Objective  To establish and validate a model for predicting left ventricular hypertrophy (LVH) in patients with essential hypertension.

Methods  332 patients with essential hypertension who were hospitalized in the Department of Cardiovascular Medicine of The Central Hospital of Wuhan from January to December 2022 were selected as the study subjects, and they were divided into the training set and validation set by K-fold cross-validation. In the training set, independent influencing factors on LVH in patients with essential hypertension were analysed using LASSO regression, univariate and multivariate Logistic regression models, and then these factors were integrated into the prediction model. The discrimination, calibration and applicability of the prediction model were judged by the receiver operating characteristic curve, Hosmer-Lemeshow, calibration curve and decision curve in the training set and validation set. The Nomogram was drawn to visualize the results of the prediction model.

Results  Systolic blood pressure [OR=1.03, 95%CI (1.01, 1.05), P<0.001] was the independent risk factor of LVH in patients with essential hypertension. Resting heart rate [OR=0.96, 95%CI (0.93, 0.98), P=0.002], serum albumin [OR=0.90, 95%CI (0.81, 0.99), P=0.032], and platelet distribution width [OR=0.36, 95%CI (0.14, 0.96), P=0.042] were protective factors of LVH in patients with essential hypertension. The prediction model had good differentiation, calibration and applicability in the training and validation sets.

Conclusion A prediction model for LVH in patients with essential hypertension was established and validated, which provided an intuitive and easy tool for the risk prediction of LVH.

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