Individualized interventions and precision health: Lessons learned from a systematic review and implications for analytics-driven geriatric research

Nutrition for the older adult - Current concepts. Report from an ESPEN symposium

BACKGROUND & AIMS

In view of the global demographic shift, a scientific symposium was organised by the European Society for Clinical Nutrition and Metabolism (ESPEN) to address nutrition-related challenges of the older population and provide an overview of the current state of knowledge.

METHODS

Eighteen nutrition-related issues of the ageing global society were presented by international experts during the symposium and summarised in this report.

RESULTS

Anorexia of ageing, dysphagia, malnutrition, frailty, sarcopenia, sarcopenic obesity, and the metabolic syndrome were highlighted as major nutrition-related geriatric syndromes. Great progress has been made in recent years through standardised definitions of some but not all syndromes. Regarding malnutrition, the GLIM approach has shown to be suitable also in older adults, justifying its continuous implementation. For anorexia of ageing, a consensus definition is still required. Intervention approaches should be integrated and person-centered with the aim of optimizing intrinsic capacity and maintaining functional capacity. Landmark studies like EFFORT and FINGER have impressively documented the potential of individualised and multifactorial interventions for functional and health benefits. Combining nutritional intervention with physical training seems particularly important whereas restrictive diets and drug treatment should generally be used with caution because of undesirable risks. Obesity management in older adults should take into account the risk of promoting sarcopenia.

CONCLUSIONS

In the future, even more individualised approaches like precision nutrition may enable better nutritional care. Meanwhile all stakeholders should focus on a better implementation of currently available strategies and work closely together to improve nutritional care for older adults.

New Horizons in artificial intelligence in the healthcare of older people

Artificial intelligence (AI) in healthcare describes algorithm-based computational techniques which manage and analyse large datasets to make inferences and predictions. There are many potential applications of AI in the care of older people, from clinical decision support systems that can support identification of delirium from clinical records to wearable devices that can predict the risk of a fall. We held four meetings of older people, clinicians and AI researchers. Three priority areas were identified for AI application in the care of older people. These included: monitoring and early diagnosis of disease, stratified care and care coordination between healthcare providers. However, the meetings also highlighted concerns that AI may exacerbate health inequity for older people through bias within AI models, lack of external validation amongst older people, infringements on privacy and autonomy, insufficient transparency of AI models and lack of safeguarding for errors. Creating effective interventions for older people requires a person-centred approach to account for the needs of older people, as well as sufficient clinical and technological governance to meet standards of generalisability, transparency and effectiveness. Education of clinicians and patients is also needed to ensure appropriate use of AI technologies, with investment in technological infrastructure required to ensure equity of access.