EARLYDRAIN- outcome after early lumbar CSF-drainage in aneurysmal subarachnoid hemorrhage: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Aneurysmal subarachnoid hemorrhage (SAH) may be complicated by delayed cerebral ischemia, which is a major cause of unfavorable clinical outcome and death in SAH-patients. Delayed cerebral ischemia is presumably related to the development of vasospasm triggered by the presence of blood in the basal cisterns. To date, oral application of the calcium antagonist nimodipine is the only prophylactic treatment for vasospasm recognized under international guidelines.</p> <p>In retrospective trials lumbar drainage of cerebrospinal fluid has been shown to be a safe and feasible measure to remove the blood from the basal cisterns and decrease the incidence of delayed cerebral ischemia and vasospasm in the respective study populations. However, the efficacy of lumbar drainage has not been evaluated prospectively in a randomized controlled trial yet.</p> <p>Methods/Design</p> <p>This is a protocol for a 2-arm randomized controlled trial to compare an intervention group receiving early continuous lumbar CSF-drainage and standard neurointensive care to a control group receiving standard neurointensive care only. Adults suffering from a first aneurysmal subarachnoid hemorrhage whose aneurysm has been secured by means of coiling or clipping are eligible for trial participation. The effect of early CSF drainage (starting < 72 h after securing the aneurysm) will be measured in the following ways: the primary endpoint will be disability after 6 months, assessed by a blinded investigator during a personal visit or standardized telephone interview using the modified Rankin Scale. Secondary endpoints include mortality after 6 months, angiographic vasospasm, transcranial Doppler sonography (TCD) mean flow velocity in both middle cerebral arteries and rate of shunt insertion at 6 months after hospital discharge.</p> <p>Discussion</p> <p>Here, we present the study design of a multicenter prospective randomized controlled trial to investigate whether early application of a lumbar drainage improves clinical outcome after aneurysmal subarachnoid hemorrhage.</p> <p>Trial registration</p> <p>www.clinicaltrials.gov Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01258257">NCT01258257</a></p

Computational modelling in disorders of consciousness: closing the gap towards personalised models for restoring consciousness

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges

Assessing organisational readiness for change:Use of diagnostic analysis prior to the implementation of a multidisciplinary assessment for acute stroke care

BACKGROUND: Achieving evidence-based practice in health care is integral to the drive for quality improvement in the National Health Service in the UK. Encapsulated within this policy agenda are challenges inherent in leading and managing organisational change. Not least of these is the need to change the behaviours of individuals and groups in order to embed new practices. Such changes are set within a context of organisational culture that can present a number of barriers and facilitators to change. Diagnostic analysis has been recommended as a precursor to the implementation of change to enable such barriers and facilitators to be identified and a targeted implementation strategy developed. Although diagnostic analysis is recommended, there is a paucity of advice on appropriate methods to use. This paper addresses the paucity and builds on previous work by recommending a mixed method approach to diagnostic analysis comprising both quantitative and qualitative data. METHODS: Twenty staff members with strategic accountability for stroke care were purposively sampled to take part in semi-structured interviews. Six recently discharged patients were also interviewed. Focus groups were conducted with one group of registered ward-based nurses (n = 5) and three specialist registrars (n = 3) purposively selected for their interest in stroke care. All professional staff on the study wards were sent the Team Climate Inventory questionnaire (n = 206). This elicited a response rate of 72% (n = 148). RESULTS: A number of facilitators for change were identified, including stakeholder support, organisational commitment to education, strong team climate in some teams, exemplars of past successful organisational change, and positive working environments. A number of barriers were also identified, including: unidisciplinary assessment/recording practices, varying in structure and evidence-base; weak team climate in some teams; negative exemplars of organisational change; and uncertainty created by impending organisational merger. CONCLUSION: This study built on previous research by proposing a mixed method approach for diagnostic analysis. The combination of qualitative and quantitative data were able to capture multiple perspectives on barriers and facilitators to change. These data informed the tailoring of the implementation strategy to the specific needs of the Trust