Access to Reliable Information about Long-Term Prognosis Influences Clinical Opinion on Use of Lifesaving Intervention

Background: Decompressive craniectomy has been traditionally used as a lifesaving rescue treatment in severe traumatic brain injury (TBI). This study assessed whether objective information on long-term prognosis would influence healthcare workers ’ opinion about using decompressive craniectomy as a lifesaving procedure for patients with severe TBI. Method: A two-part structured interview was used to assess the participants ’ opinion to perform decompressive craniectomy for three patients who had very severe TBI. Their opinion was assessed before and after knowing the predicted and observed risks of an unfavourable long-term neurological outcome in various scenarios. Results: Five hundred healthcare workers with a wide variety of clinical backgrounds participated. The participants were significantly more likely to recommend decompressive craniectomy for their patients than for themselves (mean difference in visual analogue scale [VAS] 21.5, 95 % confidence interval 21.3 to 21.6), especially when the next of kin of the patients requested intervention. Patients ’ preferences were more similar to patients who had advance directives. The participants’ preferences to perform the procedure for themselves and their patients both significantly reduced after knowing the predicted risks of unfavourable outcomes, and the changes in attitude were consistent across different specialties, amount of experience in caring for similar patients, religious backgrounds, and positions in the specialty of the participants. Conclusions: Access to objective information on risk of an unfavourable long-term outcome influenced healthcare workers

Craniectomy for Malignant Cerebral Infarction: Prevalence and Outcomes in US Hospitals

Randomized trials have demonstrated the efficacy of craniectomy for the treatment of malignant cerebral edema following ischemic stroke. We sought to determine the prevalence and outcomes related to this by using a national database.Patient discharges with ischemic stroke as the primary diagnosis undergoing craniectomy were queried from the US Nationwide Inpatient Sample from 1999 to 2008. A subpopulation of patients was identified that underwent thrombolysis. Two primary end points were examined: in-hospital mortality and discharge to home/routine care. To facilitate interpretations, adjusted prevalence was calculated from the overall prevalence and two age-specific logistic regression models. The predictive margin was then generated using a multivariate logistic regression model to estimate the probability of in-hospital mortality after adjustment for admission type, admission source, length of stay, total hospital charges, chronic comorbidities, and medical complications.After excluding 71,996 patients with the diagnosis of intracranial hemorrhage and posterior intracranial circulation occlusion, we identified 4,248,955 adult hospitalizations with ischemic stroke as a primary diagnosis. The estimated rates of hospitalizations in craniectomy per 10,000 hospitalizations with ischemic stroke increased from 3.9 in 1999-2000 to 14.46 in 2007-2008 (p for linear trend<0.001). Patients 60+ years of age had in-hospital mortality of 44% while the 18-59 year old group was found to be 24% (p = 0.14). Outcomes were comparable if recombinant tissue plasminogen activator had been administered.Craniectomy is being increasingly performed for malignant cerebral edema following large territory cerebral ischemia. We suspect that the increase in the annual incidence of DC for malignant cerebral edema is directly related to the expanding collection of evidence in randomized trials that the operation is efficacious when performed in the correct patient population. In hospital mortality is high for all patients undergoing this procedure

First Order Error Correction for Trimmed Quadrature in Isogeometric Analysis

International audienceIn this work, we develop a specialized quadrature rule for trimmed domains , where the trimming curve is given implicitly by a real-valued function on the whole domain. We follow an error correction approach: In a first step, we obtain an adaptive subdivision of the domain in such a way that each cell falls in a pre-defined base case. We then extend the classical approach of linear approximation of the trimming curve by adding an error correction term based on a Taylor expansion of the blending between the linearized implicit trimming curve and the original one. This approach leads to an accurate method which improves the convergence of the quadrature error by one order compared to piecewise linear approximation of the trimming curve. It is at the same time efficient, since essentially the computation of one extra one-dimensional integral on each trimmed cell is required. Finally, the method is easy to implement, since it only involves one additional line integral and refrains from any point inversion or optimization operations. The convergence is analyzed theoretically and numerical experiments confirm that the accuracy is improved without compromising the computational complexity

Approximate implicitization via curve fitting

We discuss methods for fitting implicitly defined (e.g. piecewise algebraic) curves to scattered data, which may contain problematic regions, such as edges, cusps or vertices. As the main idea, we construct a bivariate function, whose zero contour approximates a given set of points, and whose gradient field simultaneously approximates an estimated normal field. The coefficients of the implicit representation are found by solving a system of linear equations. In order to allow for problematic input data, we introduce a criterion for detecting points close to possible singularities. Using this criterion we split the data into segments and develop methods for propagating the orientation of the normals globally. Furthermore we present a simple fallback strategy, that can be used when the process of orientation propagation fails. The method has been shown to work successfull