scholarly journals Continuous Time-Domain Cerebrovascular Reactivity Metrics and Discriminate Capacity for the Upper and Lower Limits of Autoregulation: A Scoping Review of the Animal Literature

2021 ◽  
Vol 2 (1) ◽  
pp. 639-659
Author(s):  
Amanjyot Singh Sainbhi ◽  
Logan Froese ◽  
Alwyn Gomez ◽  
Carleen Batson ◽  
Kevin Y. Stein ◽  
...  
Author(s):  
A Gomez ◽  
L Froese ◽  
AS Sainbhi ◽  
C Batson ◽  
FA Zeiler

Background: Disruption in cerebrovascular reactivity following traumatic brain injury (TBI) is a known phenomenon that may hold prognostic value. Transcranial Doppler (TCD) has been employed to evaluate cerebrovascular reactivity following injury utilizing a continuous time-series approach. Methods: A systematically conducted scoping review of the literature on the association of continuous time-domain TCD based indices of cerebrovascular reactivity, with outcomes following moderate and severe TBI was performed. Multiple databases were searched from inception to November 2020 for relevant articles. Results: Thirty-six relevant articles were identified. There was significant evidence supporting an association with continuous time-domain TCD based indices and functional outcomes following TBI. Physiologic parameters such as intracranial pressure, cerebral perfusion pressure, Carbon Dioxide (CO2) reactivity as well as more established indices of cerebrovascular reactivity have all been associated with these TCD based indices. The literature has been concentrated in a few centres and is further limited by the lack of multivariate analysis. Conclusions: There is a substantial body of evidence that cerebrovascular reactivity as measured by time-domain TCD based indices have prognostic utility following TBI. The literature supports some associations between these indices and cerebral physiologic parameters. Further validation in multi-institution studies is required before these indices can be widely adopted clinically.


2021 ◽  
Vol 12 ◽  
Author(s):  
Alwyn Gomez ◽  
Logan Froese ◽  
Amanjyot Singh Sainbhi ◽  
Carleen Batson ◽  
Frederick A. Zeiler

Background: Disruption in cerebrovascular reactivity following traumatic brain injury (TBI) is a known phenomenon that may hold prognostic value and clinical relevance. Ultimately, improved knowledge of this process and more robust means of continuous assessment may lead to advances in precision medicine following TBI. One such method is transcranial Doppler (TCD), which has been employed to evaluate cerebrovascular reactivity following injury utilizing a continuous time-series approach.Objective: The present study undertakes a scoping review of the literature on the association of continuous time-domain TCD based indices of cerebrovascular reactivity, with global functional outcomes, cerebral physiologic correlates, and imaging evidence of lesion change.Design: Multiple databases were searched from inception to November 2020 for articles relevant to the association of continuous time-domain TCD based indices of cerebrovascular reactivity with global functional outcomes, cerebral physiologic correlates, and imaging evidence of lesion change.Results: Thirty-six relevant articles were identified. There was significant evidence supporting an association with continuous time-domain TCD based indices and functional outcomes following TBI. Indices based on mean flow velocity, as measured by TCD, were most numerous while more recent studies point to systolic flow velocity-based indices encoding more prognostic utility. Physiologic parameters such as intracranial pressure, cerebral perfusion pressure, Carbon Dioxide (CO2) reactivity as well as more established indices of cerebrovascular reactivity have all been associated with these TCD based indices. The literature has been concentrated in a few centres and is further limited by the lack of multivariate analysis.Conclusions: This systematic scoping review of the literature identifies that there is a substantial body of evidence that cerebrovascular reactivity as measured by time-domain TCD based indices have prognostic utility following TBI. Indices based on mean flow velocities have the largest body of literature for their support. However, recent studies indicate that indices based on systolic flow velocities may contain the most prognostic utility and more closely follow more established measures of cerebrovascular reactivity. To a lesser extent, the literature supports some associations between these indices and cerebral physiologic parameters. These indices provide a more complete picture of the patient’s physiome following TBI and may ultimately lead to personalized and precise clinical care. Further validation in multi-institution studies is required before these indices can be widely adopted clinically.


1990 ◽  
Vol 37 (8) ◽  
pp. 1057-1060 ◽  
Author(s):  
J.C. Mandojana ◽  
K.J. Herman ◽  
R.E. Zulinski

2010 ◽  
Vol 45 (9) ◽  
pp. 1795-1808 ◽  
Author(s):  
Cho-Ying Lu ◽  
Marvin Onabajo ◽  
Venkata Gadde ◽  
Yung-Chung Lo ◽  
Hsien-Pu Chen ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 758 ◽  
Author(s):  
Jialin Li ◽  
Xueyi Li ◽  
David He ◽  
Yongzhi Qu

Research on data-driven fault diagnosis methods has received much attention in recent years. The deep belief network (DBN) is a commonly used deep learning method for fault diagnosis. In the past, when people used DBN to diagnose gear pitting faults, it was found that the diagnosis result was not good with continuous time domain vibration signals as direct inputs into DBN. Therefore, most researchers extracted features from time domain vibration signals as inputs into DBN. However, it is desirable to use raw vibration signals as direct inputs to achieve good fault diagnosis results. Therefore, this paper proposes a novel method by stacking spare autoencoder (SAE) and Gauss-Binary restricted Boltzmann machine (GBRBM) for early gear pitting faults diagnosis with raw vibration signals as direct inputs. The SAE layer is used to compress the raw vibration data and the GBRBM layer is used to effectively process continuous time domain vibration signals. Vibration signals of seven early gear pitting faults collected from a gear test rig are used to validate the proposed method. The validation results show that the proposed method maintains a good diagnosis performance under different working conditions and gives higher diagnosis accuracy compared to other traditional methods.


Sign in / Sign up

Export Citation Format

Share Document