Key result
A mortality score model including three spectral heart rate variability indices predicted mortality in coma patients with 95.65% sensitivity, 95.83% specificity, and 95.74% overall efficiency.
Why the study?
To evaluate the functional state of the autonomic nervous system using heart rate variability measures in healthy individuals and patients in coma, and to assess its efficiency in predicting mortality.
Does heart rate variability analysis predict mortality and assess autonomic impairment in comatose patients?
Observational (n=80)
No
Does heart rate variability analysis predict mortality and assess autonomic impairment in comatose patients?
Heart rate variability analysis using the Hilbert-Huang method can reliably assess autonomic impairment and predict mortality in comatose patients with high sensitivity and specificity.
PRIMARY OBJECTIVE: The objective of this study is to assess the functional state of the autonomic nervous system in healthy individuals and in individuals in coma using measures of heart rate variability (HRV) and to evaluate its efficiency in predicting mortality. DESIGN AND METHODS: Retrospective group comparison study of patients in coma classified into two subgroups, according to their Glasgow coma score, with a healthy control group. HRV indices were calculated from 7 min of artefact-free electrocardiograms using the Hilbert-Huang method in the spectral range 0.02-0.6 Hz. A special procedure was applied to avoid confounding factors. Stepwise multiple regression logistic analysis (SMLRA) and ROC analysis evaluated predictions. RESULTS: Progressive reduction of HRV was confirmed and was associated with deepening of coma and a mortality score model that included three spectral HRV indices of absolute power values of very low, low and very high frequency bands (0.4-0.6 Hz). The SMLRA model showed sensitivity of 95.65%, specificity of 95.83%, positive predictive value of 95.65%, and overall efficiency of 95.74%. CONCLUSIONS: HRV is a reliable method to assess the integrity of the neural control of the caudal brainstem centres on the hearts of patients in coma and to predict patient mortality.
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Estévez‐Báez et al. (2019) conducted an observational in Coma (n=80). Coma vs. Healthy controls was evaluated on Mortality prediction using a stepwise multiple regression logistic analysis model of HRV indices. A mortality score model including three spectral heart rate variability indices predicted mortality in coma patients with 95.65% sensitivity, 95.83% specificity, and 95.74% overall efficiency.
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