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Frailty in combination with sarcopenia risk predicts osteoporosis in middle-aged and older patients with distal radius fractures from low-energy trauma

Revista

Injury

Fecha de publicación

4 de diciembre de 2025

Injury. 2025 Nov 27;57(2):112909. doi: 10.1016/j.injury.2025.112909. Online ahead of print.

INTRODUCTION: This study aimed to investigate the association between frailty and osteoporosis in middle-aged and older adults, and to evaluate the discriminative value of different frailty assessment tools, including the Groningen Frailty Indicator (GFI), SARC-F questionnaire, and a combined GFI + SARC-F score, in identifying patients at risk for osteoporosis.

METHODS: A total of 36 patients aged 50 years or older with distal radius fractures were included. Sociodemographic and clinical data were recorded. Osteoporosis was defined as a T-score < -2.5. Participants were assessed for frailty using GFI (cutoff ≥4), and sarcopenia risk was defined via SARC-F. Comparisons were made between patients with and without osteoporosis. Logistic regression and ROC analyses were conducted to determine associations and predictive performance.

RESULTS: Frailty, as measured by GFI, was significantly more common among osteoporotic patients (83.3 % vs. 33.3 %, p = 0.007). Logistic regression analysis showed that both GFI (OR: 1.563, 95 % CI: 1.039-2.350, p = 0.032) and the GFI + SARC-F (OR: 4.000, 95 % CI: 1.128-14.184, p = 0.032) were independently associated with osteoporosis. ROC analysis revealed AUC values of 0.717 for GFI and 0.743 for GFI + SARC-F, indicating good discriminative performance, with the combined assessment showing improved accuracy.

CONCLUSION: Frailty is a significant predictor of osteoporosis in older adults. Combining frailty with the sarcopenia risk, such as GFI and SARC-F, enhances the identification of patients at risk of osteoporosis.

LEVEL OF EVIDENCE: II.

PubMed:41344101 | DOI:10.1016/j.injury.2025.112909

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El idioma original es este artículo es el inglés. Mediante el sistema de traducción automático de la IA de emergencing, el contenido se ha traducido al español. Esta es una traducción no supervisada por lo que puede que alguna parte del contenido no refleje con exactitud la publicación original del autor/autores.