Development and validation of osteoporosis risk assessment score in patients with heart failure: comparison with the osteoporosis self-assessment tool for Asians.
| Autor: | Numazawa, Ryo, Katano, Satoshi, Yano, Toshiyuki, Koyama, Masayuki, Nagaoka, Ryohei, Fujisawa, Yusuke, Yamano, Kotaro, Honma, Suguru, Ohori, Katsuhiko, Kouzu, Hidemichi, Katayose, Masaki, Furuhashi, Masato, Tsuchihashi, Kazufumi, Hashimoto, Akiyoshi |
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| Předmět: |
OSTEOPOROSIS diagnosis
PHOTON absorptiometry CROSS-sectional method STATISTICAL models SELF-evaluation BONE density RESEARCH funding PREDICTION models BODY mass index RESEARCH methodology evaluation SCIENTIFIC observation LOGISTIC regression analysis HEART failure DESCRIPTIVE statistics MULTIVARIATE analysis MANN Whitney U Test CHI-squared test EXPERIMENTAL design RESEARCH methodology OSTEOPOROSIS MEDICAL screening CONFIDENCE intervals DATA analysis software SENSITIVITY & specificity (Statistics) GRIP strength |
| Zdroj: | European Journal of Cardiovascular Nursing; May2024, Vol. 23 Issue 4, p408-417, 10p |
| Abstrakt: | Aims Osteoporosis is prevalent and is associated with poor prognosis in patients with heart failure (HF). However, bone mineral density measurement by a dual-energy X-ray absorptiometry (DEXA) scan is not always available in a daily clinical setting or large-scale population-based studies. Methods and results A single-centre, cross-sectional observational study was conducted with 387 patients [median age: 77 years (interquartile range: 68–83 years); 37% women]. Bone mineral densities were measured by DEXA scans, and osteoporosis was diagnosed as ≤−2.5 standard deviation of the bone mineral densities 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. Osteoporosis was found in 103 (27%) of the 387 HF patients. Multivariate logistic regression analyses yielded the ORAS based on sex, body mass index, handgrip strength, and anti-coagulant therapy utilization. The C -index of ORAS in the developmental set (0.796, 95% confidence interval: 0.747–0.845) 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 cut-off point of 127 points, yielding 85% sensitivity and 62% specificity. Conclusion Osteoporosis risk assessment score 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. [ABSTRACT FROM AUTHOR] |
| Databáze: | Complementary Index |
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