The effect of tracheostomy timing during critical illness on long-term survival*
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Tracheostomy is common in intensive care unit patients, but the appropriate timing is controversial. OBJECTIVE: To determine whether earlier tracheostomy is associated with greater long-term survival. DESIGN: Retrospective cohort analysis. SETTING: Acute care hospitals in Ontario, Canada (n = 114). PATIENTS: All mechanically ventilated intensive care unit patients who received tracheostomy between April 1, 1992 and March 31, 2004, excluding extreme cases (< 2 or > or = 28 days) and children (< 18 yrs). MEASUREMENTS: For crude analyses, tracheostomy timing was classified as early (< or = 10 days) vs. late (> 10 days) with mortality measured at multiple follow-up intervals. Proportional hazards analyses considered tracheostomy as a time-dependent variable to adjust for measurable confounders and possible survivor treatment bias. We used stratification, propensity score, and instrumental variable analyses to adjust for patient differences. RESULTS: A total of 10,927 patients received tracheostomy during the study, of which one-third (n = 3758) received early and two-thirds late (n = 7169). Patients receiving early tracheostomy had lower unadjusted 90-day (34.8% vs. 36.9%; p = 0.032), 1 yr (46.5% vs. 49.8%; p = 0.001), and study mortality (63.9% vs. 67.2%; p < 0.001) than patients receiving late tracheostomy. Multivariable analyses treating tracheostomy as a time-dependent variable showed that each additional delay of 1 day was associated with increased mortality (hazard ratio 1.008, 95% confidence interval 1.004-1.012), equivalent to an increase in 90-day mortality from 36.2% to 37.6% per week of delay (relative risk increase 3.9%; number needed to treat, 71 patients to save one life per week delay). LIMITATIONS: This analysis provides guidance regarding timing but not patient selection for tracheostomy. CONCLUSIONS: Physicians performing early tracheostomy should not anticipate a large potential survival benefit. Future research should concentrate on identifying which patients will receive the most benefit.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it