Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
PLoS One. 2019 Mar 18;14(3):e0213445. doi: 10.1371/journal.pone.0213445. eCollection 2019.
Although the quick Sequential Organ Failure Assessment (qSOFA) score was recently introduced to identify patients with suspected infection/sepsis, it has limitations as a predictive tool for adverse outcomes. We hypothesized that combining qSOFA score with heart rate variability (HRV) variables improves predictive ability for mortality in septic patients at the emergency department (ED).
This was a retrospective study using the electronic medical record of a tertiary care hospital in Singapore between September 2014 and February 2017. All patients aged 21 years or older who were suspected with infection/sepsis in the ED and received electrocardiography monitoring with ZOLL X Series Monitor (ZOLL Medical Corporation, Chelmsford, MA) were included. We fitted a logistic regression model to predict the 30-day mortality using one of the HRV variables selected from one of each three domains those previously reported as strong association with mortality (i.e. standard deviation of NN [SDNN], ratio of low frequency to high frequency power [LF/HF], detrended fluctuation analysis α-2 [DFA α-2]) in addition to the qSOFA score. The predictive accuracy was assessed with other scoring systems (i.e. qSOFA alone, National Early Warning Score, and Modified Early Warning Score) using the area under the receiver operating characteristic curve.
A total of 343 septic patients were included. Non-survivors were significantly older (survivors vs. non-survivors, 65.7 vs. 72.9, p <0.01) and had higher qSOFA (0.8 vs. 1.4, p <0.01) as compared to survivors. There were significant differences in HRV variables between survivors and non-survivors including SDNN (23.7s vs. 31.8s, p = 0.02), LF/HF (2.8 vs. 1.5, p = 0.02), DFA α-2 (1.0 vs. 0.7, P < 0.01). Our prediction model using DFA-α-2 had the highest c-statistic of 0.76 (95% CI, 0.70 to 0.82), followed by qSOFA of 0.68 (95% CI, 0.62 to 0.75), National Early Warning Score at 0.67 (95% CI, 0.61 to 0.74), and Modified Early Warning Score at 0.59 (95% CI, 0.53 to 0.67).
Adding DFA-α-2 to the qSOFA score may improve the accuracy of predicting in-hospital mortality in septic patients who present to the ED. Further multicenter prospective studies are required to confirm our results.
尽管快速序贯器官衰竭评估（qSOFA）评分最近被引入以识别疑似感染/败血症的患者，但它作为预测不良结局的工具存在局限性。我们假设将 qSOFA 评分与心率变异性（HRV）变量相结合可以提高急诊科（ED）败血症患者的死亡率预测能力。
这是一项使用新加坡一家三级保健医院的电子病历进行的回顾性研究，时间为 2014 年 9 月至 2017 年 2 月。所有年龄在 21 岁或以上、在 ED 中疑似感染/败血症且接受 ZOLL X 系列监护仪（ZOLL Medical Corporation，Chelmsford，MA）心电图监测的患者均纳入研究。我们使用逻辑回归模型来预测 30 天死亡率，该模型使用从以前报告与死亡率有很强关联的三个领域中的每一个领域中选择的 HRV 变量之一（即 NN 的标准差[SDNN]、低频与高频功率比[LF/HF]、去趋势波动分析 α-2[DFA α-2]），再加上 qSOFA 评分。使用接收者操作特征曲线下的面积评估其他评分系统（即 qSOFA 单独、国家早期预警评分和改良早期预警评分）的预测准确性。
共纳入 343 例败血症患者。与幸存者相比，非幸存者年龄明显较大（幸存者 vs. 非幸存者，65.7 岁 vs. 72.9 岁，p<0.01），qSOFA 评分较高（0.8 分 vs. 1.4 分，p<0.01）。幸存者和非幸存者之间的 HRV 变量存在显著差异，包括 SDNN（23.7 秒 vs. 31.8 秒，p=0.02）、LF/HF（2.8 比 1.5，p=0.02）和 DFA α-2（1.0 比 0.7，P<0.01）。我们使用 DFA-α-2 的预测模型具有最高的 c 统计量为 0.76（95%CI，0.70 至 0.82），其次是 qSOFA 为 0.68（95%CI，0.62 至 0.75）、国家早期预警评分 0.67（95%CI，0.61 至 0.74）和改良早期预警评分 0.59（95%CI，0.53 至 0.67）。
将 DFA-α-2 添加到 qSOFA 评分中可能会提高急诊科败血症患者住院死亡率预测的准确性。需要进一步的多中心前瞻性研究来证实我们的结果。
