ArticlePractical laboratory medicine2019
Sweat chloride quantification using capillary electrophoresis.
Article in Practical laboratory medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 11 citations in OpenAlex.
- Diagnosing Cystic Fibrosis in the 21st Century-A Complex and Challenging Task.Diagnostics (Basel, Switzerland) · 2024Review
- Soft, skin-interfaced sweat stickers for cystic fibrosis diagnosis and management.Science translational medicine · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCystic fibrosis (CF) is the less rare and severe genetic disease among the European population. Biochemical diagnosis of CF is based on the demonstration of increased chloride concentration in sweat samples, obtained during the sweat test (ST). WynSep developed a capillary electrophoresis with contactless conductivity detection (CE-C4D) able to measure sweat chloride with a low sample volume. We evaluated the clinical feasibility of this device in a cohort of patients suspected of CF, in comparison with the common coulometric method (ChloroChek chloridometer).
methodsWe determined sweat chloride concentration of 65 samples from patients referred to our institution to undergo a sweat test. Each sample was submitted to coulometric method first, then WynSep-CE, with or without internal standard (IS) subject to sufficient volume sample.
resultsA total of 53 samples were analysed by both coulometric and WynSep-CE (using IS) methods. The method validation showed comparable analytical performances for both methods; no false positive or false negative was recorded. The two methods showed a high correlation (r = 0.993, p < 0.001) and a close agreement was demonstrated by two different statistical tests (Bland-Altman and Passing-Bablok).
conclusionsWynSep-CE is an accurate, fast, easy-to-use and an appropriate method for CF diagnosis.
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