title: Complexity of brain signals is associated with outcome in preterm infants.
abstract: A characteristic feature of complex healthy biological systems is the ability to react and adapt to minute changes in the environment. This 'complexity' manifests itself in highly irregular patterns of various physiological measurements. Here, we apply Multiscale Entropy (MSE) analysis to assess the complexity of systemic and cerebral near-infrared spectroscopy (NIRS) signals in a cohort of 61 critically ill preterm infants born at median (range) gestational age of 26 (23-31) weeks, before 24 h of life. We further correlate the complexity of these parameters with brain injury and mortality. Lower complexity index (CoI) of oxygenated haemoglobin (HbO2), deoxygenated haemoglobin (Hb) and tissue oxygenation index (TOI) were observed in those infants who developed intraventricular haemorrhage (IVH) compared to those who did not (P = 0.002, P = 0.010 and P = 0.038, respectively). Mean CoI of HbO2, Hb and total haemoglobin index (THI) were lower in those infants who died compared to those who survived (P = 0.012, P = 0.004 and P = 0.003, respectively). CoI-HbO2was an independent predictor of IVH (P = 0.010). Decreased complexity of brain signals was associated with mortality and brain injury. Measurement of brain signal complexity in preterm infants is feasible and could represent a significant advance in the brain-oriented care.
authors.affiliation: 1 The Rosie Hospital, Cambridge University Hospitals, Cambridge, UK.
authors.forename: Cristine
authors.initials: C
authors.lastname: Sortica da Costa
authors.affiliation: 2 Department of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland.
authors.forename: Michal M
authors.initials: MM
authors.lastname: Placek
authors.affiliation: 3 Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
authors.forename: Marek
authors.initials: M
authors.lastname: Czosnyka
authors.affiliation: 3 Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
authors.forename: Brenno
authors.initials: B
authors.lastname: Cabella
authors.affiliation: 2 Department of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland.
authors.forename: Magdalena
authors.initials: M
authors.lastname: Kasprowicz
authors.affiliation: 1 The Rosie Hospital, Cambridge University Hospitals, Cambridge, UK.
authors.forename: Topun
authors.initials: T
authors.lastname: Austin
authors.affiliation: 3 Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Smielewski
mesh_terms: D002543:Cerebral Hemorrhage; D002552:Cerebral Ventricles / Q000473:pathology; D005865:Gestational Age; D006454:Hemoglobins / Q000032:analysis / Q000378:metabolism; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature / Q000502:physiology*; D010100:Oxygen / Q000378:metabolism; D011379:Prognosis; D012720:Severity of Illness Index; D019265:Spectroscopy, Near-Infrared; D013534:Survival / Q000502:physiology*
chemical_list: D006454:Hemoglobins; D010100:Oxygen
keywords: Brain injury; brain monitoring; complexity; entropy; preterm