Prevention of Postlaryngectomy Pharyngocutaneous Fistula: The Memorial University Experience
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to compare the efficacy of a pectoralis major myogenous flap in the prevention of pharyngocutaneous fistula in patients who have undergone total laryngectomy. Our secondary objective was to estimate the economic saving to our health care system. DESIGN: Retrospective clinical study. SETTING: Grace General Hospital, St. Clare's Mercy Hospital, H. Bliss Murphy Cancer and Research Centre, St. John's, Newfoundland. MATERIALS AND METHODS: Two hundred and twenty-three consecutive total laryngectomy procedures performed between June 1978 and December 2001 were reviewed. The fistula rate in laryngectomy patients prior to 1988 without pectoralis major myogenous flaps (group A) was compared with that of patients after June 1988 who had this flap routinely used at primary surgery (group B). Analysis of risk factors within those two groups was essentially similar. RESULTS: In group A, the overall pharyngocutaneous fistula rate was 22.9%. The fistula rate in group B was less than 1%. CONCLUSION: Our study has demonstrated that at our tertiary care head and neck oncology centre, we have dramatically decreased the incidence of postlaryngectomy pharyngocutaneous fistula. By the routine addition of a pectoralis major myogenous flap to cover the pharyngeal defect at surgery, we have substantially and dramatically reduced patient morbidity and mortality and reduced hospital stay, with major financial savings to the health care system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".