1. Synovial fluid analysis for monosodium urate (MSU) crystals is an appropriate diagnostic test for those suspected to have gout.
2. Multidimensional algorithms can help physicians make a preliminary diagnosis of gout, and dual-energy computed tomography (DECT) and ultrasonography may be appropriate techniques in certain cases of gout.
Evidence Rating Level: 1 (Excellent)
Study Rundown: Gout presents with acute attacks of synovitis that start out as intermittent but can advance to chronic symptoms. Gout is caused by excess serum urate precipitating in the joints. Although a finding of MSU crystals in synovial fluid aspirated from such joints is considered to be adequate for a diagnosis of gout, some physicians and researchers question the need for this route. Aspiration of joints can be difficult and may cause the patient pain. Also, experience and training may impact synovial fluid analysis. In addition, the accuracy of MSU assessment may be variable. Therefore, this review compared the analysis of joint aspirate for MSU crystals (considered to be the gold-standard) with the accuracy and safety of using clinical classification algorithms, DECT, or ultrasonography. Using several electronic databases, this study selected 21 case-control, cross-sectional, and prospective cohort studies to analyze. This review found that multidimensional algorithms can help physicians make a preliminary diagnosis of gout. Ultrasonography and DECT showed good results for diagnosing gout, but these methods are often unavailable. Although there are certain limitations in MSU analysis, no method was found to be consistently high in sensitivity and specificity throughout all stages of gout progression. Therefore, synovial fluid analysis for MSU crystals remains an appropriate diagnostic test for those suspected to have gout.
Strengths of the study include the use of two independent reviewers for risk-of-bias assessment and for acquiring data. In addition, strength of evidence (SOE) was determined as a group. Limitations of these studies include selection bias because there were few studies that enrolled patients who were suspected to have gout but did not have this diagnosis confirmed. Also, some studies may have included patients who had conditions similar to gout or that occur concurrently with gout. In addition, the nature of algorithm studies requires that the patients be fairly homogenous, but sensitivity and specificity levels that are applicable to the individual patient may differ from those used for trial classification purposes.
Relevant Reading: Multinational evidence-based recommendations for the diagnosis and management of gout: integrating systematic literature review and expert opinion of a broad panel of rheumatologists in the 3e initiative
In-Depth [systematic review]: This study used PubMed, EMBASE, the Cochrane Library, the Web of Science, and gray literature to find data regarding diagnosing gout. Certain criteria were used to remove results that weakened the objective of this review. This review found that newly developed algorithms (including clinical, imaging, and laboratory data) could diagnose gout with up to 88% sensitivity and up to 96% specificity, with moderate SOE. Three DECT studies could diagnose gout with 85-100% sensitivity and 83-92% specificity, with low SOE. Six ultrasonography studies could diagnose gout with 37-100% sensitivity and 68-97% specificity, with low SOE.
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