Intracranial Pressure Monitoring Signals After Traumatic Brain Injury: A Narrative Overview and Conceptual Data Science Framework.

Continuous intracranial pressure (ICP) monitoring is a cornerstone of neurocritical care after severe brain injuries such as traumatic brain injury and acts as a biomarker of secondary brain injury. With the rapid development of artificial intelligent (AI) approaches to data analysis, the acquisition, storage, real-time analysis, and interpretation of physiological signal data can bring insights to the field of neurocritical care bioinformatics. We review the existing literature on the quantification and analysis of the ICP waveform and present an integrated framework to incorporate signal processing tools, advanced statistical methods, and machine learning techniques in order to comprehensively understand the ICP signal and its clinical importance. Our goals were to identify the strengths and pitfalls of existing methods for data cleaning, information extraction, and application. In particular, we describe the use of ICP signal analytics to detect intracranial hypertension and to predict both short-term intracranial hypertension and long-term clinical outcome. We provide a well-organized roadmap for future researchers based on existing literature and a computational approach to clinically-relevant biomedical signal data.

A similarity based methodology for machine prognostics by using kernel two sample test.

This paper proposes a novel similarity-based algorithm for Remaining Useful Life (RUL) prediction and a methodology for machine prognostics. In the proposed RUL prediction algorithm, a Similarity Matching Procedure including the Kernel Two Sample Test (KTST) is developed to query similar run-to-failure (R2F) profiles from historical data library. Next, the preliminary predictions of RUL are obtained as remaining time-to-failure from the similar R2F records. In the last step, Weibull analysis is performed to fuse the preliminary predictions and to obtain the probability distribution of RUL. Moreover, a methodology for machine prognostics is developed based on the RUL prediction algorithm. Compared with existing similarity-based methods for RUL prediction, the proposed method holds several advantages: 1) the similarities between sensor readings or feature matrices are directly measured without extra health assessment procedure; 2) the proposed method presents good probabilistic interpretations of the prediction uncertainties; 3) the estimated RUL distribution is statistically sound by applying KTST to prescreening the historical R2F records. The effectiveness and the superiority of the proposed method are justified based on the public aero-engine dataset.

Prognostic Value of Spreading Depolarizations in Patients With Severe Traumatic Brain Injury.

Importance: Advances in treatment of traumatic brain injury are hindered by the inability to monitor pathological mechanisms in individual patients for targeted neuroprotective treatment. Spreading depolarizations, a mechanism of lesion development in animal models, are a novel candidate for clinical monitoring in patients with brain trauma who need surgery. Objective: To test the null hypothesis that spreading depolarizations are not associated with worse neurologic outcomes. Design, Setting, and Participants: This prospective, observational, multicenter cohort study was conducted from February 2009 to August 2013 in 5 level 1 trauma centers. Consecutive patients who required neurological surgery for treatment of acute brain trauma and for whom research consent could be obtained were enrolled; participants were excluded because of technical problems in data quality, patient withdrawal, or loss to follow-up. Primary statistical analysis took place from April to December 2018. Evaluators of outcome assessments were blinded to other measures. Interventions: A 6-contact electrode strip was placed on the brain surface during surgery for continuous electrocorticography during intensive care. Main Outcomes and Measures: Electrocorticography was scored for depolarizations, following international consensus procedures. Six-month outcomes were assessed by the Glasgow Outcome Scale-Extended score. Results: A total of 157 patients were initially enrolled; 19 were subsequently excluded. The 138 remaining patients (104 men [75%]; median [interquartile range] age, 45 [29-64] years) underwent a median (interquartile range) of 75.5 (42.2-117.1) hours of electrocorticography. A total of 2837 spreading depolarizations occurred in 83 of 138 patients (60.1% incidence) who, compared with patients who did not have spreading depolarizations, had lower prehospital systolic blood pressure levels (mean [SD], 133 [31] mm Hg vs 146 [33] mm Hg; P = .03), more traumatic subarachnoid hemorrhage (depolarization incidences of 17 of 37 [46%], 18 of 32 [56%], 22 of 33 [67%], and 23 of 30 patients [77%] for Morris-Marshall Grades 0, 1, 2, and 3/4, respectively; P = .047), and worse radiographic pathology (in 38 of 73 patients [52%] and 42 of 60 patients [70%] for Rotterdam Scores 2-4 vs 5-6, respectively; P = .04). Of patients with depolarizations, 32 of 83 (39%) had only sporadic events that induced cortical spreading depression of spontaneous electrical activity, whereas 51 of 83 patients (61%) exhibited temporal clusters of depolarizations (≥3 in a 2-hour span). Nearly half of those with clusters (23 of 51 [45%]) also had depolarizations in an electrically silent area of the cortex (isoelectric spreading depolarization). Patients with clusters did not improve in motor neurologic examinations from presurgery to postelectrocorticography, while other patients did improve. In multivariate ordinal regression adjusting for baseline prognostic variables, the occurrence of depolarization clusters had an odds ratio of 2.29 (95% CI, 1.13-4.65; P = .02) for worse outcomes. Conclusions and Relevance: In this cohort study of patients with acute brain trauma, spreading depolarizations were predominant but heterogeneous and independently associated with poor neurologic recovery. Monitoring the occurrence of spreading depolarizations may identify patients most likely to benefit from targeted management strategies.

Continuous Electroencephalography After Moderate to Severe Traumatic Brain Injury.

OBJECTIVES: After traumatic brain injury, continuous electroencephalography is widely used to detect electrographic seizures. With the development of standardized continuous electroencephalography terminology, we aimed to describe the prevalence and burden of ictal-interictal patterns, including electrographic seizures after moderate-to-severe traumatic brain injury and to correlate continuous electroencephalography features with functional outcome. DESIGN: Post hoc analysis of the prospective, randomized controlled phase 2 multicenter INTREPID study (ClinicalTrials.gov: NCT00805818). Continuous electroencephalography was initiated upon admission to the ICU. The primary outcome was the 3-month Glasgow Outcome Scale-Extended. Consensus electroencephalography reviews were performed by raters certified in standardized continuous electroencephalography terminology blinded to clinical data. Rhythmic, periodic, or ictal patterns were referred to as "ictal-interictal continuum"; severe ictal-interictal continuum was defined as greater than or equal to 1.5 Hz lateralized rhythmic delta activity or generalized periodic discharges and any lateralized periodic discharges or electrographic seizures. SETTING: Twenty U.S. level I trauma centers. PATIENTS: Patients with nonpenetrating traumatic brain injury and postresuscitation Glasgow Coma Scale score of 4-12 were included. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 152 patients with continuous electroencephalography (age 34 ± 14 yr; 88% male), 22 (14%) had severe ictal-interictal continuum including electrographic seizures in four (2.6%). Severe ictal-interictal continuum burden correlated with initial prognostic scores, including the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (r = 0.51; p = 0.01) and Injury Severity Score (r = 0.49; p = 0.01), but not with functional outcome. After controlling clinical covariates, unfavorable outcome was independently associated with absence of posterior dominant rhythm (common odds ratio, 3.38; 95% CI, 1.30-9.09), absence of N2 sleep transients (3.69; 1.69-8.20), predominant delta activity (2.82; 1.32-6.10), and discontinuous background (5.33; 2.28-12.96) within the first 72 hours of monitoring. CONCLUSIONS: Severe ictal-interictal continuum patterns, including electrographic seizures, were associated with clinical markers of injury severity but not functional outcome in this prospective cohort of patients with moderate-to-severe traumatic brain injury. Importantly, continuous electroencephalography background features were independently associated with functional outcome and improved the area under the curve of existing, validated predictive models.