The Craniocaudal Extension of Posterolateral Approaches and Their Combination
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to describe quantitatively the properties of the posterolateral approaches and their combination. METHODS: Six silicone-injected cadaveric heads were dissected bilaterally. Quantitative data were generated with the Optotrak 3020 system (Northern Digital, Waterloo, Canada) and Surgiscope (Elekta Instruments, Inc., Atlanta, GA), including key anatomic points on the skull base and brainstem. All parameters were measured after the basic retrosigmoid craniectomy and then after combination with a basic far-lateral extension. The clinical results of 20 patients who underwent a combined retrosigmoid and far-lateral approach were reviewed. RESULTS: The change in accessibility to the lower clivus was greatest after the far-lateral extension (mean change, 43.62 +/- 10.98 mm2; P = .001). Accessibility to the constant landmarks, Meckel's cave, internal auditory meatus, and jugular foramen did not change significantly between the 2 approaches (P > .05). The greatest change in accessibility to soft tissue between the 2 approaches was to the lower brainstem (mean change, 33.88 +/- 5.25 mm2; P = .0001). Total removal was achieved in 75% of the cases. The average postoperative Glasgow Outcome Scale score of patients who underwent the combined retrosigmoid and far-lateral approach improved significantly, compared with the preoperative scores. CONCLUSION: The combination of the far-lateral and simple retrosigmoid approaches significantly increases the petroclival working area and access to the cranial nerves. However, risk of injury to neurovascular structures and time needed to extend the craniotomy must be weighed against the increased working area and angles of attack.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".