Observational studyCritical care (London, England)2019
Early prognostication of neurological outcome by heart rate variability in adult patients with out-of-hospital sudden cardiac arrest.
Observational study in Critical care (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 33 citations in OpenAlex.
- Prediction of Neurological Outcome and Mortality in Cardiac Arrest Patients: An Explainable Machine Learning Study Integrating HRV, EEG, and Clinical Features.Neurocritical care · 2026Article
- Prediction of neurological outcome after pediatric cardiac arrest using heart rate variability and machine learning.Resuscitation · 2026Article
- Potential common key genes associated with myocardial dysfunction and brain injury following cardiac arrest resuscitation in a rat model.World journal of emergency medicine · 2025Article
- Anthropometric Predictors of Heart Rate Variability in Overweight Individuals: A Comparative Study.Cureus · 2024Article
- Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury.Annals of clinical and translational neurology · 2024Article
- Heart rate and heart rate variability as a prognosticating feature for functional outcome after cardiac arrest: A scoping review.Resuscitation plus · 2023Article
- Skin sympathetic nerve activity as a biomarker for outcomes in spontaneous intracerebral hemorrhage.Annals of clinical and translational neurology · 2023Article
- Electrocardiogram monitoring as a predictor of neurological and survival outcomes in patients with out-of-hospital cardiac arrest: a single-center retrospective observational study.Frontiers in neurology · 2023Article
- Using sleep heart rate variability to investigate the sleep quality in children with obstructive sleep apnea.Frontiers in public health · 2023Article
- Influence of Obesity on Heart Rate Variability in Nurses with Age and Shift Type as Moderators.BioMed research international · 2021Article
- Increased QT Dispersion Is Linked to Worse Outcomes in Patients Hospitalized for Out-of-Hospital Cardiac Arrest.Journal of the American Heart Association · 2020Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMost deaths of comatose survivors of out-of-hospital sudden cardiac arrest result from withdrawal of life-sustaining treatment (WLST) decisions based on poor neurological prognostication and the family's intention. Thus, accurate prognostication is crucial to avoid premature WLST decisions. However, targeted temperature management (TTM) with sedation or neuromuscular blockade against shivering significantly affects early prognostication. In this study, we investigated whether heart rate variability (HRV) analysis could prognosticate poor neurological outcome in comatose patients undergoing hypothermic TTM.
methodsBetween January 2015 and December 2017, adult patients with out-of-hospital sudden cardiac arrest, successfully resuscitated in the emergency department and admitted to the intensive care unit of the Niigata University in Japan, were prospectively included. All patients had an initial Glasgow Coma Scale motor score of 1 and received hypothermic TTM (at 34 °C). Twenty HRV-related variables (deceleration capacity; 4 time-, 3 geometric-, and 7 frequency-domain; and 5 complexity variables) were computed based on RR intervals between 0:00 and 8:00 am within 24 h after return of spontaneous circulation (ROSC). Based on Glasgow Outcome Scale (GOS) at 2 weeks after ROSC, patients were divided into good outcome (GOS 1-2) and poor outcome (GOS 3-5) groups.
resultsSeventy-six patients were recruited and allocated to the good (n = 22) or poor (n = 54) outcome groups. Of the 20 HRV-related variables, ln very-low frequency (ln VLF) power, detrended fluctuation analysis (DFA) (α1), and multiscale entropy (MSE) index significantly differed between the groups (p = 0.001), with a statistically significant odds ratio (OR) by univariate logistic regression analysis (p = 0.001). Multivariate logistic regression analysis of the 3 variables identified ln VLF power and DFA (α1) as significant predictors for poor outcome (OR = 0.436, p = 0.006 and OR = 0.709, p = 0.024, respectively). The area under the receiver operating characteristic curve for ln VLF power and DFA (α1) in predicting poor outcome was 0.84 and 0.82, respectively. In addition, the minimum value of ln VLF power or DFA (α1) for the good outcome group predicted poor outcome with sensitivity = 61% and specificity = 100%.
conclusionsThe present data indicate that HRV analysis could be useful for prognostication for comatose patients during hypothermic TTM.
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