Immediate dental implants in fibula free flaps to reconstruct the mandible: A pilot study of the short‐term effects on radiotherapy for patients with head and neck cancer
Bibliographic record
Abstract
OBJECTIVES: The current pilot study aims to report short-term experience as it relates to acute radiotherapy treatment outcomes comparing patients with immediate dental implants in fibula free flap reconstructions to a historical cohort of patients with fibula free flap reconstructions without dental implants. MATERIALS AND METHODS: A retrospective review of patients who underwent segmental mandibulectomy, reconstruction with fibula free flaps, and adjuvant radiotherapy with (n = 10) and without immediate dental implants (n = 10) at a tertiary cancer center from 2015 to 2018 was performed (IRB #17-271). Incidence of postoperative complications, time to initiation of radiation therapy, development of acute toxicity, and patient reported outcome data were recorded. The radiation plans were evaluated to identify the mean and maximum doses received by the mandible and oral cavity as well as the locations of radiation global hot spots. RESULTS: There was a similar number of postoperative complications in both cohorts, with three events in the case group and two events in the control group. Patients with dental implants reported less trismus than control patients. Evaluation of the radiation treatment plans revealed similar median radiation global hot spots in both groups. CONCLUSIONS: The current study suggests that the presence of dental implants does not increase the risk of complications following surgery or during radiation treatment. Implants do not alter radiation dosimetry but do appear to positively impact early patient quality of life. Although longer follow-up is needed, based on this preliminary experience, cancer patients should be offered this type of reconstruction without fear of impacting radiation timing or delivery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".