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Filter by:Introduction: Due to the worldwide ageing population and the increasing prevalence of chronic illnesses and cognitive deficits, appropriate instruments for frailty early screening and assessment of geriatric syndromes are required. Digital tools based on artificial intelligence can help improve the evaluation and screening of health risks in the older adults. Objectives: This study aims to evaluate the effectiveness of the PRESAGE CARE questionnaire in screening geriatric syndromes among older adults and to assess its correlation with standardized test scores of the comprehensive geriatric assessment (CGA). Methods: A monocentric prospective observational study will be conducted between October 2023 and July 2024, on seniors who are in the day hospitalization service of Charles-Foix hospital in France. During the consultation with older adults, the investigators will ask the patient's home caregiver to use the PRESAGE CARE application to fill in the PRESAGE CARE questionnaire. Once the questionnaire will be completed on the application, the PRESAGE platform will automatically recorde specific risks for each senior. Subsequently, the investigators will retrieve the data from standardized tests conduct on the same day and enter the results for each patient into the platform. The primary outcome will be the correlation between standardized test scores and the risks computed by the Presage Care system for the risk of depression, the risk of undernutrition, the risk of cognitive impairment and the risk of loss of autonomy in activities of daily living. Secondary outcome will be the comparison of the Area Under the Median Curve (AUC), and the sensitivity, specificity and positive predictive values of artificial intelligence (AI)-based models on the Présage Care questionnaire.
The Effect of Mandala Activity on Happiness and Well-Being Levels in Elderly People Living in Nursing Homes: Colorize Life Project
Delayed discharge in geriatric units is a health and economic issue. There is no algorithm to automatically measure the appropriateness of admissions or hospital days. 30% of the days of hospitalization in acute geriatric units (AGU) are not appropriate. Waiting for a transfer to a follow-up care and rehabilitation unit (SSR) is the main risk factor for inappropriate days. The purpose of this project is to develop an algorithm using natural language processing to predict the appropriateness of an admission to UGA, or a day at UGA.
This cluster randomization study aims to compare the village-doctor led telemedicine integrated care versus usual care to improve compliance with the Atrial Fibrillation Better Care (ABC) pathway components and outcomes for older patients with atrial fibrillation in rural China.
Older patients with chronic renal failure suffer from sarcopenia. Loss of muscle function is associated with increased morbidity and mortality. Currently few treatment are available. The aim of this study is to evaluate the impact of physical rehabilitation in this population on muscle performance and quality of life.