13C-Urea Breath Test for the Diagnosis of Helicobacter pylori Infection in Children: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The (13) C-urea breath test ((13) C-UBT) is a safe, noninvasive and reliable method for diagnosing H. pylori infection in adults. However, the test has shown variable accuracy in the pediatric population, especially in young children. We aimed to carry out a systematic review and meta-analysis to evaluate the performance of the (13) C-UBT diagnostic test for H. pylori infection in children. METHODS: We conducted a systematic review of the PubMed, Embase and Liliacs databases including studies from January 1998 to May 2009. Selection criteria included studies with at least 30 children and reporting the comparison of (13) C-UBT against a gold standard for H. pylori diagnosis. Thirty-one articles and 135 studies were included for analysis. Children were stratified in subgroups of <6 and ≥6 years of age, and we considered variables such as type of meal, cutoff value, tracer dose, and delta time for the analysis. DISCUSSION: The (13) C-UBT performance meta-analyses showed 1, good accuracy in all ages combined (sensitivity 95.9%, specificity 95.7%, LR+ 17.4, LR- 0.06, diagnostic odds ratio (DOR) 424.9), 2, high accuracy in children >6 years (sensitivity 96.6%, specificity 97.7%, LR+ 42.6, LR- 0.04, DOR 1042.7), 3, greater variability in accuracy estimates and on average a few percentage points lower, particularly specificity, in children ≤6 years (sensitivity 95%, specificity 93.5%, LR+ 11.7, LR- 0.12, DOR 224.8). Therefore, the meta-analysis shows that the (13) C-UBT test is less accurate for the diagnosis of H. pylori infection in young children, but adjusting cutoff value, pretest meal, and urea dose, this accuracy can be improved.
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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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".