Department of Anesthesiology, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands.
Department of Intensive Care, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands.
JAMA. 2020 Mar 17;323(11):1052-1060. doi: 10.1001/jama.2020.0592.
Intraoperative hypotension is associated with increased morbidity and mortality. A machine learning-derived early warning system to predict hypotension shortly before it occurs has been developed and validated.
To test whether the clinical application of the early warning system in combination with a hemodynamic diagnostic guidance and treatment protocol reduces intraoperative hypotension.
DESIGN, SETTING, AND PARTICIPANTS: Preliminary unblinded randomized clinical trial performed in a tertiary center in Amsterdam, the Netherlands, among adult patients scheduled for elective noncardiac surgery under general anesthesia and an indication for continuous invasive blood pressure monitoring, who were enrolled between May 2018 and March 2019. Hypotension was defined as a mean arterial pressure (MAP) below 65 mm Hg for at least 1 minute.
Patients were randomly assigned to receive either the early warning system (n = 34) or standard care (n = 34), with a goal MAP of at least 65 mm Hg in both groups.
The primary outcome was time-weighted average of hypotension during surgery, with a unit of measure of millimeters of mercury. This was calculated as the depth of hypotension below a MAP of 65 mm Hg (in millimeters of mercury) × time spent below a MAP of 65 mm Hg (in minutes) divided by total duration of operation (in minutes).
Among 68 randomized patients, 60 (88%) completed the trial (median age, 64 [interquartile range {IQR}, 57-70] years; 26 [43%] women). The median length of surgery was 256 minutes (IQR, 213-430 minutes). The median time-weighted average of hypotension was 0.10 mm Hg (IQR, 0.01-0.43 mm Hg) in the intervention group vs 0.44 mm Hg (IQR, 0.23-0.72 mm Hg) in the control group, for a median difference of 0.38 mm Hg (95% CI, 0.14-0.43 mm Hg; P = .001). The median time of hypotension per patient was 8.0 minutes (IQR, 1.33-26.00 minutes) in the intervention group vs 32.7 minutes (IQR, 11.5-59.7 minutes) in the control group, for a median difference of 16.7 minutes (95% CI, 7.7-31.0 minutes; P < .001). In the intervention group, 0 serious adverse events resulting in death occurred vs 2 (7%) in the control group.
In this single-center preliminary study of patients undergoing elective noncardiac surgery, the use of a machine learning-derived early warning system compared with standard care resulted in less intraoperative hypotension. Further research with larger study populations in diverse settings is needed to understand the effect on additional patient outcomes and to fully assess safety and generalizability.
ClinicalTrials.gov Identifier: NCT03376347.
术中低血压与发病率和死亡率增加有关。已经开发和验证了一种基于机器学习的预警系统，用于在低血压发生前不久进行预测。
测试在术中低血压预警系统与血流动力学诊断指导和治疗方案联合应用的情况下，是否可以减少术中低血压的发生。
设计、地点和参与者：这是在荷兰阿姆斯特丹的一家三级中心进行的初步非盲随机临床试验，纳入了接受全身麻醉下择期非心脏手术且需要连续有创血压监测的成年患者，研究于 2018 年 5 月至 2019 年 3 月期间入组。低血压定义为平均动脉压（MAP）至少 1 分钟低于 65mmHg。
患者被随机分配接受预警系统（n=34）或标准护理（n=34），两组的目标 MAP 均至少为 65mmHg。
主要结局是手术期间的时间加权平均低血压，单位为毫米汞柱。这是通过将低于 65mmHg 的 MAP 深度（毫米汞柱）乘以低于 65mmHg 的 MAP 时间（分钟）除以手术总持续时间（分钟）计算得出。
在 68 名随机患者中，60 名（88%）完成了试验（中位年龄 64 [四分位距 {IQR} ，57-70] 岁；26 名 [43%] 女性）。手术中位时长为 256 分钟（IQR，213-430 分钟）。干预组的时间加权平均低血压为 0.10mmHg（IQR，0.01-0.43mmHg），对照组为 0.44mmHg（IQR，0.23-0.72mmHg），中位数差异为 0.38mmHg（95%CI，0.14-0.43mmHg；P=0.001）。干预组中每名患者的低血压时间中位数为 8.0 分钟（IQR，1.33-26.00 分钟），对照组为 32.7 分钟（IQR，11.5-59.7 分钟），中位数差异为 16.7 分钟（95%CI，7.7-31.0 分钟；P<0.001）。干预组无 1 例与死亡相关的严重不良事件，对照组有 2 例（7%）。
在这项对接受择期非心脏手术患者进行的单中心初步研究中，与标准护理相比，使用基于机器学习的预警系统可导致术中低血压的发生减少。需要在不同环境下的更大患者群体中进行进一步研究，以了解对其他患者结局的影响，并全面评估安全性和普遍性。
ClinicalTrials.gov 标识符：NCT03376347。
