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Kim KH, Park JH, Ro YS, Hong KJ, Song KJ, Shin SD. Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain. PLoS One 2020; 15:e0241920. [PMID: 33152007 PMCID: PMC7644067 DOI: 10.1371/journal.pone.0241920] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 10/22/2020] [Indexed: 11/21/2022] Open
Abstract
Background Due to an aging population and the increasing proportion of patients with various comorbidities, the number of patients with acute ischemic heart disease (AIHD) who present to the emergency department (ED) with atypical chest pain is increasing. The aim of this study was to develop and validate a prediction model for AIHD in patients with atypical chest pain. Methods and results A chest pain workup registry, ED administrative database, and clinical data warehouse database were analyzed and integrated by using nonidentifiable key factors to create a comprehensive clinical dataset in a single academic ED from 2014 to 2018. Demographic findings, vital signs, and routine laboratory test results were assessed for their ability to predict AIHD. An extreme gradient boosting (XGB) model was developed and evaluated, and its performance was compared to that of a single-variable model and logistic regression model. The area under the receiver operating characteristic curve (AUROC) was calculated to assess discrimination. A calibration plot and partial dependence plots were also used in the analyses. Overall, 4,978 patients were analyzed. Of the 3,833 patients in the training cohort, 453 (11.8%) had AIHD; of the 1,145 patients in the validation cohort, 166 (14.5%) had AIHD. XGB, troponin (single-variable), and logistic regression models showed similar discrimination power (AUROC [95% confidence interval]: XGB model, 0.75 [0.71–0.79]; troponin model, 0.73 [0.69–0.77]; logistic regression model, 0.73 [0.70–0.79]). Most patients were classified as non-AIHD; calibration was good in patients with a low predicted probability of AIHD in all prediction models. Unlike in the logistic regression model, a nonlinear relationship-like threshold and U-shaped relationship between variables and the probability of AIHD were revealed in the XGB model. Conclusion We developed and validated an AIHD prediction model for patients with atypical chest pain by using an XGB model.
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Affiliation(s)
- Ki Hong Kim
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Korea
| | - Jeong Ho Park
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Korea
- * E-mail:
| | - Young Sun Ro
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Korea
| | - Ki Jeong Hong
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Korea
| | - Kyoung Jun Song
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Department of Emergency Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Sang Do Shin
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Korea
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Fakhri Y, Sejersten M, Schoos MM, Hansen HS, Dubois-Rande JL, Hall TS, Larsen AI, Jensen SE, Engblom H, Arheden H, Kastrup J, Atar D, Clemmensen P. Electrocardiographic scores of severity and acuteness of myocardial ischemia predict myocardial salvage in patients with anterior ST-segment elevation myocardial infarction. J Electrocardiol 2017; 51:195-202. [PMID: 29174706 DOI: 10.1016/j.jelectrocard.2017.11.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Indexed: 12/23/2022]
Abstract
BACKGROUND Terminal "QRS distortion" on the electrocardiogram (ECG) (based on Sclarovsky-Birnbaum's Grades of Ischemia Score) is a sign of severe ischemia, associated with adverse cardiovascular outcome in ST-segment elevation myocardial infarction (STEMI). In addition, ECG indices of the acuteness of ischemia (based on Anderson-Wilkins Acuteness Score) indicate myocardial salvage potential. We assessed whether severe ischemia with or without acute ischemia is predictive of infarct size (IS), myocardial salvage index (MSI) and left ventricular ejection fraction (LVEF) in anterior versus inferior infarct locations. METHODS In STEMI patients, the severity and acuteness scores were obtained from the admission ECG. Based on the ECG patients were assigned with severe or non-severe ischemia and acute or non-acute ischemia. Cardiac magnetic resonance (CMR) was performed 2-6days after primary percutaneous coronary intervention (pPCI). LVEF was measured by echocardiography 30days after pPCI. RESULTS ECG analysis of 85 patients with available CMR resulted in 20 (23%) cases with severe and non-acute ischemia, 43 (51%) with non-severe and non-acute ischemia, 17 (20%) with non-severe and acute ischemia, and 5 (6%) patients with severe and acute ischemia. In patients with anterior STEMI (n=35), ECG measures of severity and acuteness of ischemia identified significant and stepwise differences in myocardial damage and function. Patients with severe and non-acute ischemia had the largest IS, smallest MSI and lowest LVEF. In contrast, no difference was observed in patients with inferior STEMI (n=50). CONCLUSIONS The applicability of ECG indices of severity and acuteness of myocardial ischemia to estimate myocardial damage and salvage potential in STEMI patients treated with pPCI, is confined to anterior myocardial infarction.
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Affiliation(s)
- Yama Fakhri
- Department of Cardiology, The Heart Centre, Rigshospitalet, Copenhagen, Denmark; Department of Medicine, Division of Cardiology, Nykøbing F Hospital, Nykøbing F, Denmark.
| | - Maria Sejersten
- Department of Cardiology, Herlev University Hospital, Herlev, Denmark
| | | | | | | | - Trygve S Hall
- Department of Cardiology B, Oslo University Hospital Ullevål, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Alf-Inge Larsen
- Department of Cardiology, Stavanger University Hospital, Stavanger, Norway, Institute of Clinical Science, University of Begen, Norway
| | | | - Henrik Engblom
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Hakon Arheden
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Jens Kastrup
- Department of Cardiology, The Heart Centre, Rigshospitalet, Copenhagen, Denmark
| | - Dan Atar
- Department of Cardiology B, Oslo University Hospital Ullevål, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Peter Clemmensen
- Department of Medicine, Division of Cardiology, Nykøbing F Hospital, Nykøbing F, Denmark; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Eppendorf, Germany
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Atwater BD, Bacharova L, Pahlm O, Swenne CA. Special issue of the Journal of Electrocardiology to commemorate Dr. Galen Wagner (1939-2016). J Electrocardiol 2016; 50:1-2. [PMID: 27939927 DOI: 10.1016/j.jelectrocard.2016.11.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Brett D Atwater
- Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Olle Pahlm
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Cees A Swenne
- Cardiology Department, Leiden University Medical Center, Leiden, The Netherlands.
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