Date Published: March 18, 2019
Publisher: Public Library of Science
Author(s): Sumanth Madhusudan Prabhakar, Takashi Tagami, Nan Liu, Mas’uud Ibnu Samsudin, Janson Cheng Ji Ng, Zhi Xiong Koh, Marcus Eng Hock Ong, Juan Carlos Lopez-Delgado.
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.
Sepsis is a severe and life-threatening condition with high mortality and morbidity . Several studies and guidelines suggest that early identification and immediate bundle management are essential components of sepsis management in order to improve sepsis patient’s outcome [2–4]. Thus, a quick, simple, non-invasive, and efficient risk stratification tool to identify high-risk patients may initiate the bundle management as recommended by the updated survival sepsis campaign bundle , especially in the early phase of sepsis during the emergency department (ED) setting.
This study was approved by the SingHealth Centralised Institutional Review Board (Ref: 2016/2858) with a waiver of informed patient consent.
During the study period, 343 patients met the inclusion criteria for this study. Table 1 shows the characteristics of the patients in the current study. There was no significant difference in the proportion of gender, race, source of infection, medical and drug history between survivors and non- survivors. However, non-survivors were significantly older and had higher qSOFA, NEWS, and MEWS scores as compared to survivors.
The results of the current study suggested that the model created from HRV variable (especially DFA α-2) in addition to qSOFA score may improve the accuracy in predicting all-cause 30-day mortality in patients who present to the ED with suspicion of infection/sepsis. This prediction model may work as simple, non-invasive, and efficient risk stratification tool to identify high-risk septic patients at the ED.
Adding HRV variables, especially 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.