Capillary Flow Rates in the Duodenum of Pediatric Ulcerative Colitis Patients Are Increased and Unrelated to Inflammation
Bibliographic record
Abstract
BACKGROUND AND AIM: Inflammatory bowel diseases (IBD), including Crohn disease (CD) and ulcerative colitis (UC), are chronic pediatric disorders. Changes in vasculature are described in IBD, but these could be secondary to inflammation and the role in pathogenesis is poorly understood. Assessing circulatory changes in typically unaffected sites in IBD (eg, duodenum), when inflammation is absent, can identify vascular changes associated with pathogenesis. The aim of the study is to measure capillary flow rates in duodenal mucosa using probe-based confocal laser endomicroscopy (pCLE) during endoscopy in children with IBD. METHODS: Images of villi with visible blood vessels obtained using pCLE were captured as video sequences. Capillary flow rate (mm/s) was calculated by dividing the distance travelled by blood cells by the duration of the sequence. Flow rates were correlated with various clinical parameters. RESULTS: Forty-five patients (22 non-IBD, 14 CD, 9 UC) were included in the study. Duodenal capillary flow rates were significantly higher in UC patients (0.75 ± 0.07 mm/s) as compared to non-IBD (0.57 ± 0.03) and CD (0.65 ± 0.04). There was no correlation between serum hemoglobin and albumin, disease activity indices, serum inflammatory markers, and capillary flow rates in patients. CONCLUSIONS: This pilot study shows, for the first time, increased capillary blood flow in the duodenum of UC patients that was unrelated to inflammatory markers or disease activity. Thus, early vascular changes can be assessed using pCLE during endoscopy.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".