Tendances parmi les candidats en ophtalmologie non jumelés dans le cadre du Service canadien de jumelage des résidents

Background: Applicants to ophthalmology have high rates of going unmatched during the CaRMS process, but how this compares to other competitive or surgical specialties remains unclear. Our research aims to examine this phenomenon by identifying trends and comparing match data with other specialties, to identify disparities that may inform the need for future interventions to improve the match process for applicants. Methods: We used a cross-sectional analysis of data provided by CaRMS on the residency match from 2013 to 2022. Results: We obtained data from 608 ophthalmology, 5,153 surgery, and 3,092 top five (most competitive) specialty first choice applicants from 2013-2022. Ophthalmology applicants were more likely to go unmatched (18.9% [120/608]) than applicants to the top five (11.9% [371/3,092]) and surgical (13.5% [702/5,153]) specialties (p<0.001) and were twice as likely to rank no alternate disciplines (31.8%, p < 0.001) over the study period. In the first iteration, when alternate disciplines were ranked, the match rate to alternate disciplines was highest for ophthalmology applicants (0.41, p < 0.001). The majority (57.8%) of unmatched ophthalmology applicants do not participate in the second iteration. Conclusion: Compared to other competitive specialties, first choice ophthalmology applicants were more likely to go unmatched, rank no alternate disciplines, and choose not to participate in the second iteration. Ophthalmology applicant behaviours should be further studied to help explain these study findings.Contexte : Les candidats à l'ophtalmologie ont un taux élevé de non-jumelage au cours du processus CaRMS, mais une comparaison avec d'autres spécialités compétitives ou chirurgicales reste à faire. Notre travail a pour but d’examiner ce phénomène en identifiant des tendances et en comparant les données de jumelage avec celles d'autres spécialités, à la recherche de disparités susceptibles d'éclairer le besoin d'interventions futures pour améliorer le processus de jumelage pour les candidats. Méthodes : Nous avons procédé à une analyse transversale des données fournies par CaRMS sur le jumelage des résidents de 2013 à 2022. Résultats : Nous avons obtenu des données sur 608 candidats en ophtalmologie, 5 153 en chirurgie et 3 092 candidats dont le premier choix était l’une des cinq spécialités les plus compétitives de 2013 à 2022. Les candidats en ophtalmologie étaient plus susceptibles de ne pas être jumelés (18,9 % [120/608]) que les candidats aux cinq spécialités les plus compétitives (11,9 % [371/3 092]) et aux spécialités chirurgicales (13,5 % [702/5 153]) (p<0,001), et étaient deux fois plus susceptibles de ne classer aucune autre discipline (31,8 %, p<0,001) au cours de la période d'étude. Lors du premier tour, lorsque des disciplines alternatives ont été classées, le taux de jumelage avec les disciplines alternatives était le plus élevé pour les candidats en ophtalmologie (0,41, p<0,001). La majorité (57,8 %) des candidats non jumelés en ophtalmologie ne participent pas au deuxième tour. Conclusion : Comparativement à d'autres spécialités compétitives, les candidats dont le premier choix étaient l’ophtalmologie étaient plus susceptibles de ne pas être jumelés, de ne pas classer d'autres disciplines et de choisir de ne pas participer au deuxième tour. Les comportements des candidats en ophtalmologie devraient faire l'objet d'études plus approfondies afin d'expliquer nos résultats

Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics

A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease prediction. Supported by a vast literature on the predictive power of neural networks, our proposed solution uses neural networks to extract from neuroimaging data features that are relevant for predicting Alzheimer's Disease (AD) for subsequent relation to genetics. Our neuroimaging-genetic pipeline is comprised of image processing, neuroimaging feature extraction and genetic association steps. We propose a neural network classifier for extracting neuroimaging features that are related with disease and a multivariate Bayesian group sparse regression model for genetic association. We compare the predictive power of these features to expert selected features and take a closer look at the SNPs identified with the new neuroimaging features.Comment: Under revie

Successful radiopeptide targeting of metastatic anaplastic meningioma: Case report

A patient with anaplastic meningioma and lung metastases resistant to conventional treatment underwent radiopeptide therapy with 177Lu- DOTA-octreotate in our institute. The treatment resulted in significant improvement in patient's quality of life and inhibition of tumor progression. This case may eventually help to establish the value of radiopeptide therapy in patients with this rare condition

Internet-based medical education: a realist review of what works, for whom and in what circumstances

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Acquired Epidermodysplasia Verruciformis Due to Multiple and Unusual HPV Infection Among Vertically-Infected, HIV-Positive Adolescents in Zimbabwe

We have characterized the EV-like dermatosis of acquired HIV in 4 adolescents. Multiple HPV types were isolated in skin tissue samples, including β-HPV, but also high levels of HPV 1 and 2. ARV did not improve the EV eruption

Clinical Predictors and Outcome of Metabolic Acidosis in Under-Five Children Admitted to an Urban Hospital in Bangladesh with Diarrhea and Pneumonia

BACKGROUND: Clinical features of metabolic acidosis and pneumonia frequently overlap in young diarrheal children, resulting in differentiation from each other very difficult. However, there is no published data on the predictors of metabolic acidosis in diarrheal children also having pneumonia. Our objective was to evaluate clinical predictors of metabolic acidosis in under-five diarrheal children with radiological pneumonia, and their outcome. METHODS: We prospectively enrolled all under-five children (n = 164) admitted to the Special Care Ward (SCW) of the Dhaka Hospital of icddr, b between September and December 2007 with diarrhea and radiological pneumonia who also had their total serum carbon-dioxide estimated. We compared the clinical features and outcome of children with radiological pneumonia and diarrhea with (n = 98) and without metabolic acidosis (n = 66). RESULTS: Children with metabolic acidosis more often had higher case-fatality (16% vs. 5%, p = 0.039) compared to those without metabolic acidosis on admission. In logistic regression analysis, after adjusting for potential confounders such as age of the patient, fever on admission, and severe wasting, the independent predictors of metabolic acidosis in under-five diarrheal children having pneumonia were clinical dehydration (OR 3.57, 95% CI 1.62-7.89, p = 0.002), and low systolic blood pressure even after full rehydration (OR 1.02, 95% CI 1.01-1.04, p = 0.005). Proportions of children with cough, respiratory rate/minute, lower chest wall indrawing, nasal flaring, head nodding, grunting respiration, and cyanosis were comparable (p>0.05) among the groups. CONCLUSION AND SIGNIFICANCE: Under-five diarrheal children with radiological pneumonia having metabolic acidosis had frequent fatal outcome than those without acidosis. Clinical dehydration and persistent systolic hypotension even after adequate rehydration were independent clinical predictors of metabolic acidosis among the children. However, metabolic acidosis in young diarrheal children had no impact on the diagnostic clinical features of radiological pneumonia which underscores the importance of early initiation of appropriate antibiotics to combat morbidity and deaths in such population

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines

The association of APOE genotype and cognitive decline in interaction with risk factors in a 65–69 year old community sample

<p>Abstract</p> <p>Background</p> <p>While the evidence of an association between the apolipoprotein E (<it>APOE</it>) <it>*E4 </it>allele and Alzheimer's disease is very strong, the effect of the <it>*E4 </it>allele on cognitive decline in the general population is more equivocal. A cross-sectional study on the lifespan effects of the <it>*E4 </it>allele <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> failed to find any effect of the <it>*E4 </it>allele on cognitive performance at ages 20–24, 40–44 or 60–64 years.</p> <p>Methods</p> <p>In this four year follow-up study, we reexamine the effect of <it>*E4 </it>in the sample of 2,021 individuals, now aged 65–69 years.</p> <p>Results</p> <p>Performance on the Mini-Mental State Examination (MMSE) was significantly poorer for <it>*E4 </it>homozygotes than heterozygotes or non-carriers. The effects of the <it>*E4 </it>genotype on cognitive decline over four years were found on the MMSE and Symbol-Digit Modalities test but only when controlling for risk factors such as head injury and education. Analyses were repeated with the exclusion of participants diagnosed with a mild cognitive disorder, with little change.</p> <p>Conclusion</p> <p>It is possible that <it>*E4 </it>carriers become vulnerable to greater cognitive decline in the presence of other risk factors at 65–69 years of age.</p

Enterohaemorrhagic Escherichia coli and Shigella dysenteriae type 1-induced haemolytic uraemic syndrome

Haemolytic uraemic syndrome (HUS) can be classified according to the aetiology of the different disorders from which it is composed. The most prevalent form is that induced by shigatoxin producing Escherichia coli (STEC) and, in some tropical regions, by Shigella dysenteriae type 1. STEC cause a zoonosis, are widely distributed in nature, enter the food chain in different ways, and show regional differences. Not all STEC are human pathogens. Enterohaemorrhagic E. coli usually cause attachment and effacing lesions in the intestine. This is not essential, but production of a shigatoxin (Stx) is. Because Stx are encoded by a bacteriophage, this property is transferable to naïve strains. Laboratory methods have improved by identifying STEC either via the toxin or its bacteriophage. Shigella dysenteriae type 1 produces shigatoxin, identical to Stx-1, but also has entero-invasive properties that enterohaemorrhagic Escherichia coli (EHEC) do not. Shigella patients risk bacteremia and benefit from early antibiotic treatment, unlike those with EHEC