Outcome in Tracheostomized Patients With Severe Traumatic Brain Injury Following Implementation of a Specialized Multidisciplinary Tracheostomy Team
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of a specialized multidisciplinary tracheostomy team on outcome of patients with severe traumatic brain injury (sTBI). DESIGN: Retrospective study with historical controls. PARTICIPANTS: Twenty-seven patients with sTBI tracheostomized before implementation of the tracheostomy team approach and 34 patients followed by the team. SETTING: A regional level 1 tertiary care trauma center, McGill University Health Centre-Montreal General Hospital. MAIN OUTCOME MEASURES: Time to decannulation, length of stay (LOS), Passy-Muir speaking valve use, and extended Glasgow Outcome Scale (GOS-E) scores given at acute care discharge. RESULTS: The groups were similar for injury severity, age, and premorbid health conditions. Postteam patients had a significantly shorter LOS (P = .025) and more of them used Passy-Muir speaking valves (P = .004). Furthermore, there was a trend toward decreased time to decannulation in the postteam group. GOS-E scores did not differ significantly between groups (P > .05). CONCLUSION: Implementation of the tracheostomy team appears to have had positive clinical benefits for this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".