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Record W4391162783 · doi:10.1093/ecco-jcc/jjad212.0210

P080 High faecal pH and low total microbial load associate with normalisation of faecal calprotectin in children with Crohn’s disease treated with exclusive enteral nutrition; results from iPENS, a multicentre, prospective study

2024· article· en· W4391162783 on OpenAlexaff
Konstantinos Gkikas, Murilo Moura Lima, Shona Mckirdy, Ben Nichols, Caroline Kerbiriou, Lisa Gervais, Gillian Smith, L. Armstrong, T. Jordan, Iain Chalmers, Helen Barlow, Ghassan Al Hourani, Rafeeq Muhammed, D Wands, Priya Narula, Millan S. Patel, Umer Zeeshan Ijaz, Simon Milling, Marco Gasparetto, Paul Henderson, David C. Wilson, Richard Hansen, R K Russell, Konstantinos Gerasimidis

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineFaecal calprotectinGastroenterologyInternal medicineCalprotectinFecesCrohn's diseaseAnthropometryDiseaseInflammatory bowel diseaseMicrobiologyBiology

Abstract

fetched live from OpenAlex

Abstract Background Exclusive enteral nutrition (EEN) is a main therapy for active Crohn’s disease (CD) in children, but normalisation of faecal calprotectin (FCAL) varies among patients, even in those who enter clinical remission. To better understand disease characteristics related to EEN efficacy and its mechanism of action, we compared clinical and microbial parameters between patients whose FCAL normalised against those who did not at EEN completion. Methods Children with CD, clinically responding to EEN, were recruited from 11 UK hospitals (January 2020- May 2023, NCT04225689) and provided a single faecal sample before EEN completion. Patients were divided in two groups according to levels of FCAL at EEN completion (FCAL<250 and FCAL>250 mg/kg). Levels of faecal short chain fatty acids (SCFA), faecal sample characteristics (pH, water content (%), bristol stool score) and total microbial load (qPCR) were compared between the two groups. Anthropometric and clinical parameters (blood inflammatory markers, use of immunosuppressants, disease duration, disease location) were also compared. Machine learning using feature elimination with data imputation for missing data was performed to identify associations between clinical, anthropometry, microbial parameters and FCAL normalisation. Results At EEN completion, 84 children (female, 35%) were recruited [age, median (IQR): 13.2 (11.8, 14.9 years)] with a median (Q1, Q3) FCAL of 643 (146, 2033) mg/kg. Out of 84 patients, 35 (42%) had an FCAL<250 mg/kg. Total microbial load and SCFA were measured in a subset of patients (n=44). Patients with FCAL<250mg/kg had a higher faecal pH and lower microbial load compared to those with FCAL>250mg/kg [faecal pH; FCAL<250 mg/kg: 8.3 (8.1, 8.6) vs FCAL>250 mg/kg; 7.95 (7.6, 8.3), p=0.001; microbial load (log10 16S rRNA gene copies/g): FCAL<250mg/kg: 10.7 (10.4, 10.9) vs FCAL>250mg/kg: 11.0 (10.5, 11.2), p=0.02]. Median BMI z-score was also non-significantly (p=0.052) higher in patients with FCAL<250mg/kg. The use of immunosuppressants at EEN completion, disease duration, disease location and other faecal parameters were not different between the two groups. A multicomponent random forest model (clinical, blood inflammatory markers, anthropometry, faecal parameters) predicted normalisation of FCAL with 71% accuracy (sensitivity: 69%, specificity: 71%, p=<0.001, Figure 1). Higher faecal pH, BMI z-scores and lower total microbial load were the most influential parameters relating to FCAL<250mg/kg. Conclusion We showed that the efficacy of EEN in reducing gut inflammation might be, at least in part, mediated via reducing gut bacterial biomass and modulating luminal pH and the downstream effects this may have on inflammatory members of the microbial community.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.203
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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