Assessing Impairment and Disability of Facial Paralysis in Patients With Vestibular Schwannoma
Bibliographic record
Abstract
OBJECTIVE: To evaluate facial impairment and disability with respect to quality of life in patients with facial paresis after vestibular schwannoma surgery. DESIGN: Cross-sectional observational study. SETTING: Academic, tertiary care hospital. PATIENTS: All consecutive patients during a 5-year period who underwent vestibular schwannoma surgery. MAIN OUTCOME MEASURES: The validated, patient-graded Facial Clinimetric Evaluation (FaCE) scale questionnaire was administered to all study patients. Main outcome measures included total and social function FaCE scores. Subgroup analysis was performed on patient factors (age and sex), surgical factors (tumor size and time since operation), and House-Brackmann grade. RESULTS: A total of 56 FaCE questionnaires were returned (85% response rate): 28 patients (50%) had normal facial function (House-Brackmann grade I), and 28 patients (50%) had abnormal facial function (House-Brackmann grades II-VI). There were no demographic differences between the normal and abnormal groups. The normal group had a total FaCE score of 96.2 compared with 67.1 in the abnormal group (P<.05). Subgroup analysis of patients with facial paresis revealed that age, sex, time since operation, tumor size, and House-Brackmann grade were not statistically significant factors predicting the FaCE social function score (P<.05). CONCLUSIONS: Facial paresis is an important complication of vestibular schwannoma surgery and will impair a patient's quality of life. The level of impairment may not be predicted by a patient's age, sex, tumor size, time since operation, or severity of facial paresis.
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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 | 0.003 |
| 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".