Colorimetric correcting for sample concentration in stool samples.

IF 3.8 2区 医学 Q1 MEDICAL LABORATORY TECHNOLOGY
Joris R Delanghe, Jan Van Elslande, Maaike J Godefroid, Alexandre M Thieuw Barroso, Marc L De Buyzere, Thomas M Maenhout
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引用次数: 0

Abstract

Objectives: Fecal immunochemical tests (FIT) for hemoglobin are currently considered the screening investigation of choice for colorectal cancer and are worldwide recommended. Similarly, fecal calprotectin is a widely used test for monitoring intestinal inflammation. The pre-analytical issues regarding stool samples have hardly been dealt with and are difficult to solve. Currently, there are no reference analytes available which allow to correct test results for the variable water content of the stool sample. Studies on preanalytics of stool samples have generally focused on sample preparation and sample storage, but generally have paid little attention to the variability in sample hydration and sample composition.

Methods: Stercobilin is a stable heme metabolite which is abundant in stool. Stercobilin concentration can be simply assayed in stool extracts using colorimetry (determination of the I index). Serum indices (H, I and L) and bilirubin concentration of fecal extracts were determined on a Atellica Platform (Siemens).

Results: The inter-individual variation of stercobilin was found to be high. Assaying stercobilin allows to correct for stool sample dilution. The median value of the I-index was used as a reference for correcting the data. Correcting fecal blood results for sample dilution resulted in a significant increase in positive tests (from 9.3 to 11.7 %). For calprotectin, correction resulted in 3.1 % extra positive results and 7.7 % negative results.

Conclusions: Except in the case of obstructive jaundice, this correction can be applied. Correcting test results of common fecal analytes like FIT and calprotectin may result in a better tailored test interpretation.

用比色法校正粪便样本中的样本浓度。
目的:目前,粪便血红蛋白免疫化学检验(FIT)被认为是筛查结直肠癌的首选方法,也是全世界推荐使用的方法。同样,粪便钙蛋白也是一种广泛用于监测肠道炎症的检测方法。有关粪便样本的分析前问题几乎没有得到处理,也很难解决。目前,还没有参考分析物可以根据粪便样本中不同的含水量来校正检测结果。有关粪便样本预分析的研究一般都集中在样本制备和样本储存方面,但普遍很少关注样本水合和样本成分的变化:方法:软骨素是一种稳定的血红素代谢物,在粪便中含量丰富。使用比色法(测定 I 指数)可简单地测定粪便提取物中的软骨素浓度。血清指数(H、I 和 L)和粪便提取物中的胆红素浓度是在 Atellica 平台(西门子)上测定的:结果表明:粪卟啉的个体间差异很大。检测胱抑素可以校正粪便样本的稀释。I 指数的中值被用作校正数据的参考。对粪血结果进行样本稀释校正后,阳性检测结果显著增加(从 9.3% 增加到 11.7%)。就钙粘蛋白而言,校正后阳性结果增加了 3.1%,阴性结果增加了 7.7%:结论:除阻塞性黄疸外,这一校正方法是可行的。对常见粪便分析物(如 FIT 和钙蛋白)的检测结果进行校正,可以更好地解释检测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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