Reduced Heart Rate Volatility: An Early Predictor of Death in Trauma Patients
Reduced Heart Rate Volatility: An Early Predictor of Death in Trauma Patients
复制标题
心率波动性降低：创伤患者死亡的早期预测因素
作者：
E. Grogan;John A. Morris;Patrick R. Norris;D. France;A. Ozdas;R. Stiles;P. Harris;B. Dawant;T. Speroff
目的：确定使用密集数据捕获测量5分钟间隔测量的心率波动率（标准差）是否能预测死亡。背景：自20世纪初以来，评估危重患者生命体征的基本方法几乎没有变化。我们之前在这一领域的工作已经证明了密集采样数据的实用性，特别是整个患者住院期间的心率波动，用于预测死亡和延长通气时间。方法：前瞻性收集1316例创伤ICU患者近30个月的1.2亿心率数据点并存档。数据每1到4秒采样一次，存储在关系数据库中，链接到结果数据，并去标识化。每隔5分钟连续计算心率标准差（CVRD，心脏波动相关功能障碍）。在一组患者（N = 923）中建立了包含年龄和损伤严重程度评分的Logistic回归模型，并在一组单独的验证集（N = 393）中对ICU前24小时的数据进行前瞻性分析。结果：CVRD的分布随生存期的变化而变化。在验证集中对该模型进行前瞻性评价，受试者工作曲线的面积为0.81，敏感性和特异性分别为70.1和80.0。在验证组中，CVRD预测早在24小时内死亡。结论：CVRD确定了一个高死亡概率患者亚组。预计病人会在24小时内死亡。我们假设CVRD是自主神经系统功能障碍的替代物。
Objective:To determine if using dense data capture to measure heart rate volatility (standard deviation) measured in 5-minute intervals predicts death. Background:Fundamental approaches to assessing vital signs in the critically ill have changed little since the early 1900s. Our prior work in this area has demonstrated the utility of densely sampled data and, in particular, heart rate volatility over the entire patient stay, for predicting death and prolonged ventilation. Methods:Approximately 120 million heart rate data points were prospectively collected and archived from 1316 trauma ICU patients over 30 months. Data were sampled every 1 to 4 seconds, stored in a relational database, linked to outcome data, and de-identified. HR standard deviation was continuously computed over 5-minute intervals (CVRD, cardiac volatility–related dysfunction). Logistic regression models incorporating age and injury severity score were developed on a test set of patients (N = 923), and prospectively analyzed in a distinct validation set (N = 393) for the first 24 hours of ICU data. Results:Distribution of CVRD varied by survival in the test set. Prospective evaluation of the model in the validation set gave an area in the receiver operating curve of 0.81 with a sensitivity and specificity of 70.1 and 80.0, respectively. CVRD predict death as early as 24 hours in the validation set. Conclusions:CVRD identifies a subgroup of patients with a high probability of dying. Death is predicted within first 24 hours of stay. We hypothesize CVRD is a surrogate for autonomic nervous system dysfunction.
波动性：使用新颖的床边监测策略识别的新生命体征。
DOI：
10.1097/01.ta.0000151179.74839.98
发表时间：
2005
期刊：
The Journal of trauma
影响因子：
--
作者：
Grogan,EricL;Norris,PatrickR;Speroff,Theodore;Ozdas,Asli;France,DanielJ;Harris,PaulA;Jenkins,JudithM;Stiles,Renee;Dittus,RobertS;MorrisJr,JohnA
通讯作者：
MorrisJr,JohnA
万维网上的实时患者监护系统。
DOI：
--
发表时间：
1996
期刊：
Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium
影响因子：
--
作者：
Wang,K;Kohane,I;Bradshaw,KL;Fackler,J
通讯作者：
Fackler,J