Minetto J, Espeche W, Leiva Sisnieguez C E, Cerri G, Perez Duhalde J I, Olano D, Salazar M R
Cardiometabolic Diseases Unit, San Martin Hospital, La Plata, Argentina.
School of Medicine, National University of La Plata, La Plata, Argentina.
J Hum Hypertens. 2025 Mar;39(3):199-204. doi: 10.1038/s41371-024-00980-9. Epub 2024 Nov 27.
The conventional assessment of the relationship between arterial hypertension (AH) and cardiovascular damage has predominantly relied on office measurements. However, the diagnostic significance of ambulatory and home measurements has gained prominence, particularly in identifying distinct AH phenotypes like masked hypertension (MH), characterized by normal office values but elevated readings outside the clinical setting, carrying comparable risks to sustained AH. Current guidelines advocate for Ambulatory Blood Pressure Monitoring (ABPM) in individuals with office values exceeding 130/85 mmHg. This study aims to develop a clinical prediction model to identify masked hypertension in individuals with normal office blood pressure and to create a clinical score.A cross-sectional study was conducted in a secondary level hospital, including patients aged 18-85 years with average office blood pressure <140/90 mmHg who underwent a valid ABPM on the same day. Pregnant and postpartum women were excluded. A multivariable logistic regression model with calibration, discrimination, and stability parameters was applied to predict masked hypertension. 506 individuals with valid ABPM were analysed. The prevalence of masked hypertension was 30.8%. The selected variables were: diastolic blood pressure, pulse pressure, waist diameter and sex. The model calibrated adequately (Hosmer-Lemeshow test p = 0.35), with an AUC of 0.72 (95% CI, 0.67-0.77). Significant differences existed between the traditional and the new models (p < 0.001). A user-friendly clinical model was developed, with a clinical score achieving 90% specificity using an estimated probability of 0.4 with a 10-point score.A novel model, performed with easily collectable clinical variables, showed robust calibration, stability, and discrimination. It outperforms sole reliance on office blood pressure, exhibiting high specificity (~90%) for masked hypertension detection. Its internal validity suggests a potential for enhanced masked hypertension identification.
对动脉高血压（AH）与心血管损害之间关系的传统评估主要依赖于诊室测量。然而，动态血压和家庭血压测量的诊断意义日益凸显，尤其是在识别不同的AH表型方面，如隐匿性高血压（MH），其特点是诊室血压值正常，但在临床环境之外的测量值升高，与持续性AH具有相当的风险。当前指南提倡对诊室血压值超过130/85 mmHg的个体进行动态血压监测（ABPM）。本研究旨在开发一种临床预测模型，以识别诊室血压正常个体中的隐匿性高血压，并创建一个临床评分。在一家二级医院进行了一项横断面研究，纳入年龄在18 - 85岁、诊室平均血压<140/90 mmHg且在同一天接受有效ABPM的患者。排除孕妇和产后妇女。应用具有校准、鉴别和稳定性参数的多变量逻辑回归模型来预测隐匿性高血压。对506名具有有效ABPM的个体进行了分析。隐匿性高血压的患病率为30.8%。所选变量为：舒张压、脉压、腰围和性别。该模型校准良好（Hosmer-Lemeshow检验p = 0.35），曲线下面积（AUC）为0.72（95%置信区间，0.67 - 0.77）。传统模型与新模型之间存在显著差异（p < 0.001）。开发了一种用户友好的临床模型，通过10分制评分，使用估计概率0.4时临床评分的特异性达到90%。一个采用易于收集的临床变量构建的新型模型显示出强大的校准、稳定性和鉴别能力。它优于单纯依靠诊室血压，对隐匿性高血压检测具有高特异性（约90%）。其内部有效性表明在增强隐匿性高血压识别方面具有潜力。
