Exposure to Antibiotics in a United States-Mexico Border Birth Cohort
Bibliographic record
Abstract
OBJECTIVE: The goal was to compare the frequency of children's antibiotic intake, emphasizing antibiotics with anti-Helicobacter pylori effects, in El Paso, Texas, and Juarez, Mexico. METHODS: Hispanic children were enrolled prenatally at mother-child clinics in El Paso, and Juarez, in 1998-2000, to identify determinants of H pylori infection. During follow-up examinations targeted every 6 months from 6 to 84 months of age, caretakers reported medication use during the preceding interval. Courses of any systemic and H pylori-effective antibiotics were compared for US and Mexican children. RESULTS: Antibiotic data were available for 602 children, from 2938 follow-up visits. Overall antibiotic intake was higher in Juarez, where 84% of children received > or = 1 course during the follow-up period (52% of visits), compared with El Paso, where 76% of children received > or = 1 course (40% of visits). In contrast, the intake of H pylori-effective antibiotics was higher in El Paso, where 65% of children received > or = 1 course during the follow-up period (27% of visits), compared with Juarez, where 44% of children received > or = 1 course (16% of visits). Of H pylori-effective courses, 94% contained amoxicillin and 2% each clarithromycin, metronidazole, and furazolidone; uses were primarily for throat and ear infections, diarrhea, and cold/flu. CONCLUSIONS: Pediatric antibiotic use was higher in Mexico than on the US side of the border. Apparent misuse of H pylori-effective antibiotics was more frequent in Juarez but also occurred in El Paso. Such misuse of antibiotics may lead to drug resistance and may impair the control of H pylori infection in this region.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".