Determining the clinical significance of computer interpreted electrocardiography conclusions

Daniel J Kersten; Kyla D'Angelo; Juana Vargas; Gagan Verma; Uzma Malik; Schlomo Shavolian; Roman Zeltser; Ofek Hai; Amgad N Makaryus

Determining the clinical significance of computer interpreted electrocardiography conclusions

Am J Cardiovasc Dis. 2021 Jun 15;11(3):375-381. eCollection 2021.

Authors

Daniel J Kersten^{1

2}, Kyla D'Angelo¹, Juana Vargas^{1

3}, Gagan Verma², Uzma Malik⁴, Schlomo Shavolian¹, Roman Zeltser^{1

3}, Ofek Hai¹, Amgad N Makaryus^{1

3}

Affiliations

¹ Department of Cardiology, Nassau University Medical Center East Meadow, NY, USA.
² New York Institute of Technology College of Osteopathic Medicine Old Westbury, NY, USA.
³ Donald and Barbara Zucker School of Medicine at Hofstra/Northwell Hempstead, NY, USA.
⁴ Department of Medicine, Nassau University Medical Center East Meadow, NY, USA.

PMID: 34322307
PMCID: PMC8303043

Abstract

Background: Computerized electrocardiogram (EKG) interpretation technology was developed in the mid-20th century, but its use continues to be controversial. This study aims to determine clinical factors which indicate greater odds of clinical significance of an abnormal computerized EKG interpretation.

Methods: The inclusion criteria for this retrospective study were patients who underwent outpatient echocardiography for the indication of an abnormal EKG and had an EKG abnormality diagnosed by the computerized EKG system. Qualifying patients had the results of their computerized EKG, echocardiogram, and charted patient characteristics collected. Computerized diagnoses and patient characteristics were assessed to determine if they were associated with increasing or decreasing the odds of an echocardiographic abnormality via logistic regression. Chi-square and t-test analyses were used for categorical and continuous variables, respectively. Odds ratios are presented as odds ratio [95% confidence interval]. A P-value of ≤ 0.05 was considered statistically significant.

Results: A total of 515 patients were included in this study. The population was 59% women with an average age of 57 ± 16 years, and a mean BMI of 30.1 ± 7.3 kg/m². Patients with echocardiographic abnormalities tended to have more cardiac risk factors than patients without abnormalities. In our final odds ratio model consisting of both patient characteristics and EKG diagnoses, age, coronary disease (CAD), and diabetes mellitus (DM) increased the odds of an echocardiographic abnormality (1.04 [1.02-1.06], 2.68 [1.41-5.09], and 1.75 [1.01-3.04], respectively). That model noted low QRS voltage decreased the odds of an abnormal echocardiogram (0.31 [0.10-0.91]).

Conclusion: Our findings suggest that in patients with an abnormal computerized EKG reading, the specific factors of older age, CAD, and DM are associated with higher odds of abnormalities on follow-up echocardiography. These results, plus practitioner overreading, can be used to determine more appropriate management when faced with an abnormal computerized EKG diagnosis.

Keywords: Electrocardiography; clinical management; computerized electrocardiographic interpretation; echocardiography.