A pilot study of masticatory function after maxillectomy comparing rehabilitation with an obturator prosthesis and reconstruction with a digitally planned, prefabricated, free, vascularized fibula flap
Bibliographic record
Abstract
STATEMENT OF PROBLEM: Oral rehabilitation after maxillectomy can be performed by prosthetic obturation or with a free fibula flap. Successful prosthetic obturation of large maxillectomy defects can be difficult, and masticatory function is at risk in these patients. Surgical reconstruction might provide adequate masticatory function, but the literature is lacking evidence regarding this topic. PURPOSE: The purpose of this pilot clinical study was to assess masticatory functions and health-related quality of life (HR-QoL) outcomes in patients after maxillectomy reconstructed by using the Rohner or the Alberta Reconstructive Technique and to compare outcomes with patients rehabilitated with an obturator prosthesis. MATERIAL AND METHODS: Mixing ability, maximum occlusal force, maximum mouth opening, and HR-QoL were assessed. Differences between the 2 groups were analyzed by using the Kruskal-Wallis tests for continuous variables and chi-squared tests for categorical variables. RESULTS: The reconstructed patients (n=11) showed better mixing ability, occlusal force (nonoperated side), and overall mean HR-QoL. The nonreconstructed group (n=13) did not differ from the reconstructed groups in terms of maximum mouth opening, overall mean occlusal force, occlusal force on the operated side, and most HR-QoL questionnaire domains. CONCLUSIONS: Maxillary reconstruction might be beneficial for masticatory performance in patients undergoing maxillectomy. A larger study is justified to support the possible benefit of the reconstruction of maxillary defects regarding mixing ability, occlusal force (nonoperated side), and HR-QoL.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".