建立急性冠状动脉综合征、心肌梗死和中风的综合监测:基于德国急诊科常规数据的登记研究。

IF 3.5 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Madlen Schranz, Mirjam Rupprecht, Annette Aigner, Leo Benning, Carmen Schlump, Nesrine Charfeddine, Michaela Diercke, Linus Grabenhenrich, Alexander Ullrich, Hannelore Neuhauser, Birga Maier, Felix Patricius Hans, Sabine Blaschke
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引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishing Syndromic Surveillance of Acute Coronary Syndrome, Myocardial Infarction, and Stroke: Registry Study Based on Routine Data From German Emergency Departments.

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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来源期刊
CiteScore
13.70
自引率
2.40%
发文量
136
审稿时长
12 weeks
期刊介绍: JMIR Public Health & Surveillance (JPHS) is a renowned scholarly journal indexed on PubMed. It follows a rigorous peer-review process and covers a wide range of disciplines. The journal distinguishes itself by its unique focus on the intersection of technology and innovation in the field of public health. JPHS delves into diverse topics such as public health informatics, surveillance systems, rapid reports, participatory epidemiology, infodemiology, infoveillance, digital disease detection, digital epidemiology, electronic public health interventions, mass media and social media campaigns, health communication, and emerging population health analysis systems and tools.
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