Sonmez Cemile, Demir Tulin, Uzunmehmetoglu Tahir, Maden Hakan, Kilic Selcuk
Cemile Sonmez, MD, Public Health Institution of Turkey, Microbiology Reference Laboratories, Adnan Saygun Street no:55 Sihhiye, Ankara, Turkey;
Acta Dermatovenerol Croat. 2018 Jun;26(2):146-152.
Different algorithms have been proposed to increase the diagnostic capacity of syphilis. We analyzed three common algorithms for detecting suspected syphilis cases in low prevelance Turkish population. The study included a total of 340 clinical serum samples from adults throughout Turkey, who had syphilis as a clinical preliminary diagnosis and were positive on at least one of the following tests: Rapid Plasma Reagin (RPR), Treponema pallidum Haemagglutination test (TPHA) and FTA-abs Ig. In adittion to percent agreement, kappa coefficients were calculated to compare the conformity between the three algorithms. Both the reverse and the ECDC algorithms had higher diagnostic efficacy than the conventional algorithm. The sensitivity/specificity/ accuracy of conventional, reverse and ECDC algorithms were 51.3%/86.1%/55%; 80.9%/86.1%/81.4% and 80.9%/100%/82.9% respectively. The interrater reliability was moderate for conventional-reverse algorithm (73.53%; к=0.484; 95%CI=0.41-0.56; p=0.001) and conventional-ECDC algorithm (72.06%; к=0.454; 95% CI= 0.37-0.54; p=0.001), and near perfect for reverse-ECDC algorithm (98.53%; к=0.963; 95% CI=0.93-0.99; p=0.0001). Our data support the use of ECDC algorithm in serological diagnosis of syphilis. It may increase the diagnostic capacity if treponemal tests are used for screening, and then positive results are confirmed with a different and second treponemal test.
人们已经提出了不同的算法来提高梅毒的诊断能力。我们分析了三种用于在梅毒患病率较低的土耳其人群中检测疑似梅毒病例的常见算法。该研究共纳入了来自土耳其各地的340份成人临床血清样本，这些样本临床初步诊断为梅毒，并且在以下至少一项检测中呈阳性：快速血浆反应素试验（RPR）、梅毒螺旋体血凝试验（TPHA）和荧光螺旋体抗体吸收试验（FTA-abs Ig）。除了计算一致率外，还计算了kappa系数以比较三种算法之间的一致性。反向算法和欧洲疾病预防控制中心（ECDC）算法的诊断效能均高于传统算法。传统算法、反向算法和ECDC算法的灵敏度/特异度/准确度分别为51.3%/86.1%/55%；80.9%/86.1%/81.4%和80.9%/100%/82.9%。传统-反向算法（73.53%；κ=0.484；95%可信区间=0.41-0.56；p=0.001）和传统-ECDC算法（72.06%；κ=0.454；95%可信区间=0.37-0.54；p=0.001）的评分者间信度为中等，反向-ECDC算法（98.53%；κ=0.963；95%可信区间=0.93-0.99；p=0.0001）的评分者间信度近乎完美。我们的数据支持在梅毒血清学诊断中使用ECDC算法。如果使用梅毒螺旋体检测进行筛查，然后用另一种不同的梅毒螺旋体检测来确认阳性结果，可能会提高诊断能力。
