Within-Stool and Within-Day Sample Variability of Fecal Calprotectin in Patients With Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND GOALS: The use of fecal calprotectin (FC) as a stool biomarker for differentiating inflammatory bowel disease (IBD) from IBS has been well validated, and there is a strong correlation between FC and the presence of endoscopic inflammatory lesions. However, recent studies have demonstrated intraindividual sample variability in patients with IBD, possibly limiting the reliability of using a single sample for monitoring disease activity. Our aim was to assess the within-stool and within-day sample variability of FC concentrations in patients with IBD. STUDY: We examined a cross-sectional cohort of 50 adult IBD patients. Eligible patients were instructed to collect 3 samples from different parts of the stool from their first bowel movement of the day and 3 samples from each of up to 2 additional bowel movements within 24 hours. FC concentrations were measured by a rapid, quantitative point-of-care test using lateral flow technology (Quantum Blue). Descriptive statistics were used to assess FC variability within a single bowel movement and between different movements at different FC positivity cutoffs. RESULTS: Within a single bowel movement, there was clinically significant sample variability ranging from 8% to 23% depending on the time of the day or on the FC positivity cutoff value. Between bowel movements, there was clinically significant sample variability ranging from 13% to 26% depending on the FC positivity cutoff. CONCLUSIONS: Considering a single FC sample, the first sample of the day with an FC positivity cutoff of 250 μg/g provided the most reliable indication of disease activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".