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Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

ABSTRACT: Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A total of 417 patients with essential hypertension (EH), including 214 males and 203 females aged 31-80 years, were enrolled in this study; of these, 161 (38.6%) were diagnosed with LVH. Based on variables demonstrating significant disparities between the LVH and Non-LVH groups, three multivariate stepwise logistic regression models were constructed for risk assessment: the "Clinical characteristics" model, the "Biomarkers" model (each based on their respective variables), and the "Clinical characteristics + Biomarkers" model, which amalgamated both sets of variables. The results revealed that the "Clinical characteristics + Biomarkers" model surpassed the baseline models in performance (AUC values of the "Clinical characteristics + Biomarkers" model, the "Biomarkers" model, and the "Clinical characteristics" model were .83, .75, and .74, respectively; P < .0001 for both comparisons). The optimized model suggested that being female (OR: 4.26, P <.001), being overweight (OR: 1.88, p = .02) or obese (OR: 2.36, p = .02), duration of hypertension (OR: 1.04, P = .04), grade III hypertension (OR: 2.12, P < .001), and sST2 (log-transformed, OR: 1.14, P < .001) were risk factors, while eGFR acted as a protective factor (OR: .98, P = .01). These findings suggest that the integration of clinical characteristics and biomarkers can enhance the performance of LVH risk assessment.

SUBMITTER: Wang CC

PROVIDER: S-EPMC11007794 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Wang Chuang-Chang CC Liang Li-Keng LK Luo Sheng-Ming SM Wang Hui-Cheng HC Wang Xiao-Li XL Cheng Ya-Hui YH Pan Guang-Ming GM Peng Jiang-Yang JY Han Shu-Jie SJ Wang Xia X

Journal of clinical hypertension (Greenwich, Conn.) 20240302 4

Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A t ...[more]

PMID: 38430459

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Project description:AimLeft ventricular hypertrophy (LVH) is one of the most common types of target organ damage in hypertension. The red blood cell distribution width (RDW) is closely related to many cardiovascular diseases, including hypertension. The aim of this study was to analyze the relationship between the RDW level and LVH in pediatric essential hypertension.Materials and methodsA total of 429 untreated children and adolescents with essential hypertension were recruited and divided into an LVH group (n = 114) and non-LVH group (n = 315) according to left ventricular mass index (LVMI) and relative wall thickness (RWT) by color Doppler ultrasound. Spearman correlation analysis was used to determine the relationship between RDW and LVMI, RWT. The effect of RDW on LVH was determined using a multivariate logistic regression analysis. To assess the predictive value of RDW on LVH, the receiver operating characteristic (ROC) curve was used.ResultsThe level of RDW in children with hypertension in the LVH group was significantly higher than that in the non-LVH group (13.0 [12.0, 13.0] vs. 12.4 [12.0, 13.0] %, P = 0.001). The incidence of low and high quantiles of LVH was 21.0% and 32.0%, respectively. Spearman correlation analysis showed that RDW was positively correlated with C-reactive protein (CRP), LVMI, RWT, and red blood cell (RBC) count (P all < 0.05), and negatively correlated with hemoglobin (HGB) level, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) (P all < 0.05). After adjusting for various confounding factors, a multivariate logistic regression model revealed that RDW was an independent risk factor for LVH (OR = 1.946, 95% CI: 1.324-2.861, P = 0.001). The area under the ROC curve of RDW predicting centripetal hypertrophy was 0.700 (95% CI: 0.541-0.859, P < 0.05) in pediatric essential hypertension.ConclusionsIncreased RDW levels are an independent risk factor for LVH in pediatric essential hypertension, and RDW may be a predictor of LVH in untreated pediatric essential hypertension.

Dataset Information

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Publications

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Similar Datasets

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