The incidence of type 2 diabetes (T2D) has reached epidemic proportions globally, and it is rapidly growing resulting in a great clinical and economic burden for the healthcare systems over the world (1, 2). T2D is managed through the implementation of complications prevention plans based on lifestyle and dietary modifications usually followed by metformin monotherapy and, when necessary, the further addition of an increasingly complex array of therapies, including oral and injectable medications (1, 2). These prevention plans are aimed at reducing the microvascular (e.g., retinopathy, neuropathy, nephropathy) and macrovascular (e.g., ischemic heart disease, peripheral vascular disease, and cerebrovascular disease) complications that exert a strong impact in terms of morbidity and mortality of T2D patients (3). In addition to microvascular and macrovascular complications, older adults with T2D are at higher risk of developing geriatric syndromes leading to important cognitive or functional impairments (4). Accordingly, while in older adults with intact cognitive and physical functions the implementation of prevention plans should pursue the same targets adopted for younger adults, in many other older diabetic patients, their implementation is complicated and strongly depends on the cognitive function, depression, physical disability, comorbidities, and degree of frailty (5–7). Therefore, several clinical parameters should be taken into account when planning therapeutic strategies for complications risk reduction in the older patients: (i) older T2D patients are at high risk of adverse drug reactions consequent to the kidney and liver function disorders; (ii) the impaired adrenergic alert symptoms makes the incidence of asymptomatic hypoglycemia more frequent in this population setting; (iii) the lower medication adherence of older patients with respect to younger people (8). For these reasons, the promotion of healthy ageing in T2D patients requires a comprehensive age‐related healthcare approach, as advocated by the latest ADA standard of care recommendations for this age group (2, 9). On the basis of these recommendations, it is a priority to establish methodologic approaches to individualize prevention plans in order to avoid overtreatment in frail patients and under treatment in other groups of patients (6), recommending different glycosylated hemoglobin targets and glucose-lowering therapies focused on patient preferences, needs, and risk profile. The ADA recommendations, however, are difficult to implement because modern T2D care systems require integrated care between general practitioners, diabetologists and geriatricians, and other members of the healthcare team. Often, older T2D patients are excluded from the personalized treatment targets.

Several studies have identified the risk factors associated with survival in T2D patients younger than 70 years (10–14). Among these, the duration of diabetes, hypertension, hypercholesterolemia, and poor glycemic control were the most relevant (10, 15, 16). However, there is no clear evidence that such factors might also influence the risk of mortality of older diabetic patients. To date, there are few comprehensive data on the risk factors related to survival at the oldest ages and their interaction with indicators of frailty in T2D patients (16–18).

The aim of the present study is to evaluate the link between chemical-clinical risk factors, geriatric parameters, and mortality in T2D patients aged ≥70 years.

T2D is a chronic disease, affecting an increasing number of older patient’s world wild. The associated micro- and macrovascular complications are drivers of morbidity and mortality. There is increasing interest in using stratification in type 2 diabetes to target resources, individualize care, and improve outcomes. The systematic reviews of studies applying population stratification in T2D identifies common themes in stratification and outcome variables, in particular a focus on HbA1c (34). The guidelines for managing diabetes in the T2D older patients recognize the need to consider frailty, comorbidities, and functionality when making decisions on patient management (35, 36). Frailty, considered as a generalized loss in physiological reserve capacity, is emerging as a high‐impact geriatric syndrome, and according to a number of studies, T2D adds a fivefold increase in the risk of frailty in middle‐aged and older people (37). Frailty is currently recognized as a complication of diabetes that may subsequently account for the unexplained disability excess seen in older diabetic populations (38).

However, in the clinical practice of diabetes care, especially in outpatient clinics, physical performance measures are not always performed routinely because of several practical issues such as limited consultation time, space, and manpower. Although the biological processes that underlie frailty are still unclear and likely to be complex and multifactorial, sarcopenia may play an important role in the accelerated decline in leg lean mass, muscle strength, and functional capacity seen in older people with diabetes compared with those without diabetes (39, 40).

The aim of the present study is to evaluate the interaction between diabetic features and parameters related to geriatric assessment, on the mortality risk prediction in a large sample of T2D outpatients aged ≥70 years. Since a prediction model derived from real-world data should be an important tool for managing the setting of older T2D patients, we applied an innovative analysis performed through the automatic machine-learning (ML) tool JADBIO, to identify the mathematical models able to correctly stratify the patients according to their mortality risk. ML has been slowly entering every aspect of our lives, and its positive impact on biomedical challenges is under investigation. JADBIO analysis identified eight features such as age, sex, SPPB, CKD, myocardial ischemia, PAD, neuropathy, and myocardial infarction as the minimal set of predictors needed for optimally estimating the risk of death for T2D patients. The SPPB is a well-established tool to assess lower-extremity physical performance status (39). In addition to the non-modifiable parameters such as age and sex, the SPPB test together with the evaluation of the complications of the disease are useful for predicting the risk of mortality and guiding the management of the older diabetic patient on an outpatient basis (41). Large literature data have confirmed that poor performance on the SPPB is associated with an increased risk of all-cause mortality, suggesting that the systematic implementation of the SPPB in clinical practice settings should be useful prognostic information (42–44).

Recently, it was demonstrated that the assessment of the SPPB scale before hospital discharge increased the ability to predict adverse events in older patients affected by acute coronary syndrome (45). We observed that the SPPB score was the best predictor of T2D mortality with respect to the other parameters. Patients with SPPB <5 experienced a 3.42-fold increased mortality risk compared with patients with SPPB >8. As previously reported, HbA1c was not associated with mortality risk (17). T2D patients in the lowest SPPB score group were significantly more disabled and had higher prevalence of cognitive impairment and depression symptoms and showed a better self-reported health and nutritional status.

Decision tree analysis highlighted the relationship among mortality, lower SPPB categories, loss of IADL, poor nutrition, and depression symptoms.

Group-based trajectories of SPPB scores identified distinct subgroups in LIFE Study participants, and using these group assignments in outcome models, a significant association with major mobility disability was observed (46). SPPB is a parameter of physical frailty, recently included as the primary outcome measure in the REHAB-HF clinical trial on older patients with heart failure (47). We did not include other parameters of sarcopenia and frailty, as we used SPPB as the index of physical frailty and sarcopenia (48). A multicomponent intervention seems to be effective in the reduction of the incidence of disability in older adults with physical frailty and sarcopenia, characterized by SPPB scores of 3–7. These data strongly suggest that physical frailty and sarcopenia may be targeted to preserve mobility in vulnerable older people (48).

In conclusion, stratification is an important tool to optimize effectiveness and efficiency in T2D management of older patients. Targeting interventions to the highest mortality risk T2D patients may allow resources to be better used and costs to be reduced.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Ethical Committee of IRCCS INRCA, Ancona, Italy (reference number: CE-INRCA-18013). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants' legal guardians/next of kin because the study is retrospective. Considering that the data concerned routine visits for the management of diabetes in elderly subjects and that the observation period was rather long, the ethics committee approved the study protocol, waiving informed consent.

AM: Formal analysis, Writing – original draft. VL: Formal analysis, Writing – original draft. LS: Formal analysis, Writing – review & editing. ET: Writing – original draft, Data curation, Investigation. SR: Writing – original draft, Data curation, Investigation. AC: Supervision, Writing – review & editing. LS: Writing – original draft, Formal analysis. JS: Supervision, Writing – review & editing. AC: Funding acquisition, Writing – review & editing. MCo: Writing – review & editing. MCapr: Writing – review & editing. MCapa: Resources, Writing – review & editing. FL: Project administration, Writing – review & editing. FO: Writing – review & editing, Funding acquisition, Methodology. ARB: Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing, Data curation, Investigation.