Comparison of Frequency- and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia.

Brain hypoxia Cerebrovascular circulation Hypothermia Ischemia Newborn

Journal

Developmental neuroscience
ISSN: 1421-9859
Titre abrégé: Dev Neurosci
Pays: Switzerland
ID NLM: 7809375

Informations de publication

Date de publication:
02 May 2019
Historique:
received: 19 10 2018
accepted: 06 03 2019
entrez: 4 5 2019
pubmed: 3 5 2019
medline: 3 5 2019
Statut: aheadofprint

Résumé

The optimal method to detect impairments in cerebrovascular pressure autoregulation in neonates with hypoxic-ischemic encephalopathy (HIE) is unclear. Improving autoregulation monitoring methods would significantly advance neonatal neurocritical care. We tested several mathematical algorithms from the frequency and time domains in a piglet model of HIE, hypothermia, and hypotension. We used laser Doppler flowmetry and induced hypotension to delineate the gold standard lower limit of autoregulation (LLA). Receiver operating characteristics curve analyses were used to determine which indices could distinguish blood pressure above the LLA from that below the LLA in each piglet. Phase calculation in the frequency band with maximum coherence, as well as the correlation between mean arterial pressure (MAP) and near-infrared spectroscopy relative total tissue hemoglobin (HbT) or regional oxygen saturation (rSO2), accurately discriminated functional from dysfunctional autoregulation. Neither hypoxia-ischemia nor hypothermia affected the accuracy of these indices. Coherence alone and gain had low diagnostic value relative to phase and correlation. Our findings indicate that phase shift is the most accurate component of autoregulation monitoring in the developing brain, and it can be measured using correlation or by calculating phase when coherence is maximal. Phase and correlation autoregulation indices from MAP and rSO2 and vasoreactivity indices from MAP and HbT are accurate metrics that are suitable for clinical HIE studies.

Identifiants

pubmed: 31048593
pii: 000499425
doi: 10.1159/000499425
pmc: PMC6824917
mid: NIHMS1018935
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1-13

Subventions

Organisme : NINDS NIH HHS
ID : R01 NS038684
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS060703
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL139543
Pays : United States
Organisme : NINDS NIH HHS
ID : K08 NS080984
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS107417
Pays : United States

Informations de copyright

© 2019 S. Karger AG, Basel.

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Auteurs

Rathinaswamy B Govindan (RB)

Fetal Medicine Institute, Children's National Health System, Washington, District of Columbia, USA.
The George Washington University School of Medicine, Washington, District of Columbia, USA.

Ken M Brady (KM)

Department of Anesthesiology, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas, USA.

An N Massaro (AN)

Fetal Medicine Institute, Children's National Health System, Washington, District of Columbia, USA.
The George Washington University School of Medicine, Washington, District of Columbia, USA.
Neonatology, Children's National Health System, Washington, District of Columbia, USA.

Jamie Perin (J)

Center for Child and Community Health Research, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Jacky M Jennings (JM)

Center for Child and Community Health Research, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Adre J DuPlessis (AJ)

Fetal Medicine Institute, Children's National Health System, Washington, District of Columbia, USA.
The George Washington University School of Medicine, Washington, District of Columbia, USA.

Raymond C Koehler (RC)

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Jennifer K Lee (JK)

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA, jklee@jhmi.edu.

Classifications MeSH