Key result
ECG-based nomogram accurately identifies dilated cardiomyopathy with a validation AUC of ~0.88.
Why the study?
Dilated cardiomyopathy is a leading cause of heart failure, making screening and early diagnosis beneficial via inexpensive and easily available tools such as electrocardiography.
Does an ECG-based nomogram accurately screen for dilated cardiomyopathy?
Observational (n=234)
Does an ECG-based nomogram accurately screen for dilated cardiomyopathy?
Effect estimate: AUC 0.904 (training), 0.878 (validation)
An ECG-based nomogram incorporating specific wave amplitudes and PR interval provides a simple and accurate screening tool for identifying potential dilated cardiomyopathy patients.
May support ECG nomogram for DCM screening; leaves open prospective validation before adoption.
Dilated cardiomyopathy (DCM) is one of the most common causes of heart failure. Therefore, screening and early diagnosis of potential DCM patients is beneficial. Electrocardiogram (ECG) can be an inexpensive and easily available screening tool. We aimed to construct a simple screening model for DCM based on electrocardiogram. In this retrospective observational study, we consecutively enrolled 117 DCM patients between July 1, 2016 and July 1, 2021 as the DCM group, while 117 patients hospitalized in the same period with normal echocardiography and ECG were selected as the non-DCM group. Patients were randomly assigned to the training and validation sets at 8:2. ECG parameters of left ventricular related leads were exacted. Logistic regression was performed to evaluate screening indicators of ECG parameters and a nomogram was conducted. The screening ability of the model was evaluated using receiver operating characteristic analysis. Furthermore, the nomogram was assessed using calibration curve and decision curve analysis. Screening indicators included in the nomogram were the amplitude of S wave in V1 and V3 leads, the amplitude of R wave in aVF and V6 leads, and PR interval. The nomogram performed satisfactory discrimination in the training (area under the receiver operating characteristic curve = 0.904) and validation (area under the receiver operating characteristic curve = 0.878) sets and good calibration (Hosmer-Lemeshow P = .066). Decision curve analysis demonstrated the model can generate a net benefit of 0.33 when the threshold probability was 0.543. The nomogram based on electrocardiogram is a simple and practical screening tool for potential DCM patients.
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Wang et al. (2023) conducted an observational in Dilated cardiomyopathy (n=234). Electrocardiogram-based screening model (nomogram) vs. Non-DCM patients was evaluated on Screening ability (discrimination) evaluated using receiver operating characteristic analysis (AUC 0.904 (training), 0.878 (validation)). An electrocardiogram-based nomogram demonstrated satisfactory discrimination for identifying dilated cardiomyopathy, with an area under the curve of 0.904 in the training set and 0.878 in validation.
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