BackgroundMusculoskeletal ultrasound is widely used in diagnosing gout, but its accuracy is debatable. We conducted a systematic review and meta-analysis to quantitatively evaluate the value of ultrasound in the diagnosis of gout.MethodsWe systematically searched for publications using Cochrane Library, PubMed/Medline and Embase and manually screened the references of eligible articles for additional relevant publications. Studies were included in this systematic review if they assessed the diagnostic accuracy of ultrasound in gout compared to that of the gold standard, demonstration of monosodium urate crystals in joint fluid or tophi. We then conducted quantitative analyses by extracting data from each study and calculating the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR). The summary receiver operating characteristic curves (sROCs) were constructed to obtain the Q*-index and the area under the curve (AUC).ResultsThirteen studies were included in this meta-analysis. The diagnostic performances of three distinctive ultrasonographic features of gout, double contour sign (DCS), the presence of tophi and the snowstorm sign, were evaluated. For person-based evaluations, the pooled sensitivity, specificity, DOR, AUC and Q* were as follows: for the DCS, 66% (95% confidence interval (CI) 62%-69%), 92% (95% CI 90%-94%), 25.91 (95% CI 11.80–56.89), 0.8163 and 0.7503, respectively; for the presence of tophi, 56% (95% CI 52%-60%), 94% (95% CI 92%-96%), 21.11 (95% CI 7.84–56.89), 0.8928 and 0.8236, respectively; for the snowstorm sign, 31% (95% CI 27%-36%), 91% (95% CI 88%-93%), 4.54(95% CI 3.13–6.58), 0.5946 and 0.5712, respectively; and for simultaneous consideration of these ultrasonographic features, 80% (95% CI 76%-83%), 83% (95% CI 79%-86%), 19.03 (95% CI 13.97–25.93), 0.889 and 0.8197, respectively. For the joint-/location-based evaluations, the pooled sensitivity, specificity, DOR, AUC and Q* were as follows: for the DCS, 75% (95% CI 68%-80%), 65% (95% CI 59%-70%), 16.90 (95% CI 5.10–56.03), 0.871 and 0.8014, respectively; and for the presence of tophi, 48% (95% CI 40%-57%), 96% (95% CI 91%-99%), 30.20 (95% CI 9.23–98.87), 0.8776 and 0.8081, respectively.ConclusionsIn this meta-analysis, relatively high specificity but modest or low sensitivity were demonstrated in the diagnosis of gout using each of the three ultrasonographic features for person-based evaluations. Simultaneous consideration of these ultrasound findings may improve the diagnostic sensitivity. However, the double contour sign alone is weak in the differentiation of gout and non-gout for joint-/location-based evaluations. Further well-designed studies are still needed to support the current findings.

Background Low back pain (LBP) is a common musculoskeletal problem during pregnancy, with an estimated prevalence ranging from 30–78% (Mota MJ et al. J Back Musculoskelet Rehabil 28(2):351-7,2015 and Abebe E et al. J Med Sc Tech 3(3). 37-44,2014). Women reporting LBP are at increased risk of developing perinatal depression. Pregnancy-related LBP is highly heterogeneous and can be divided into lumbar pain (LP), posterior pelvic pain (PPP), and combined pain (CP). Therefore, the purpose of this study was to investigate the associations between LBP and perinatal depressive symptoms. Methods This was a retrospective case-control study conducted from January 2016 to April 2019. A total of 484 pregnant women were enrolled in this study: a case group of 242 pregnant women who were diagnosed with LBP and an age-matched control group of 242 pregnant women without LBP. The Edinburgh Postnatal Depression Scale (EPDS), LBP characteristics, and questionnaires about pregnancy that included demographic, parity, work, comorbidity, and previous pregnancy data were completed and compared between the case group and the control group. Results A total of 68 of 242 (28.1%) women experienced PPP, 142 (58.7%) had lumbar pain(LP), and 32 (13.2%) had combined pain. Furthermore, 26.5% of women with prenatal depression in the LP subgroup remained depressed 6 months postnatally, while the percentages for women in the PPP subgroup and CP subgroup were just 10.6% and 15.6%, respectively. The percentage of women who recovered anytime between delivery and six months postnatally in the PPP subgroup was significantly higher than that in the LP subgroup (31.7% vs. 14.7%, P < 0.001). Conclusions There is a difference in the prevalence of prenatal, postnatal, and perinatal depressive symptoms among pregnant women with different types of LBP. It is necessary to screen prenatal and postnatal depression separately and differentiate the types of LBP during pregnancy. Attention to these factors may help to outline better management strategies to improve maternal health.

Supplemental Digital Content is available in the text