ID-19. E-bikes have the potential to overcome some of the barriers that stroke survivors face with regards to physical activity. This study aims to explore the factors that affect e-bike usage by stroke survivors. A mixed methods multiple case studies design, using semi-structured interviews and GPS data. Subject to GP approval, participants loaned an e-bike or e-trike for up to three months. Interviews were undertaken pre and post intervention. The COM-B behaviour change model acted as a framework for analysis. GPS data relating to journey duration and distance travelled was collected fortnightly. Six participants were recruited; only three loaned an e-bike/e-trike (with adaptations as required). Storage, being unable to get GP approval, and safety were withdrawal reasons. Level of impairment was a factor influencing the type of e-bike used, level of support required and the motivation of the participants. Stroke survivors can use e-bikes although barriers exist. Electrical assistance was a positive factor was a positive factor in enabling some of the participants to cycle outdoors. Due to the small sample size and the number of participants who were able to loan an e-bike, further research is required to determine whether e-bikes are a feasible and effective intervention to increase physical activity for stroke survivors. IMPLICATIONS FOR REHABILITATION The assistance provided by the e-bike/e-trike could provide stroke survivors the opportunity to cycle outdoors. E-bikes/e-trikes could facilitate participation of activities of everyday living such as shopping, hobbies and increase levels of physical activity. Rehabilitation could focus on physical impairment, its effects on self-confidence, and knowledge surrounding the e-bike to overcome barriers to cycling. Social support, the belief that e-bike was an enjoyable mode of physical activity that was good for their health were reported by the participants as important factors for using the e-bike/e-trike.Coronavirus Disease 2019 is a very fast-spreading infectious disease. Severe forms are marked by a high mortality rate. The objective of this study is to identify routine biomarkers that can serve as early predictors of the disease progression. This is a prospective, single-center, cohort study involving 330 SARS-CoV-2 infected patients who were admitted at the University Hospital of Blida, Algeria in the period between the 27th of March and 22nd of April 2020. The ROC curve was used to evaluate the predictive performance of biomarkers, assessed at admission, in the early warning of progression toward severity. Multivariate logistic regression was used to quantify the independent risk for each marker. After an average follow-up period of 13.9 ± 3.5 days, 143 patients (43.3%) were classified as severe cases. Six biological abnormalities were identified as potential risk markers independently related to the severity elevated urea nitrogen (>8.0 mmol/L, OR = 9.3 [2.7-31.7], p 7.99, OR = 4.2, [1.4-12.2], p = .009). These easy-to-measure, time-saving and very low-cost parameters have been shown to be effective in the early prediction of the COVID-19 severity. Their use at the early admission stage can improve the risk stratification and management of medical care resources in order to reduce the mortality rate.Phenomenon There is currently a move to provide residency programs with accurate competency-based assessments of their candidates, yet there is a gap in knowledge regarding the role and effectiveness of interventions in easing the transition to residency. The impact of key stakeholder engagement, learner-centeredness, intrinsic competencies, and assessment on the efficacy of this process has not been examined. The objective of this scoping review was to explore the nature of the existing scholarship on programs that aim to facilitate the transition from medical school to residency. Approach We searched MEDLINE and EMBASE from inception to April 2020. Programs were included if they were aimed at medical students completing undergraduate medical training or first year residents and an evaluative component. Two authors independently screened all abstracts and full text articles in duplicate. Data were extracted and categorized by type of program, study design, learner-centeredness, key stakeholder engagement, thal school to residency can enhance both Medical Expert and other intrinsic competencies, there is much room for novel transition programs to define their goals more broadly and to incorporate multiple areas of professional development. The existing literature highlights various gaps in approaches to easing the transition from medical school to residency, particularly with respect to key stakeholder engagement, addressing intrinsic CanMEDS competencies, and focusing on individual learners' needs. As a step towards the development of an audiological diagnostic supporting tool employing machine learning methods, this article aims at evaluating the classification performance of different audiological measures as well as Common Audiological Functional Parameters (CAFPAs). CAFPAs are designed to integrate different clinical databases and provide abstract representations of measures. Classification and evaluation of classification performance in terms of sensitivity and specificity are performed on a data set from a previous study, where statistical models of diagnostic cases were estimated from expert-labelled data. The data set contains 287 cases. The classification performance in clinically relevant comparison sets of two competing categories was analysed for audiological measures and CAFPAs. ex229 ic50 It was found that for different audiological diagnostic questions a combination of measures using different weights of the parameters is useful. A set of four to six measures was already sufficient to achieve maximum classification performance which indicates that the measures contain redundant information. The current set of CAFPAs was confirmed to yield in most cases approximately the same classification performance as the respective optimum set of audiological measures. Overall, the concept of CAFPAs as compact, abstract representation of auditory deficiencies is confirmed.The current set of CAFPAs was confirmed to yield in most cases approximately the same classification performance as the respective optimum set of audiological measures. Overall, the concept of CAFPAs as compact, abstract representation of auditory deficiencies is confirmed.