Personalised Approach to the Management of Older People with Type 2 Diabetes Mellitus-A Comprehensive Narrative Review

针对老年2型糖尿病患者的个性化管理方法——一项综合叙述性综述

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Abstract

The global population is ageing due to increased life expectancy, and the prevalence of diabetes is proportionally increasing. With advancing age, diabetes in older people is a complex condition due to associated morbidities and geriatric syndromes. As a result, the management of diabetes in old age is challenging. Due to the wide heterogeneity of older people, diabetes management in this age group should be personalised. While strict targets are accepted in fit individuals, relaxed targets should be considered in patients with multiple morbidities and a high risk of hypoglycaemia. The development of frailty changes the metabolic profile of older people, and their insulin resistance and diabetes trajectory, which will have an impact on the choice of glucose-lowering agents and the goals of therapy. For example, intensive therapy, the use of SGLT-2 inhibitors and GLP-1RA, and tight targets should be continued in frail, sarcopenic, obese individuals due to their increased insulin resistance and cardiovascular risk. On the other hand, relaxed targets and deintensification of therapy should be considered in anorexic, malnourished, frail individuals with significant weight loss due to their low insulin resistance, low prevalence of cardiovascular risk factors, and high risk of hypoglycaemia. Annual reviews of older people with diabetes should include screening for frailty, depression and dementia for early diagnosis, and appropriate interventions. The introduction of continuous glucose monitoring is increasingly used in older people with diabetes and has the potential to reduce the incidence of hypoglycaemia. With the expectation of a continued increase in the prevalence of older people with diabetes, the use of mobile health may allow care delivery on a wider scale without the need for face-to-face appointments. In addition, there is a promising scope for artificial intelligence to achieve better diabetes outcomes. Future research is still required to expand the use of these technologies in older age groups.

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