Clinical and Demographic Characteristics, Natural History and Outcomes in Patients with Moyamoya Vasculopathy in the Canadian population (2941)
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».