Articles: traumatic-brain-injuries.
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J Clin Monit Comput · Feb 2019
Multicenter StudyForewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.
Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most dangerous secondary insults and is related to poor outcome in patients. The overall aim of this study was to get proof of the concept that advanced statistical techniques (machine learning) are methods that are able to provide early warning of impending hypotensive events before they occur during neuro-critical care. ⋯ With a decision threshold of 0.3, > 15 min warning of patient instability can be achieved. We have shown, using advanced machine learning techniques running in a live neuro-critical care environment, that it would be possible to give neurointensive teams early warning of potential hypotensive events before they emerge, allowing closer monitoring and earlier clinical assessment in an attempt to prevent the onset of hypotension. The multi-centre clinical infrastructure developed to support the clinical studies provides a solid base for further collaborative research on data quality, false positive correction and the display of early warning data in a clinical setting.
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Randomized Controlled Trial Multicenter Study
Evaluation of a targeted, theory-informed implementation intervention designed to increase uptake of emergency management recommendations regarding adult patients with mild traumatic brain injury: results of the NET cluster randomised trial.
Evidence-based guidelines for management of mild traumatic brain injury (mTBI) in the emergency department (ED) are now widely available; however, clinical practice remains inconsistent with these guidelines. A targeted, theory-informed implementation intervention (Neurotrauma Evidence Translation (NET) intervention) was designed to increase the uptake of three clinical practice recommendations regarding the management of patients who present to Australian EDs with mild head injuries. The intervention involved local stakeholder meetings, identification and training of nursing and medical local opinion leaders, train-the-trainer workshops and standardised education materials and interactive workshops delivered by the opinion leaders to others within their EDs during a 3 month period. This paper reports on the effects of this intervention. ⋯ Our intervention was effective in improving the uptake of the PTA recommendation; however, it did not appreciably increase the uptake of the other two practice recommendations. Improved screening for PTA may be clinically important as it leads to appropriate periods of observation prior to safe discharge. The estimated intervention effect on anxiety was of limited clinical significance. We were not able to compare characteristics of EDs who declined trial participation with those of participating sites, which may limit the generalizability of the results.
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Brain injury : [BI] · Jan 2019
Multicenter Study Comparative Study Observational StudyComparison of the Neurobehavioral Symptom Inventory and the Rivermead Postconcussion Symptoms Questionnaire.
Objective: This study sought to determine the similarity of constructs measured by the Neurobehavioral Symptom Inventory (NSI) and Rivermead Postconcussive Symptoms Questionnaire (RPQ) and the potential for interchangeability of scores from the two scales. Setting: Three acute inpatient rehabilitation hospitals in the USA. Participants: 497 community dwelling persons with traumatic brain injury (TBI) who completed the NSI and the RPQ during the same assessment. ⋯ A crosswalk between the two measures was created by equating scores from the scales based on percentile ranks. Conclusion: Results indicate substantial conceptual and empirical overlap between the NSI and RPQ. The percentile crosswalk developed from this dataset may allow combined analysis of post-concussive symptoms from datasets that include either the NSI or the RPQ.
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Journal of neurotrauma · Jan 2019
Multicenter StudyTesting a Multivariate Proteomic Panel for Traumatic Brain Injury Biomarker Discovery: A TRACK-TBI Pilot Study.
The complex and heterogeneous nature of traumatic brain injury (TBI) has rendered the identification of diagnostic and prognostic biomarkers elusive. A single acute biomarker may not be sufficient to categorize injury severity and/or predict outcome. Using multivariate dimension reduction analyses, we tested the sensitivity and specificity of a multi-analyte panel of proteins as an ensemble biomarker for TBI. ⋯ Inflammatory signatures were significantly increased in patients with positive CT findings, as well as in those who showed poor or incomplete recovery. Inflammation biomarker scores also showed significant sensitivity and specificity as a discriminator of these outcome measures (all areas under the curve [AUCs] >0.62). This proof of concept for the feasibility of multivariate biomarker identification demonstrates the prognostic validity of using a proteomic panel as a potential biomarker for TBI.
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Multicenter Study
Comparison of two simple models for prediction of short term mortality in patients after severe traumatic brain injury.
The subscale motor score of Glasgow Coma Scale (msGCS) and the Abbreviated Injury Score of head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim was to compare the prognostic performance of a HAIS-based prediction model including HAIS, pupil reactivity and age, and the reference prediction model including msGCS in emergency department (ED), pupil reactivity and age. ⋯ Performance of prediction for short-term mortality after severe TBI with HAIS-based prediction model was non-inferior to reference prediction model using msGCS as predictor.