PURPOSE: To assess whether magnetic resonance (MR) imaging-based cross-sectional measures of @entity75 can be used to predict knee replacement during the following year. MATERIALS AND METHODS: @entity1 were drawn from the @entity571 Initiative, a longitudinal observational study that includes 4796 @entity1 who have knee @entity571 or are at risk. The HIPAA-compliant protocol was approved by the institutional review boards of all participating centers, and written informed consent was obtained from all @entity1 . During the 5 years of follow-up, 199 knees underwent knee replacement and were matched with 199 control knees that did not undergo knee replacement. Knees were matched according to @entity66 stage and @entity1 sex and age. All knees that underwent knee replacement and had MR images available from the year before surgery were included. MR images were assessed for @entity16 , @entity236 , @entity16 , meniscal extrusion, @entity603 , and effusion prior to reported knee replacement. Conditional logistic regression was applied to assess the risk of knee replacement. Analyses were performed on a compartmental and knee level. RESULTS: @entity1 had a mean age    standard deviation of 64.2 years    8.4 (range, 47-82 years) and were predominantly @entity1 (232 of 398 @entity1 , 58.3%). Risk for knee replacement was significantly increased for knees that exhibited two or more subregions with severe @entity393 (odds ratio [OR], 16.5; 95% confidence interval [CI]: 3.96, 68.76), more than two subregions with @entity236 (OR, 4.00; 95% CI: 1.75, 9.16), medial meniscal maceration (OR, 1.84; 95% CI: 1.13, 2.99), effusion (OR, 4.75; 95% CI: 2.55, 8.85), or @entity603 (OR, 2.17; 95% CI: 1.33, 3.56), but not extrusion (OR, 1.00; 95% CI: 0.60,1.67), when compared with knees that did not exhibit these features as the reference standard. CONCLUSION: Apart from meniscal extrusion, all features of tissue abnormalities at MR imaging were related to clinical prognosis and could be used to predict knee replacement in the following year.

Can XXXX measured with MR imaging be used to predict knee replacement in the following year?

@entity1 :: ('9606', 'Species') :: ['participants', 'women', 'patient', 'Participants'] @entity571 :: ('MESH:D010003', 'Disease') :: ['osteoarthritis', 'Osteoarthritis'] @entity66 :: ('MESH:D004194', 'Disease') :: ['radiographic disease'] @entity75 :: ('MESH:D001927', 'Disease') :: ['structural joint damage'] @entity16 :: ('MESH:D009422', 'Disease') :: ['meniscal damage', 'cartilage damage'] @entity603 :: ('MESH:D013585', 'Disease') :: ['synovitis'] @entity236 :: ('MESH:D001855', 'Disease') :: ['bone marrow lesions'] @entity393 :: ('MESH:D034381', 'Disease') :: ['cartilage loss']
@entity75 :: (MESH:D001927,Disease) :: ['structural joint damage']
