Functional Outcomes after Hemiglossectomy and Reconstruction with a Bilobed Radial Forearm Free Flap
Bibliographic record
Abstract
OBJECTIVE: This study examines prospectively the functional outcomes of a cohort of patients who had undergone hemiglossectomy and reconstruction with a bilobed radial forearm free flap (RFFF) for oral tongue squamous cell carcinoma. METHODS: Speech and swallowing data were compiled for patients treated for oral tongue cancer with hemiglossectomy and and reconstruction with a bilobed RFFF. The three evaluation periods were preoperative, postoperatively, and postradiation therapy. RESULTS: Eleven patients were included in the study. A significant difference between preoperative and postoperative single-word intelligibility scores was observed. There was no significant difference across any of the evaluation times for sentence intelligibility. Swallowing analysis revealed fewer instances of laryngeal penetration with liquids postoperatively. No significant differences were found in laryngeal penetration with either the pudding or cookie consistencies across any of the evaluation times. There was no incidence of aspiration at any of the evaluation times. There were no significant differences in the number of problems with the oral or oral preparatory phases across any of the evaluation times. The neurotization status of the RFFF had no significant effect on any of the observed speech or swallowing parameters. CONCLUSIONS: The bilobed RFFF provides functional speech and excellent swallowing outcomes in the reconstruction of hemiglossectomy defects.
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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 | 0.001 |
| 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) | 0.001 | 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".