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Effective Health Care Program

Diagnosis of Gout

Systematic Review

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This report was republished with an addendum in October 2016.

Structured Abstract

Objectives

The aim of this review is to assess the evidence for the accuracy and safety of tests to diagnose gout in patients with no prior diagnosis of gout. The review also assesses factors that affect accuracy of diagnostic tests. Tests include algorithms that combine clinical signs and symptoms, dual-energy computed tomography (DECT), ultrasound, and plain x ray, with particular emphasis on tests that can be conducted in primary and acute (urgent and emergent) care settings.

Data sources

We searched Medline® (from 1946), Embase® (from 1972), the Cochrane Library (from 1945), and the Web of Scienc™ (from 1980) to November 7, 2014, for published studies. We also searched ClinicalTrials.gov and the Web of Science and contacted manufacturers of imaging equipment and test kits for unpublished data on gout diagnosis.

Review methods

We reviewed published and unpublished prospective cohort, cross-sectional, and case-control studies, as well as prior systematic reviews on the accuracy (sensitivity and specificity) of diagnostic tests for gout compared with a validated reference standard in patients without a prior gout diagnosis. We also reviewed studies and prior reviews of factors affecting the accuracy of monosodium urate crystal assessment in synovial fluid. We reviewed prospective cohort, cross-sectional, and case-control studies; case reports of any size; and systematic reviews that reported adverse events associated with diagnostic tests for gout and outcomes of gout misdiagnosis. A standardized protocol with predefined criteria was used to extract details on study design, interventions, outcomes, and study quality, and to assess the strength of evidence for each conclusion.

Results

Six clinical algorithms comprising clinical signs and symptoms have been tested for diagnostic accuracy against the presence of monosodium urate crystals in synovial fluid aspirated from affected joints. Most studies were conducted with small groups of patients in academic rheumatology departments. Two recently developed clinical algorithms, the Diagnostic Rule, which is the only one developed and validated with primary care physicians and patients, and the Clinical Gout Diagnosis (CGD), demonstrated sensitivities of 88 percent and 97 percent, respectively, and specificities of 75 percent and 96 percent, respectively, in patients with shorter (2 years or less) and longer durations of symptoms, and they are simple to administer. However, the strength of evidence supporting their use is low, as validation of these tools remains limited. Three studies of DECT that enrolled patients without a previous gout diagnosis revealed sensitivities ranging from 85 percent to 100 percent and specificities ranging from 83 percent to 92 percent in diagnosing gout; the strength of evidence regarding the use of DECT for gout diagnosis is low. Four studies of ultrasound that enrolled patients without a previous diagnosis showed sensitivities ranging from 37 percent to 100 percent and specificities ranging from 68 percent to 97 percent, depending on the ultrasound signs assessed; the strength of evidence is low for the utility of ultrasound in diagnosing gout. A small number of studies examined factors that affected the accuracy of tests for the diagnosis of gout. The accuracy of monosodium urate analysis in synovial fluid varies widely among practitioners, but evidence on the effects of skill and experience is insufficient. No studies examined differences among practitioners in the rate of successful joint aspiration. No studies reported adverse events directly associated with techniques used to diagnose gout. However in one small study, missed gout diagnosis resulted in unnecessary surgery, longer hospital stays, and delay in appropriate treatment.

Conclusions

Promising diagnostic clinical algorithms such as the Diagnostic Rule and CGD need to be validated more broadly in primary and urgent care settings. A clinical algorithm with high diagnostic accuracy ideally can form part of a diagnostic decision tree, with referral of more clinically challenging cases to rheumatologists for more invasive tests or imaging. Research is needed to assess the incremental value of synovial fluid monosodium urate crystal analysis and imaging over that of a diagnostic clinical algorithm.

Addendum – October 2016

An update search was conducted to prepare a manuscript based on the report (end date of update search February 29, 2016) and identified six new studies that met inclusion criteria. Five addressed Key Question (KQ) 1 (validity) (three reported on algorithms [Jatuworapruk et al., 2016; Taylor et al., 2015; Neogi et al., 2016] and two reported on imaging [Löffler et al., 2015; Pascal et al., 2015]). One addressed KQ2 (adverse events [Taylor et al., 2016]).

KQ1 Validity of Diagnostic Methods

One study reported on the development and validation of the new American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) gout classification criteria (Neogi et al., 2016). Using monosodium urate (MSU) crystal analysis as the reference standard, the classification criteria had a sensitivity of 92 percent and a specificity of 89 percent (including clinical and imaging domains) or 85 percent and 78 percent (excluding imaging). Thus, imaging findings improved both the sensitivity and specificity of clinical and laboratory criteria (study quality high).

Two studies further validated existing classification and diagnostic algorithms in different populations (Jatuworapruk, et al., 2015; Taylor et al., 2015). Based on these additional studies, the strength of evidence for the use of Janssens’ Diagnostic Rule (the Netherlands criteria) or the Clinical Gout Diagnosis criteria was raised from low to moderate.

Two studies further validated the use of the ultrasound double contour sign to diagnose gout (Löffler et al., 2015; Pascal et al., 2015). The pooled sensitivity and specificity for the double contour sign from the three studies in the original report and one of the two new studies (464 joints) were 74 percent (95% confidence interval [CI] 52, 88) and 88 percent (95% CI 68, 96), respectively. The strength of evidence supporting the use of ultrasound for gout diagnosis remains low. No new studies were identified that report on the use of dual energy computerized tomography or x ray.

KQ2. Adverse Events Associated with Gout Diagnostic Methods

One new study identified one serious adverse event after synovial fluid aspiration (septic arthritis 11 days post arthrocentesis, event rate 0.1%, 95% CI 0, 0.34) and 11 nonserious adverse events (mostly mild pain following the procedure; event rate 1.4%, 95% CI 0.6–2.1) (Taylor et al., 2016). More information is located in the Annals of Internal Medicine manuscript.

References

  1. Jatuworapruk K, Lhakum P, Pattamapaspong N, et al. Performance of the existing classification criteria for gout in Thai patients presenting with acute arthritis. Medicine (Baltimore). 2016;95(5):e27jatu30. Epub 6 Feb 2016. doi: 10.1097/md.0000000000002730. PMID: 2684451.
  2. Löffler C, Sattler H, Peters L, et al. Distinguishing gouty arthritis from calcium pyrophosphate disease and other arthritides. Journal of Rheumatology. 2015;42(3):513-20. PMID: 2015796981. http://dx.doi.org/10.3899/jrheum.140634.
  3. Neogi T, Jansen TL, Dalbeth N, et al. 2015 Gout classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Annals of the Rheumatic Diseases. 2015;74(10):1789-98. Epub 12 Sept 2015. doi: 10.1136/annrheumdis-2015-208237. PubMed PMID: 26359487; PMCID: PMCPmc4602275.
  4. Pascal Z, Valcov R, Fabreguet I, et al. A prospective evaluation of ultrasound as a diagnostic tool in acute microcrystalline arthritis. Arthritis research & therapy. 2015;17:188. Epub 23 July 2015. doi: 10.1186/s13075-015-0701-7. PMID: 26198435; PMCID: PMCPmc4511437.
  5. Taylor WJ, Fransen J, Dalbeth N, et al. Diagnostic arthrocentesis for suspicion of gout is safe and well tolerated. The Journal of rheumatology. 2016;43(1):150-3. Epub 2015 Dec 3. doi: 10.3899/jrheum.150684. PMID: 26628602.
  6. Taylor WJ, Fransen J, Jansen TL, et al. Study for Updated Gout Classification Criteria (SUGAR): identification of features to classify gout. Arthritis care & research. 2015. Epub 18 Mar 2015. doi: 10.1002/acr.22585. PMID: 25777045.

Journal Publications

Newberry SJ, FitzGerald JD, Motala A, Booth M, Maglione MA, Han D, et al. Diagnosis of Gout: A Systematic Review in Support of an American College of Physicians Clinical Practice Guideline. Ann Intern Med. [Epub ahead of print 1 November 2016] doi: 10.7326/M16-0462

Shekelle PG, Newberry SJ, FitzGerald JD, Motala A, O'Hanlon CE, Tariq A, et al. Management of Gout: A Systematic Review in Support of an American College of Physicians Clinical Practice Guideline. Ann Intern Med. [Epub ahead of print 1 November 2016] doi: 10.7326/M16-0461