Unplanned Extubations in Pediatric Critical Care: A Case–Control Study
Bibliographic record
Abstract
Abstract The aim of this study was to quantify associations between the risk of unplanned extubation and patient-, environment-, and care-related factors in pediatric critical care and to compare outcomes between children who did and did not experience an unplanned extubation. This is a retrospective case–control analysis including patients <18 years who experienced an unplanned extubation during intensive care unit (ICU) admission (2004–2014). Cases were matched by age, duration of mechanical ventilation, and date to control patients (4:1) who were intubated but did not experience an unplanned extubation. Conditional logistic regression was used to evaluate associations between unplanned extubations and the abstracted characteristics. We identified 1,601 eligible controls matched to 458 case patients. When adjusted for confounders, eight variables were associated with unplanned extubation: three patient-related factors (previous ICU admission, previous intubation, and the volume of secretions); one environment-related factor (patient room setup); and four care-related factors (intubation route, and the use of sedation, muscle relaxation, and restraints). Patients who had an unplanned extubation had longer length of stay, but lower rate of mortality. This is the largest case–control study identifying variables associated with unplanned extubation in pediatric critical care. Several are potentially modifiable and may provide opportunities to improve quality of care in controlled ICU environments.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".