Development and validation of osteoporosis risk assessment score, ORAS, in heart failure patients: comparison with the Osteoporosis Self-Assessment Tool for Asians (OSTA).

ABSTRACT

AIM: Osteoporosis is prevalent and is associated with poor prognosis in heart failure (HF) patients. However, bone mineral density (BMD) measurement by a dual-energy X-ray absorptiometry (DEXA) scan is not always available in a daily clinical setting and large-scale population-based studies. METHODS: A single-center, cross-sectional observational study was conducted with 387 patients (median age 77 years [interquartile range 68 to 83 years]; 37% women). BMDs were measured by DEXA scans, and osteoporosis was diagnosed as ≤ -2.5 standard deviation of the BMDs in healthy young adults. Osteoporosis risk assessment score (ORAS) was developed using significant predictors from a logistic regression model for osteoporosis and was subsequently validated. RESULTS: Osteoporosis was found in 103 (27%) of the 387 HF patients. Multivariate logistic regression analyses yielded the ORAS based on sex, BMI, handgrip strength, and anti-coagulant therapy utilization. The C-index of ORAS in the developmental set (0.796, 95% confidence interval 0.747 to 0.845) was similar to the bootstrap validation of the prediction model (0.784), and tended to be higher than that of the Osteoporosis Self-Assessment Tool for Asians (OSTA). A nomogram of ORAS, established on the basis of the final logistic regression model, demonstrated 100% sensitivity at the lowest score (35 points), with an optimal cutoff point of 127 points, yielding 85% sensitivity and 62% specificity. CONCLUSIONS: ORAS exhibits superior predictive performance to OSTA in predicting osteoporosis in HF patients, establishing itself as a valuable tool for early detection in both daily clinical practice and large-scale population-based studies.