Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
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DOI：
10.1186/s41038-019-0147-2
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发表时间：
2019-04-18
期刊：
影响因子：
5.3
通讯作者：
Ong, Marcus Eng Hock
中科院分区：
文献类型：
--
作者：
Kumar, Aravin;Liu, Nan;Ong, Marcus Eng Hock
背景：创伤分诊评分用于确定创伤患者的处置、干预和预后。心率变异性（HRV）和心率复杂性（HRC）反映了自主神经系统，由心电图（ECG）分析得出。在这项研究中，我们旨在建立一个结合HRV和HRC的模型，以预测急诊24小时内创伤患者对挽救生命干预（LSI）的需求。方法：我们纳入2014年10月至2015年10月在新加坡综合医院急诊科就诊的成人创伤患者（>= 18岁）。我们在心电图分析中排除了非窦性心律和较大比例伪影和/或异位的患者。我们从电子健康记录中获得了患者人口统计数据、实验室结果、生命体征和结果。我们进行了单变量和多变量分析，以建立预测模型。结果：225例患者符合纳入标准，其中49例患者需要lsi。LSI组的死亡率更高（10.20.41% vs 1.0.57%, p < 0.001）。LSI组去趋势波动分析(DFA)-alpha 1的平均值（1.24 vs 1.12, p = 0.045）和DFA-alpha 2的中位数（1.09 vs 1.00, p = 0.027）显著升高。多变量逐步逻辑回归分析确定，较低的格拉斯哥昏迷量表、较高的DFA-alpha 1和较高的DFA-alpha 2是需要lsi的独立预测因子。我们模型的曲线下面积（AUC）（0.75, 95%置信区间，0.66-0.83）高于其他评分系统和所选生命体征。结论：HRV/HRC模型在预测lsi需求方面优于其他分诊创伤评分和选择的生命体征，但需要在更大的患者群体中进行验证。
Background: Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are derived from electrocardiogram (ECG) analysis. In this study, we aimed to develop a model incorporating HRV and HRC, to predict the need for life-saving interventions (LSI) in trauma patients, within 24 h of emergency department presentation.Methods: We included adult trauma patients (>= 18 years of age) presenting at the emergency department of Singapore General Hospital between October 2014 and October 2015. We excluded patients who had non-sinus rhythms and larger proportions of artefacts and/or ectopics in ECG analysis. We obtained patient demographics, laboratory results, vital signs and outcomes from electronic health records. We conducted univariate and multivariate analyses for predictive model building.Results: Two hundred and twenty-five patients met inclusion criteria, in which 49 patients required LSIs. The LSI group had a higher proportion of deaths (10, 20.41% vs 1, 0.57%, p < 0.001). In the LSI group, the mean of detrended fluctuation analysis (DFA)-alpha 1 (1.24 vs 1.12, p = 0.045) and the median of DFA-alpha 2 (1.09 vs 1.00, p = 0.027) were significantly higher. Multivariate stepwise logistic regression analysis determined that a lower Glasgow Coma Scale, a higher DFA-alpha 1 and higher DFA-alpha 2 were independent predictors of requiring LSIs. The area under the curve (AUC) for our model (0.75, 95% confidence interval, 0.66-0.83) was higher than other scoring systems and selected vital signs.Conclusions: An HRV/HRC model outperforms other triage trauma scores and selected vital signs in predicting the need for LSIs but needs to be validated in larger patient populations.