Rates and Determinants of Prosthodontic Rehabilitation After Segmental Jaw Surgery
Bibliographic record
Abstract
BACKGROUND: Management of maxillofacial pathologies often requires ablative surgeries of the jaw which may include the tooth-bearing segment resulting in loss of oral function. Advances in maxillomandibular reconstruction with vascularized free flaps (VFFs) and dental implants have enabled prosthodontic rehabilitation (PR) in most patients. However, the impact of these advancements on rates and barriers of PR remains unclear. PURPOSE: The purpose of this study was to estimate the rate of PR and identify risk factors associated with failure to achieve PR. STUDY DESIGN, SETTING, SAMPLE: This 7-year retrospective cohort study was conducted at the Montreal General Hospital and included patients aged ≥15 years who underwent vascularized free flap reconstruction following jaw segmental resection between 2015 and 2021. PREDICTOR VARIABLE: Predictor variables included age, sex, smoking, clinical diagnosis, adjuvant radiotherapy, flap type, and anterior tooth loss. MAIN OUTCOME VARIABLE(S): The primary outcome is time to PR and secondary outcomes were PR status (not performed vs performed) and PR type (conventional vs implant-supported) respectively. COVARIATES: NA. ANALYSES: Descriptive statistics, comparison tests, Kaplan-Meier analysis, and univariate and multivariate Cox and logistic regression analyses were conducted (P < .05). RESULTS: The study included 184 subjects with a mean age of 58 years (SD = 17), and 52% (n = 95) were men. The median follow-up was 20 months (interquartile range = 32). Malignancy was the most common diagnosis leading to surgery (n = 106; 58%), followed by benign tumors (n = 46; 25%). Cumulative proportion of PR was 41% (n = 76), including 19.5% (n = 36) of implant-supported prostheses. Median time to start PR was 44 months (95% CI: 30 to 78) and was significantly delayed in men, ever smokers, cancer patients, and those who received radiotherapy. In multivariate analysis, radiotherapy was the main predictor of failure to receive PR overall (P = .014) and implant-supported PR specifically (P = .025). CONCLUSION AND RELEVANCE: Many patients with dental morbidity after segmental jaw surgery, especially cancer patients requiring radiotherapy, did not receive PR, and even fewer received implant-supported prostheses, highlighting the need for preradiotherapy solutions.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".