 31, 2011. INTERVENTION: Multidisciplinary, unit wide implementation of an evidence-based care bundle to prevent ventilator-associated airway infection. MEASUREMENTS AND MAIN RESULTS: There were 725 patients included in the analysis (338 patients preintervention and 387 patients postintervention). Baseline ventilator-associated tracheobronchitis rate in the preintervention period was 3.9 cases per 1,000 ventilator days compared with 1.8 cases per 1,000 ventilator days postintervention (p = 0.04, Fisher exact test). Compared with patients without ventilator-associated tracheobronchitis or ventilator-associated pneumonia, patients with ventilator-associated tracheobronchitis had fewer ventilator-free days in 28 days (4.9 vs 22; p < 0.0001, Mann-Whitney U test) and fewer ICU-free days in 28 days (0.5 vs 19; p < 0.0001, Mann-Whitney U test). These relationships remained significant after adjusting for covariates by multivariable linear regression. CONCLUSIONS: Successful implementation of a care bundle to prevent ventilator-associated infection was associated with decreased incidence of ventilator-associated tracheobronchitis. Development of ventilator-associated tracheobronchitis was independently associated with adverse outcomes in our cohort of pediatric ICU patients.
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 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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".