Point‐of‐Care Non‐Invasive Assessments of Cerebrovascular Reactivity in Traumatic Brain Injury: Integrating the Physiome with Clinical Phenotype

2021 ◽  
Author(s):  
FA Zeiler
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Clinical Phenotype ◽  
Point Of Care ◽  
Cerebrovascular Reactivity ◽  
Non Invasive

Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury

2020 ◽  
Vol 132 (6) ◽  
pp. 1952-1960 ◽  
Author(s):  
Seung-Bo Lee ◽  
Hakseung Kim ◽  
Young-Tak Kim ◽  
Frederick A. Zeiler ◽  
Peter Smielewski ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Neurological Status ◽  
Cerebrovascular Reactivity ◽  
Cerebral Hypoperfusion ◽  
Clinical Parameters ◽  
Artifact Removal ◽  
Clinical Events ◽  
Arterial Blood ◽  
Before And After

OBJECTIVEMonitoring intracranial and arterial blood pressure (ICP and ABP, respectively) provides crucial information regarding the neurological status of patients with traumatic brain injury (TBI). However, these signals are often heavily affected by artifacts, which may significantly reduce the reliability of the clinical determinations derived from the signals. The goal of this work was to eliminate signal artifacts from continuous ICP and ABP monitoring via deep learning techniques and to assess the changes in the prognostic capacities of clinical parameters after artifact elimination.METHODSThe first 24 hours of monitoring ICP and ABP in a total of 309 patients with TBI was retrospectively analyzed. An artifact elimination model for ICP and ABP was constructed via a stacked convolutional autoencoder (SCAE) and convolutional neural network (CNN) with 10-fold cross-validation tests. The prevalence and prognostic capacity of ICP- and ABP-related clinical events were compared before and after artifact elimination.RESULTSThe proposed SCAE-CNN model exhibited reliable accuracy in eliminating ABP and ICP artifacts (net prediction rates of 97% and 94%, respectively). The prevalence of ICP- and ABP-related clinical events (i.e., systemic hypotension, intracranial hypertension, cerebral hypoperfusion, and poor cerebrovascular reactivity) all decreased significantly after artifact removal.CONCLUSIONSThe SCAE-CNN model can be reliably used to eliminate artifacts, which significantly improves the reliability and efficacy of ICP- and ABP-derived clinical parameters for prognostic determinations after TBI.

Critical Thresholds for Cerebrovascular Reactivity After Traumatic Brain Injury

2011 ◽  
Vol 16 (2) ◽  
pp. 258-266 ◽  
Author(s):  
E. Sorrentino ◽  
J. Diedler ◽  
M. Kasprowicz ◽  
K. P. Budohoski ◽  
C. Haubrich ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cerebrovascular Reactivity ◽  
Critical Thresholds

scholarly journals Detection of S-100β Protein in Plasma and Urine After a Mild Traumatic Brain Injury

2019 ◽  
Vol 46 (5) ◽  
pp. 599-602 ◽  
Author(s):  
Natalie Le Sage ◽  
Pier-Alexandre Tardif ◽  
Jérôme Frenette ◽  
Marcel Émond ◽  
Jean-Marc Chauny ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Trauma Center ◽  
Invasive Procedure ◽  
Urine Samples ◽  
Non Invasive ◽  
Plasma And Urine Samples ◽  
Level 1 ◽  
Level 1 Trauma Center

ABSTRACT:This study assessed whether S-100β protein could be measured in urine when detectable in plasma after a mild traumatic brain injury (mTBI). Clinical data, plasma and urine samples were collected for the 46 adult patients prospectively enrolled in the emergency department (ED) of a Level 1 trauma center. S-100β protein concentrations were analysed using ELISA. S-100β protein was detectable in 91% and 71% of plasma and urine samples, but values were not correlated (r = 0.002). Urine sampling would have been a non-invasive procedure, but it does not appear to be useful in the ED during the acute phase after an mTBI.

scholarly journals Transcranial Doppler Systolic Flow Index and ICP-Derived Cerebrovascular Reactivity Indices in Traumatic Brain Injury

2018 ◽  
Vol 35 (2) ◽  
pp. 314-322 ◽  
Author(s):  
Frederick A. Zeiler ◽  
Danilo Cardim ◽  
Joseph Donnelly ◽  
David K. Menon ◽  
Marek Czosnyka ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Transcranial Doppler ◽  
Cerebrovascular Reactivity ◽  
Flow Index ◽  
Reactivity Indices
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