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  • Title: Prevalence and predictors of Lymphogranuloma venereum in a high risk population attending a STD outpatients clinic in Italy.
    Author: Foschi C, Marangoni A, D'Antuono A, Nardini P, Compri M, Bellavista S, Filippini A, Bacchi Reggiani ML, Cevenini R.
    Journal: BMC Res Notes; 2014 Apr 09; 7():225. PubMed ID: 24716676.
    Abstract:
    BACKGROUND: We evaluated LGV prevalence and predictors in a high risk population attending a STI Outpatients Clinic in the North of Italy. METHODS: A total of 108 patients (99 MSM and 9 women), with a history of unsafe anal sexual intercourses, were enrolled. Anorectal swabs and urine samples were tested for Chlamydia trachomatis (CT) DNA detection by Versant CT/GC DNA 1.0 Assay (Siemens Healthcare Diagnostics Terrytown, USA). RFLP analysis was used for CT molecular typing. RESULTS: L2 CT genotype was identified in 13/108 (12%) rectal swabs. All LGV cases were from MSM, declaring high-risk sexual behaviour and complaining anorectal symptoms. Patients first attending the STI Outpatient Clinic received a significant earlier LGV diagnosis than those first seeking care from general practitioners or gastroenterologists (P = 0.0046). LGV prevalence and characteristics found in our population are in agreement with international reports. Statistical analysis showed that LGV positive patients were older (P = 0.0008) and presented more STIs (P = 0.0023) than LGV negative ones, in particular due to syphilis (P < 0.001), HIV (P < 0.001) and HBV (P = 0.001).Multivariate logistic regression analysis revealed that HIV and syphilis infections are strong risk factors for LGV presence (respectively, P = 0.001 and P = 0.010). CONCLUSIONS: Even if our results do not provide sufficient evidence to recommend routine screening of anorectal swabs in high-risk population, they strongly suggest to perform CT NAAT tests and genotyping on rectal specimens in presence of ulcerative proctitis in HIV and/or syphilis-positive MSM. In this context, CT DNA detection by Versant CT/GC DNA 1.0 Assay, followed by RFLP analysis for molecular typing demonstrated to be an excellent diagnostic algorithm for LGV identification.
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