Comparison of wavelet and correlation indices of cerebral autoregulation in a pediatric swine model of cardiac arrest

Scientific Reports

Peter Smielewski¹  Joseph Donnelly²  Marek Czosnyka³  Jennifer K. Lee⁴  Raymond Koehler⁵  Xiuyun Liu⁶  Xiao Hu⁷  Ken M. Brady⁸ 

[1]Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK

[2]Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK

[3]Department of Anaesthesiology, University of Auckland, Auckland, New Zealand

[4]Brain Physics Laboratory, Department of Clinical Neurosciences, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK

[5]Institute of Electronic Systems, Warsaw University of Technology, Warsaw, Poland

[6]Department of Anesthesiology and Critical Care Medicine, Division of Pediatric Anesthesiology, Johns Hopkins University, Baltimore, MD, USA

[7]Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

[8]Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

[9]Department of Physiological Nursing, University of California, San Francisco, CA, USA

[10]Department of Physiological Nursing, University of California, San Francisco, CA, USA

[11]Department of Neurosurgery, School of Medicine, University of California, Los Angeles, CA, USA

[12]Department of Neurological Surgery, University of California, San Francisco, CA, USA

[13]Institute of Computational Health Sciences, University of California, San Francisco, CA, USA

[14]Northwestern University, Ann & Robert H. Lurie Children’s Hospital of Chicago, Department of Anesthesiology, Chicago, IL, USA

DOI  :  10.1038/s41598-020-62435-8

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY