Skip to main navigation Skip to search Skip to main content

Performance of fecal inflammatory biomarkers to identify watery shigellosis: Findings from the Enterics for Global Health (EFGH) Shigella surveillance study

  • Billy Ogwel
  • , Farhana Khanam
  • , Henry Badji
  • , Mary Charles
  • , Sonia Qureshi
  • , Bri'Anna Horne
  • , Stephanie A. Brennhofer
  • , James A. Platts-Mills
  • , Khandra Sears
  • , Sharon Tennant
  • , Sara Kim
  • , Richard Omore
  • , Alex O. Awuor
  • , Caleb Okonji
  • , Junaid Iqbal
  • , Naveed Ahmed
  • , Zarfishan Hussain
  • , Firdausi Qadri
  • , S. M.Azadul Alam Raz
  • , Elias Shawon Bhuiyan
  • Pablo Penataro Yori, Maribel Paredes Olortegui, Margaret N. Kosek, Samba Juma Jallow, Bubacarr E. Ceesay, Bakary Conteh, Atusaye K. Nyirenda, Vitumbiko Munthali, Clement Lefu, Taufiqur Rahman Bhuiyan, Stephen Munga, M. Jahangir Hossain, Jennifer Cornick, Farah Naz Qamar, David Benkeser, Elizabeth T. Rogawski Mcquade

Research output: Contribution to journalArticlepeer-review

Abstract

Background Current syndromic guidelines for diarrhea treatment miss watery Shigella cases, leading to undertreatment of children who may benefit. Incorporating fecal inflammatory biomarkers into diagnosis may improve case identification. Methods We conducted an ancillary analysis using samples from six sites (The Gambia, Kenya, Malawi, Bangladesh, Pakistan, and Peru) from the Enterics for Global Health (EFGH)-Shigella surveillance study, a facility-based hybrid study of children aged 6-35 months with diarrhea. Four fecal biomarkers were quantified by enzyme-linked immunosorbent assays at enrollment: myeloperoxidase, calprotectin, neutrophil gelatinase-associated lipocalin (lipocalin-2), and hemoglobin. An ensemble model with leave-one-site-out cross-validation was used to predict watery shigellosis, incorporating biomarkers and nine clinical and socio-economic predictors. We compared the predictive performance of the algorithm using: a) all predictors (including biomarkers); b) all non-biomarker predictors; c) all predictors (with selected biomarkers). Results Between June 2022 and August 2024, a total of 4,191/9,476 (44.2%) children presented with watery diarrhea (non-bloody) and had their whole stool tested for the biomarkers and 4,083 stool samples or rectal swabs were tested by qPCR; 735 (18.0%) had Shigella-attributable diarrhea by qPCR. The full model incorporating all 13 predictors achieved an area under the curve (AUC) of 0.75 [95% CI: 0.67–0.78], with a sensitivity of 0.67 and specificity of 0.75. Excluding biomarkers reduced model performance by 8% (AUC 0.67, 95% CI: 0.61–0.70). Adding hemoglobin alone improved the model's discriminatory ability by 7%, while further adding myeloperoxidase had marginal contribution (1%), and lipocalin-2 (0%) and calprotectin none (0%). Conclusion Fecal hemoglobin substantially improved prediction scores for watery shigellosis. Consequently, implementation of point-of-care assays for hemoglobin could improve clinical diagnosis in these settings and inform appropriate antibiotic treatment.

Original languageEnglish (US)
Article numbere0014025
JournalPLoS Neglected Tropical Diseases
Volume20
Issue number6
DOIs
Publication statusPublished - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Performance of fecal inflammatory biomarkers to identify watery shigellosis: Findings from the Enterics for Global Health (EFGH) Shigella surveillance study'. Together they form a unique fingerprint.

Cite this