Laryngotracheal Reconstruction in the Pediatric Burn Patient: Surgical Techniques and Decision Making
Bibliographic record
Abstract
The management of laryngotracheal stenosis (LTS) in the pediatric burn patient is complex and requires a multidisciplinary approach. The mainstay of treatment for LTS is laryngotracheal reconstruction (LTR), however, limited reports of burn-specific LTR techniques exist. Here, we provide insight into the initial airway evaluation, surgical decision making, anesthetic challenges, and incision modifications based on our experience in treating patients with this pathology. The initial airway evaluation can be complicated by microstomia, trismus, and neck contractures-the authors recommend treatment of these complications prior to initial airway evaluation to optimize safety. The surgical decision making regarding pursuing single-stage LTR, double-stage LTR, and 1.5-stage LTR can be challenging-the authors recommend 1.5-stage LTR when possible due to the extra safety of rescue tracheostomy and the decreased risk of granuloma, which is especially important in pro-inflammatory burn physiology. Anesthetic challenges include obtaining intravenous access, securing the airway, and intravenous induction-the authors recommend peripherally inserted central catheter when appropriate, utilizing information from the initial airway evaluation to secure the airway, and avoidance of succinylcholine upon induction. Neck and chest incisions are often within the TBSA covered by the burn injury-the authors recommend modifying typical incisions to cover unaffected skin whenever possible in order to limit infection and prevent wound healing complications. Pediatric LTR in the burn patient is challenging, but can be safe when the surgeon is thoughtful in their 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".