Blood pressure (BP) variability is one of the important risk factors of cardiovascular disease (CVD). "Surge BP," which represents short-term BP variability, is defined as pathological exaggerated BP increase capable of triggering cardiovascular events. Surge BP is effectively evaluated by our new BP monitoring device. To the best of our knowledge, we are the first to develop an algorithm for the automatic detection of surge BP from continuous "beat-by-beat" (BbB) BP measurements. It enables clinicians to save significant time identifying surge BP in big data from their patients' continuous BbB BP measurements. A total of 94 subjects (74 males and 20 females) participated in our study to develop the surge BP detection algorithm, resulting in a total of 3272 surges collected from the study subjects. The surge BP detection algorithm is a simple classification model based on supervised learning which formulates shape of surge BP as detection rules. Surge BP identified with our algorithm was evaluated against surge BP manually labeled by experts with 5-fold cross validation. The recall and precision of the algorithm were 0.90 and 0.64, respectively. Processing time on each subject was 11.0 ± 4.7 s. Our algorithm is adequate for use in clinical practice and will be helpful in efforts to better understand this unique aspect of the onset of CVD. Graphical abstract Surge blood pressure (surge BP) which is defined as pathological short-term (several tens of seconds) exaggerated BP increase capable of triggering cardiovascular events. We have already developed a wearable continuous beat-by-beat (bBb) BP monitoring device and observed surge BPs successfully in obstructive sleep apnea patients. In this, we developed an algorithm for the automatic detection of surge BP from continuous BbB BP measurements to save significant time identifying surge BP among > 30,000 BbB BP measurements. Our result shows this algorithm can correctly detect surge BPs with a recall of over 0.9.

中文翻译：

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用于确定“喘振血压”标准的自动检测算法。

血压（BP）的变异性是心血管疾病（CVD）的重要危险因素之一。代表短期BP变异性的“喘振BP”定义为能够触发心血管事件的病理性BP夸大。我们的新型BP监测设备可有效评估Surge BP。据我们所知，我们是第一个开发用于从连续“逐个拍”（BbB）BP测量中自动检测喘振BP的算法的公司。它使临床医生可以节省大量时间，从患者的连续BbB BP测量中识别大数据中的喘振BP。共有94位受试者（74位男性和20位女性）参加了我们的研究，以开发喘振BP检测算法，从而从研究受试者中总共采集了3272次激增。喘振BP检测算法是一种基于监督学习的简单分类模型，将喘振BP的形状作为检测规则。我们的算法确定的Surge BP是针对专家手动标记的带有5倍交叉验证的Surge BP进行评估的。该算法的召回率和精度分别为0.90和0.64。每个对象的处理时间为11.0±4.7 s。我们的算法足以用于临床实践，并且将有助于更好地了解CVD发作的这一独特方面。图形摘要激增血压（surge BP）定义为病理性短期（数十秒）夸大的BP升高，能够触发心血管事件。我们已经开发出了一种可穿戴的连续心跳（bBb）血压监测设备，并成功地在阻塞性睡眠呼吸暂停患者中观察到了喘振BP。在此，我们开发了一种算法，可从连续的BbB BP测量中自动检测喘振BP，以节省大量时间来识别> 30,000 BbB BP测量中的喘振BP。我们的结果表明，该算法可以正确检测喘振BP，召回率超过0.9。