A Proposed Grading Scale for Predicting Outcomes After Stereotactic Radiosurgery for Dural Arteriovenous Fistulas
Bibliographic record
Abstract
BACKGROUND: There are presently no grading scales that specifically address the outcomes of cranial dural arteriovenous fistula (dAVF) after stereotactic radiosurgery (SRS). OBJECTIVE: To design a practical grading system that would predict outcomes after SRS for cranial dAVFs. METHODS: From the International Radiosurgery Research Foundation (University of Pittsburgh [41 patients], University of Pennsylvania [6 patients], University of Sherbrooke [2 patients], University of Manitoba [1 patient], West Virginia University [2 patients], University of Puerto Rico [1 patient], Beaumont Health System 1 [patient], Na Homolce Hospital [13 patients], the University of Virginia [48 patients], and Yale University [6 patients]) centers, 120 patients with dAVF treated with SRS were included in the study. The factors predicting favorable outcome (obliteration without post-SRS hemorrhage) after SRS were assessed using logistic regression analysis. These factors were pooled with the factors that were found to be predictive of obliteration from 7 studies with 736 patients after a systematic review of literature. These were entered into stepwise multiple regression and the best-fit model was identified. RESULTS: Based on the predictive model, 3 factors emerged to develop an SRS scoring system: cortical venous reflux (CVR), prior intracerebral hemorrhage (ICH), and noncavernous sinus location. Class I (score of 0-1 points) predicted the best favorable outcome of 80%. Class II patients (2 points score) had an intermediate favorable outcome of 57%, and class III (score 3 points) had the least favorable outcome at 37%. The ROC analysis showed better predictability to prevailing grading systems (AUC = 0.69; P = .04). Kaplan-Meier analysis showed statistically significant difference between the 3 subclasses of the proposed grading system for post-SRS dAVF obliteration (P = .001). CONCLUSION: The proposed dAVF grading system incorporates angiographic, anatomic, and clinical parameters and improves the prediction of the outcomes following SRS for dAVF as compared to the existing scoring systems.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".