Anderson Cody P, Layec Gwenael, Park Song-Young
School of Health and Kinesiology, University of Nebraska at Omaha, Omaha, Nebraska, United States.
Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, Nebraska, United States.
Am J Physiol Heart Circ Physiol. 2025 Oct 1;329(4):H873-H879. doi: 10.1152/ajpheart.00513.2025. Epub 2025 Sep 5.
The purpose of this study was to test the initial feasibility of an acute hypertension detection platform (AHDP) for wearable devices that may be useful for the rapid detection of malignant hypertensive crises. The overall hypothesis was that the AHDP could detect laboratory-simulated elevations in blood pressure (BP). 42 healthy young participants (21.3 ± 2.1 yr, 16 males and 26 females) rested and then performed isometric handgrip exercise with blood flow restriction to elevate BP. Electrocardiogram (ECG), BP, and photoplethysmography (PPG) were assessed continuously. Pulse arrival time (PAT) was calculated with ECG and PPG using a proprietary algorithm and was standardized to -scores. The PAT -scores were used to classify normotensive and elevated BPs with logistic regression, and the optimal PAT -score that classified BP was calculated. Elevated BPs were those that exceeded the baseline central tendency by +3 SD. The precision-recall area under the curve (PR-AUC) was used to quantify model performance. K-fold cross-validation was used to assess performance variability. Compared with baseline, BP increased during exercise (Δ18.8 ± 15.1 mmHg, < 0.001) and PAT decreased (Δ-5.6 ± 5.7 ms, < 0.001). The PR-AUC of the model was 0.68 with 95% confidence intervals (95% CIs) of 0.53 to 0.81, which was greater than random chance ( < 0.001). No sex differences were observed in performance ( = 0.075). The optimal PAT -score threshold was -3.87 with 95% CIs of -5.04 to -2.15. The data support that the AHDP successfully detected laboratory-simulated elevated BP. The further development of the AHDP is expected to lead to effective hypertensive crisis detection systems for wearable devices. The initial feasibility of an acute malignant hypertension detection platform using pulse arrival time and machine learning was assessed for cuffless blood pressure devices. The acute hypertension detection platform was sensitive to relatively small laboratory-simulated elevations in blood pressure and was generalizable among individuals with no sex differences in performance. The novel acute hypertension detection platform may be useful for detecting malignant hypertensive crises in wearable devices such as smartwatches.
本研究的目的是测试一种用于可穿戴设备的急性高血压检测平台（AHDP）的初步可行性，该平台可能有助于快速检测恶性高血压危象。总体假设是AHDP能够检测出实验室模拟的血压（BP）升高。42名健康年轻参与者（21.3±2.1岁，16名男性和26名女性）先休息，然后进行带血流限制的等长握力运动以升高血压。连续评估心电图（ECG）、血压和光电容积脉搏波描记法（PPG）。使用专有算法通过ECG和PPG计算脉搏到达时间（PAT），并将其标准化为z分数。PAT的z分数用于通过逻辑回归对正常血压和血压升高进行分类，并计算出对血压进行分类的最佳PAT z分数。血压升高是指超过基线中心趋势+3个标准差的值。曲线下精确召回面积（PR-AUC）用于量化模型性能。采用K折交叉验证来评估性能变异性。与基线相比，运动期间血压升高（Δ18.8±15.1 mmHg，P<0.001），PAT降低（Δ-5.6±5.7 ms，P<0.001）。该模型的PR-AUC为0.68，95%置信区间（95%CI）为0.53至0.81，大于随机概率（P<0.001）。在性能方面未观察到性别差异（P=0.075）。最佳PAT z分数阈值为-3.87，95%CI为-5.04至-2.15。这些数据支持AHDP成功检测出实验室模拟的血压升高。预计AHDP的进一步开发将带来适用于可穿戴设备的有效高血压危象检测系统。评估了一种使用脉搏到达时间和机器学习的急性恶性高血压检测平台对无袖带血压设备的初步可行性。该急性高血压检测平台对相对较小的实验室模拟血压升高敏感，且在性能上不存在性别差异，具有普遍适用性。这种新型急性高血压检测平台可能有助于在智能手表等可穿戴设备中检测恶性高血压危象。
