Lactose Breath Test in Children: Relationship Between Symptoms During the Test and Test Results
Bibliographic record
Abstract
BACKGROUND: Lactose malabsorption affects 70% of the world population. The hydrogen breath test (HBT) is used clinically to test for this condition. The aim of our study was to describe the relationship between symptoms experienced before and during the HBT and test results. METHODS: We included children who underwent the HBT in the pediatric gastroenterology unit at Dana-Dwek Children's Hospital during a 6-month period. Previous symptoms and those experienced before and after the HBT were assessed using a questionnaire and a validated pain scale. RESULTS: Ninety-five children were included in the study, and 66.3% had a positive HBT. Diarrhea and flatulence during the test were significantly more frequent in the group with a positive HBT compared to those with a negative test (31.7% vs. 9.4%, P = 0.016 and 69.8% vs. 40.6%, P = 0.006, respectively). The frequency of abdominal pain and bloating was similar. CONCLUSIONS: Diarrhea and flatulence during the HBT are the most specific symptoms of lactose intolerance. Abdominal pain should not be automatically attributed to lactose intolerance even in the presence of lactose malabsorption. Coupling the HBT with a real-time questionnaire facilitates interpretation of results and subsequent recommendations.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".