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Competing Interests: Dr. Lee’s institution received funding from the National Research Medical Council and the Thrasher Foundation. Dr. Chong has disclosed that she does not have any potential conflicts of interest.

Sepsis is a potentially life-threatening condition that requires prompt recognition and treatment. Recently, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality. This paper presents using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and comparing against current mortality prediction scores. This study was a retrospective cohort study on patients presenting to the emergency department of a tertiary hospital in Singapore between September 2014 to April 2017. Patients were included if they were above 21 years old and were suspected of having sepsis by their attending physician. The primary outcome was 30-day in-hospital mortality. Stepwise multivariable logistic regression model was built to predict the outcome, and the results based on 10-fold cross-validation were presented using receiver operating curve analysis. The final predictive model comprised 21 variables, including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve of the model was 0.77 (95% confidence interval 0.70-0.84), outperforming several established clinical scores. The HRnV measures may have the potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality. Our exploration of the use of wealthy inherent information obtained from novel HRnV measures could also create a new perspective for data scientists to develop innovative approaches for ECG analysis and risk monitoring., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: NL and MEHO are the inventors on a patent (US10299689B2) that is issued by the United States Patent and Trademark Office relevant to the material in this paper. NL, DG, ZXK, and MEHO own stock in TIIM Healthcare that produces a product relevant to the subject material. MLC, MZQF, JZP, AFWH, CN, and SLC report no conflict of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction: Neonatal sepsis has a high mortality rate that varies across different populations. We aim to perform a contemporary global evidence synthesis to determine the case fatality rates of neonatal sepsis, in order to better delineate this public health urgency and inform strategies to reduce fatality in this high-risk population., Methods and Analysis: We will search PubMed, Cochrane Central, Embase and Web of Science for articles in English language published between January 2010 and December 2019. All clinical trials and observational studies involving infants less than 90 days old with a clinical diagnosis of sepsis and reported case fatality rate will be included. Two independent reviewers will screen the studies and extract data on study variables chosen a priori. Quality of evidence and risk of bias will be assessed using Cochrane Collaboration's tool and ROBINS-I. Results will be synthesised qualitatively and pooled for meta-analysis., Ethics and Dissemination: No formal ethical approval is required as there is no collection of primary data. This systematic review and meta-analysis will be disseminated through conference meetings and peer-reviewed publications., Prospero Registration Number: CRD42020164321., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

A quick, objective, non-invasive means of identifying high-risk septic patients in the emergency department (ED) can improve hospital outcomes through early, appropriate management. Heart rate variability (HRV) analysis has been correlated with mortality in critically ill patients. We aimed to develop a Singapore ED sepsis (SEDS) predictive model to assess the risk of 30-day in-hospital mortality in septic patients presenting to the ED. We used demographics, vital signs, and HRV parameters in model building and compared it with the modified early warning score (MEWS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA) score.Adult patients clinically suspected to have sepsis in the ED and who met the systemic inflammatory response syndrome (SIRS) criteria were included. Routine triage electrocardiogram segments were used to obtain HRV variables. The primary endpoint was 30-day in-hospital mortality. Multivariate logistic regression was used to derive the SEDS model. MEWS, NEWS, and qSOFA (initial and worst measurements) scores were computed. Receiver operating characteristic (ROC) analysis was used to evaluate their predictive performances.Of the 214 patients included in this study, 40 (18.7%) met the primary endpoint. The SEDS model comprises of 5 components (age, respiratory rate, systolic blood pressure, mean RR interval, and detrended fluctuation analysis α2) and performed with an area under the ROC curve (AUC) of 0.78 (95% confidence interval [CI]: 0.72-0.86), compared with 0.65 (95% CI: 0.56-0.74), 0.70 (95% CI: 0.61-0.79), 0.70 (95% CI: 0.62-0.79), 0.56 (95% CI: 0.46-0.66) by qSOFA (initial), qSOFA (worst), NEWS, and MEWS, respectively.HRV analysis is a useful component in mortality risk prediction for septic patients presenting to the ED.