ArticleEuropean journal of pediatrics2026
A multivariate electrocardiographic predictive model for left ventricular hypertrophy in children with primary hypertension.
Article in European journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Current electrocardiographic (ECG) criteria are of low diagnostic value compared with echocardiography (ECHO) for LVH, establishing a more effective ECG predictive model is required. The research purpose was to establish and validate a model to improve the diagnostic capability of ECG for LVH in pediatric primary hypertension. A retrospective study of 502 hypertensive children were recruited in the study between January 2019 and December 2024. The cohort were randomly divided into training (n = 402) and test sets (n = 100) with a proportion of 8:2. LVH was diagnosed using ECHO criteria. A total of 22 ECG parameters were evaluated. A predictive nomogram was developed using least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. LVH was identified in 117 (29.1%) of the training set and 29 (29.0%) of the test set. Body mass index (BMI), R
conclusionsThe nomogram model incorporating BMI, R WHAT IS KNOWN: • We established a pediatric-specific nomogram integrating BMI and two composite ECG indices (R WHAT IS NEW: • Our current study developed a nomogram model combining BMI, RI + SV4, and SD + SV4 that significantly improves ECG diagnostic accuracy for LVH in children with primary hypertension. • The research innovatively transforms BMI into a corrective factor addressing voltage attenuation caused by chest wall fat in obese children. • The model identifies pediatric-specific composite ECG indices superior to adult-derived criteria, demonstrating good discrimination, calibration, and clinical utility.
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