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Abazid RM, Pati N, Elrayes M, Awadallah S, Ibrahim MM, Alaref A, Bureau Y, Akincioglu C, Bagur R, Tzemos N. Use of downstream stress imaging tests for risk stratification of patients presenting to the emergency department with chest pain and low HEART score. Open Heart 2024; 11:e002735. [PMID: 39214533 PMCID: PMC11367375 DOI: 10.1136/openhrt-2024-002735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 08/11/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Patients with low HEART (History, Electrocardiogram, Age, Risk factors, and Troponin level) risk scores who are discharged from the emergency department (ED) may present clinical challenges and diagnostic dilemmas. The use of downstream non-invasive stress imaging (NISI) tests in this population remains uncertain. Therefore, this study aims to investigate the value of NISI in risk stratification and predicting cardiac events in patients with low-risk HEART scores (LRHSs). METHODS We prospectively included 1384 patients with LRHSs between March 2019 and March 2021. All the patients underwent NISI (involving myocardial perfusion imaging/stress echocardiography). The primary endpoints included cardiac death, non-fatal myocardial infarction and unplanned coronary revascularisation. Secondary endpoints encompassed cardiovascular-related admissions or ED visits. RESULTS The mean patient age was 64±14 years, with 670 (48.4%) being women. During the 634±104 days of follow-up, 58 (4.2%) patients experienced 62 types of primary endpoints, while 60 (4.3%) developed secondary endpoints. Multivariable Cox models, adjusted for clinical and imaging variables, showed that diabetes (HR: 2.38; p=0.008), HEART score of 3 (HR: 1.32; p=0.01), history of coronary artery disease (HR: 2.75; p=0.003), ECG changes (HR: 5.11; p<0.0001) and abnormal NISI (HR: 16.4; p<0.0001) were primary endpoint predictors, while abnormal NISI was a predictor of secondary endpoints (HR: 3.05; p<0.0001). CONCLUSIONS NISI significantly predicted primary cardiac events and cardiovascular-related readmissions/ED visits in patients with LRHSs.
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Affiliation(s)
- Rami M Abazid
- Department of Medicine, Northern Ontario School of Medicine (NOSM) University, Sault Ste Marie, Ontario, Canada
| | - Nilkanth Pati
- Department of Cardiology, Asian Institute of Gastroenterology (AIG) Hospitals, Gachibowli, Hyderabad, India
- Department of medicine, Dividion of Cardiology, London Health Sciences Centre, London, Ontario, Canada
| | - Maged Elrayes
- Department of medicine, Dividion of Cardiology, London Health Sciences Centre, London, Ontario, Canada
| | - Sameh Awadallah
- Department of medicine, Dividion of Cardiology, London Health Sciences Centre, London, Ontario, Canada
| | - Mohamed M Ibrahim
- Department of Medicine, Northern Ontario School of Medicine (NOSM) University, Sudbury, Ontario, Canada
| | - Amer Alaref
- Department of Medicine, Northern Ontario School of Medicine (NOSM) University, Thunderbay, Ontario, Canada
| | - Yves Bureau
- Department of Psychology, London Health Sciences Centre, London, Ontario, Canada
| | - Cigdem Akincioglu
- Department of Medical Imaging, Dividion of Nuclear Medicine, London Health Sciences Centre, London, Ontario, Canada
| | - Rodrigo Bagur
- Department of medicine, Dividion of Cardiology, London Health Sciences Centre, London, Ontario, Canada
| | - Nikolaos Tzemos
- Department of medicine, Dividion of Cardiology, London Health Sciences Centre, London, Ontario, Canada
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2
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Strehlow M, Gisondi MA, Caretta-Weyer H, Ankel F, Brackett A, Brar P, Chan TM, Garabedian A, Gunn B, Isaacs E, von Isenburg M, Jarman A, Kuehl D, Limkakeng AT, Lydston M, McGregor A, Pierce A, Raven MC, Salhi RA, Stave C, Tan J, Taylor RA, Wong HN, Yiadom MYA, Zachrison KS, Vogel J. 2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy-relevant, patient-centered research agenda. Acad Emerg Med 2024; 31:805-816. [PMID: 38779704 PMCID: PMC11335437 DOI: 10.1111/acem.14932] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/04/2024] [Accepted: 04/11/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVES Precision medicine is data-driven health care tailored to individual patients based on their unique attributes, including biologic profiles, disease expressions, local environments, and socioeconomic conditions. Emergency medicine (EM) has been peripheral to the precision medicine discourse, lacking both a unified definition of precision medicine and a clear research agenda. We convened a national consensus conference to build a shared mental model and develop a research agenda for precision EM. METHODS We held a conference to (1) define precision EM, (2) develop an evidence-based research agenda, and (3) identify educational gaps for current and future EM clinicians. Nine preconference workgroups (biomedical ethics, data science, health professions education, health care delivery and access, informatics, omics, population health, sex and gender, and technology and digital tools), comprising 84 individuals, garnered expert opinion, reviewed relevant literature, engaged with patients, and developed key research questions. During the conference, each workgroup shared how they defined precision EM within their domain, presented relevant conceptual frameworks, and engaged a broad set of stakeholders to refine precision EM research questions using a multistage consensus-building process. RESULTS A total of 217 individuals participated in this initiative, of whom 115 were conference-day attendees. Consensus-building activities yielded a definition of precision EM and key research questions that comprised a new 10-year precision EM research agenda. The consensus process revealed three themes: (1) preeminence of data, (2) interconnectedness of research questions across domains, and (3) promises and pitfalls of advances in health technology and data science/artificial intelligence. The Health Professions Education Workgroup identified educational gaps in precision EM and discussed a training roadmap for the specialty. CONCLUSIONS A research agenda for precision EM, developed with extensive stakeholder input, recognizes the potential and challenges of precision EM. Comprehensive clinician training in this field is essential to advance EM in this domain.
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Affiliation(s)
| | | | | | | | - Alexandria Brackett
- Harvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, CT, USA
| | - Pawan Brar
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Teresa M. Chan
- Toronto Metropolitan University, Toronto; McMaster University, Hamilton, ON, Canada
| | | | | | - Eric Isaacs
- University of California San Francisco, San Francisco, CA, USA
| | | | - Angela Jarman
- University of California, Davis, Sacramento, CA, USA
| | - Damon Kuehl
- Virginia Tech Carilion School of Medicine, Roanoke, VA, USA
| | | | - Melis Lydston
- Treadwell Library, Massachusetts General Hospital, Boston, MA, USA
| | - Alyson McGregor
- Prisma Health, University of South Carolina School of Medicine, Greenville, SC, USA
| | - Ava Pierce
- UT Southwestern Medical Center, Dallas, TX, USA
| | - Maria C. Raven
- University of California San Francisco, San Francisco, CA, USA
| | | | | | - Josephine Tan
- University of California San Francisco, San Francisco, CA, USA
| | | | - Hong-Nei Wong
- Lane Medical Library, Stanford University, Stanford, CA, USA
| | | | | | - Jody Vogel
- Stanford University School of Medicine, Palo Alto, CA, USA
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3
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Hasnie A, Clarkson S, Hage FG. A novel cardiovascular risk assessment tool for the prediction of myocardial ischemia on imaging. J Nucl Cardiol 2023; 30:335-342. [PMID: 35982209 DOI: 10.1007/s12350-022-03079-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 07/18/2022] [Indexed: 10/15/2022]
Affiliation(s)
- Ammar Hasnie
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Stephen Clarkson
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA
| | - Fadi G Hage
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA.
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA.
- Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham, 701 19th Street South, 306 Lyons-Harrison Research Building, Birmingham, AL, 35294, USA.
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O'Neill JC, Ashburn NP, Paradee BE, Snavely AC, Stopyra JP, Noe G, Mahler SA. Rural and socioeconomic differences in the effectiveness of the HEART Pathway accelerated diagnostic protocol. Acad Emerg Med 2023; 30:110-123. [PMID: 36527333 PMCID: PMC10009897 DOI: 10.1111/acem.14643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND The HEART Pathway is a validated accelerated diagnostic protocol (ADP) for patients with possible acute coronary syndrome (ACS). This study aimed to compare the safety and effectiveness of the HEART Pathway based on patient rurality (rural vs. urban) or socioeconomic status (SES). METHODS We performed a preplanned subgroup analysis of the HEART Pathway Implementation Study. The primary outcomes were death or myocardial infarction (MI) and hospitalization at 30 days. Proportions were compared by SES and rurality with Fisher's exact tests. Logistic regression evaluated for interactions of ADP implementation with SES or rurality and changes in outcomes within subgroups. RESULTS Among 7245 patients with rurality and SES data, 39.9% (2887/7245) were rural and 22.2% were low SES (1607/7245). The HEART Pathway identified patients as low risk in 32.2% (818/2540) of urban versus 28.1% (425/1512) of rural patients (p = 0.007) and 34.0% (311/915) of low SES versus 29.7% (932/3137) high SES patients (p = 0.02). Among low-risk patients, 30-day death or MI occurred in 0.6% (5/818) of urban versus 0.2% (1/425) rural (p = 0.67) and 0.6% (2/311) with low SES versus 0.4% (4/932) high SES (p = 0.64). Following implementation, 30-day hospitalization was reduced by 7.7% in urban patients (adjusted odds ratio [aOR] 0.76, 95% confidence interval [CI] 0.66-0.87), 10.6% in low SES patients (aOR 0.68, 95% CI 0.54-0.86), and 4.5% in high SES patients (aOR 0.83, 95% CI 0.73-0.94). However, rural patients had a nonsignificant 3.3% reduction in hospitalizations. CONCLUSIONS HEART Pathway implementation decreased 30-day hospitalizations regardless of SES and for urban patients but not rural patients. The 30-day death or MI rate was similar among low-risk patients.
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Affiliation(s)
- James C O'Neill
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Nicklaus P Ashburn
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Brennan E Paradee
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Anna C Snavely
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jason P Stopyra
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Greg Noe
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Simon A Mahler
- Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Implementation Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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5
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Ashburn NP, Snavely AC, Paradee BE, O'Neill JC, Stopyra JP, Mahler SA. Age differences in the safety and effectiveness of the HEART Pathway accelerated diagnostic protocol for acute chest pain. J Am Geriatr Soc 2022; 70:2246-2257. [PMID: 35383887 PMCID: PMC9378522 DOI: 10.1111/jgs.17777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/17/2022] [Accepted: 03/22/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND The HEART Pathway is a validated protocol for risk stratifying emergency department (ED) patients with possible acute coronary syndrome (ACS). Its performance in different age groups is unknown. The objective of this study is to evaluate its safety and effectiveness among older adults. METHODS A pre-planned subgroup analysis of the HEART Pathway implementation study was conducted. This prospective interrupted time series accrued adult ED patients with possible ACS who were without ST-elevation across three US sites from 11/2013-01/2016. After implementation, providers prospectively used the HEART Pathway to stratify patients as low-risk or non-low-risk. Patients were classified as older adults (≥65 years), middle-aged (46-64 years), and young (21-45 years). Primary safety and effectiveness outcomes were 30-day death or MI and hospitalization at 30 days, determined from health records, insurance claims, and death index data. Fisher's exact test compared low-risk proportions between groups. Sensitivity for 30-day death or MI and adjusted odds ratios (aORs) for hospitalization and objective cardiac testing were calculated. RESULTS The HEART Pathway implementation study accrued 8474 patients, of which 26.9% (2281/8474) were older adults, 45.5% (3862/8474) middle-aged, and 27.5% (2331/8474) were young. The HEART Pathway identified 7.4% (97/1303) of older adults, 32.0% (683/2131) of middle-aged, and 51.4% (681/1326) of young patients as low-risk (p < 0.001). The HEART Pathway was 98.8% (95% CI 97.1-100) sensitive for 30-day death or MI among older adults. Following implementation, the rate of 30-day hospitalization was similar among older adults (aOR 1.25, 95% CI 1.00-1.55) and cardiac testing increased (aOR 1.25, 95% CI 1.04-1.51). CONCLUSION The HEART Pathway identified fewer older adults as low-risk and did not decrease hospitalizations in this age group.
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Affiliation(s)
- Nicklaus P. Ashburn
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Section on Cardiovascular Medicine, Department of Internal MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Anna C. Snavely
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Department of Biostatistics and Data ScienceWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Brennan E. Paradee
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James C. O'Neill
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jason P. Stopyra
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Simon A. Mahler
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Department of Epidemiology and PreventionWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Department of Implementation ScienceWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
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McGinnis HD, Ashburn NP, Paradee BE, O'Neill JC, Snavely AC, Stopyra JP, Mahler SA. Major adverse cardiac event rates in moderate-risk patients: Does prior coronary disease matter? Acad Emerg Med 2022; 29:688-697. [PMID: 35166427 PMCID: PMC9232933 DOI: 10.1111/acem.14462] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/04/2022] [Accepted: 02/10/2022] [Indexed: 02/01/2023]
Abstract
BACKGROUND Despite negative troponins and nonischemic electrocardiograms (ECGs), patients at moderate risk for acute coronary syndrome (ACS) are frequently admitted. The objective of this study was to describe the major adverse cardiac event (MACE) rate in moderate-risk patients and how it differs based on history of coronary artery disease (CAD). METHODS A secondary analysis of the HEART Pathway implementation study was conducted. This prospective interrupted time-series study accrued adults with possible ACS from three sites (November 2013-January 2016). This analysis excluded low-risk patients determined by emergency providers' HEART Pathway assessments. Non-low-risk patients were further classified as high risk, based on elevated troponin measures or ischemic ECG findings or as moderate risk, based on HEAR score ≥ 4, negative troponin measures, and a nonischemic ECG. Moderate-risk patients were then stratified by the presence or absence of prior CAD (MI, revascularization, or ≥70% coronary stenosis). MACE (death, myocardial infarction, or revascularization) at 30 days was determined from health records, insurance claims, and death index data. MACE rates were compared among groups using a chi-square test and likelihood ratios (LRs) were calculated. RESULTS Among 4,550 patients with HEART Pathway assessments, 24.8% (1,130/4,550) were high risk and 37.7% (1715/4550) were moderate risk. MACE at 30 days occurred in 3.1% (53/1,715; 95% confidence interval [CI] = 2.3% to 4.0%) of moderate-risk patients. Among moderate-risk patients, MACE occurred in 7.1% (36/508, 95% CI = 5.1% to 9.8%) of patients with known CAD versus 1.4% (17/1,207, 95% CI = 0.9% to 2.3%) in patients without known prior CAD (p < 0.0001). The negative LR for 30-day MACE among moderate-risk patients without prior CAD was 0.08 (95% CI = 0.05 to 0.12). CONCLUSION MACE rates at 30 days were low among moderate-risk patients but were significantly higher among those with prior CAD.
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Affiliation(s)
- Henderson D. McGinnis
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Nicklaus P. Ashburn
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Brennan E. Paradee
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James C. O'Neill
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Anna C. Snavely
- Department of Biostatistics and Data ScienceDepartment of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jason P. Stopyra
- Department of Emergency MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Simon A. Mahler
- Department of Emergency MedicineDepartment of Implementation ScienceDepartment of Epidemiology and PreventionWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
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7
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O'Rielly CM, Andruchow JE, McRae AD. External validation of a low HEAR score to identify emergency department chest pain patients at very low risk of major adverse cardiac events without troponin testing. CAN J EMERG MED 2022; 24:68-74. [PMID: 34273102 DOI: 10.1007/s43678-021-00159-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 06/05/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND The history, ECG, age, risk factor (HEAR) score has been proposed to identify patients at sufficiently low risk of acute coronary syndrome that they may not require troponin testing. The objective of this study was to externally validate a low HEAR score to identify emergency department (ED) patients with chest pain at very low risk of 30-day major adverse cardiac events (MACE). METHODS This was a secondary analysis of a prospective cohort of patients requiring troponin testing to rule out myocardial infarction (MI) in a large urban ED. HEAR scores were calculated in two cohorts: (1) patients with no known history of coronary artery disease (CAD); and (2) all eligible patients. The proportion of patients classified as very low risk, sensitivity, specificity, predictive values and likelihood ratios at each cut-off were quantified for index acute myocardial infarction (AMI) and 30-day MACE at HEAR = 0 and HEAR ≤ 1 thresholds. RESULTS Of the 1150 patients included in this study, 820 (71.3%) had no history of CAD, 97 (8.4%) had index AMI and 123 (10.7%) had 30-day MACE. In patients with no prior history of CAD, HEAR ≤ 1 identified 202 (24.6%) of patients as very low risk for 30-day MACE with 98.4% (95% CI 91.6-99.9%) sensitivity. Among all patients, HEAR ≤ 1 identified 202 (17.6%) patients as very low risk for 30-day MACE with 99.2% (95% CI 95.6-99.9%) sensitivity. CONCLUSIONS A HEAR score ≤ 1 can identify more than 17% of all patients as very low risk for index AMI and 30-day MACE and unlikely to benefit from troponin testing. Broad implementation of this strategy could lead to significant resource savings.
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Affiliation(s)
- Connor M O'Rielly
- Department of Emergency Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Room 3E34, Calgary, AB, T2N 4Z6, Canada
| | - James E Andruchow
- Department of Emergency Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Room 3E34, Calgary, AB, T2N 4Z6, Canada
| | - Andrew D McRae
- Department of Emergency Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Room 3E34, Calgary, AB, T2N 4Z6, Canada.
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8
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Kim MJ, Ha SO, Park YS, Yi JH, Yang WS, Kim JH. Validation and modification of HEART score components for patients with chest pain in the emergency department. Clin Exp Emerg Med 2021; 8:279-288. [PMID: 35000355 PMCID: PMC8743685 DOI: 10.15441/ceem.20.106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 09/24/2020] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE This study aimed to clarify the relative prognostic value of each History, Electrocardiography, Age, Risk Factors, and Troponin (HEART) score component for major adverse cardiac events (MACE) within 3 months and validate the modified HEART (mHEART) score. METHODS This study evaluated the HEART score components for patients with chest symptoms visiting the emergency department from November 19, 2018 to November 19, 2019. All components were evaluated using logistic regression analysis and the scores for HEART, mHEART, and Thrombolysis in Myocardial Infarction (TIMI) were determined using the receiver operating characteristics curve. RESULTS The patients were divided into a derivation (809 patients) and a validation group (298 patients). In multivariate analysis, age did not show statistical significance in the detection of MACE within 3 months and the mHEART score was calculated after omitting the age component. The areas under the receiver operating characteristics curves for HEART, mHEART and TIMI scores in the prediction of MACE within 3 months were 0.88, 0.91, and 0.83, respectively, in the derivation group; and 0.88, 0.91, and 0.81, respectively, in the validation group. When the cutoff value for each scoring system was determined for the maintenance of a negative predictive value for a MACE rate >99%, the mHEART score showed the highest sensitivity, specificity, positive predictive value, and negative predictive value (97.4%, 54.2%, 23.7%, and 99.3%, respectively). CONCLUSION Our study showed that the mHEART score better detects short-term MACE in high-risk patients and ensures the safe disposition of low-risk patients than the HEART and TIMI scores.
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Affiliation(s)
- Min Jae Kim
- Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea
| | - Sang Ook Ha
- Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea,Correspondence to: Sang Ook Ha Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, 22 Gwanpyeong-ro 170 beongil, Donan-gu, Anyang 14068, Korea E-mail:
| | - Young Sun Park
- Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea
| | - Jeong Hyeon Yi
- Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea
| | - Won Seok Yang
- Department of Emergency Medicine, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea
| | - Jin Hyuck Kim
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University Medical Center, Anyang, Korea
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9
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Ashburn NP, O’Neill JC, Stopyra JP, Mahler SA. Scoring systems for the triage and assessment of short-term cardiovascular risk in patients with acute chest pain. Rev Cardiovasc Med 2021; 22:1393-1403. [PMID: 34957779 PMCID: PMC9038214 DOI: 10.31083/j.rcm2204144] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/21/2021] [Accepted: 10/21/2021] [Indexed: 02/01/2023] Open
Abstract
Acute chest pain is a common emergency department (ED) chief complaint. Evaluating patients for acute coronary syndrome is challenging because missing the diagnosis carries substantial morbidity, mortality, and medicolegal consequences. However, over-testing is associated with increased cost, overcrowding, and possible iatrogenic harm. Over the past two decades, multiple risk scoring systems have been developed to help emergency providers evaluate patients with acute chest pain. The ideal risk score balances safety by achieving high sensitivity and negative predictive value for major adverse cardiovascular events while also being effective in identifying a large proportion of patients for early discharge from the ED. This review examines contemporary risk scores used to risk stratify patients with acute chest pain.
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Affiliation(s)
- Nicklaus P. Ashburn
- Department of Emergency Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
| | - James C. O’Neill
- Department of Emergency Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
| | - Jason P. Stopyra
- Department of Emergency Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
| | - Simon A. Mahler
- Department of Emergency Medicine, Department of Implementation Science, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
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10
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Ioannides KL, Sun BC, Baecker AS, Redberg RF, Lee M, Ferencik M, Wu Y, Shen E, Zheng C, Musigdilok V, Park SJ, Sharp AL. Not all HEART scores are created equal: identifying "low-risk" patients at higher risk. J Am Coll Emerg Physicians Open 2020; 1:1161-1167. [PMID: 33392519 PMCID: PMC7771830 DOI: 10.1002/emp2.12315] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVE We sought to identify sub-groups of "low-risk" HEART score patients (history, ECG, age, risk factors, and troponin) at elevated risk of acute myocardial infarction or death within 30 days. METHODS We performed a secondary analysis of prospective emergency department (ED) encounters for suspected acute coronary syndrome in a large health system with low-risk HEART scores (0-5 points). Logistic regression using the 5 components of the HEART score analyzed the increase risk attributable to points from each of the 5 score components. RESULTS Of 30,971 encounters among 28,992 unique patients, 135 (0.44%, 95% confidence interval [CI] = 0.37-0.51) experienced acute myocardial infarction or death. Risk increased for each component of the HEART score from 0 to 1 to 2 points (history, 0.4% to 0.5% to 0.6%; ECG, 0.3% to 0.7% to 0.7%; age, 0.2% to 0.3% to 0.7%; risk factors, 0.1% to 0.4% to 0.8%), except troponin, which had the highest risk with 1 point (troponin, 0.4% to 2.7% to 0.9%). Odds ratios from our regression, which adjusts for other components, showed a similar pattern (from 1 vs 0 and 2 vs 0 points, respectively: history, 1.0 and 1.8; ECG, 2.2 and 3.5; age, 1.2 and 2.1; risk factors, 2.4 and 4.2; and troponin, 6.0 and 3.6). CONCLUSION Among "low-risk" suspected acute coronary syndrome encounters, increasing points within each of the 5 categories demonstrated small increases in risk of death or acute myocardial infarction, with the troponin and ECG components representing the largest risk increases.
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Affiliation(s)
- Kimon L.H. Ioannides
- NationalClinician Scholars ProgramDepartment of Emergency MedicineUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| | - Benjamin C. Sun
- Department of Emergency Medicine and the Leonard Davis Institute of Health EconomicsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Aileen S. Baecker
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Rita F. Redberg
- Division of CardiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Ming‐Sum Lee
- Division of CardiologyLos Angeles Medical CenterKaiser Permanente Southern CaliforniaLos AngelesCaliforniaUSA
| | - Maros Ferencik
- Knight Cardiovascular InstituteOregon Health and Science UniversityPortlandOregonUSA
| | - Yi‐Lin Wu
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Ernest Shen
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Chengyi Zheng
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Visanee Musigdilok
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Stacy J. Park
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
| | - Adam L. Sharp
- Research and Evaluation DepartmentKaiser Permanente Southern CaliforniaPasadenaCaliforniaUSA
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Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain. Scand J Trauma Resusc Emerg Med 2020; 28:93. [PMID: 32917261 PMCID: PMC7488862 DOI: 10.1186/s13049-020-00786-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 09/02/2020] [Indexed: 02/07/2023] Open
Abstract
Background A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in the emergency department (ED). Therefore, we conducted the present study to clarify it. Methods In total, 85,254 ED patients with chest pain in three hospitals between 2009 and 2018 were identified. We randomized the patients into a 70%/30% split for ML model training and testing. We used 14 clinical variables from their electronic health records to construct a random forest model with the synthetic minority oversampling technique preprocessing algorithm to predict acute myocardial infarction (AMI) < 1 month and all-cause mortality < 1 month. Comparisons of the predictive accuracies among random forest, logistic regression, support-vector clustering (SVC), and K-nearest neighbor (KNN) models were also performed. Results Predicting MACE using the random forest model produced areas under the curves (AUC) of 0.915 for AMI < 1 month and 0.999 for all-cause mortality < 1 month. The random forest model had better predictive accuracy than logistic regression, SVC, and KNN. We further integrated the AI prediction model with the HIS to assist physicians with decision-making in real time. Validation of the AI prediction model by new patients showed AUCs of 0.907 for AMI < 1 month and 0.888 for all-cause mortality < 1 month. Conclusions An AI real-time prediction model is a promising method for assisting physicians in predicting MACE in ED patients with chest pain. Further studies to evaluate the impact on clinical practice are warranted.
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Stopyra JP, Snavely AC, Lenoir KM, Wells BJ, Herrington DM, Hiestand BC, Miller CD, Mahler SA. HEART Pathway Implementation Safely Reduces Hospitalizations at One Year in Patients With Acute Chest Pain. Ann Emerg Med 2020; 76:555-565. [PMID: 32736933 DOI: 10.1016/j.annemergmed.2020.05.035] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 05/14/2020] [Accepted: 05/27/2020] [Indexed: 01/23/2023]
Abstract
STUDY OBJECTIVE We determine whether implementation of the HEART (History, ECG, Age, Risk Factors, Troponin) Pathway is safe and effective in emergency department (ED) patients with possible acute coronary syndrome through 1 year of follow-up. METHODS A preplanned analysis of 1-year follow-up data from a prospective pre-post study of 8,474 adult ED patients with possible acute coronary syndrome from 3 US sites was conducted. Patients included were aged 21 years or older, evaluated for possible acute coronary syndrome, and without ST-segment elevation myocardial infarction. Accrual occurred for 12 months before and after HEART Pathway implementation, from November 2013 to January 2016. The HEART Pathway was integrated into the electronic health record at each site as an interactive clinical decision support tool. After integration, ED providers prospectively used the HEART Pathway to identify patients with possible acute coronary syndrome as low risk (appropriate for early discharge without stress testing or angiography) or nonlow risk (appropriate for further inhospital evaluation). Safety (all-cause death and myocardial infarction) and effectiveness (hospitalization) at 1 year were determined from health records, insurance claims, and death index data. RESULTS Preimplementation and postimplementation cohorts included 3,713 and 4,761 patients, respectively. The HEART Pathway identified 30.7% of patients as low risk; 97.5% of them were free of death and myocardial infarction within 1 year. Hospitalization at 1 year was reduced by 7.0% in the postimplementation versus preimplementation cohort (62.1% versus 69.1%; adjusted odds ratio 0.70; 95% confidence interval 0.63 to 0.78). Rates of death or myocardial infarction at 1 year were similar (11.6% versus 12.4%; adjusted odds ratio 1.00; 95% confidence interval 0.87 to 1.16). CONCLUSION HEART Pathway implementation was associated with decreased hospitalizations and low adverse event rates among low-risk patients at 1-year follow-up.
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Affiliation(s)
- Jason P Stopyra
- Departments of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, NC.
| | - Anna C Snavely
- Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC
| | - Kristin M Lenoir
- Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC
| | - Brian J Wells
- Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC
| | - David M Herrington
- Internal Medicine, Division of Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Brian C Hiestand
- Departments of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Chadwick D Miller
- Departments of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Simon A Mahler
- Departments of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, NC; Implementation Science and Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
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