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.

中文翻译：

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基于列线图的原发性高血压患者左心室肥厚风险评估模型：结合临床特征和生物标志物

左心室肥厚（LVH）是一种高血压性心脏病，会显着增加临床心血管事件的风险。其病因可能涉及各种临床特征，例如性别、年龄和肾功能。从机制角度来看，LVH 的重塑过程可以触发某些生物标志物的增加，特别是 sST2 和 NT-proBNP。这项多中心、回顾性研究旨在构建 LVH 风险评估模型并识别风险因素。共有417例原发性高血压（EH）患者入组，其中男性214例，女性203例，年龄31~80岁；其中，161 例 (38.6%) 被诊断患有 LVH。基于显示 LVH 组和非 LVH 组之间显着差异的变量，构建了三个多元逐步逻辑回归模型进行风险评估：“临床特征”模型、“生物标志物”模型（每个模型均基于各自的变量）和“临床特征+生物标志物”模型，合并了两组变量。结果显示，“临床特征+生物标志物”模型的性能优于基线模型（“临床特征+生物标志物”模型、“生物标志物”模型和“临床特征”模型的AUC值为0.83、0.75） 、 和 .74，分别；两个比较P  < .0001）。优化模型表明，女性（OR：4.26，P  <.001）、超重（OR：1.88，p  = .02）或肥胖（OR：2.36，p  = .02）、高血压持续时间（OR：1.04） ，P  = .04）、III 级高血压（OR：2.12，P  < .001）和 sST2（对数转换，OR：1.14，P  < .001）是危险因素，而 eGFR 充当保护因素（OR ：.98，P  = .01）。这些发现表明，临床特征和生物标志物的整合可以提高 LVH 风险评估的表现。