Home‐based fecal calprotectin utilization in a general pediatric gastroenterology clinic
Bibliographic record
Abstract
OBJECTIVE: Remote investigation and monitoring have gained importance in ambulatory practice. A home-based fecal calprotectin (FC) test has been developed where the sample is processed and analyzed at home through a smartphone application. We aimed to assess the use of standard ELISA (sFC) versus home-based (hFC) FC testing in a general pediatric gastroenterology clinic. METHODS: Ambulatory pediatric patients with hFC or sFC performed between August 2019 and November 2020 were included. Data regarding demographics, clinical characteristics, medication use, investigations, and final diagnosis, categorized as inflammatory bowel disease (IBD), functional gastrointestinal (GI) disorders, organic non-IBD (ONI) GI disorders, non-GI disorders, and undetermined after 6 months of investigation, were recorded. RESULTS: A total of 453 FC tests from 453 unique patients were included. Of those, 249 (55%) were hFC. FC levels (median) were higher in children with IBD compared to non-IBD diagnosis (sFC 795 vs. 57 μg/g, hFC 595 vs. 47 μg/g, p < 0.001), and in ONI compared to functional GI disorders (sFC 85 vs. 54 μg/g, p = 0.003, hFC 57 vs. 40 μg/g, p < 0.001). No significant difference was observed between different ONI GI disorders or subtypes of functional disorders. Age did not significantly influence levels. CONCLUSIONS: Overall, hFC and sFC provide similar results in the general pediatric GI ambulatory setting. FC is a sensitive but not disease-specific marker to identify patients with IBD. Values appear to be higher in ONI GI disorders over functional disorders, although cut-off values have yet to be determined.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".