METHODS: In a community-based study, faecal samples were collected from 605 participants and examined by wet mount, formalin-ether sedimentation, trichrome staining and nested multiplex PCR techniques. Demographic, socio-economic and environmental information was collected using a pre-tested questionnaire.
RESULTS: Overall, 324 (53.6%) of the samples were positive for Entamoeba cysts and/or trophozoites by microscopic examination. Molecular analysis revealed that 20.2%, 15.7% and 18.2% of the samples were positive for E. histolytica, E. dispar and E. moshkovskii, respectively. Multivariate analysis showed different sets of species-specific risk factors among these communities. Educational level was identified as the significant risk factor for E. histolytica; age and gender were the significant risk factors for E. moshkovskii; and sources of drinking water and consumption of unwashed vegetables were the significant risk factors for E. dispar. Moreover, living in coastal/foothill areas and presence of other infected family members were risk factors for both E. histolytica and E. moshkovskii infections.
CONCLUSION: The study reveals that Entamoeba spp. infection is highly prevalent among rural communities in Yemen, with E. histolytica, E. dispar and E. moshkovskii differentiated for the first time. Identifying and treating infected family members, providing health education pertinent to good personal and food hygiene practices and providing clean drinking water should be considered in developing a strategy to control intestinal parasitic infections in these communities, particularly in the coastal/foothill areas of the country.
METHODS: Samples were obtained from 172/192 children presenting to a site in rural India with acute encephalitis syndrome.
RESULTS: Using the reference VT ELISA, infection with Japanese encephalitis virus (JEV) was confirmed in 44 (26%) patients, with central nervous system infection confirmed in 27 of these; seven patients were dengue seropositive. Of the 121 remaining patients, 37 (31%) were JEV negative and 84 (69%) were JEV unknown because timing of the last sample tested was <10 day of illness or unknown. For patient classification with XCyton, using cerebrospinal fluid alone (the recommended sample), sensitivity was 77.8% (59.2-89.4) with specificity of 97.3% (90.6-99.2). For Panbio ELISA, using serum alone (the recommended sample), sensitivity was 72.5% (57.2-83.9) with specificity of 97.5% (92.8-99.1). Using all available samples for patient classification, sensitivity and specificity were 63.6% (95% CI: 48.9-76.2) and 98.4% (94.5-99.6), respectively, for XCyton ELISA and 75.0% (59.3-85.4) and 97.7% (93.3-99.2) for Panbio ELISA.
CONCLUSION: The two commercially available ELISAs had reasonable sensitivities and excellent specificities for diagnosing JEV.
METHODS: Patients initiating cART between 2006 and 2013 were included. TI was defined as stopping cART for >1 day. Treatment failure was defined as confirmed virological, immunological or clinical failure. Time to treatment failure during cART was analysed using Cox regression, not including periods off treatment. Covariables with P < 0.10 in univariable analyses were included in multivariable analyses, where P < 0.05 was considered statistically significant.
RESULTS: Of 4549 patients from 13 countries in Asia, 3176 (69.8%) were male and the median age was 34 years. A total of 111 (2.4%) had TIs due to AEs and 135 (3.0%) had TIs for other reasons. Median interruption times were 22 days for AE and 148 days for non-AE TIs. In multivariable analyses, interruptions >30 days were associated with failure (31-180 days HR = 2.66, 95%CI (1.70-4.16); 181-365 days HR = 6.22, 95%CI (3.26-11.86); and >365 days HR = 9.10, 95% CI (4.27-19.38), all P < 0.001, compared to 0-14 days). Reasons for previous TI were not statistically significant (P = 0.158).
CONCLUSIONS: Duration of interruptions of more than 30 days was the key factor associated with large increases in subsequent risk of treatment failure. If TI is unavoidable, its duration should be minimised to reduce the risk of failure after treatment resumption.
METHODS: Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS-2.
RESULTS: Twenty-six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91-100% and 79.3-86%, respectively. Another model which evaluated the 30-day mortality of dengue infection had an accuracy of 98.5%.
CONCLUSION: Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future.