Laboratory Values for Children With Newly Diagnosed Inflammatory Bowel Disease
Bibliographic record
Abstract
OBJECTIVE: The goal was to determine how often common laboratory tests yield normal results at the time of diagnosis for children with inflammatory bowel disease. METHODS: Data were obtained from a registry of children with newly diagnosed inflammatory bowel disease who were enrolled prospectively in 18 US/Canadian centers. Laboratory values investigated included hemoglobin level, platelet count, albumin level, and erythrocyte sedimentation rate. Disease severity was categorized by physician global assessment. RESULTS: A total of 526 children (mean age: 11.6 years; 58% male; 392 with Crohn disease and 134 with ulcerative colitis) were studied. All 4 values were normal for 21% of patients with mild Crohn disease and 54% with mild ulcerative colitis. In contrast, only 3.8% of children with moderate/severe Crohn disease and 4.3% with moderate/severe ulcerative colitis had normal results for all 4 tests. The erythrocyte sedimentation rate was least likely to be normal; overall, 26% of patients with inflammatory bowel disease had a normal erythrocyte sedimentation rate, including 18% with moderate/severe disease. Hemoglobin levels were normal for 32%, platelet counts for 50%, and albumin levels for 60%. There was no clear association between Crohn disease location and either severity or number of normal laboratory values. In contrast, there were direct correlations between ulcerative colitis disease severity and both the extent of bowel inflammation and the number of abnormal laboratory tests. CONCLUSION: The presence of normal screening laboratory studies should not dissuade clinicians from considering a diagnosis of inflammatory bowel disease.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".