Early versus late tracheostomy in cardiovascular intensive care patients
Bibliographic record
Abstract
BACKGROUND: Benefits of tracheostomy have been well established. Most of the literature, refers these benefits to general intensive care population, excluding cardiac surgery or including only small number of these patients. On the other hand, there is no clear definition describing the proper time to perform the procedure and defining what are potential benefits of early compared to late tracheostomy. This retrospective cohort aims to assess the potential benefits of early tracheostomy on post-operative outcomes, length of stay and post-tracheostomy complications within cardiac surgical population. METHODS: After obtaining REB approval, we conducted a retrospective chart review in a single, tertiary care institution, identifying patients who underwent tracheostomy after cardiac surgery from 1999 to 2006. Time-to-tracheostomy was defined as "early" if < 7 days or "late" if ≥ 7 days post-cardiac surgery). RESULTS: 14,101 patients underwent cardiac surgery over the 7-year study period; from those, 147 (1.36%) received tracheostomy. 32 (22%) patients underwent early tracheostomy and 115 (78%) late tracheostomy. Incidence of atrial fibrillation (31.2% vs 61.7%; P = 0.003), kidney dysfunction (6.3% vs 27.2%; P=0.015) and kidney failure 18.8% vs 43.5%; P = 0.013) were lower in the early tracheostomy group. There were no differences on post tracheostomy infection or presence of acute respiratory distress syndrome. Both the ICU and hospital length of stay were significantly shorter in early tracheostomy group, 21.5 (ET) vs 36.9 (LT) days and 37.5 (ET) vs 57.6 (LT) days respectively. There were no differences in mortality between groups. CONCLUSIONS: There are significant benefits in reduction of postoperative morbidities with overall shorter ICU and hospital stay. These benefits may promote faster patient rehabilitation with reduced healthcare costs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".