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Table 2 Multivariate binary logistic regression analysis for predictors of osteoarthritis progression

From: Novel nomogram for predicting the progression of osteoarthritis based on 3D-MRI bone shape: data from the FNIH OA biomarkers consortium

Time Intercept and variable β OR 95% CI.low 95% CI.upp p-value
Baseline Intercept 0.1749     0.856
KL2 -0.4584 0.6323 0.3705 1.0790 0.093
KL3 -0.1662 0.8468 0.4711 1.5221 0.578
Age, year 0.0158 1.0159 0.9965 1.0356 0.108
Sex, female -0.3020 0.7393 0.5157 1.0601 0.100
Race 0, Other Non-white Reference Reference Reference Reference Reference
Race 1, White or Caucasian -0.6816 0.5058 0.1276 2.0050 0.332
Race 2, Black or African American -1.2803 0.2779 0.0671 1.1507 0.077
Race 3, Asian -0.5724 0.5642 0.0539 5.9064 0.633
Tibia OA Vector -0.1646 0.8483 0.7268 0.9901 0.037
Patella OA Vector -0.1748 0.8380 0.749 0.9375 0.002
24 m Intercept -1.4507     0.143
Age, year 0.0295 1.0299 1.0093 1.0509 0.004
Sex, female -0.8186 0.4422 0.3039 0.6434 0.000
Race 0, Other Non-white Reference Reference Reference Reference Reference
Race 1, White or Caucasian -0.6009 0.5483 0.1308 2.2989 0.411
Race 2, Black or African American -1.1677 0.3111 0.0702 1.3784 0.124
Race 3, Asian -0.9037 0.4039 0.039 4.1849 0.447
Femur OA Vector change24 -2.6689 0.0693 0.0315 0.1528 0.000
Tibia OA Vector change24 -1.0035 0.3666 0.2216 0.6066 0.0001