Bae Tae-Wuk, Park Ji-Hyun, Park Jong-Won, Kwon Kee-Koo, Kim Kwang-Yong
Daegu-Gyeongbuk Research Center, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of Korea.
Division of Nephrology, Department of Internal Medicine, College of Medicine, Yeungnam University, Daegu 42415, Republic of Korea.
Diagnostics (Basel). 2024 Nov 26;14(23):2664. doi: 10.3390/diagnostics14232664.
To date, most intradialytic hypotension (IDH) studies have proposed technologies to comprehensively predict the occurrence of IDH using the patient's baseline information and ultrafiltration (UF) information, but it is difficult to apply the technologies while identifying the patient's condition in real time.
In this study, we propose an IDH indicator that uses heart rate (HR) change information to identify the patient's condition in real time and visually shows whether IDH has occurred. The data used were collected from 40 dialysis patients in a clinical trial conducted in the Artificial Kidney Unit at Yeungnam University Medical Center, Korea, from 18 July to 29 November 2023.
The IDH indicator infers changes in the patient's blood pressure during dialysis by analyzing the upper and lower maximum HRs based on the real-time average HR. Medical staff can respond to IDH in real time by looking at the IDH indicator, which visually expresses changes in the patient's HR. In addition, we propose a multilayer perceptron structure that inputs upper and lower maximum HR information based on the average HR for the time interval accumulated in real time. In learning using 40 min of data up to 5 min before IDH occurred, models using two and five layers showed excellent performance, with accuracy of 88.6% and 85.2%, respectively.
By combining IDH visual indicators and the multi-layer perceptron method, medical staff can effectively respond to IDH in real time.
迄今为止,大多数透析中低血压(IDH)研究都提出了利用患者基线信息和超滤(UF)信息来全面预测IDH发生的技术,但在实时识别患者病情时难以应用这些技术。
在本研究中,我们提出了一种IDH指标,该指标利用心率(HR)变化信息实时识别患者病情,并直观显示IDH是否发生。所使用的数据是从2023年7月18日至11月29日在韩国庆南大学医学中心人工肾科进行的一项临床试验中的40名透析患者收集的。
IDH指标通过基于实时平均心率分析最高和最低心率来推断透析期间患者血压的变化。医护人员可以通过查看直观表达患者心率变化的IDH指标来实时应对IDH。此外,我们提出了一种多层感知器结构,该结构基于实时累积的时间间隔的平均心率输入最高和最低心率信息。在使用IDH发生前5分钟内长达40分钟的数据进行学习时,使用两层和五层的模型表现出色,准确率分别为88.6%和85.2%。
通过结合IDH视觉指标和多层感知器方法,医护人员可以有效地实时应对IDH。