Comparative Outcomes of Flap Maturation Versus Conventional Pediatric Tracheotomy Techniques
Bibliographic record
Abstract
OBJECTIVE: To compare postoperative outcomes of flap maturation (FMT) and conventional tracheotomy techniques in pediatric patients. METHODS: A retrospective cohort study was performed using data from the American College of Surgeons National Surgical Quality Improvement Program Pediatric database (2020-2021). Pediatric patients ≤ 18 years who underwent FMT (CPT 31610) or conventional tracheotomy (CPT 31600, 31,601) were included. Primary outcomes were 30-day reoperation, surgical site infection, pneumonia, seizures, mortality, unplanned reintubation, readmission, and length of stay. RESULTS: Among 2353 patients (mean age 2.9 years, 95% CI 2.7-3.1), 381 (16.2%) underwent FMT and 1972 (83.8%) underwent conventional tracheotomy. An FMT was associated with lower odds of 30-day reoperation (0.5% vs. 3.3%, p = 0.003; adjusted OR = 0.17, 95% CI 0.1-0.6, p = 0.005). Rates of surgical site infection, pneumonia, and seizures did not differ significantly between groups after adjustment. No differences were observed in mortality, reintubation, readmission, or length of stay. CONCLUSION: FMT is independently associated with lower reoperation rates without increased postoperative complications. FMT may be a favorable tracheotomy option for select patients and warrants consideration during surgical decision-making to optimize outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".