Article (Scientific journals)
A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network
Riganello, Francesco; Larroque, Stephen Karl; Bahri, Mohamed Ali et al.
2018In Frontiers in Neurology, 9, p. 769
Peer Reviewed verified by ORBi
 

Files


Full Text
fneur-09-00769.pdf
Publisher postprint (3.5 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Abstract :
[en] Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.
Disciplines :
Neurology
Author, co-author :
Riganello, Francesco  ;  Université de Liège - ULiège > Doct. sc. méd. (paysage)
Larroque, Stephen Karl   ;  Université de Liège - ULiège > GIGA : Coma Group
Bahri, Mohamed Ali  ;  Université de Liège - ULiège > GIGA-CRC In vivo Imaging
Heine, Lizette 
Martial, Charlotte  ;  Université de Liège - ULiège > GIGA : Coma Group
Carrière, Manon ;  Université de Liège - ULiège > GIGA : Coma Group
CHARLAND-VERVILLE, Vanessa ;  Centre Hospitalier Universitaire de Liège - CHU > Services opérationnels de l'Administrateur Délégué > Unité de psychologie de la santé
Aubinet, Charlène  ;  Université de Liège - ULiège > GIGA : Coma Group
VANHAUDENHUYSE, Audrey  ;  Centre Hospitalier Universitaire de Liège - CHU > Département d'Anesthésie et réanimation > Centre interdisciplinaire d'algologie
Chatelle, Camille ;  Université de Liège - ULiège > GIGA : Coma Group
LAUREYS, Steven  ;  Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Coma Science Group
Di Perri, Carol ;  Université de Liège - ULiège > GIGA : Coma Group
 These authors have contributed equally to this work.
Language :
English
Title :
A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network
Publication date :
12 September 2018
Journal title :
Frontiers in Neurology
eISSN :
1664-2295
Publisher :
Frontiers Media S.A., Switzerland
Volume :
9
Pages :
769
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 13 October 2018

Statistics


Number of views
152 (22 by ULiège)
Number of downloads
119 (9 by ULiège)

Scopus citations®
 
46
Scopus citations®
without self-citations
32
OpenCitations
 
30

Bibliography


Similar publications



Contact ORBi