TY - JOUR
T1 - Performance of fecal inflammatory biomarkers to identify watery shigellosis
T2 - Findings from the Enterics for Global Health (EFGH) Shigella surveillance study
AU - Ogwel, Billy
AU - Khanam, Farhana
AU - Badji, Henry
AU - Charles, Mary
AU - Qureshi, Sonia
AU - Horne, Bri'Anna
AU - Brennhofer, Stephanie A.
AU - Platts-Mills, James A.
AU - Sears, Khandra
AU - Tennant, Sharon
AU - Kim, Sara
AU - Omore, Richard
AU - Awuor, Alex O.
AU - Okonji, Caleb
AU - Iqbal, Junaid
AU - Ahmed, Naveed
AU - Hussain, Zarfishan
AU - Qadri, Firdausi
AU - Alam Raz, S. M.Azadul
AU - Bhuiyan, Elias Shawon
AU - Penataro Yori, Pablo
AU - Paredes Olortegui, Maribel
AU - Kosek, Margaret N.
AU - Jallow, Samba Juma
AU - Ceesay, Bubacarr E.
AU - Conteh, Bakary
AU - Nyirenda, Atusaye K.
AU - Munthali, Vitumbiko
AU - Lefu, Clement
AU - Rahman Bhuiyan, Taufiqur
AU - Munga, Stephen
AU - Hossain, M. Jahangir
AU - Cornick, Jennifer
AU - Qamar, Farah Naz
AU - Benkeser, David
AU - Rogawski Mcquade, Elizabeth T.
N1 - Publisher Copyright:
© 2026, Ogwel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/4.0/
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105041543285
U2 - 10.1371/journal.pntd.0014025
DO - 10.1371/journal.pntd.0014025
M3 - Article
C2 - 42224289
AN - SCOPUS:105041543285
SN - 1935-2727
VL - 20
JO - PLoS Neglected Tropical Diseases
JF - PLoS Neglected Tropical Diseases
IS - 6
M1 - e0014025
ER -