Geographic Clustering of Emergency Department Presentations for Atrial Fibrillation and Flutter in Alberta, Canada
Notice bibliographique
Résumé
OBJECTIVES: Atrial fibrillation and flutter (AFF) are the most common arrhythmias seen in the outpatient setting, and they affect more than 300,000 adult Canadians. The aims of this study were to examine temporal and geographic trends in emergency department (ED) presentations made by adults (age ≥ 35 years) for AFF in Alberta, Canada, from 1999 to 2011. Statistical disease cluster detection techniques were used to identify geographic areas with higher numbers of individuals presenting with AFF and higher numbers of ED presentations for AFF than expected by chance alone. Geographic clusters of individuals with stroke or heart failure follow-up within 365 days of ED presentations for AFF were also identified. METHODS: All ED presentations for AFF made by individuals aged ≥35 years were extracted from Alberta's Ambulatory Care Classification System. The Alberta Health Care Insurance Plan provided population counts and demographics for the patients presenting (age, sex, year, geographic unit). The Physician Claims File provided non-ED physician claims data after a patient's ED presentation. Statistical analyses included numerical and graphical summaries, directly standardized rates, and statistical disease cluster detection tests. RESULTS: During 12 years, there were 63,395 ED presentations for AFF made by 32,101 individuals. Standardized rates remained relatively stable over time, at about two per 1,000 for individuals presenting to the ED for AFF and about three per 1,000 for ED presentations for AFF. The northern and southeastern parts of the province were identified as clusters of individuals presenting for AFF, and ED presentations for AFF, and several of the areas demonstrated clusters in multiple years. Further, several of the geographic clusters were also identified as potential clusters for stroke or heart failure within 365 days after the ED presentations for AFF. CONCLUSIONS: This population-based study spanned 12 fiscal years and showed variations in the number of people presenting to EDs for AFF and the number of ED presentations for AFF over geography. The potential clusters identified may represent geographic areas with higher disease severity or a lower availability of non-ED health services. The clusters are not all likely to have occurred by chance, and further investigation and intervention could occur to reduce ED presentations for AFF.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».