Increased MIB-1 Labeling Index Is Associated with Abducens Nerve Morbidity in Primary Sporadic Petroclival Meningioma Surgery: Beyond Location and Approach
Bibliographic record
Abstract
Abducens nerve palsy is a severe dysfunction after petroclival meningioma (PC MNG) surgery. The objective of this investigation was to analyze abducens nerve outcomes in patients who underwent the retrosigmoid approach in relation to the MIB-1 index. Thirty-two patients with primary sporadic PC MNG were retrospectively analyzed. Mean follow-up was 28.0 months. Analysis of the MIB-1 index was performed to evaluate the abducens nerve outcome. An optimal MIB-1 index cut-off value (<4/≥4) in the association with postoperative CN VI palsy was determined by ROC analysis (AUC: 0.74, 95% CI: 0.57−0.92). A new-onset CN VI palsy was present in 7 cases (21.88%) and was significantly associated with an increased MIB-1 index (≥4%, p = 0.025) and a peritumoral edema in the brachium pontis (p = 0.047) which might be caused by the increased growth rate. Tumor volume, cavernous sinus infiltration, auditory canal invasion, and Simpson grading were not associated with new CN VI deficits. Six (85.7%) of the 7 patients with both an increased MIB-1 index (≥4%) and new abducens nerve palsy still had a CN VI deficit at the 12-month follow-up. A peritumoral edema caused by a highly proliferative PC MNG with an elevated MIB-1 index (≥4%) is associated with postoperative abducens nerve deficits.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".