Diagnosis and management of vasospasm

An overview of the main features of cerebral vasospasm is provided in this report, highlighting the possible future direction of development in the diagnosis and management of this severe complication of aneurysmal subarachnoid hemorrhage

Pro/con clinical debate: Tracheostomy is ideal for withdrawal of mechanical ventilation in severe neurological impairment

Most clinical trials on the topic of extubation have involved patients outside the neurological intensive care unit. As a result, in this area clinicians are left with little evidence on which to base their decision making. Although tracheostomies are increasingly common procedures, they are not without complications and costs, and hence a decision to perform them should not be taken lightly. In this issue of Critical Care two groups debate the merits of tracheostomy before extubation in a patient with neurological impairment. What becomes very clear is the need for more high quality data for this common clinical problem

Accuracy of Plateau Pressure and Stress Index to Identify Injurious Ventilation in Patients with Acute Respiratory Distress Syndrome.

BACKGROUND: Guidelines suggest a plateau pressure (PPLAT) of 30 cm H(2)O or less for patients with acute respiratory distress syndrome, but ventilation may still be injurious despite adhering to this guideline. The shape of the curve plotting airway pressure versus time (STRESS INDEX) may identify injurious ventilation. The authors assessed accuracy of PPLAT and STRESS INDEX to identify morphological indexes of injurious ventilation. METHODS: Indexes of lung aeration (computerized tomography) associated with injurious ventilation were used as a "reference standard." Threshold values of PPLAT and STRESS INDEX were determined assessing the receiver-operating characteristics ("training set," N = 30). Accuracy of these values was assessed in a second group of patients ("validation set," N = 20). PPLAT and STRESS INDEX were partitioned between respiratory system (Pplat,Rs and STRESS INDEX,RS) and lung (PPLAT,L and STRESS INDEX,L; esophageal pressure; "physiological set," N = 50). RESULTS: Sensitivity and specificity of PPLAT of greater than 30 cm H(2)O were 0.06 (95% CI, 0.002-0.30) and 1.0 (95% CI, 0.87-1.00). PPLAT of greater than 25 cm H(2)O and a STRESS INDEX of greater than 1.05 best identified morphological markers of injurious ventilation. Sensitivity and specificity of these values were 0.75 (95% CI, 0.35-0.97) and 0.75 (95% CI, 0.43-0.95) for PPLAT greater than 25 cm H(2)O versus 0.88 (95% CI, 0.47-1.00) and 0.50 (95% CI, 0.21-0.79) for STRESS INDEX greater than 1.05. Pplat,Rs did not correlate with PPLAT,L (R(2) = 0.0099); STRESS INDEX,RS and STRESS INDEX,L were correlated (R(2) = 0.762). CONCLUSIONS: The best threshold values for discriminating morphological indexes associated with injurious ventilation were Pplat,Rs greater than 25 cm H(2)O and STRESS INDEX,RS greater than 1.05. Although a substantial discrepancy between Pplat,Rs and PPLAT,L occurs, STRESS INDEX,RS reflects STRESS INDEX,L

European society of intensive care medicine study of therapeutic hypothermia (32-35 °C) for intracranial pressure reduction after traumatic brain injury (the Eurotherm3235Trial).

BACKGROUND: Traumatic brain injury is a major cause of death and severe disability worldwide with 1,000,000 hospital admissions per annum throughout the European Union.Therapeutic hypothermia to reduce intracranial hypertension may improve patient outcome but key issues are length of hypothermia treatment and speed of re-warming. A recent meta-analysis showed improved outcome when hypothermia was continued for between 48 hours and 5 days and patients were re-warmed slowly (1 °C/4 hours). Previous experience with cooling also appears to be important if complications, which may outweigh the benefits of hypothermia, are to be avoided. METHODS/DESIGN: This is a pragmatic, multi-centre randomised controlled trial examining the effects of hypothermia 32-35 °C, titrated to reduce intracranial pressure 20 mmHg in accordance with the Brain Trauma Foundation Guidelines, 2007. DISCUSSION: The Eurotherm3235Trial is the most important clinical trial in critical care ever conceived by European intensive care medicine, because it was launched and funded by the European Society of Intensive Care Medicine and will be the largest non-commercial randomised controlled trial due to the substantial number of centres required to deliver the target number of patients. It represents a new and fundamental step for intensive care medicine in Europe. Recruitment will continue until January 2013 and interested clinicians from intensive care units worldwide can still join this important collaboration by contacting the Trial Coordinating Team via the trial website http://www.eurotherm3235trial.eu. TRIAL REGISTRATION: Current Controlled Trials ISRCTN34555414

The brain monitoring with information technology (BrainIT) collaborative network: EC feasibility study results

The BrainIT group works collaboratively on developing standards for collection and analyses of data from brain injured patients towards providing a more efficient infrastructure for assessing new health technology. Materials and methods Over a 2 year period, core dataset data (grouped by nine categories) were collected from 200 head-injured patients by local nursing staff. Data were uploaded by the BrainIT web and random samples of received data were selected automatically by computer for validation by data validation (DV) research nurse staff against gold standard sources held in the local centre. Validated data was compared with original data sent and percentage error rates calculated by data category. Findings Comparisons, 19,461, were made in proportion to the size of the data received with the largest number checked in laboratory data (5,667) and the least in the surgery data (567). Error rates were generally less than or equal to 6%, the exception being the surgery data class where an unacceptably high error rate of 34% was found. Conclusions The BrainIT core dataset (with the exception of the surgery classification) is feasible and accurate to collect. The surgery classification needs to be revised

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio