What Faces Reveal: A Novel Method to Identify Patients at Risk of Deterioration Using Facial Expressions.
What Faces Reveal: A Novel Method to Identify Patients at Risk of Deterioration Using Facial Expressions.
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面部表情揭示：一种利用面部表情识别病情恶化风险患者的新方法。
DOI：
10.1097/ccm.0000000000003128
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发表时间：
2018
影响因子：
8.8
通讯作者：
Madrigal-Garcia MI
中科院分区：
文献类型：
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作者：
Madrigal-Garcia MI
目的：识别医院病房中有恶化风险的患者的面部表情。设计：前瞻性观察可行性研究。设置：英国伦敦社区医院的普通病房患者。患者：34名有临床恶化风险的患者。干预：5分钟的视频（25帧/秒; 7，500张图像）被记录、加密，随后由一位训练有素的面部动作编码系统心理学家对结果不知情地分析动作单元。测量和主要结果：结合国家预警评分中收集的临床指标，对上面部、头部位置、眼睛位置、嘴唇和下颌位置以及下面部的动作单元进行分析。最常检测到的动作单元是上面部动作单元43（73%）、头部位置动作单元51（11.7%）、眼睛位置动作单元62（5.8%）、嘴唇和下颌动作单元25（44.1%）和下面部动作单元15（67.6%）。在需要进入重症监护室的患者中，某些组合面部显示的存在增加，即动作单元43+ 15+ 25（面部显示1，p< 0.013），动作单元43+ 15+ 51/52（面部显示2，p< 0.003）和动作单元43+ 15+ 51+ 25（面部显示3，p< 0.002）。具有面部显示器1、面部显示器2和面部显示器3分别增加了8倍、18倍和确定事件的重症监护风险。以面部显示1、面部显示2、面部显示3和国家早期预警评分作为独立协变量的logistic回归模型描述了重症监护病房的入院情况，平均一致性统计量（C指数）为0.71（p= 0.009）。结论：在恶化的普通病房患者中可以识别模式化面部表情。该工具可能会增加当前评分系统的风险预测。
Objectives:To identify facial expressions occurring in patients at risk of deterioration in hospital wards.Design:Prospective observational feasibility study.Setting:General ward patients in a London Community Hospital, United Kingdom.Patients:Thirty-four patients at risk of clinical deterioration.Interventions:A 5-minute video (25 frames/s; 7,500 images) was recorded, encrypted, and subsequently analyzed for action units by a trained facial action coding system psychologist blinded to outcome.Measurements and Main Results:Action units of the upper face, head position, eyes position, lips and jaw position, and lower face were analyzed in conjunction with clinical measures collected within the National Early Warning Score. The most frequently detected action units were action unit 43 (73%) for upper face, action unit 51 (11.7%) for head position, action unit 62 (5.8%) for eyes position, action unit 25 (44.1%) for lips and jaw, and action unit 15 (67.6%) for lower face. The presence of certain combined face displays was increased in patients requiring admission to intensive care, namely, action units 43+ 15+ 25 (face display 1, p< 0.013), action units 43+ 15+ 51/52 (face display 2, p< 0.003), and action units 43+ 15+ 51+ 25 (face display 3, p< 0.002). Having face display 1, face display 2, and face display 3 increased the risk of being admitted to intensive care eight-fold, 18-fold, and as a sure event, respectively. A logistic regression model with face display 1, face display 2, face display 3, and National Early Warning Score as independent covariates described admission to intensive care with an average concordance statistic (C-index) of 0.71 (p= 0.009).Conclusions:Patterned facial expressions can be identified in deteriorating general ward patients. This tool may potentially augment risk prediction of current scoring systems.