Noninvasive Diagnostic Tests for Helicobacter Pylori Infection in Children
Bibliographic record
Abstract
Noninvasive tests can be used for the initial diagnosis of Helicobacter pylori infection and to monitor the success of eradication therapy. In populations with a low prevalence of H. pylori infection (children living in North America and Europe), a high sensitivity is required to make the test valuable for clinical practice. The 13C-urea breath test has been validated in children of different age groups in a significant number of infected and noninfected children in several countries and, thus far, is the only noninvasive test that fulfills sensitivity and specificity quality standards. In studies to date, enzyme immunoassays using monoclonal antibodies to detect H. pylori antigen in stool provide excellent results, but the number of children tested, particularly post-treatment, is not sufficient to recommend the test. All other noninvasive stool tests or methods based on the detection of specific antibodies in serum, whole blood, urine or saliva have limited accuracy in comparison with the 13C-urea breath test. Therefore, these tests cannot be recommended for clinical decision making in pediatric patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".