Outcomes of bypass surgery in asymptomatic moyamoya angiopathy: A multicenter study with propensity-score weighting
Bibliographic record
Abstract
Introduction: Asymptomatic moyamoya angiopathy (MMA) is increasingly detected through noninvasive imaging; however, its optimal management remains controversial. This multicenter retrospective cohort study compared outcomes in asymptomatic versus symptomatic MMA patients undergoing surgical revascularization. Patients and methods: A total of 475 patients treated with bypass surgery across multiple academic centers were included, with 56 (11.8%) classified as asymptomatic and 419 (88.2%) as symptomatic. Baseline demographics, surgical characteristics, and outcomes-including perioperative stroke, intraoperative complications, and follow-up stroke events-were collected. Asymptomatic MMA was defined as the absence of any prior ischemic or hemorrhagic stroke, seizures, or other neurological symptoms at the time of diagnosis. Both unadjusted analyses and propensity score weighting using inverse probability of treatment weighting (IPTW) were performed to adjust for potential confounders. Results: In the unadjusted analysis, asymptomatic patients had significantly lower rates of all perioperative strokes (1.7% vs 11.4%; p = 0.05) and intraoperative complications (1.7% vs 11.2%; p = 0.05) compared to symptomatic patients. Additionally, follow-up stroke rates were lower in the asymptomatic group (1.7% vs 11.2%; p = 0.05). After IPTW adjustment, the reduction in intraoperative complications (OR: 0.08, 95% CI: 0.01–0.64; p = 0.01) and follow-up stroke rates (OR: 0.12, 95% CI: 0.01–0.91; p = 0.04) persisted, while differences in overall perioperative stroke were not statistically significant. Conclusion: Bypass surgery in selected asymptomatic MMA patients is associated with reduced intraoperative complications, and fewer follow-up stroke rates. These findings support the careful consideration of surgical intervention in asymptomatic patients, emphasizing the importance of patient selection for optimal outcomes.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".