Glycemic control and prescription profiles in internal medicine inpatients: The role of frailty

Arévalo Lorido, Jose Carlos; Carretero Gomez, Juana; Vazquez Rodriguez, Patricia; Gómez Huelgas, Ricardo; Marín Silvente, Carmen; Sánchez Lora, Fernando Javier; Isaba Ares, Elena; Pardo i Pelegrín, Anna; Pérez Hernández, Onán; Ena, Javier

doi:10.1016/j.ejim.2023.10.022

Cited by 2 publications

(1 citation statement)

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“…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 ).…”

Section: Discussionmentioning

confidence: 99%

Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification

Montesanto,

Lagani,

Spazzafumo

et al. 2024

Front. Endocrinol.

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BackgroundPrognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning.Materials and methodsA retrospective longitudinal study was conducted in a real-world sample of older diabetic patients afferent to the outpatient facilities of the Diabetology Unit of the IRCCS INRCA Hospital of Ancona (Italy). A total of 1,001 T2D patients aged more than 70 years were consecutively evaluated by a multidimensional geriatric assessment, including physical performance evaluated using the Short Physical Performance Battery (SPPB). The mortality was assessed during a 5-year follow-up. We used the automatic machine-learning (AutoML) JADBio platform to identify parsimonious mathematical models for risk stratification.ResultsOf 977 subjects included in the T2D cohort, the mean age was 76.5 (SD: 4.5) years and 454 (46.5%) were men. The mean follow-up time was 53.3 (SD:15.8) months, and 209 (21.4%) patients died by the end of the follow-up. The JADBio AutoML final model included age, sex, SPPB, chronic kidney disease, myocardial ischemia, peripheral artery disease, neuropathy, and myocardial infarction. The bootstrap-corrected concordance index (c-index) for the final model was 0.726 (95% CI: 0.687–0.763) with SPPB ranked as the most important predictor. Based on the penalized Cox regression model, the risk of death per unit of time for a subject with an SPPB score lower than five points was 3.35 times that for a subject with a score higher than eight points (P-value <0.001).ConclusionAssessment of physical performance needs to be implemented in clinical practice for risk stratification of T2D older patients.

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Section: Discussionmentioning

confidence: 99%