The mini clinical evaluation exercise (mini-CEX) for assessing clinical performance of international medical graduates

Objective: To evaluate the feasibility, reliability and acceptability of the mini clinical evaluation exercise (mini-CEX) for performance assessment among international medical graduates (IMGs). Design, setting and participants: Observational study of 209 patient encounters involving 28 IMGs and 35 examiners at three metropolitan teaching hospitals in New South Wales, Victoria and Queensland, September-December 2006. Main outcome measures: The reliability of the mini-CEX was estimated using generatisability (G) analysis, and its acceptability was evaluated by a written survey of the examiners and IMGs. Results: The G coefficient for eight encounters was 0.88, suggesting that the reliability of the mini-CEX was 0.90 for 10 encounters. Almost half of the IMGs (7/16) and most examiners (14/18) were satisfied with the mini-CEX as a learning tool. Most of the IMGs and examiners enjoyed the immediate feedback, which is a strong component of the tool. Conclusion: The mini-CEX is a reliable tool for performance assessment of IMGs, and is acceptable to and well received by both learners and supervisors.

HER2 positive gastric and gastroesophageal adenocarcinoma; An Irish tertiary center experience

Background: Trastuzumab has been approved for patients with human epidermal growth factor receptor 2 (HER2) over expression and gene amplification metastatic gastric cancer. Here we present the prevalence of HER2 positive gastric cancer in an Irish population, the use of Trastuzumab in first line and beyond progression. Methods: The study was conducted in St James's Hospital, Dublin. A retrospective analysis of the date of patients with HER2 positive gastric cancer over a period of 3 years was carried out. Her2 positive was defined as immunohistochemistry (IHC) score of +3, of IHC score of +2 and increased gene copy number by fluorescence in situ hybridization (FISH). Overall survival was calculated from the day of initiation of treatment with Trastuzumab until death. Results: During the study period 140 patients with gastric and gastro-esophageal junction adenocarcinoma were treated. Out of those, 30 (21.4%) had HER2 positive disease. Among HER2 positive disease patients 18 (12.8%) were treated with first line Trastuzumab containing regimen with a median overall survival of 13 months. Nine (50%) developed progressive disease while on Trastuzumab and of those, 4 (22.2%) patients continued on Trastuzumab beyond progression, two (11.1%) of whom achieved stable disease and a prolonged survival. Conclusion: HER2 positivity rate in an Irish population with advanced gastric and gastro-esophageal junction adenocarcinoma is 21.4%. Treatment with Trastuzumab in the first line in combination with chemotherapy is a reasonable approach. Continuation of Trastuzumab beyond progression is a feasible strategy that requires further exploration.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.