Performance evaluation of a smartphone-based home test for fecal calprotection.

IF 3.8 2区 医学 Q1 MEDICAL LABORATORY TECHNOLOGY
Simon Michaelis, Anna Hochfellner, Christopher Schneider, Wolfgang J Schnedl, Andreas Baranyi, Dietmar Enko
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Abstract

Objectives: Fecal calprotectin (FC) serves as a non-invasive marker for the assessment of gut inflammation in patients with inflammatory bowel disease (IBD). Laboratory measurements are usually performed with immunologic methods like enzyme-linked immunosorbent assay. Recently, quantitative home tests based on the lateral flow technology with smartphones as read-out devices have been developed. We compared the quantitative and qualitative performance of the quantitative lateral flow home test Preventis SmarTest® Calprotectin Home and the immunological test used in our laboratory (Eurospital Calprest® Turbo).

Methods: Fourty-five routine samples were analyzed in parallel with both tests according to the manufacturer's instructions. The read-out of the home test was performed with two smartphones (Apple iPhone 14 Pro and Samsung Galaxy XCover 5). The qualitative interpretation (positive, negative, borderline) was conducted using the cut-offs provided by the manufacturers.

Results: Statistically significant correlations with the laboratory standard method were observed for both smartphones (Spearman's rho 0.703 and 0.715, all p<0.005). The home test showed systematically higher concentrations compared to the routine assay. We found minimal qualitative agreement between the two tests (Cohen's kappas (κ)=0.323 and 0.300; p=0.003 and 0.005) showing a lower rate of positives with the home test. Both used smartphones showed good quantitative and qualitative agreement.

Conclusions: The tests are quantitatively not interchangeable. However, the home test may be applicable for the serial follow-up management of patients with IBD. The higher rate of samples classified as negative with the home test may lead to an underestimation of affected patients.

基于智能手机的家庭粪便热量保护测试性能评估。
目的:粪便钙蛋白(FC)是评估炎症性肠病(IBD)患者肠道炎症的非侵入性标记物。实验室测量通常采用酶联免疫吸附试验等免疫学方法。最近,基于横向流动技术、以智能手机为读取设备的家用定量检测方法应运而生。我们比较了Preventis SmarTest® Calprotectin Home家用横向流动定量检测仪和我们实验室使用的免疫学检测仪(Eurospital Calprest® Turbo)的定量和定性性能:方法:根据生产商的说明,对 45 份常规样本同时进行了两种检测方法的分析。家用检测仪的读数由两部智能手机(苹果 iPhone 14 Pro 和三星 Galaxy XCover 5)完成。定性分析(阳性、阴性、边缘)采用制造商提供的临界值:结果:两款智能手机与实验室标准方法之间存在明显的统计学相关性(Spearman's rho 分别为 0.703 和 0.715,均为 pConclusions):这两种测试在数量上不可互换。不过,家庭检测可能适用于对 IBD 患者的连续跟踪管理。家用检测法的阴性样本率较高,可能会导致低估受影响的患者人数。
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来源期刊
Clinical chemistry and laboratory medicine
Clinical chemistry and laboratory medicine 医学-医学实验技术
CiteScore
11.30
自引率
16.20%
发文量
306
审稿时长
3 months
期刊介绍: Clinical Chemistry and Laboratory Medicine (CCLM) publishes articles on novel teaching and training methods applicable to laboratory medicine. CCLM welcomes contributions on the progress in fundamental and applied research and cutting-edge clinical laboratory medicine. It is one of the leading journals in the field, with an impact factor over 3. CCLM is issued monthly, and it is published in print and electronically. CCLM is the official journal of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and publishes regularly EFLM recommendations and news. CCLM is the official journal of the National Societies from Austria (ÖGLMKC); Belgium (RBSLM); Germany (DGKL); Hungary (MLDT); Ireland (ACBI); Italy (SIBioC); Portugal (SPML); and Slovenia (SZKK); and it is affiliated to AACB (Australia) and SFBC (France). Topics: - clinical biochemistry - clinical genomics and molecular biology - clinical haematology and coagulation - clinical immunology and autoimmunity - clinical microbiology - drug monitoring and analysis - evaluation of diagnostic biomarkers - disease-oriented topics (cardiovascular disease, cancer diagnostics, diabetes) - new reagents, instrumentation and technologies - new methodologies - reference materials and methods - reference values and decision limits - quality and safety in laboratory medicine - translational laboratory medicine - clinical metrology Follow @cclm_degruyter on Twitter!
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