2016
DOI: 10.1097/ccm.0000000000001838
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Predicting Intracranial Pressure and Brain Tissue Oxygen Crises in Patients With Severe Traumatic Brain Injury

Abstract: Our algorithms provide accurate and timely predictions of intracranial hypertension and tissue hypoxia crises in patients with severe traumatic brain injury. Almost all of the information needed to predict the onset of these events is contained within the signal of interest and the time since last crisis.

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Cited by 47 publications
(63 citation statements)
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“…Primary injury is characterized by immediate bleeding and loss of brain tissue when a blunt or sharp object impacts the head. Secondary injury involves complicated cellular and biochemical cascade reactions, including oxidative stress, excitotoxicity, neuroinflammation, free radical-induced injury, and calcium-mediated damage, which lead to blood-brain barrier (BBB) damage, elevated intracranial pressure, cerebral hypoxia, brain edema, and neuronal apoptosis (38). Mitochondrial dysfunction has been demonstrated to be a key participant in the pathological processes of secondary brain injury (9, 10).…”
Section: Introductionmentioning
confidence: 99%
“…Primary injury is characterized by immediate bleeding and loss of brain tissue when a blunt or sharp object impacts the head. Secondary injury involves complicated cellular and biochemical cascade reactions, including oxidative stress, excitotoxicity, neuroinflammation, free radical-induced injury, and calcium-mediated damage, which lead to blood-brain barrier (BBB) damage, elevated intracranial pressure, cerebral hypoxia, brain edema, and neuronal apoptosis (38). Mitochondrial dysfunction has been demonstrated to be a key participant in the pathological processes of secondary brain injury (9, 10).…”
Section: Introductionmentioning
confidence: 99%
“…Prec@75Rec Prec@90Rec AUPRC Optimal 0.377 ± 0.001 0.303 ± 0.001 0.517 ± 0.003 BL1: Hu et al [20] 0.331 ± 0.001 0.274 ± 0.001 0.473 ± 0.003 BL2: Myers et al [21] 0.338 ± 0.002 0.259 ± 0.001 0.484 ± 0.003…”
Section: Modelsmentioning
confidence: 99%
“…This requires exploration of high-quality large multivariate datasets comprised of continuous, real time physiologic data, and clinical/imaging characteristics to identify phenotypes of injury and patient-specific pathophysiological trajectories. Machine learning methodologies have been emerging with high accuracy in predicting episodes of IHT or brain tissue hypoxia; they do though require prospective validation [29][30][31]. In this overall direction, hugely important are ongoing collaborative projects such as Transforming Research and Clinical Knowledge in TBI (TRACK TBI), and CENTER-TBI.…”
Section: Concluding Thoughts On Future Directionsmentioning
confidence: 99%