The choice of anesthesia influences oxidative energy metabolism and tissue survival in critically ischemic murine skin

In surgical animal studies anesthesia is used regularly. Several reports in the literature demonstrate respiratory and cardiovascular side effects of anesthesiologic agents. The aim of this study was to compare two frequently used anesthesia cocktails (ketamine/xylazine [KX] versus medetomidine/climazolam/fentanyl [MCF]) in skin flap mouse models. Systemic blood values, local metabolic parameters, and surgical outcome should be analyzed in critical ischemic skin flap models. Systemic hypoxia was found in the animals undergoing KX anesthesia compared with normoxia in the MCF group (sO(2): 89.2% +/- 2.4% versus 98.5% +/- 1.2%, P < 0.01). Analysis of tissue metabolism revealed impaired anaerobic oxygen metabolism and increased cellular damage in critical ischemic flap tissue under KX anesthesia (lactate/pyruvate ratio: KX 349.86 +/- 282.38 versus MCF 64.53 +/- 18.63; P < 0.01 and glycerol: KX 333.50 +/- 83.91 micromol/L versus MCF 195.83 +/- 29.49 micromol/L; P < 0.01). After 6 d, different rates of flap tissue necrosis could be detected (MCF 57% +/- 6% versus KX 68% +/- 6%, P < 0.01). In summary we want to point out that the type of anesthesia, the animal model and the goal of the study have to be well correlated. Comparing the effects of KX and MCF anesthesia in mice on surgical outcome was a novel aspect of our study.

Rarely selected distractors in high stakes medical multiple-choice examinations and their recognition by item authors: A simulation and survey

Background Many medical exams use 5 options for multiple choice questions (MCQs), although the literature suggests that 3 options are optimal. Previous studies on this topic have often been based on non-medical examinations, so we sought to analyse rarely selected, 'non-functional' distractors (NF-D) in high stakes medical examinations, and their detection by item authors as well as psychometric changes resulting from a reduction in the number of options. Methods Based on Swiss Federal MCQ examinations from 2005-2007, the frequency of NF-D (selected by <1% or <5% of the candidates) was calculated. Distractors that were chosen the least or second least were identified and candidates who chose them were allocated to the remaining options using two extreme assumptions about their hypothetical behaviour: In case rarely selected distractors were eliminated, candidates could randomly choose another option - or purposively choose the correct answer, from which they had originally been distracted. In a second step, 37 experts were asked to mark the least plausible options. The consequences of a reduction from 4 to 3 or 2 distractors - based on item statistics or on the experts' ratings - with respect to difficulty, discrimination and reliability were modelled. Results About 70% of the 5-option-items had at least 1 NF-D selected by <1% of the candidates (97% for NF-Ds selected by <5%). Only a reduction to 2 distractors and assuming that candidates would switch to the correct answer in the absence of a 'non-functional' distractor led to relevant differences in reliability and difficulty (and to a lesser degree discrimination). The experts' ratings resulted in slightly greater changes compared to the statistical approach. Conclusions Based on item statistics and/or an expert panel's recommendation, the choice of a varying number of 3-4 (or partly 2) plausible distractors could be performed without marked deteriorations in psychometric characteristics.

Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.