Department of Cardiovascular, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Applicants with the same educational background for master's degree, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
J Clin Hypertens (Greenwich). 2024 Apr;26(4):363-373. doi: 10.1111/jch.14786. Epub 2024 Mar 2.
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.
左心室肥厚（LVH）是一种高血压性心脏病，可显著增加临床心血管事件的风险。其病因可能包含多种临床特征，如性别、年龄和肾功能。从机制角度来看，LVH 的重塑过程会引发某些生物标志物（特别是 sST2 和 NT-proBNP）的增加。这项多中心、回顾性研究旨在构建 LVH 风险评估模型并确定风险因素。共纳入 417 名原发性高血压（EH）患者，其中男性 214 例，女性 203 例，年龄 31-80 岁，其中 161 例（38.6%）被诊断为 LVH。基于 LVH 组和非 LVH 组之间存在显著差异的变量，构建了三个用于风险评估的多变量逐步逻辑回归模型：“临床特征”模型、“生物标志物”模型（基于各自的变量）和“临床特征+生物标志物”模型，该模型综合了两组变量。结果表明，“临床特征+生物标志物”模型在性能上优于基线模型（“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 值分别为.83、.75 和.74；P<.0001，均有统计学意义）。优化模型提示女性（OR：4.26，P<.001）、超重（OR：1.88，P=.02）或肥胖（OR：2.36，P=.02）、高血压病程（OR：1.04，P=.04）、高血压 3 级（OR：2.12，P<.001）和 sST2（对数转换，OR：1.14，P<.001）为风险因素，而 eGFR 为保护因素（OR：.98，P=.01）。这些发现表明，将临床特征和生物标志物相结合可以提高 LVH 风险评估的性能。
