Establishing Syndromic Surveillance of Acute Coronary Syndrome, Myocardial Infarction, and Stroke: Registry Study Based on Routine Data From German Emergency Departments
Notice bibliographique
Résumé
Background: Emergency department (ED) routine data offer a unique opportunity for syndromic surveillance of communicable and noncommunicable diseases (NCDs). In 2020, the Robert Koch Institute established a syndromic surveillance system using ED data from the AKTIN registry. The system provides daily insights into ED utilization for infectious diseases. Adding NCD indicators to the surveillance is of great public health importance, especially during acute events, where timely monitoring enables targeted public health responses and communication. Objective: This study aimed to develop and validate syndrome definitions for the NCD indicators of acute coronary syndrome (ACS), myocardial infarction (MI), and stroke (STR). Methods: First, syndrome definitions were developed with clinical experts combining ED diagnosis, chief complaints, diagnostic certainty, and discharge information. Then, using the multicenter retrospective routine ED data provided by the AKTIN registry, we conducted internal validation by linking ED cases fulfilling the syndrome definition with the hospital discharge diagnoses and calculating sensitivity, specificity, and accuracy. Lastly, external validation comprised the comparison of the ED cases fulfilling the syndrome definition with the federal German hospital diagnosis statistic. Ratios comparing the relative number of cases for all syndrome definitions were calculated and stratified by age and sex. Results: We analyzed data from 9 EDs, totaling 704,797 attendances from January 1, 2019, to March 5, 2021. Syndrome definitions were based on ICD-10 (International Statistical Classification of Diseases and Related Health Problems 10th Revision-German Modification) diagnoses, chief complaints, and discharge information. We identified 4.3% of all cases as ACS, 0.6% as MI, and 3.2% as STR. Patients with ACS and MI were more likely to be male (58.3% and 64.7%), compared to the overall attendances (52.7%). For all syndrome definitions, the prevalence was higher in the older age groups (60-79 years and >80 years), and the highest proportions of cases were assigned an urgency level (3=urgent or 2=very urgent). The internal validation showed accuracy and specificity levels above 96% for all syndrome definitions. The sensitivity was 85.3% for ACS, 56.6% for MI, and 80.5% for STR. The external validation showed high levels of correspondence between the ED data and the German hospital statistics, with most ratios ranging around 1, indicating congruence, particularly in older age groups. The highest differences were noted in younger age groups, with the highest ratios in women aged between 20 and 39 years (4.57 for MI and 4.17 for ACS). Conclusions: We developed NCD indicators for ACS, MI, and STR that showed high levels of internal and external validity. The integration of these indicators into the syndromic surveillance system for EDs could enable daily monitoring of NCD patterns and trends to enhance timely public health surveillance in Germany.
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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 | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».