Development and validation of a nomogram-based model to predict primary hypertension within the next year in children and adolescents: retrospective cohort study (Preprint)

BACKGROUND Primary hypertension (PH) poses significant risks to children and adolescents. Few prediction models for the risk of PH in children and adolescents currently exist, posing a challenge for doctors in making informed clinical decisions. OBJECTIVE This study aimed to investigate the incidence and risk factors of PH in Chinese children and adolescents. It also aimed to establish and validate a nomogram-based model for predicting the next year PH risk. METHODS A retrospective cohort (N=3,938, between January 1, 2008 and December 31, 2020) and prospective (N=1,269, between January 1, 2021 and July 1, 2023) cohort were established for model training and validation. An independent cohort of 190 individuals was established for external validation of the model. The result of the least absolute shrinkage and selection operator (LASSO) regression technique was employed to select the optimal predictive features, and multivariate logistic regression to construct the nomogram. The performance of the nomogram underwent assessment and validation through the area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curves, decision curve analysis (DCA), clinical impact curves, and sensitivity analysis. RESULTS The PH risk factors that we have ultimately identified include gender, age, family history of hypertension, fasting blood glucose (FBG), low-density lipoprotein cholesterol (LDL-C), and uric acid (UA), while factor breastfeeding has been identified as a protective factor. Subsequently, a nomogram has been constructed incorporating these factors. AUCs of the nomogram were 0.892 in the training cohort, 0.808 in the validation cohort, and 0.849 in the external validation cohort. C-index of the nomogram were 0.892 in the training cohort, 0.808 in the validation cohort, and 0.849 in the external validation cohort. The nomogram has been proven to have good clinical benefits and stability in calibration curves, DCA, clinical impact curves, and sensitivity analysis. Finally, we observed noteworthy differences in UA levels and family history of hypertension among various subgroups, demonstrating a high correlation with PH. Moreover, the web-based calculator of the nomogram was built online. CONCLUSIONS We have developed and validated a stable and reliable nomogram that can accurately predict PH risk within the next year among children and adolescents in primary care and offer effective and cost-efficient support for clinical decision support for the risk prediction of PH.