Stereotactic Radiosurgery for Cavernous Sinus Versus Noncavernous Sinus Dural Arteriovenous Fistulas: Outcomes and Outcome Predictors
Bibliographic record
Abstract
BACKGROUND: Dural arteriovenous fistulas (DAVFs) can be categorized based on location. OBJECTIVE: To compare stereotactic radiosurgery (SRS) outcomes between cavernous sinus (CS) and non-CS DAVFs and to identify respective outcome predictors. METHODS: This is a retrospective study of DAVFs treated with SRS between 1988 and 2016 at 10 institutions. Patients' variables, DAVF characters, and SRS parameters were included for analyses. Favorable clinical outcome was defined as angiography-confirmed obliteration without radiological radiation-induced changes (RIC) or post-SRS hemorrhage. Other outcomes were DAVFs obliteration and adverse events (including RIC, symptomatic RIC, and post-SRS hemorrhage). RESULTS: The overall study cohort comprised 131 patients, including 20 patients with CS DAVFs (15%) and 111 patients with non-CS DAVFs (85%). Rates of favorable clinical outcome were comparable between the 2 groups (45% vs 37%, P = .824). Obliteration rate after SRS was higher in the CS DAVFs group, even adjusted for baseline difference (OR = 4.189, P = .044). Predictors of favorable clinical outcome included higher maximum dose (P = .014) for CS DAVFs. Symptomatic improvement was associated with obliteration in non-CS DAVFs (P = .005), but symptoms improved regardless of whether obliteration was confirmed in CS DAVFs. Non-CS DAVFs patients with adverse events after SRS were more likely to be male (P = .020), multiple arterial feeding fistulas (P = .018), and lower maximum dose (P = .041). CONCLUSION: After SRS, CS DAVFs are more likely to obliterate than non-CS ones. Because these 2 groups have different total predictors for clinical and radiologic outcomes after SRS, they should be considered as different entities.
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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 | 0.002 |
| 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 | 0.000 |
| 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".