Comparison of wavelet and correlation indices of cerebral autoregulation in a pediatric swine model of cardiac arrest
Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial press...
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Published in | Scientific reports Vol. 10; no. 1; p. 5926 |
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Main Authors | , , , , , , , |
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Language | English |
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03.04.2020
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Abstract | Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial pressure (ICP) decreases index variability compared to that of commonly used correlation indices. We also compared whether the methods identify the optimal arterial blood pressure (ABPopt) and lower limit of autoregulation (LLA). 68 piglets were randomized to cardiac arrest or sham procedure with continuous monitoring of cerebral blood flow using laser Doppler, NIRS and ICP. The arterial blood pressure (ABP) was gradually reduced until it dropped to below the LLA. Several autoregulation indices were calculated using correlation and wavelet methods, including the pressure reactivity index (PRx and wPRx), cerebral oximetry index (COx and wCOx), and hemoglobin volume index (HVx and wHVx). Wavelet methodology had less index variability with smaller standard deviations. Both wavelet and correlation methods distinguished functional autoregulation (ABP above LLA) from dysfunctional autoregulation (ABP below the LLA). Both wavelet and correlation methods also identified ABPopt with high agreement. Thus, wavelet methodology using NIRS may offer an accurate vasoreactivity monitoring method with reduced signal noise after pediatric cardiac arrest. |
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AbstractList | Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial pressure (ICP) decreases index variability compared to that of commonly used correlation indices. We also compared whether the methods identify the optimal arterial blood pressure (ABPopt) and lower limit of autoregulation (LLA). 68 piglets were randomized to cardiac arrest or sham procedure with continuous monitoring of cerebral blood flow using laser Doppler, NIRS and ICP. The arterial blood pressure (ABP) was gradually reduced until it dropped to below the LLA. Several autoregulation indices were calculated using correlation and wavelet methods, including the pressure reactivity index (PRx and wPRx), cerebral oximetry index (COx and wCOx), and hemoglobin volume index (HVx and wHVx). Wavelet methodology had less index variability with smaller standard deviations. Both wavelet and correlation methods distinguished functional autoregulation (ABP above LLA) from dysfunctional autoregulation (ABP below the LLA). Both wavelet and correlation methods also identified ABPopt with high agreement. Thus, wavelet methodology using NIRS may offer an accurate vasoreactivity monitoring method with reduced signal noise after pediatric cardiac arrest. Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial pressure (ICP) decreases index variability compared to that of commonly used correlation indices. We also compared whether the methods identify the optimal arterial blood pressure (ABPopt) and lower limit of autoregulation (LLA). 68 piglets were randomized to cardiac arrest or sham procedure with continuous monitoring of cerebral blood flow using laser Doppler, NIRS and ICP. The arterial blood pressure (ABP) was gradually reduced until it dropped to below the LLA. Several autoregulation indices were calculated using correlation and wavelet methods, including the pressure reactivity index (PRx and wPRx), cerebral oximetry index (COx and wCOx), and hemoglobin volume index (HVx and wHVx). Wavelet methodology had less index variability with smaller standard deviations. Both wavelet and correlation methods distinguished functional autoregulation (ABP above LLA) from dysfunctional autoregulation (ABP below the LLA). Both wavelet and correlation methods also identified ABPopt with high agreement. Thus, wavelet methodology using NIRS may offer an accurate vasoreactivity monitoring method with reduced signal noise after pediatric cardiac arrest. |
ArticleNumber | 5926 |
Author | Liu, Xiuyun Donnelly, Joseph Koehler, Raymond Lee, Jennifer K. Brady, Ken M. Smielewski, Peter Hu, Xiao Czosnyka, Marek |
Author_xml | – sequence: 1 givenname: Xiuyun surname: Liu fullname: Liu, Xiuyun email: Liuxiuyun1@gmail.com organization: Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University, Department of Physiological Nursing, University of California – sequence: 2 givenname: Xiao surname: Hu fullname: Hu, Xiao organization: Department of Physiological Nursing, University of California, Department of Neurosurgery, School of Medicine, University of California, Department of Neurological Surgery, University of California, Institute of Computational Health Sciences, University of California – sequence: 3 givenname: Ken M. surname: Brady fullname: Brady, Ken M. organization: Northwestern University, Ann & Robert H. Lurie Children’s Hospital of Chicago, Department of Anesthesiology – sequence: 4 givenname: Raymond surname: Koehler fullname: Koehler, Raymond organization: Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University – sequence: 5 givenname: Peter surname: Smielewski fullname: Smielewski, Peter organization: Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge – sequence: 6 givenname: Marek surname: Czosnyka fullname: Czosnyka, Marek organization: Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge, Institute of Electronic Systems, Warsaw University of Technology – sequence: 7 givenname: Joseph surname: Donnelly fullname: Donnelly, Joseph organization: Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge, Department of Anaesthesiology, University of Auckland – sequence: 8 givenname: Jennifer K. surname: Lee fullname: Lee, Jennifer K. organization: Department of Anesthesiology and Critical Care Medicine, Division of Pediatric Anesthesiology, Johns Hopkins University |
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CitedBy_id | crossref_primary_10_1007_s10877_024_01136_3 crossref_primary_10_1097_CP9_0000000000000087 crossref_primary_10_1016_j_resuscitation_2021_08_020 crossref_primary_10_3389_fneur_2021_662839 crossref_primary_10_3389_fneur_2023_1155986 crossref_primary_10_3390_bioengineering11010033 crossref_primary_10_1097_CCM_0000000000004737 crossref_primary_10_3390_biomedicines10123057 |
Cites_doi | 10.1186/s12883-015-0464-4 10.3174/ajnr.A4083 10.1161/STROKEAHA.108.536094 10.1097/CCM.0b013e3182514eb6 10.1213/ANE.0b013e31824762d5 10.1038/s41598-018-24836-8 10.1016/j.neuroscience.2015.12.046 10.1161/JAHA.118.009415 10.1016/j.resuscitation.2014.07.006 10.1113/JP274708 10.1159/000452833 10.3389/fped.2017.00174 10.1016/j.athoracsur.2013.07.086 10.1097/CCM.0b013e318223b910 10.3389/fped.2014.00144 10.1201/9781420033397 10.1089/neu.2017.5003 10.1097/00006123-199707000-00005 10.17863/cam.33006 10.1038/jcbfm.2014.245 10.1177/0271678X17733639 10.1016/j.resuscitation.2016.05.019 10.1213/ane.0b013e3181964848 10.1371/journal.pmed.1002348 10.1016/j.jpeds.2015.03.041 10.1038/pr.2017.94 10.1016/j.resuscitation.2015.08.007 10.1159/000499425 10.1097/CCM.0000000000003745 10.1056/NEJMoa1610493 10.1111/pan.13293 10.1159/000457833 10.1152/japplphysiol.00238.2013 |
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SubjectTerms | 631/378 692/308 692/617 Animals Arterial Pressure - physiology Blood flow Blood pressure Cardiac arrest Cerebral blood flow Cerebrovascular Circulation - physiology Child Disease Models, Animal Heart Heart Arrest - complications Heart Arrest - physiopathology Hemoglobin Hemoglobins - analysis Homeostasis - physiology Humanities and Social Sciences Humans Hypoxia, Brain - diagnosis Hypoxia, Brain - etiology Hypoxia, Brain - physiopathology Infrared spectroscopy Intracranial Pressure - physiology Laser-Doppler Flowmetry Male Monitoring methods multidisciplinary Neurophysiological Monitoring - methods Oximetry - methods Pediatrics Science Science (multidisciplinary) Spectroscopy, Near-Infrared Swine |
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Title | Comparison of wavelet and correlation indices of cerebral autoregulation in a pediatric swine model of cardiac arrest |
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