Mortality and patient disposition after ICU tracheostomy for secretion management vs. prolonged ventilation: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: There is little research on long-term, patient-centered outcomes in critically ill patients undergoing tracheostomy for secretion management or prolonged ventilation. The goal of this study was to determine and compare hospital and long-term mortality, and incidence of new institutionalization amongst patients who underwent an ICU tracheostomy for these two aforementioned indications. METHODS: This was a single center historic cohort study of all ICU patients who received a tracheostomy for secretion management or prolonged ventilation from 2011 to 2022. We compared hospital and long-term mortality and incidence of new institutionalization between these two groups. RESULTS: A cohort of 247 patients (133 secretion management, 114 prolonged ventilation) was established. Overall hospital mortality was 86/247 (35%), mortality at 1 year was 106/207 (51%), and at 3 years was 117/167 (70%), with no significant difference between the two indications. Patients with prolonged ventilation indication had a significantly higher ICU mortality [34/114 (30%) vs. 13/133 (10%), P < 0.001]. Amongst hospital survivors, 49/137 (36%) were unable to return home, with significantly more patients tracheostomized for secretion management requiring new institutionalization [37/78 (47%) vs. 12/59 (20%), P = 0.002]. CONCLUSIONS: Tracheostomy indication may be an important determinant of short- and long-term patient-centered outcomes. Patients receiving a tracheostomy for secretion management were twice as likely to be discharged to a new institution compared to prolonged ventilation patients. Patient-centered outcomes should be included in future studies and if confirmed, these outcomes should be incorporated into discussions about tracheostomy decision making.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 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".