Application of the Radial Forearm Free Flap in Intraoral Reconstruction - A Retrospective Study
Bibliographic record
Abstract
Abstract Introduction: The radial forearm free flap (RFFF) is an established technique for the reconstruction of intraoral defects following oncological resection. The objective of this study was to evaluate the functional, aesthetic and complication-related outcomes of the RFFF in immediate microvascular reconstruction of intraoral defects. Materials and Methods: A retrospective, observational and descriptive study was conducted based on the clinical records of 15 patients who underwent resection and immediate reconstruction with a RFFF at Hospital de Clínicas “José de San Martín” between May 2019 and June 2024. Post-operative oral function was assessed using the functional oral intake scale for swallowing, the speech intelligibility rating for speech and the modified Vancouver Scar Scale for aesthetic outcomes. Complications were classified according to the Clavien–Dindo system adapted for reconstructive microsurgery. Descriptive and inferential statistical analyses were performed, with significance set at P < 0.05. Results: The mean age was 62.8 years; 60% were female. The most frequent diagnosis was oral cavity squamous cell carcinoma (80%). Flap survival was 100%. Swallowing function was adequate in 86.7% of cases, speech in 73.3% and aesthetic outcome in 80%. The overall complication rate was 20.0%, with only one case requiring microsurgical reintervention. No statistically significant association was found between the occurrence of complications and functional or aesthetic outcomes. Discussion: The RFFF proved to be a safe and effective technique for immediate reconstruction of intraoral defects, offering high survival rates and satisfactory functional and aesthetic outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".