BACKGROUND: Alternative strategies exist for diagnosing gout that do not rely solely on the documentation of monosodium urate (MSU) crystals. PURPOSE: To summarize evidence regarding the accuracy of clinical tests and classification algorithms compared with that of a reference standard of MSU crystals in joint aspirate for diagnosing gout. DATA SOURCES: Several electronic databases from inception to 29 February 2016. STUDY SELECTION: 21 prospective cohort, cross-sectional, and case-control studies including participants with joint inflammation and no previous definitive gout diagnosis who had MSU analysis of joint aspirate. DATA EXTRACTION: Data extraction and risk-of-bias assessment by 2 reviewers independently; overall strength of evidence (SOE) judgment by group. DATA SYNTHESIS: Recently developed algorithms including clinical, laboratory, and imaging criteria demonstrated good sensitivity (up to 88%) and fair to good specificity (up to 96%) for diagnosing gout (moderate SOE). Three studies of dual-energy computed tomography (DECT) showed sensitivities of 85% to 100% and specificities of 83% to 92% for diagnosing gout (low SOE). Six studies of ultrasonography showed sensitivities of 37% to 100% and specificities of 68% to 97%, depending on the ultrasonography signs assessed (pooled sensitivity and specificity for the double contour sign: 74% [95% CI, 52% to 88%] and 88% [CI, 68% to 96%], respectively [low SOE]). LIMITATION: Important study heterogeneity and selection bias; scant evidence in primary and urgent care settings and in patients with conditions that may be confused with or occur with gout. CONCLUSION: Multidimensional algorithms, which must be validated in primary and urgent care settings, may help clinicians make a provisional diagnosis of gout. Although DECT and ultrasonography also show promise for gout diagnosis, accessibility to these methods may be limited. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality. (Protocol registration: https://effectivehealthcare.ahrq.gov/ehc/products/564/1937/gout-protocol-140716.pdf).
BACKGROUND: Alternative strategies exist for diagnosing gout that do not rely solely on the documentation of monosodium urate (MSU) crystals. PURPOSE: To summarize evidence regarding the accuracy of clinical tests and classification algorithms compared with that of a reference standard of MSU crystals in joint aspirate for diagnosing gout. DATA SOURCES: Several electronic databases from inception to 29 February 2016. STUDY SELECTION: 21 prospective cohort, cross-sectional, and case-control studies including participants with joint inflammation and no previous definitive gout diagnosis who had MSU analysis of joint aspirate. DATA EXTRACTION: Data extraction and risk-of-bias assessment by 2 reviewers independently; overall strength of evidence (SOE) judgment by group. DATA SYNTHESIS: Recently developed algorithms including clinical, laboratory, and imaging criteria demonstrated good sensitivity (up to 88%) and fair to good specificity (up to 96%) for diagnosing gout (moderate SOE). Three studies of dual-energy computed tomography (DECT) showed sensitivities of 85% to 100% and specificities of 83% to 92% for diagnosing gout (low SOE). Six studies of ultrasonography showed sensitivities of 37% to 100% and specificities of 68% to 97%, depending on the ultrasonography signs assessed (pooled sensitivity and specificity for the double contour sign: 74% [95% CI, 52% to 88%] and 88% [CI, 68% to 96%], respectively [low SOE]). LIMITATION: Important study heterogeneity and selection bias; scant evidence in primary and urgent care settings and in patients with conditions that may be confused with or occur with gout. CONCLUSION: Multidimensional algorithms, which must be validated in primary and urgent care settings, may help clinicians make a provisional diagnosis of gout. Although DECT and ultrasonography also show promise for gout diagnosis, accessibility to these methods may be limited. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality. (Protocol registration: https://effectivehealthcare.ahrq.gov/ehc/products/564/1937/gout-protocol-140716.pdf).
Authors: Penny Wang; Stacy E Smith; Rajesh Garg; Fengxin Lu; Alyssa Wohlfahrt; Anarosa Campos; Kathleen Vanni; Zhi Yu; Daniel H Solomon; Seoyoung C Kim Journal: RMD Open Date: 2018-03-09