Objective
To determine which clinical, laboratory and imaging features most accurately distinguished gout from non-gout.
Methods
A cross-sectional study of consecutive rheumatology clinic patients with at least one swollen joint or subcutaneous tophus. Gout was defined by synovial fluid or tophus aspirate microscopy by certified examiners in all patients. The sample was randomly divided into a model development (2/3) and test sample (1/3). Univariate and multivariate association between clinical features and MSU-defined gout was determined using logistic regression modelling. Shrinkage of regression weights was performed to prevent over-fitting of the final model. Latent class analysis was conducted to identify patterns of joint involvement.
Results
In total, 983 patients were included. Gout was present in 509 (52%). In the development sample (n=653), these features were selected for the final model (multivariate OR) joint erythema (2.13), difficulty walking (7.34), time to maximal pain < 24 hours (1.32), resolution by 2 weeks (3.58), tophus (7.29), MTP1 ever involved (2.30), location of currently tender joints: Other foot/ankle (2.28), MTP1 (2.82), serum urate level > 6 mg/dl (0.36 mmol/l) (3.35), ultrasound double contour sign (7.23), Xray erosion or cyst (2.49). The final model performed adequately in the test set with no evidence of misfit, high discrimination and predictive ability. MTP1 involvement was the most common joint pattern (39.4%) in gout cases.
Conclusion
Ten key discriminating features have been identified for further evaluation for new gout classification criteria. Ultrasound findings and degree of uricemia add discriminating value, and will significantly contribute to more accurate classification criteria.
Objectives
To examine the performance of ultrasound for the diagnosis of gout using presence of monosodium urate (MSU) crystals as the gold standard.
Methods
We analyzed data from the Study for Updated Gout Classification Criteria (SUGAR), a large, multi-center observational cross-sectional study of consecutive subjects with at least one swollen joint who conceivably may have gout. All subjects underwent arthrocentesis; cases were subjects with MSU crystal confirmation. Rheumatologists or radiologists, blinded to the results of the MSU crystal analysis, performed ultrasound on one or more clinically affected joints. Ultrasound findings of interest were: double contour sign (DCS), tophus, and ‘snowstorm’ appearance. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated. Multivariable logistic regression models were used to examine factors associated with positive ultrasound results among subjects with gout.
Results
Ultrasound was performed in 824 subjects (416 cases and 408 controls). The sensitivity, specificity, PPV and NPV for the presence of any one of the features were 76.9%, 84.3%, 83.3% and 78.1% respectively. Sensitivity was higher among subjects with disease ≥2 years duration and among subjects with subcutaneous nodules on exam (suspected tophus). Associations with a positive ultrasound finding included suspected clinical tophus (odds ratio 4.77; 95% CI 2.23–10.21), any abnormal plain film radiograph (4.68; 2.68–8.17) and serum urate (1.31; 1.06–1.62).
Conclusions
Ultrasound features of MSU crystal deposition had high specificity and high positive predictive value but more limited sensitivity for early gout. The specificity remained high in subjects with early disease and without clinical signs of tophi.
The definition of gout flare that requires fulfillment of at least 3 of 4 patient-reported criteria is now validated to be sensitive, specific, and accurate for gout flares, as demonstrated using an independent large international patient sample. The availability of a validated gout flare definition will improve the ascertainment of an important clinical outcome in studies of gout.
Existing classification criteria for gout have sensitivity of over 80% in early and established disease but currently available criteria that do not require synovial fluid analysis have inadequate specificity especially later in the disease. Classification criteria for gout with better specificity are required, although the findings should be cautiously applied to non-rheumatology clinic populations.
A simple definition of "self-report of gout or urate-lowering therapy use" has the best test performance characteristics of existing definitions that use routinely available data. A more complex combination of features is more sensitive, but still lacks good specificity. If a more accurate case definition is required for a particular study, the 2015 ACR/EULAR gout classification criteria should be considered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.