Clinical and Demographic Characteristics, Natural History and Outcomes in Patients with Moyamoya Vasculopathy in the Canadian population (2941)
Bibliographic record
Abstract
Objective: To describe demographic, clinical and imaging characteristics, and long-term outcomes in patients with Moyamoya vasculopathy evaluated at a regional subspecialty clinic in Canada. Background: Moyamoya vasculopathy is a rare and chronic cerebrovascular condition that predisposes to stroke. Due to its rarity and heterogeneity, there is a lack of knowledge in the medical world regarding Moyamoya vasculopathy and the disease is not well characterized. Design/Methods: We retrospectively reviewed data from adult patients with Moyamoya vasculopathy who were evaluated and followed at the Vancouver Stroke Program Moyamoya clinic between 2015 and 2020. Results: Seventy-nine patients were assessed, receiving clinical follow-up over periods ranging from one to thirty years. Moyamoya disease was seen in 62%, and Moyamoya syndrome in 38%. The majority (62%) were female. The commonest race-ethnicity was Asian (65%), followed by white (23%). The majority (86%) were symptomatic at the time of their diagnosis, with median age at symptom onset of 42 years (range 75). The commonest first-time clinical presentations were transient ischemic attack (44%) and ischemic stroke (28%), with 23% presenting with intracerebral hemorrhage, intraventricular hemorrhage or subarachnoid hemorrhage. Symptoms were provoked in 19% of the cases, mostly through exercising and hyperventilating. Initial modified Rankin Score (mRS) at first presentation to clinic was <3 in 84% of cases. Regarding management, most patients were treated with antiplatelet therapy (72%), mostly with aspirin (98%). Half (49%) received surgical management, with ten of them (30%) undergoing bilateral surgery. Direct revascularization was the commonest surgical approach (77%). The perioperative complication rate was 6%, and postoperative complication rate was 20%, most commonly due to seizures. There was one patient death during follow-up. Conclusions: Our Canadian centre follows a large number of individuals with Moyamoya. Further work will compare the clinical characteristics and natural history of our patient population to the clinical experience reported predominantly from centres in Asia. Disclosure: Dr. Lloret has nothing to disclose. Miss Lim has nothing to disclose. Leah Kuzmuk has nothing to disclose. Dr. Field has received personal compensation for serving as an employee of Springer. Dr. Field has received personal compensation in the range of $5,000-$9,999 for serving as an Expert Witness for Canadian Medical Protective Association. The institution of Dr. Field has received research support from Bayer Canada. Peter Gooderham has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Stryker. Peter Gooderham has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Baxter. Dr. Teal has nothing to disclose. Dr. Yip has nothing to disclose.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".