RESUMO
Background: Clinical diagnosis of neurocysticercosis (NC) is established by CT scan and MRI. However, absolute diagnosis is not possible in a fair number of cases, and serological assays are used as adjunct. Besides, CT scan and MR imaging are resource-intensive tests and not practical for screening in endemic areas. Aim: To provide a low-cost, efficient, and reproducible assay for the detection of antibodies against cysticerci. Hence we have attempted to standardize and evaluate the diagnostic utility of the cysticercus fasciolaris antigen in a Dot ELISA assay for diagnosis of NC. Setting and Design: Tertiary hospital-based, case-control series. Materials and Methods: Confirmed cases of NC diagnosed by presence of ring lesions in CT scan or MR imaging with presence of scolex were taken as positive controls (n = 50). Negative controls (n = 50) included subjects with normal CT scan studies (n = 30) and diseased controls with ring lesions in CT scan confirmed to be neurotuberculosis (n = 20). Dot ELISA was standardized and validated with commercially available ELISA (UBI, USA) using sera from the study groups. Statistical Analysis: Chi-square test was used to compare the immunodiagnostic performance of the two tests. P value less than .05 (P < 0.05) was considered significant. Results: The Dot ELISA had a sensitivity of 88% and specificity of 74% with a positive predictive value of 77.19% and negative predictive value of 81.06%. Likelihood ratios for a positive and a negative test were 3.4 and 0.2. The sensitivity and specificity of commercial ELISA were 92% and 84% respectively. Difference between the performances of the two tests was not significant statistically. Conclusions: Dot ELISA has sensitivity and specificity comparable to ELISA for the diagnosis of NC. The test is simpler, not requiring expertise and instrumentation. Further validation of the test as a screening tool is required.
RESUMO
In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.