Endoscopic cauterisation and injection of Voicegel for treatment of congenital pyriform fossa sinus tracts
Bibliographic record
Abstract
OBJECTIVE: To demonstrate our experience in treating pyriform fossa sinus tracts (PFST) using a novel technique of endoscopic cauterisation of the pyriform fossa sinus opening combined with injection of sodium carboxymethylcellulose gel (VoiceGel) lateral to the tract to encourage tight closure. METHODS: Over a 48-month period, we used this technique on 11 patients who were diagnosed with PFST at BC Children's Hospital, a tertiary paediatric centre in Vancouver, BC, Canada. RESULTS: The 11 patients included 8 males and 3 females, and mean age at presentation was 69 months (range 22-108 months). Mean time from beginning of symptoms till diagnosis was 15 months (range 12-22 months). Ten PFST were on the left side of the neck and one on the right. Nine patients presented with recurrent neck infections and two had suppurative thyroiditis. All patients had endoscopic cauterisation of their PFST opening combined with injection of carboxymethylcellulose lateral to the sinus tract to cause tract collapse. Mean follow up was 15.8 months (range 8-24). All patients are asymptomatic without recurrence at the last follow-up visit. No post-operative complications were reported. CONCLUSIONS: Endoscopic management of paediatric PFST combined with the injection of sodium carboxymethylcellulose gel lateral to the sinus tract appears to be a safe and effective treatment option for PFST.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".