Multimodal predictor of neurodevelopmental outcome in newborns with hypoxic-ischaemic encephalopathy

Computers in Biology and Medicine - Tập 63 - Trang 169-177 - 2015
Andriy Temko1,2, Orla Doyle3, Deirdre Murray4,2, Gordon Lightbody1,2, Geraldine Boylan4,2, William Marnane1,2
1Department of Electrical and Electronic Engineering, University College Cork, Ireland
2Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland
3Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
4Department of Pediatrics and Child Health, University College Cork, Ireland

Tài liệu tham khảo

Volpe, 2001 Murray, 2009, Early EEG findings in hypoxic-ischemic encephalopathy predict outcome at 2 years, Pediatrics, 124, 459, 10.1542/peds.2008-2190 Sinclair, 1999, EEG and long-term outcome of term infants with neonatal hypoxic-iischemic encephalopathy, Clin. Neurophys., 110, 655, 10.1016/S1388-2457(99)00010-3 van Lieshout, 1995, The prognostic value of the EEG in asphyxiated newborns, Acta Neurol. Scand., 91, 203, 10.1111/j.1600-0404.1995.tb00435.x Pressler, 2001, Early serial EEG in hypoxic ischaemic encephalopathy, Clin. Neurophysiol., 112, 31, 10.1016/S1388-2457(00)00517-4 Ramaswamy, 2009, Systematic review of biomarkers of brain injury in term neonatal encephalopathy, Pediatr Neurol., 40, 215, 10.1016/j.pediatrneurol.2008.09.026 Laptook, 2009, Outcome of term infants using apgar scores at 10 minutes following hypoxic-iscemic encephalopathy, Pediatrics, 124, 1619, 10.1542/peds.2009-0934 American Academy of Pediatrics, 2006, The Apgar score, Pediatrics, 117, 1444, 10.1542/peds.2006-0325 Lingwood, 2009, Prediction of outcome following hypoxic/ischaemia in the human infant using cerebral impedance, Clin. Neurophysiol., 120, 225, 10.1016/j.clinph.2008.11.008 Jyoti, 2006, Predicting outcome in term neonates with hypoxic-ischaemic encephalopathy using simplified MR criteria, Pediatr. Radiol., 36, 38, 10.1007/s00247-005-0024-y Rennie, 2008, 130 Temko, 2013, Robust neonatal EEG Seizure detection through adaptive background modelling, Int. J. Neural Syst., 23, 10.1142/S0129065713500184 Doyle, 2010, Heart rate based automatic seizure detection in the newborn, Med. Eng. Phys., 32, 829, 10.1016/j.medengphy.2010.05.010 Moorman, 2006, Heart rate characteristics monitoring for neonatal sepsis, IEEE Trans. Biomed. Eng., 53, 26, 10.1109/TBME.2005.859810 Sarnat, 1976, Neonatal encephalopathy following fetal distress: a clinical and electroencephalographic study, Arch. Neurol., 33, 696, 10.1001/archneur.1976.00500100030012 Amiel-Tison, 2002, Update of the Amiel-Tison neurological assessment for the term neonate or at 40 weeks corrected age, Pediatr. Neurol., 27, 196, 10.1016/S0887-8994(02)00436-8 Griffths, 1954 Thomas, 2013, Discriminative and generative classification techniques applied to automated neonatal seizure detection, IEEE J. Biomed. Health Inform., 17, 297, 10.1109/JBHI.2012.2237035 Faul, 2009, Age-independent seizure detection, Proc. IEEE Eng. Med. Biol. Soc., 6612 Lofhede, 2010, Automated classification of background EEG activity in healthy and sick neonates, J. Neural Eng., 7, 10.1088/1741-2560/7/1/016007 van Putten, 2007, The revised brain symmetry index, Clin. Neurophysiol., 118, 2362, 10.1016/j.clinph.2007.07.019 Bell, 1990, Power spectral analysis of the EEG of term infants following birth asphyxia, Dev. Med. Child Neurol., 32, 990, 10.1111/j.1469-8749.1990.tb08122.x Hamilton, 1986, Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmis database, IEEE Trans. Biomed. Eng., 33, 1157, 10.1109/TBME.1986.325695 Malik, 1996, Heart rate variabiltiy: standards of measurement, physiological interpretation and clinical use. Task force of the european society of cardiology and the north american society of pacing and electrophysiology, Eur. Heart J., 17, 354, 10.1093/oxfordjournals.eurheartj.a014868 De Chazal, 2003, Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea, IEEE Trans. Biomed. Eng., 50, 686, 10.1109/TBME.2003.812203 Doyle, 2009, Heart rate variability during sleep in healthy term newborns in the early postnatal period, Physiol. Meas., 30, 10.1088/0967-3334/30/8/009 Kovatchev, 2003, Sample asymmetry analysis of heart rate characteristics with application to neonatal sepsis and systemic inflammatory response syndrome, Pediatr. Res., 54, 892, 10.1203/01.PDR.0000088074.97781.4F Toichi, 1997, A new method of assessing caridac autonomic function and its comparison with spectral analysis and coefficient of variation of RR interval, J. Auton. Nerv. Syst., 62, 79, 10.1016/S0165-1838(96)00112-9 Twomey, 2014, Fully-automated allergy detection from paediatric ECG, IEEE J. Biomed. Health Inform., 18, 1051, 10.1109/JBHI.2013.2290706 J. Platt, Probabilistic outputs from SVM and comparison to regularized likelihood methods in: Alexander J. Smola, Peter Bartlett, Bernhard Schoelkopf, Dale Schuurmans (Eds.), Advances in Large Margin Classifiers, pp. 61–74, MIT Press, Massachusetts, USA, 1999. Guyon, 2002, Gene selection for cancer classification using support vector machines, Mach. Learn., 46, 389, 10.1023/A:1012487302797 Vapnik, 1982 Temko, 2011, EEG signal description with spectral-envelope-based speech recognition features for detection of neonatal seizures, IEEE Trans. Inf. Technol. Biomed., 15, 839, 10.1109/TITB.2011.2159805 Niedermeyer, 2004 Guyon, 2008, Design and analysis of the causation and prediction challenge, J. Mach. Learn. Res., 3, 1 McNeil, 1975, Primer on certain elements of medical decision making, N. Engl. J. Med., 293, 211, 10.1056/NEJM197507312930501 Temko, 2013, Robust neonatal EEG classification through adaptive background modelling, Int. J. Neural Syst., v. 23, 10.1142/S0129065713500184 Stevenson, 2013, An automated system for grading EEG abnormality in term neonates with hypoxic-ischaemic encephalopathy, Ann. Biomed. Eng., 41, 775, 10.1007/s10439-012-0710-5 Lofhede, 2008, Classification of burst and suppression in the neonatal electroencephalogram, J. Neural Eng., 5, 402, 10.1088/1741-2560/5/4/005 B. Vergales, S. Zanelli, J. Matsumoto, H. Goodkin, D. Lake, J. Moorman, K. Fairchild, “Depressed heart rate variability is associated with abnormal EEG, MRI, and death in neonates with hypoxic ischemic encephalopathy,” Am. J. Perinatol., 2014. R. Ahmed, A. Temko, W. Marnane, G. Boylan, G. Lightbody, Grading Brain Injury in Neonatal EEG Using SVM and Supervector Kernel, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP׳14, Florence, Italy, May 2014. Zweig, 1993, Receiver-operating characteristics (ROC) plots: a fundamental evaluation tool in clinical medicine, Clin. Chem., 39, 561, 10.1093/clinchem/39.4.561 Hanley, 1982, The meaning of use of the area under a receiver operating characteristic (ROC) curve, Radiology, 143, 29, 10.1148/radiology.143.1.7063747 Temko, 2015, Clinical implementation of a neonatal seizure detection algorithm, Decis. Support Syst., 70, 86, 10.1016/j.dss.2014.12.006