Abstract
OBJECTIVE: To identify potential electrocardiographic predictors of peripartum cardiomyopathy (PPCM). METHODS: This was a case-control study carried out in three hospitals in Kano, Nigeria. Logistic regression models and a risk score were developed to determine electrocardiographic predictors of PPCM. RESULTS: A total of 54 PPCM and 77 controls were consecutively recruited after satisfying the inclusion criteria. After controlling for confounding variables, a rise in heart rate of one beat/minute increased the risk of PPCM by 6.4% (p = 0.001), while the presence of ST-T-wave changes increased the odds of PPCM 12.06-fold (p < 0.001). In the patients, QRS duration modestly correlated (r = 0.4; p < 0.003) with left ventricular dimensions and end-systolic volume index, and was responsible for 19.9% of the variability of the latter (R(2) = 0.199; p = 0.003). A risk score of ≥ 2, developed by scoring 1 for each of the three ECG disturbances (tachycardia, ST-T-wave abnormalities and QRS duration), had a sensitivity of 85.2%, specificity of 64.9%, negative predictive value of 86.2% and area under the curve of 83.8% (p < 0.0001) for potentially predicting PPCM. CONCLUSION: In postpartum women, using the risk score could help to streamline the diagnosis of PPCM with significant accuracy, prior to confirmatory investigations.