http://repub.eur.nl/res/aut/47988/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/34338/ 2011-12-01T00:00:00Z Background: Pathological waves of spreading mass neuronal depolarisation arise repeatedly in injured, but potentially salvageable, grey matter in 50-60% of patients after traumatic brain injury (TBI). We aimed to ascertain whether spreading depolarisations are independently associated with unfavourable neurological outcome. Methods: We did a prospective, observational, multicentre study at seven neurological centres. We enrolled 109 adults who needed neurosurgery for acute TBI. Spreading depolarisations were monitored by electrocorticography during intensive care and were classified as cortical spreading depression (CSD) if they took place in spontaneously active cortex or as isoelectric spreading depolarisation (ISD) if they took place in isoelectric cortex. Investigators who treated patients and assessed outcome were masked to electrocorticographic results. Scores on the extended Glasgow outcome scale at 6 months were fitted to a multivariate model by ordinal regression. Prognostic score (based on variables at admission, as validated by the IMPACT studies) and spreading depolarisation category (none, CSD only, or at least one ISD) were assessed as outcome predictors. Findings: Six individuals were excluded because of poor-quality electrocorticography. A total of 1328 spreading depolarisations arose in 58 (56%) patients. In 38 participants, all spreading depolarisations were classified as CSD; 20 patients had at least one ISD. By multivariate analysis, both prognostic score (p=0·0009) and spreading depolarisation category (p=0·0008) were significant predictors of neurological outcome. CSD and ISD were associated with an increased risk of unfavourable outcome (common odds ratios 1·56 [95% CI 0·72-3·37] and 7·58 [2·64-21·8], respectively). Addition of depolarisation category to the regression model increased the proportion of variance in outcome that could be attributed to predictors from 9% to 22%, compared with the prognostic score alone. Interpretation: Spreading depolarisations were associated with unfavourable outcome, after controlling for conventional prognostic variables. The possibility that spreading depolarisations have adverse effects on the traumatically injured brain, and therefore might be a target in the treatment of TBI, deserves further research. Funding: US Army CDMRP PH/TBI research programme. http://repub.eur.nl/res/pub/32361/ 2008-07-01T00:00:00Z The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and assessment tools were discussed. Recommendations were made for enhancing the utility of available or emerging tools in order to facilitate implementation of a pathoanatomic classification approach for clinical trials.