OBJECTIVE: We aimed to establish and validate a user-friendly and clinically practical nomogram for estimating the probability of echocardiographic left ventricular hypertrophy (echo-LVH) indexed to BSA among hypertensive patients from northern China. METHODS: A total of 4954 hypertensive patients were recruited from a population-based cohort study from January 2012 to August 2013. The dataset was randomly split into two sets: training (n = 3303) and validation (n = 1651). Three nomograms were initially constructed. That is the Cornell product nomogram, the non-ECG nomogram, and the integrated nomogram which integrated non-ECG risk factors and Cornell-voltage duration product. The least absolute shrinkage and selection operator strategies were employed to screen for non-ECG features. The performance of the nomograms was evaluated using discrimination, calibration, and decision curve analysis (DCA). The net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were also calculated. RESULTS: The AUCs, NRIs, IDIs, and DCA curves of the nomograms demonstrated that the integrated nomogram performed best among all three nomograms. The integrated nomogram incorporated age, sex, educational level, hypertension duration, SBP, DBP, eGFR, sleep duration, tea consumption, and the Cornell-voltage duration product. The AUC was 0.758 and had a good calibration (Hosmer-Lemeshow test, P = 0.73). Internal validation showed an acceptable AUC of 0.735 and good calibration was preserved (Hosmer-Lemeshow test, P = 0.19). The integrated nomogram was clinically beneficial across a range of thresholds of 10-50%. CONCLUSION: The integrated nomogram is a convenient and reliable tool that enables early identification of hypertensive patients at high odds of LVH and can assist clinicians in their decision-making.
OBJECTIVE: We aimed to establish and validate a user-friendly and clinically practical nomogram for estimating the probability of echocardiographic left ventricular hypertrophy (echo-LVH) indexed to BSA among hypertensive patients from northern China. METHODS: A total of 4954 hypertensive patients were recruited from a population-based cohort study from January 2012 to August 2013. The dataset was randomly split into two sets: training (n = 3303) and validation (n = 1651). Three nomograms were initially constructed. That is the Cornell product nomogram, the non-ECG nomogram, and the integrated nomogram which integrated non-ECG risk factors and Cornell-voltage duration product. The least absolute shrinkage and selection operator strategies were employed to screen for non-ECG features. The performance of the nomograms was evaluated using discrimination, calibration, and decision curve analysis (DCA). The net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were also calculated. RESULTS: The AUCs, NRIs, IDIs, and DCA curves of the nomograms demonstrated that the integrated nomogram performed best among all three nomograms. The integrated nomogram incorporated age, sex, educational level, hypertension duration, SBP, DBP, eGFR, sleep duration, tea consumption, and the Cornell-voltage duration product. The AUC was 0.758 and had a good calibration (Hosmer-Lemeshow test, P = 0.73). Internal validation showed an acceptable AUC of 0.735 and good calibration was preserved (Hosmer-Lemeshow test, P = 0.19). The integrated nomogram was clinically beneficial across a range of thresholds of 10-50%. CONCLUSION: The integrated nomogram is a convenient and reliable tool that enables early identification of hypertensive patients at high odds of LVH and can assist clinicians in their decision-making.