POS0511 USING HIP STRUCTURAL ANALYSIS MEASUREMENTS TO PREDICT FRACTURE IN RHEUMATOID ARTHRITIS

Background: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease and increases the risk of developing osteoporosis. Incidence fracture higher in this group patients compared to general population can lead increased morbidity (1). Bone strength proximal femur not only linked bone mineral density; it also depends on geometric properties mass (2). Hip structural analysis (HSA) technique used assess hip structure that takes measurements from dual-energy X-ray absorptiometry (DEXA) images (3). Objectives: To determine whether HSA help predict with RA. Methods: Data were collected June 2004 August 2017 RA who underwent DEXA scan at District General Hospital. This included axis length (HAL), cross-sectional area (CSA), moment inertia (CSMI), distance centre femoral head neck (D1) inter-trochanteric line (D2), mean diameter (D3), shaft angle (A) neck/shaft (Θ) index (SI) superior margin (Y). Fracture was predicted by series binomial logistic regression models, adjusted for sex, age density (BMD). Odds ratios 95% confidence intervals under receiver operating characteristic curve (AUC) calculated. Results: 2077 identified, 1632 female 66.7. HAL, D1, D2, D3, A, Θ Y significant predictors models; odds are table 1. CSA, CSMI SI risk. The AUC models 0.632, 0.609 0.625 respectively. Table different parameters Parameter Ratio (95% Confidence Interval ) HAL 1.01410 (0.99958 - 1.02883) 0.99994 (0.99990 0.99998) CSA 0.98523 (0.98065 0.98982) D1 1.01683 (0.98925 1.04518) D2 1.01286 (0.99886 1.02705) D3 1.00664 (0.96958 1.04511) 1.04580 (0.98633 1.10886) A 1.00898 (0.98878 1.02959) 1.00276 (0.98672 1.01906) 0.56769 (0.43400 0.74258) Figure Receiver curves (red), (green) (blue). CSMI-0.609 SI-0.625. Conclusion: These data suggest do fracture. model strongest predictor therefore conjunction other factors. Limitations study retrospective studied had scan. References: [1]Xue Wu S, Jiang L, Feng Guo H, Zhao P. rheumatoid arthritis: meta-analysis. Medicine. 2017; 96 (36): e6983. Available from: doi: 10.1097/MD.0000000000006983. [2]Faulkner KG, Wacker WK, Barden HS, Simonelli C, Burke PK, Ragi Del Rio L. Femur predicts independent length. Osteoporos Int. 2006;17(4):593-9. 10.1007/s00198-005-0019-4. [3]Kaptoge Beck TJ, Reeve J, Stone KL, Hillier TA, Cauley JA, et al. Prediction Incident Risk Geometry Variables Measured Structural Analysis Study Osteoporotic Fractures. Journal Mineral Research. 2008; 23 (12): 1892-1904. https://doi.org/10.1359/jbmr.080802 . Disclosure Interests: None declared