Postoperative critical care management of congenital heart disease patients requires prompt intervention when the patient deviates significantly from clinician‐determined vital sign and hemodynamic goals. Current monitoring systems only allow for static thresholds to be set on individual variables, despite the expectations that these signals change as the patient recovers and that variables interact. To address this incongruency, we have employed statistical process monitoring (SPM) techniques originally developed to monitor batch industrial processes to monitor high‐frequency vital sign and hemodynamic data to establish multivariate trajectory maps for patients with d‐transposition of the great arteries following the arterial switch operation. In addition to providing multivariate trajectory maps, the multivariate control charts produced by the SPM framework allow for assessment of adherence to the desired trajectory at each time point as the data is collected. Control charts based on slow feature analysis were compared with those based on principal component analysis. Alarms generated by the multivariate control charts are discussed in the context of the available clinical documentation.

中文翻译：

---

统计过程监测创建小儿心脏手术后的血流动力学轨迹图：动脉调转手术的案例研究


当先天性心脏病患者的生命体征和血流动力学目标明显偏离时，先天性心脏病患者的术后重症监护管理需要立即干预。当前的监测系统仅允许对各个变量设置静态阈值，尽管预期这些信号会随着患者的康复而变化并且变量会相互作用。为了解决这种不一致问题，我们采用了最初开发用于监测批量工业流程的统计过程监测（SPM）技术，以监测高频生命体征和血流动力学数据，从而为动脉跟随的大动脉 d 转位患者建立多元轨迹图。开关操作。除了提供多元轨迹图之外，SPM 框架生成的多元控制图还可以在收集数据时评估每个时间点对所需轨迹的遵守情况。将基于慢速特征分析的控制图与基于主成分分析的控制图进行了比较。由多变量控制图生成的警报在可用的临床文档的背景下进行讨论。