ArticleReviews in cardiovascular medicine2023
Prehospital Misdiagnosed Acute Coronary Syndrome-Incidence, Discriminating Features, and Differential Diagnoses.
Article in Reviews in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial intelligence in prehospital assessment of acute coronary syndrome: a scoping review.BMC emergency medicine · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute coronary syndrome (ACS) is a major cause of morbidity and mortality in the western world. Classic angina pectoris (AP) is a common reason to request prehospital emergency medical services (EMS). Nevertheless, data on diagnostic accuracy and common misdiagnoses are scarce. Therefore, the aim of this study is to evaluate the amount and variety of misdiagnoses and assess discriminating features. Methods: For this retrospective cohort study, all patients requiring EMS for suspected ACS in the city of Bonn (Germany) during 2018 were investigated. Prehospital and hospital medical records were reviewed regarding medical history, presenting signs and symptoms, as well as final diagnosis. Results: Out of 740 analyzed patients with prehospital suspected ACS, 283 (38.2%) were ultimately diagnosed with ACS (ACS group). Common diagnoses in the cohort with non-confirmed ACS (nACS group) consisted of unspecific pain syndromes, arrhythmias, hypertensive crises, and heart failure. ST segment elevation (adjusted odds-ratios [adj. OR] 2.70), male sex (adj. OR 1.71), T wave changes (adj. OR 1.27), angina pectoris (adj. OR 1.15) as well as syncope (adj. OR 0.63) were identified among others as informative predictors in a multivariable analysis using the lasso technique for data-driven variable selection. Conclusions: Misdiagnosed ACS is as common as 61.8% in this cohort and analyses point to a complex of conditions and symptoms (i.e., male sex, electrocardiographic (ECG) changes, AP) for correct ACS diagnosis while neurological symptoms were observed significantly more often in the nACS group (e.g., Glasgow Coma Scale (GCS)
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