Comparing Intraoperative and In‐Office Steroid Injections for Management of Subglottic Stenosis
Bibliographic record
Abstract
INTRODUCTION: Intralesional corticosteroid injection for management of subglottic stenosis (SGS) is thought to improve patients' surgery free interval (SFI). The objective of this study was to determine the difference in SFI between idiopathic SGS (iSGS) patients treated with endoscopic dilation alone, dilation with a single intraoperative intralesional corticosteroid injection, or dilation with intraoperative steroid injection followed by serial in-office serial intralesional steroid injection (SILSI) procedures. METHODS: Retrospective review of patients with iSGS from 1/1/2012 to 12/1/2023. The SFI was calculated as the time between surgical interventions and independent samples median test was used to compare the difference in SFIs between treatment groups. RESULTS: This study identified 305 procedures, involving 104 patients. Fifty-five procedures involved endoscopic dilation alone (median SFI = 658, IQR: 595 days), 102 involved one injection of steroids intraoperatively (median SFI = 395, IQR: 296 days), 27 involved endoscopic dilation (ED) followed by a single postoperative ILSI (median SFI = 533, IQR: 351), and 15 involved postoperative SILSI (median SFI = 585, IQR: 338 days). Comparing SFI between groups found mean SFI was significantly longer among patients managed with only ED compared with a single intraoperative steroid injection (p = 0.001). Patients who were initially managed with ED and an intraoperative steroid injection has a statistically significant decrease in SFI (p = 0.032) when transitioned to management with ED and intraoperative steroid injection followed by a single ILSI postoperatively. CONCLUSION: Patients who received a single intraoperative steroid injection experienced shorter SFI when compared with those managed with dilation alone. SILSI did not result in a significant increase of SFI within this population. LEVEL OF EVIDENCE: 3 Laryngoscope, 135:1438-1443, 2025.
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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 | 0.000 |
| 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".