Comorbidity and osteoporotic fracture: approach through predictive modeling techniques using the OSTEOMED registry.

Purpose: To examine the response to anti-osteoporotic treatment, considered as incident fragility fractures after a minimum follow-up of 1 year, according to sex, age, and number of comorbidities of the patients.

Methods: For this retrospective observational study, data from baseline and follow-up visits on the number of comorbidities, prescribed anti-osteoporotic treatment and vertebral, humerus or hip fractures in 993 patients from the OSTEOMED registry were analyzed using logistic regression and an artificial network model.

Results: Logistic regression showed that the probability of reducing fractures for each anti-osteoporotic treatment considered was independent of sex, age, and the number of comorbidities, increasing significantly only in males taking vitamin D (OR = 7.

SNPs in bone-related miRNAs are associated with the osteoporotic phenotype.

Biogenesis and function of microRNAs can be influenced by genetic variants in the pri-miRNA sequences leading to phenotypic variability. This study aims to identify single nucleotide polymorphisms (SNPs) affecting the expression levels of bone-related mature microRNAs and thus, triggering an osteoporotic phenotype. An association analysis of SNPs located in pri-miRNA sequences with bone mineral density (BMD) was performed in the OSTEOMED2 cohort (n = 2183).

[Clinical usefulness of biochemical markers of bone turnover in early postmenopausal women: two years longitudinal study].

Background And Objective: Many studies have been performed on the ability of bone turnover markers (BTM) for the prediction of bone loss and to assess the correlation of BTM with bone mineral density (BMD). However, the results from these studies have been mixed. The aim of this study was to assess the usefulness of BTM to predict bone loss and to analize the correlation of BTM with BMD in early postmenopausal women.