Standardisation of lymphatic filariasis microfilaraemia prevalence estimates based on different diagnostic methods: a systematic review and meta-analysis

基于不同诊断方法的淋巴丝虫病微丝蚴血症患病率估计值的标准化:系统评价和荟萃分析

阅读:2

Abstract

BACKGROUND: Lymphatic filariasis (LF) infection is generally diagnosed through parasitological identification of microfilariae (mf) in the blood. Although historically the most commonly used technique for counting mf is the thick blood smear based on 20 µl blood (TBS20), various other techniques and blood volumes have been applied. It is therefore a challenge to compare mf prevalence estimates from different LF-survey data. Our objective was to standardise microfilaraemia (mf) prevalence estimates to TBS20 as the reference diagnostic technique. METHODS: We first performed a systematic review to identify studies reporting on comparative mf prevalence data as measured by more than one diagnostic test, including TBS20, on the same study population. Associations between mf prevalences based on different diagnostic techniques were quantified in terms of odds ratios (OR, with TBS20 blood as reference), using a meta-regression model. RESULTS: We identified 606 articles matching our search strategy and included 14 in our analyses. The OR of the mf prevalences as measured by the more sensitive counting chamber technique (≥ 50 µl blood) was 2.90 (95% confidence interval (CI): 1.60-5.28). For membrane filtration (1 ml blood) the OR was 2.39 (95% CI: 1.62-3.53), Knott's technique it was 1.54 (95% CI: 0.72-3.29), and for TBS in ≥ 40 µl blood it was 1.37 (95% CI: 0.81-2.30). CONCLUSIONS: We provided transformation factors to standardise mf prevalence estimates as detected by different diagnostic techniques to mf prevalence estimates as measured by TBS20. This will facilitate the use and comparison of more datasets in meta-analyses and geographic mapping initiatives across countries and over time.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。