The Alberta standardized orbital technique in the management of spheno-orbital meningiomas
Bibliographic record
Abstract
PURPOSE: To describe a standardized orbital resection technique and outcomes for spheno-orbital meningiomas with soft-tissue invasion of the orbit. METHODS: A retrospective case review of patients with spheno-orbital meningioma that underwent resection utilizing the Alberta Standardized Orbital Technique (ASOT) between 2008 and 2017 was performed. RESULTS: Twenty patients met the inclusion criteria. Fifteen females and five males, with an average age of 53.4 years (SD ± 13.1 years). Mean follow-up was 57.3 months (SD ± 29.5 months). Eight cases (40%) had attempted resection prior to referral. Based on pre-operative plan, patients were divided into two groups based on goal of resection. Of those with planned complete resection (Group I), 11/13 patients (84.6%) underwent complete excision, with no cases of orbital recurrence. Incomplete resection in two cases occurred because of unexpected involvement of critical intra-cranial structures. Thus, in total 9/20 patients (Group II and 2 from Group I) underwent subtotal resection. Of these incomplete resections, five cases of orbital recurrence were observed; four patients required adjuvant external beam radiotherapy (EBRT) and one patient underwent further debulking surgery. Orbital control was achieved in three of these recurrent cases. Complications reported were persistent postoperative diplopia (three cases/15%) and wound infection (one case/5%). Overall, stable orbital disease was obtained in 18 patients (90%). CONCLUSION: The ASOT demonstrated to be effective, achieving the pre-operative plan of complete resection in 11/13 cases (84.6%) with no recurrence in those with clear orbital margins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".