Literature DB >> 24626114

Computerized interpretation of the prehospital electrocardiogram: predictive value for ST segment elevation myocardial infarction and impact on on-scene time.

François de Champlain, Lucy J Boothroyd, Alain Vadeboncoeur, Thao Huynh, Viviane Nguyen, Mark J Eisenberg, Lawrence Joseph, Jean-François Boivin, Eli Segal.   

Abstract

INTRODUCTION: Computerized interpretation of the prehospital electrocardiogram (ECG) is increasingly being used in the basic life support (BLS) ambulance setting to reduce delays to treatment for patients suspected of ST segment elevation myocardial infarction (STEMI).
OBJECTIVES: To estimate 1) predictive values of computerized prehospital 12-lead ECG interpretation for STEMI and 2) additional on-scene time for 12-lead ECG acquisition.
METHODS: Over a 2-year period, 1,247 ECGs acquired by primary care paramedics for suspected STEMI were collected. ECGs were interpreted in real time by the GE-Marquette 12SL ECG analysis program. Predictive values were estimated with a bayesian latent class model incorporating the computerized ECG interpretations, consensus ECG interpretations by study cardiologists, and hospital diagnosis. On-scene time was compared for ambulance-transported patients with (n  =  985) and without (n  =  5,056) prehospital ECGs who received prehospital aspirin and/or nitroglycerin.
RESULTS: The computer's positive and negative predictive values for STEMI were 74.0% (95% credible interval [CrI] 69.6-75.6) and 98.1% (95% CrI 97.8-98.4), respectively. The sensitivity and specificity were 69.2% (95% CrI 59.0-78.5) and 98.9% (95% CrI 98.1-99.4), respectively. Prehospital ECGs were associated with a mean increase in on-scene time of 5.9 minutes (95% confidence interval 5.5-6.3).
CONCLUSIONS: The predictive values of the computerized prehospital ECG interpretation appear to be adequate for diversion programs that direct patients with a positive result to hospitals with angioplasty facilities. The estimated 26.0% chance that a positive interpretation is false is likely too high for activation of a catheterization laboratory from the field. Acquiring prehospital ECGs does not substantially increase on-scene time in the BLS setting.

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Year:  2014        PMID: 24626114     DOI: 10.2310/8000.2013.131031

Source DB:  PubMed          Journal:  CJEM        ISSN: 1481-8035            Impact factor:   2.410


  5 in total

1.  Push Notifications Reduce Emergency Department Response Times to Prehospital ST-segment Elevation Myocardial Infarction.

Authors:  Mathew Goebel; Joseph Bledsoe
Journal:  West J Emerg Med       Date:  2019-02-11

2.  Late Outcomes of Patients With Prehospital ST-Segment Elevation and Appropriate Cardiac Catheterization Laboratory Nonactivation.

Authors:  Amir Faour; Reece Pahn; Callum Cherrett; Oliver Gibbs; Karen Lintern; Christian J Mussap; Rohan Rajaratnam; Dominic Y Leung; David A Taylor; Steven C Faddy; Sidney Lo; Craig P Juergens; John K French
Journal:  J Am Heart Assoc       Date:  2022-06-29       Impact factor: 6.106

Review 3.  Systematic Review and Meta-Analysis of Diagnostic Accuracy to Identify ST-Segment Elevation Myocardial Infarction on Interpretations of Prehospital Electrocardiograms.

Authors:  Akihito Tanaka; Kunihiro Matsuo; Migaku Kikuchi; Sunao Kojima; Hiroyuki Hanada; Toshiaki Mano; Takahiro Nakashima; Katsutaka Hashiba; Takeshi Yamamoto; Junichi Yamaguchi; Naoki Nakayama; Osamu Nomura; Tetsuya Matoba; Yoshio Tahara; Hiroshi Nonogi
Journal:  Circ Rep       Date:  2022-05-25

4.  Utility of prehospital electrocardiogram interpretation in ST-segment elevation myocardial infarction utilizing computer interpretation and transmission for interventional cardiologist consultation.

Authors:  Amir Faour; Callum Cherrett; Oliver Gibbs; Karen Lintern; Christian J Mussap; Rohan Rajaratnam; Dominic Y Leung; David A Taylor; Steve C Faddy; Sidney Lo; Craig P Juergens; John K French
Journal:  Catheter Cardiovasc Interv       Date:  2022-06-29       Impact factor: 2.585

5.  Reducing Delay to Treatment of ST-Elevation Myocardial Infarction With Software Electrocardiographic Interpretation and Transmission (SCINET).

Authors:  Justin M Cloutier; Christopher Hayes; John Ducas; David W Allen
Journal:  CJC Open       Date:  2020-02-15
  5 in total

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