OBJECTIVES: To determine the causes of software misinterpretation of ST elevation myocardial infarction (STEMI) compared to clinically identified STEMI to identify opportunities to improve prehospital STEMI identification. METHODS: We compared ECGs acquired from July 2011 through June 2012 using the LIFEPAK 15 on adult patients transported by the Los Angeles Fire Department. Cases included patients ≥18 years who received a prehospital ECG. Software interpretation of the ECG (STEMI or not) was compared with data in the regional EMS registry to classify the interpretation as true positive (TP), true negative (TN), false positive (FP), or false negative (FN). For cases where classification was not possible using registry data, 3 blinded cardiologists interpreted the ECG. Each discordance was subsequently reviewed to determine the likely cause of misclassification. The cardiologists independently reviewed a sample of these discordant ECGs and the causes of misclassification were updated in an iterative fashion. RESULTS: Of 44,611 cases, 50% were male (median age 65; inter-quartile range 52-80). Cases were classified as 482 (1.1%) TP, 711 (1.6%) FP, 43371 (97.2%) TN, and 47 (0.11%) FN. Of the 711 classified as FP, 126 (18%) were considered appropriate for, though did not undergo, emergent coronary angiography, because the ECG showed definite (52 cases) or borderline (65 cases) ischemic ST elevation, a STEMI equivalent (5 cases) or ST-elevation due to vasospasm (4 cases). The sensitivity was 92.8% [95% CI 90.6, 94.7%] and the specificity 98.7% [95% CI 98.6, 98.8%]. The leading causes of FP were ECG artifact (20%), early repolarization (16%), probable pericarditis/myocarditis (13%), indeterminate (12%), left ventricular hypertrophy (8%), and right bundle branch block (5%). There were 18 additional reasons for FP interpretation (<4% each). The leading causes of FN were borderline ST-segment elevations less than the algorithm threshold (40%) and tall T waves reducing the ST/T ratio below threshold (15%). There were 11 additional reasons for FN interpretation occurring ≤3 times each. CONCLUSION: The leading causes of FP automated interpretation of STEMI were ECG artifact and non-ischemic causes of ST-segment elevation. FN were rare and were related to ST-segment elevation or ST/T ratio that did not meet the software algorithm threshold.
OBJECTIVES: To determine the causes of software misinterpretation of ST elevation myocardial infarction (STEMI) compared to clinically identified STEMI to identify opportunities to improve prehospital STEMI identification. METHODS: We compared ECGs acquired from July 2011 through June 2012 using the LIFEPAK 15 on adult patients transported by the Los Angeles Fire Department. Cases included patients ≥18 years who received a prehospital ECG. Software interpretation of the ECG (STEMI or not) was compared with data in the regional EMS registry to classify the interpretation as true positive (TP), true negative (TN), false positive (FP), or false negative (FN). For cases where classification was not possible using registry data, 3 blinded cardiologists interpreted the ECG. Each discordance was subsequently reviewed to determine the likely cause of misclassification. The cardiologists independently reviewed a sample of these discordant ECGs and the causes of misclassification were updated in an iterative fashion. RESULTS: Of 44,611 cases, 50% were male (median age 65; inter-quartile range 52-80). Cases were classified as 482 (1.1%) TP, 711 (1.6%) FP, 43371 (97.2%) TN, and 47 (0.11%) FN. Of the 711 classified as FP, 126 (18%) were considered appropriate for, though did not undergo, emergent coronary angiography, because the ECG showed definite (52 cases) or borderline (65 cases) ischemic ST elevation, a STEMI equivalent (5 cases) or ST-elevation due to vasospasm (4 cases). The sensitivity was 92.8% [95% CI 90.6, 94.7%] and the specificity 98.7% [95% CI 98.6, 98.8%]. The leading causes of FP were ECG artifact (20%), early repolarization (16%), probable pericarditis/myocarditis (13%), indeterminate (12%), left ventricular hypertrophy (8%), and right bundle branch block (5%). There were 18 additional reasons for FP interpretation (<4% each). The leading causes of FN were borderline ST-segment elevations less than the algorithm threshold (40%) and tall T waves reducing the ST/T ratio below threshold (15%). There were 11 additional reasons for FN interpretation occurring ≤3 times each. CONCLUSION: The leading causes of FP automated interpretation of STEMI were ECG artifact and non-ischemic causes of ST-segment elevation. FN were rare and were related to ST-segment elevation or ST/T ratio that did not meet the software algorithm threshold.
Entities:
Keywords:
electrocardiography; emergency medical services; myocardial infarction
Authors: Ziad Faramand; Stephanie Helman; Abdullah Ahmad; Christian Martin-Gill; Clifton Callaway; Samir Saba; Richard E Gregg; John Wang; Salah Al-Zaiti Journal: J Electrocardiol Date: 2021-08-18 Impact factor: 1.438
Authors: C Cato Ter Haar; Jan A Kors; Ron J G Peters; Michael W T Tanck; Marieke B Snijder; Arie C Maan; Cees A Swenne; Bert-Jan H van den Born; Jonas S S G de Jong; Peter W Macfarlane; Pieter G Postema Journal: J Am Heart Assoc Date: 2020-06-23 Impact factor: 5.501
Authors: S S Anroedh; I Kardys; K M Akkerhuis; M Biekart; B van der Hulst; G J Deddens; P Smits; M Gardien; E Dubois; F Zijlstra; E Boersma Journal: Neth Heart J Date: 2018-11 Impact factor: 2.380
Authors: Michael C Kontos; Michael R Gunderson; Jessica K Zegre-Hemsey; David C Lange; William J French; Timothy D Henry; James J McCarthy; Claire Corbett; Alice K Jacobs; James G Jollis; Steven V Manoukian; Robert E Suter; David T Travis; J Lee Garvey Journal: J Am Heart Assoc Date: 2020-01-20 Impact factor: 5.501
Authors: Charles Richard Knoery; Janet Heaton; Rob Polson; Raymond Bond; Aleeha Iftikhar; Khaled Rjoob; Victoria McGilligan; Aaron Peace; Stephen James Leslie Journal: Crit Pathw Cardiol Date: 2020-09