Prehospital Acute ST-Elevation Myocardial Infarction Identification in San Diego: A Retrospective Analysis of the Effect of a New Software Algorithm

Coffey, Christanne; Serra, John; Goebel, Mat; Espinoza, Sarah; Castillo, Edward M.; Dunford, James

doi:10.1016/j.jemermed.2018.04.007

Cited by 7 publications

(4 citation statements)

References 44 publications

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“…[12][13][14][15][16][17][18] For cases that failed any criterion (intermediate probability), the most frequent reasons to fail meeting criteria were baseline wander and artifact, both of which have been implicated as common causes for prehospital false-positive computer interpretation of STEMI. 14,17,19,29 While there are many challenges to acquiring high-quality ECGs in the prehospital setting, it is likely that additional training on ECG acquisition skills could improve data quality. Repeating the ECG may also have a role, as previous literature has shown that repeat prehospital ECGs increase the identification of STEMI.…”

Section: Discussionmentioning

confidence: 99%

A Novel Algorithm for Improving the Diagnostic Accuracy of Prehospital ST-Elevation Myocardial Infarction

Goebel

Vaida

Kahn

et al. 2019

Prehosp. Disaster med.

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Introduction:ST-segment elevation myocardial infarction (STEMI) is a time-sensitive entity that has been shown to benefit from prehospital diagnosis by electrocardiogram (ECG). Current computer algorithms with binary decision making are not accurate enough to be relied on for cardiac catheterization lab (CCL) activation.Hypothesis:An algorithmic approach is proposed to stratify binary STEMI computerized ECG interpretations into low, intermediate, and high STEMI probability tiers.Methods:Based on previous literature, a four-criteria algorithm was developed to rule out/in common causes of prehospital STEMI false-positive computer interpretations: heart rate, QRS width, ST elevation criteria, and artifact. Prehospital STEMI cases were prospectively collected at a single academic center in Salt Lake City, Utah (USA) from May 2012 through October 2013. The prehospital ECGs were applied to the algorithm and compared against activation of the CCL by an emergency department (ED) physician as the outcome of interest. In addition to calculating test characteristics, linear regression was used to look for an association between number of criteria used and accuracy, and logistic regression was used to test if any single criterion performed better than another.Results:There were 63 ECGs available for review, 39 high probability and 24 intermediate probability. The high probability STEMI tier had excellent test characteristics for ruling in STEMI when all four criteria were used, specificity 1.00 (95% CI, 0.59-1.00), positive predictive value 1.00 (0.91-1.00). Linear regression showed a strong correlation demonstrating that false-positives increased as fewer criteria were used (adjusted r-square 0.51; P <.01). Logistic regression showed no significant predictive value for any one criterion over another (P = .80). Limiting physician overread to the intermediate tier only would reduce the number of ECGs requiring physician overread by a factor of 0.62 (95% CI, 0.48-0.75; P <.01).Conclusion:Prehospital STEMI ECGs can be accurately stratified to high, intermediate, and low probabilities for STEMI using the four criteria. While additional study is required, using this tiered algorithmic approach in prehospital ECGs could lead to changes in CCL activation and decreased requirements for physician overread. This may have significant clinical and quality implications.

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Section: Discussionmentioning

confidence: 99%

A Novel Algorithm for Improving the Diagnostic Accuracy of Prehospital ST-Elevation Myocardial Infarction

Goebel

Vaida

Kahn

et al. 2019

Prehosp. Disaster med.

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“…The most frequent criteria not met were heart rate and QRS duration, both of which have been implicated as common causes for prehospital false-positive software interpretation of STEMI. 22,25,30,32 Artifact was also a frequent cause of failure, although agreement on which ECGs contained artifact was poor. While the raters were shown examples of high- and low-quality ECGs during their standardized training, there may be a need for more objective criteria of poor ECG quality.…”

Section: Discussionmentioning

confidence: 99%

“…For this analysis, the authors sought to validate a set of criteria derived from the literature and previously applied to a small dataset, designed to exclude false-positive software interpretations of STEMI (Table 1). 22,25,30,32 Criteria suggesting a true positive were: free of artifact or baseline wander, ≥ one millimeters (mm) of ST-segment elevation in ≥ two contiguous leads, heart rate < 130 beats per minute, and QRS duration < 100 milliseconds. 23,27,30,33,34 A case was considered true positive if it met all four criteria.…”

Section: Outcome Measuresmentioning

confidence: 99%

A Novel Algorithm for Improving the Prehospital Diagnostic Accuracy of ST-Segment Elevation Myocardial Infarction

Goebel,

Westafer,

Ayala

et al. 2023

Prehosp. Disaster med.

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Introduction: Early detection of ST-segment elevation myocardial infarction (STEMI) on the prehospital electrocardiogram (ECG) improves patient outcomes. Current software algorithms optimize sensitivity but have a high false-positive rate. The authors propose an algorithm to improve the specificity of STEMI diagnosis in the prehospital setting. Methods: A dataset of prehospital ECGs with verified outcomes was used to validate an algorithm to identify true and false-positive software interpretations of STEMI. Four criteria implicated in prior research to differentiate STEMI true positives were applied: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. The test characteristics were calculated and regression analysis was used to examine the association between the number of criteria included and test characteristics. Results: There were 44,611 cases available. Of these, 1,193 were identified as STEMI by the software interpretation. Applying all four criteria had the highest positive likelihood ratio of 353 (95% CI, 201-595) and specificity of 99.96% (95% CI, 99.93-99.98), but the lowest sensitivity (14%; 95% CI, 11-17) and worst negative likelihood ratio (0.86; 95% CI, 0.84-0.89). There was a strong correlation between increased positive likelihood ratio (r2 = 0.90) and specificity (r2 = 0.85) with increasing number of criteria. Conclusions: Prehospital ECGs with a high probability of true STEMI can be accurately identified using these four criteria: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. Applying these criteria to prehospital ECGs with software interpretations of STEMI could decrease false-positive field activations, while also reducing the need to rely on transmission for physician over-read. This can have significant clinical and quality implications for Emergency Medical Services (EMS) systems.

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“…21 Presently, software algorithm ECG diagnosis of STEMI is generally used as an adjunct to physician or trained emergency medical personnel ECG interpretation in triaging patients with suspected acute coronary syndromes. 22,23 Some healthcare systems have assessed the performance of "physician-less" systems of prehospital STEMI diagnosis and CCL activation using software algorithms. 24,25 One such system described by Potter et al 25 involved the use of Zoll software (Zoll E series monitor-defibrillator; Zoll Medical Corporation, Chelmsford, MA).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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Background: Prehospital diagnosis of ST-elevation myocardial infarction (STEMI) has resulted in improved outcomes. However, many patients still walk in to the emergency department (ED) with STEMI, experiencing delays and worse outcomes. Software electrocardiogram (ECG) diagnosis of STEMI and electronic transmission to a cardiologist may result in improved door-to-device (D2D) times. Methods: We retrospectively identified all patients presenting with STEMI from January 2015 to September 2016. Components of delay in D2D, ED variables, and the patients' ECGs were extracted from our regional database. All ECGs performed for suspected myocardial infarction in the region were extracted over the study period. We assessed the accuracy of the software 12SL in diagnosing STEMI, ED

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Prehospital Acute ST-Elevation Myocardial Infarction Identification in San Diego: A Retrospective Analysis of the Effect of a New Software Algorithm

Cited by 7 publications

References 44 publications

A Novel Algorithm for Improving the Diagnostic Accuracy of Prehospital ST-Elevation Myocardial Infarction

A Novel Algorithm for Improving the Diagnostic Accuracy of Prehospital ST-Elevation Myocardial Infarction

A Novel Algorithm for Improving the Prehospital Diagnostic Accuracy of ST-Segment Elevation Myocardial Infarction

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

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