A 3 Week Geriatric Education Program for 4th Year Medical Students at Dalhousie University

Purpose -Population demographics are shifting towards an increased average age. Yet, many medical schools still do not have mandatory comprehensive education in Geriatric Medicine. In 2001, the Division of Geriatric Medicine at Dalhousie University developed a required three-week geriatric course for fourth year medical students. This paper describes the details of the curriculum so that it can be reproduced in other settings. Results - The curriculum was successfully implemented. An examination, held at the end of each 3-week rotation, documented extensive learning of important concepts in Geriatric Medicine. The students gave positive feedback about the benefits of this training program. Conclusion -A well developed formal education program teaches students specific skills in Geriatric Medicine, which may improve the care of the growing elderly populatio

Towards More Efficient Depression Risk Recognition via Gait

Depression, a highly prevalent mental illness, affects over 280 million individuals worldwide. Early detection and timely intervention are crucial for promoting remission, preventing relapse, and alleviating the emotional and financial burdens associated with depression. However, patients with depression often go undiagnosed in the primary care setting. Unlike many physiological illnesses, depression lacks objective indicators for recognizing depression risk, and existing methods for depression risk recognition are time-consuming and often encounter a shortage of trained medical professionals. The correlation between gait and depression risk has been empirically established. Gait can serve as a promising objective biomarker, offering the advantage of efficient and convenient data collection. However, current methods for recognizing depression risk based on gait have only been validated on small, private datasets, lacking large-scale publicly available datasets for research purposes. Additionally, these methods are primarily limited to hand-crafted approaches. Gait is a complex form of motion, and hand-crafted gait features often only capture a fraction of the intricate associations between gait and depression risk. Therefore, this study first constructs a large-scale gait database, encompassing over 1,200 individuals, 40,000 gait sequences, and covering six perspectives and three types of attire. Two commonly used psychological scales are provided as depression risk annotations. Subsequently, a deep learning-based depression risk recognition model is proposed, overcoming the limitations of hand-crafted approaches. Through experiments conducted on the constructed large-scale database, the effectiveness of the proposed method is validated, and numerous instructive insights are presented in the paper, highlighting the significant potential of gait-based depression risk recognition

Prevalence of Falls and Associated Factors in Elderly Population

INTRODUCTION: Fall is an important clinical marker of frailty, as evidenced by its association with other functional problems, such as incontinence, and high mortality rate. Usually falls in elderly are multifactorial in origin, resulting from an interaction between impaired stability and hazards and demand of the environment. Falls are major focus of geriatric medicine because they are common among elderly and have complex interacting causes, serious consequences and require multiple disciplines for effective management. OBJECTIVES: To determine the prevalence of Falls and associated factors in elderly population. METHODOLOGY: This study includes 200 elderly patients attending geriatric outpatient department in Rajiv Gandhi Government General Hospital, Chennai. Patients were selected according to inclusion and exclusion criteria. Relevant history like h/o falls, polypharmacy, associated comorbid conditions were obtained. Cardiovascular, Neurological and Musculoskeletal examinations, vision and hearing screening was done. To assess balance and to test lower limb muscle strength, Fall risk assessment tools like TUG,4 Stage Balance Test, 30 Second Chair Stand Test were done. RESULTS: Prevalence of falls in elderly attending outpatient department is 34.5%, out of which males contribute 44% and females 55%. Extrinsic causes for falls – 42% and intrinsic cause-57%. Major risk factors for falls- visual impairment- 33%; arthritis-50%; age>80- 8.5%; polypharmacy- 36.5%; slow gait speed-18%. CONCLUSION: Falls in elderly are multifactorial in origin. Prevalence of falls in elderly ≥ 65 years attending outpatient department in tertiary care hospital is 34.5%. Prevalence of falls is increased in females when compared to males. Visual impairment, lower limb arthritis, incontinence, depression, age >80, polypharmacy are important risk factors for fall. Impaired balance, decreased gait speed , decreased lower limb muscle strength are important predictors of falls in elderly. Increase in number of risk factors increases fall risk in elderly