Effect of Helicobacter pylori Infection on Growth Velocity of School-age Andean Children
Bibliographic record
Abstract
BACKGROUND: Helicobacter pylori infection affects about half of the world's population and is usually acquired in childhood. The infection has been associated with chronic gastritis, peptic ulcer, and stomach cancer in adulthood. Little is known, however, about its consequences on child health. We examined the effect of H. pylori infection on growth among school-age children in the Colombian Andes by comparing growth velocity in the presence and absence of H. pylori infection. METHODS: Children who were 4-8 years old in 2004 were followed up in a community where infected children received anti-H. pylori treatment (n = 165) and a comparison community (n = 161) for a mean of 2.5 years. Anthropometry measurements were made every 3 months and H. pylori status ascertained by urea breath test every 6 months. Growth velocities (cm/month) were compared across person-time with and without infection, using mixed models for repeated measures. RESULTS: In the untreated community, 83% were H. pylori-positive at baseline and 89% were -positive at study end. The corresponding prevalences were 74% and 46%, respectively, in the treated community. Growth velocity in the pretreatment interval was 0.44 (standard deviation [SD] = 0.13) cm/month. Models that adjusted for age, sex, and height estimated that H. pylori-positive children grew on average 0.022 cm/month (95% confidence interval = 0.008 to 0.035) slower than H. pylori-negative children, a result that was not appreciably altered by adjustment for socioenvironmental covariates. CONCLUSIONS: This study suggests that chronic H. pylori infection is accompanied by slowed growth in school-age Andean children.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".