Evidence map›Paper›PMID 37025093›Full record

ArticleClinical cardiology2023

ECG-based cardiodynamicsgram can reflect anomalous functional information in coronary artery disease.

Ying Wang, Jiaxin Sun, Kui Sun, Lin Li, XinXin Yu, Cong Wang, Hui Gu, Qinghua Sun, Ximing Wang

Abstract read
In one paragraph

Article in Clinical cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Ying WangDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Jiaxin SunCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, China.
Kui SunDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Lin LiDepartment of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
XinXin YuDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Cong WangCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, China.
Hui GuDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Qinghua SunCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, China.
Ximing WangDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, China.ORCID https://orcid.org/0000-0002-1213-1003

Funding

National Natural Science Foundation of China 8187354
6 · The paper itself

Abstract

backgroundThe cardiodynamicsgram (CDG), a novel noninvasive method, extracts dynamic ST-T segment information from an electrocardiogram (ECG) through deterministic learning. HYPOTHESIS: The CDG can reflect anomalous functional information in coronary artery disease (CAD).

methodsWe retrospectively enrolled 456 patients with suspected CAD who underwent coronary computed tomography angiography (CCTA) from January 2020 to 2022, followed immediately by standard 12-lead ECG acquisition. Positivity for CAD were defined as CCTA ≥ 50% or CT-derived fractional flow reserve (CT-FFR) ≤ 0.8. A CDG value <0 was considered negative; otherwise, it was considered positive. We also evaluated the diagnostic performance of the CDG in the ECG-diagnosis-negative subgroup and in patients who had undergone invasive coronary angiography (ICA) after CCTA.

resultsOf 362 patients, 168 (46.41%) were positive for CAD, and 178 (49.17%) were men. The median age was 59 (52-66) years. The accuracy of the CDG in the diagnosis of CAD was 79.56%, with a sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) of 75.60%, 82.99%, and 0.836 (95% CI: 0.794-0.878), respectively. Similarly, in the ECG-diagnosis-negative subgroup (n = 223), the accuracy of the CDG was 80.27%, with an AUC of 0.842 (95% CI: 0.790-0.895). Among the 11 patients with CAD confirmed by ICA, 10 were diagnosed positive by the CDG. Furthermore, the CDG values and CT-FFR were correlated (r = -.395; p < .001).

conclusionsThe ECG-based CDG has relatively high specificity and accuracy for the diagnosis of CAD and reflects functional cardiac information to some extent. It has the potential to be used as a screening tool for suspected CAD patients before CCTA.

Indexed as

Coronary Artery DiseaseCoronary StenosisFractional Flow Reserve, MyocardialComputed Tomography AngiographyCoronary AngiographyElectrocardiographyFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective Studiescardiodynamicsgramcomputed tomography-derived fractional flow reservecoronary artery diseasecoronary computed tomography angiographyelectrocardiogram

Identifiers

PMID37025093
PMCPMC10270272

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