The use of predictive fall models for older adults receiving aged care, using routinely collected electronic health record data : a systematic review

Background: Falls in older adults remain a pressing health concern. With advancements in data analytics and increasing uptake of electronic health records, developing comprehensive predictive models for fall risk is now possible. We aimed to systematically identify studies involving the development and implementation of predictive falls models which used routinely collected electronic health record data in home-based, community and residential aged care settings. Methods: A systematic search of entries in Cochrane Library, CINAHL, MEDLINE, Scopus, and Web of Science was conducted in July 2020 using search terms relevant to aged care, prediction, and falls. Selection criteria included English-language studies, published in peer-reviewed journals, had an outcome of falls, and involved fall risk modelling using routinely collected electronic health record data. Screening, data extraction and quality appraisal using the Critical Appraisal Skills Program for Clinical Prediction Rule Studies were conducted. Study content was synthesised and reported narratively. Results: From 7,329 unique entries, four relevant studies were identified. All predictive models were built using different statistical techniques. Predictors across seven categories were used: demographics, assessments of care, fall history, medication use, health conditions, physical abilities, and environmental factors. Only one of the four studies had been validated externally. Three studies reported on the performance of the models. Conclusions: Adopting predictive modelling in aged care services for adverse events, such as falls, is in its infancy. The increased availability of electronic health record data and the potential of predictive modelling to document fall risk and inform appropriate interventions is making use of such models achievable. Having a dynamic prediction model that reflects the changing status of an aged care client is key to this moving forward for fall prevention interventions

Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty

Most older individuals develop inflammageing, a condition characterized by elevated levels of blood inflammatory markers that carries high susceptibility to chronic morbidity, disability, frailty, and premature death. Potential mechanisms of inflammageing include genetic susceptibility, central obesity, increased gut permeability, changes to microbiota composition, cellular senescence, NLRP3 inflammasome activation, oxidative stress caused by dysfunctional mitochondria, immune cell dysregulation, and chronic infections. Inflammageing is a risk factor for cardiovascular diseases (CVDs), and clinical trials suggest that this association is causal. Inflammageing is also a risk factor for chronic kidney disease, diabetes mellitus, cancer, depression, dementia, and sarcopenia, but whether modulating inflammation beneficially affects the clinical course of non-CVD health problems is controversial. This uncertainty is an important issue to address because older patients with CVD are often affected by multimorbidity and frailty - which affect clinical manifestations, prognosis, and response to treatment - and are associated with inflammation by mechanisms similar to those in CVD. The hypothesis that inflammation affects CVD, multimorbidity, and frailty by inhibiting growth factors, increasing catabolism, and interfering with homeostatic signalling is supported by mechanistic studies but requires confirmation in humans. Whether early modulation of inflammageing prevents or delays the onset of cardiovascular frailty should be tested in clinical trials