Key result
A multivariable model incorporating novel heart rate n-variability (HRnV) measures predicted 30-day in-hospital mortality in sepsis patients with an AUC of 0.86, outperforming traditional clinical scores.
Why the study?
There is little consensus on an objective method to assess sepsis severity and mortality risk, prompting investigation of novel heart rate n-variability measures for risk prediction.
Do heart rate n-variability (HRnV) measures improve the prediction of 30-day in-hospital mortality in emergency department patients with suspected sepsis compared to traditional clinical scores?
Cohort (n=342)
No
Do heart rate n-variability (HRnV) measures improve the prediction of 30-day in-hospital mortality in emergency department patients with suspected sepsis compared to traditional clinical scores?
Effect estimate: AUC 0.86 (95% CI 0.81-0.90)
Novel heart rate n-variability measures derived from short ECG tracings can accurately predict 30-day in-hospital mortality in emergency department patients with sepsis, outperforming traditional clinical scores.
May refine sepsis mortality risk assessment; hypothesis-generating and requires prospective validation before clinical adoption.
Background Sepsis is a potentially life threatening condition that requires prompt recognition and treatment for optimal outcomes. There is little consensus on an objective way to assess for sepsis severity and risk for mortality. In recent years, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality, and its use as a prognostic variable and for risk stratification has been promising. In this paper, we present using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and compare against current mortality prediction scores. Methods This study was a retrospective cohort study on a convenience sample of patients presenting to the emergency department (ED) of Singapore General Hospital between September 2014 to April 2017. Patients were included in the study if they were above 21 years old, were suspected to have sepsis by their attending physician, triaged as emergency or urgent cases, and if they met two or more of the Systemic Inflammatory Response Syndrome (SIRS) criteria. Demographic and clinical variables were obtained from the electronic medical records, and HRV and novel HRnV parameters were calculated from five minute ECG tracings. Univariable analysis was conducted on variables obtained, with the primary outcome being 30-day in-hospital mortality (IHM). Variables selected through univariable analysis and stepwise selection were included in a multivariable logistic regression model, the results of which were presented using receiver operating curve (ROC) analysis. Results Of 342 patients included for final analysis, 66 (19%) met with the primary outcome. On univariable analysis, 85 out of 142 analysed HRV and HRnV parameters showed statistical difference between groups. The final multivariable logistic regression model comprised of 21 variables including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve (AUC) of the model was 0.86 (95% confidence interval 0.81-0.90), outperforming several established clinical scores. Conclusion The use of novel HRnV measures can provide adequate power to predictive models in the risk stratification of patients presenting to the ED with sepsis. When included in a multivariable logistic regression model, the HRnV-based model outperformed traditional risk stratification scoring systems. The HRnV measures may have potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality.
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Liu et al. (2021) conducted a cohort in Sepsis (n=342). Heart Rate n-Variability (HRnV) based predictive model vs. Established clinical scores (NEWS, MEWS, MEDS, SOFA, APACHE II, qSOFA) was evaluated on 30-day in-hospital mortality prediction (AUC) (AUC 0.86, 95% CI 0.81-0.90). A multivariable model incorporating novel heart rate n-variability (HRnV) measures predicted 30-day in-hospital mortality in sepsis patients with an AUC of 0.86, outperforming traditional clinical scores.
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