ArticleLife (Basel, Switzerland)2026
Early Identification of Low Bone Density Risk Using a Radiofrequency Echographic Multi Spectrometry-Based Prediction Model.
Article in Life (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Osteoporosis is a major public health problem characterized by reduced bone mineral density (BMD) and increased fracture risk. Early identification of individuals with low bone density remains essential for prevention. This study aimed to evaluate a multivariable logistic regression-based model integrating clinical and Radiofrequency Echographic Multi Spectrometry (REMS)-derived parameters for the detection of low bone density in women. A total of 324 women undergoing REMS assessment of the lumbar spine and hip were included. Clinical variables (age, body mass index [BMI], menopausal status, and lifestyle factors) and REMS-derived measurements were analyzed. Binary logistic regression was used to identify independent factors associated with low BMD (T-score < -1 SD). Model performance was assessed using odds ratios (ORs), omnibus chi-square testing, pseudo-R
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