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Colorimetric correcting for sample concentration in stool samples

  • Joris R. Delanghe ORCID logo EMAIL logo , Jan Van Elslande , Maaike J. Godefroid , Alexandre M. Thieuw Barroso , Marc L. De Buyzere and Thomas M. Maenhout
Published/Copyright: September 23, 2024

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.


Corresponding author: Prof. Dr. Joris R. Delanghe, Labo Maenhout, Roger Van Steenbruggestraat 64, 8790 Waregem, Belgium, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Delanghe JR: conceptualization, writing the paper, Van Elslande J: data acquisition, Godefroid M: data aquisition, Thieuw Barroso AL: practical experiments, De Buyzere ML: statistics, writing the paper, Maenhout T: supervision, writing the paper. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Raw data are available upon request.

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Received: 2024-08-18
Accepted: 2024-09-11
Published Online: 2024-09-23
Published in Print: 2025-02-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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