دورية أكاديمية
أعرض في EDS

Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis.

التفاصيل البيبلوغرافية
العنوان: Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis.
المؤلفون: Checchi F; London School of Hygiene and Tropical Medicine, United Kingdom. Francesco.checchi@lshtm.ac.uk, Chappuis F, Karunakara U, Priotto G, Chandramohan D
المصدر: PLoS neglected tropical diseases [PLoS Negl Trop Dis] 2011 Jul; Vol. 5 (7), pp. e1233. Date of Electronic Publication: 2011 Jul 05.
نوع المنشور: Evaluation Study; Journal Article
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101291488 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1935-2735 (Electronic) Linking ISSN: 19352727 NLM ISO Abbreviation: PLoS Negl Trop Dis Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science
مواضيع طبية MeSH: Diagnostic Techniques and Procedures*, Trypanosoma brucei gambiense/*isolation & purification , Trypanosomiasis, African/*diagnosis , Trypanosomiasis, African/*parasitology, Algorithms ; Congo ; Humans ; Immunoassay/methods ; Parasitology/methods ; Sensitivity and Specificity ; Sudan ; Trypanosoma brucei gambiense/immunology ; Trypanosomiasis, African/pathology ; Uganda
مستخلص: Background: Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. There is insufficient evidence on the relative accuracy of these algorithms. This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo, Southern Sudan and Uganda.
Methodology and Principal Findings: The sequence of tests in each algorithm was programmed into a probabilistic model, informed by distributions of the sensitivity, specificity and staging accuracy of each test, constructed based on a literature review. The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions. In the baseline scenario, sensitivity was estimated as 85-90% in all but one algorithm, with specificity above 99.9% except for the Republic of Congo, where CATT serology was used as independent confirmation test: here, positive predictive value (PPV) was estimated at <50% in realistic active screening prevalence scenarios. Furthermore, most algorithms misclassified about one third of true stage 1 cases as stage 2, and about 10% of true stage 2 cases as stage 1. In the worst-case scenario, sensitivity was 75-90% and PPV no more than 75% at 1% prevalence, with about half of stage 1 cases misclassified as stage 2.
Conclusions: Published evidence on the accuracy of widely used tests is scanty. Algorithms should carefully weigh the use of serology alone for confirmation, and could enhance sensitivity through serological suspect follow-up and repeat parasitology. Better evidence on the frequency of low-parasitaemia infections is needed. Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools.
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تواريخ الأحداث: Date Created: 20110714 Date Completed: 20111025 Latest Revision: 20211020
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC3130008
DOI: 10.1371/journal.pntd.0001233
PMID: 21750745
قاعدة البيانات: MEDLINE
الوصف
تدمد:1935-2735
DOI:10.1371/journal.pntd.0001233