Literature DB >> 28330412

Early Asymmetric Cardio-Cerebral Causality and Outcome after Severe Traumatic Brain Injury.

Lei Gao1, Peter Smielewski2, Marek Czosnyka2, Ari Ercole3.   

Abstract

The brain and heart are two vital systems in health and disease, increasingly recognized as a complex, interdependent network with constant information flow in both directions. After severe traumatic brain injury (TBI), the causal, directed interactions between the brain, heart, and autonomic nervous system have not been well established. Novel methods are needed to probe unmeasured, potentially prognostic information in complex biological networks that are not revealed by traditional means. In this study, we examined potential bidirectional causality between intracranial pressure (ICP), mean arterial pressure (MAP), and heart rate (HR) and its relationship to mortality in a 24-h period early post-TBI. We applied Granger causality (GC) analysis to cardio-cerebral monitoring data from 171 severe TBI patients admitted to a single neurocritical care center over a 10-year period. There was significant bidirectional causality between ICP and MAP, MAP and HR, and ICP and HR in the majority of patients (p < 0.01). MAP influenced both ICP and HR to a greater extent (higher GC, p < 0. 00001), but there was no dominant unidirectional causality between ICP and HR (p = 0.85). Those who died had significantly lower GC for ICP causing MAP and HR causing ICP (p = 0.006 and p = 0.004, respectively) and were predictors of mortality independent of age, sex, and traditional intracranial variables (ICP, cerebral perfusion pressure, GCS, and pressure reactivity index). Examining the brain and heart with GC-based features for the first time in severe TBI patients has confirmed strong interdependence and reveals a significant relationship between select causality pairs and mortality. These results support the notion that impaired causal information flow between the cerebrovascular, autonomic, and cardiovascular systems are of central importance in severe TBI.

Entities:  

Keywords:  complexity; granger causality; network; outcome; traumatic brain injury

Mesh:

Year:  2017        PMID: 28330412     DOI: 10.1089/neu.2016.4787

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  13 in total

1.  DeepClean: Self-Supervised Artefact Rejection for Intensive Care Waveform Data Using Deep Generative Learning.

Authors:  Tom Edinburgh; Peter Smielewski; Marek Czosnyka; Manuel Cabeleira; Stephen J Eglen; Ari Ercole
Journal:  Acta Neurochir Suppl       Date:  2021

2.  A pilot study evaluating a simple cardiac dysfunction score to predict complications and survival among critically-ill patients with traumatic brain injury.

Authors:  Patric W Gibbons; Robert J Goldberg; Susanne Muehlschlegel
Journal:  J Crit Care       Date:  2019-08-08       Impact factor: 3.425

Review 3.  Autoregulation in paediatric TBI-current evidence and implications for treatment.

Authors:  Joseph E Donnelly; Adam M H Young; Ken Brady
Journal:  Childs Nerv Syst       Date:  2017-09-06       Impact factor: 1.475

4.  Signal Information Prediction of Mortality Identifies Unique Patient Subsets after Severe Traumatic Brain Injury: A Decision-Tree Analysis Approach.

Authors:  Lei Gao; Peter Smielewski; Peng Li; Marek Czosnyka; Ari Ercole
Journal:  J Neurotrauma       Date:  2019-12-09       Impact factor: 5.269

5.  Development and validation of a machine-learning model for prediction of hypoxemia after extubation in intensive care units.

Authors:  Ming Xia; Chenyu Jin; Shuang Cao; Bei Pei; Jie Wang; Tianyi Xu; Hong Jiang
Journal:  Ann Transl Med       Date:  2022-05

6.  Statistical Cerebrovascular Reactivity Signal Properties after Secondary Decompressive Craniectomy in Traumatic Brain Injury: A CENTER-TBI Pilot Analysis.

Authors:  Frederick A Zeiler; Marcel Aries; Manuel Cabeleira; Thomas A van Essen; Nino Stocchetti; David K Menon; Ivan Timofeev; Marek Czosnyka; Peter Smielewski; Peter Hutchinson; Ari Ercole
Journal:  J Neurotrauma       Date:  2020-02-25       Impact factor: 5.269

7.  Fragmentation of Rest/Activity Patterns in Community-Based Elderly Individuals Predicts Incident Heart Failure.

Authors:  Lei Gao; Andrew S P Lim; Patricia M Wong; Arlen Gaba; Longchang Cui; Lei Yu; Aron S Buchman; David A Bennett; Kun Hu; Peng Li
Journal:  Nat Sci Sleep       Date:  2020-05-27

8.  Granger Causality and Jensen-Shannon Divergence to Determine Dominant Atrial Area in Atrial Fibrillation.

Authors:  Raquel Cervigón; Francisco Castells; José Manuel Gómez-Pulido; Julián Pérez-Villacastín; Javier Moreno
Journal:  Entropy (Basel)       Date:  2018-01-12       Impact factor: 2.524

Review 9.  Challenges and Opportunities in Multimodal Monitoring and Data Analytics in Traumatic Brain Injury.

Authors:  Brandon Foreman; India A Lissak; Neha Kamireddi; Dick Moberg; Eric S Rosenthal
Journal:  Curr Neurol Neurosci Rep       Date:  2021-02-02       Impact factor: 5.081

10.  Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis.

Authors:  Frederick A Zeiler; Manuel Cabeleira; Peter J Hutchinson; Nino Stocchetti; Marek Czosnyka; Peter Smielewski; Ari Ercole
Journal:  J Clin Monit Comput       Date:  2020-05-16       Impact factor: 2.502

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