Costo-beneficio de un programa preventivo y terapéutico para reducir la deficiencia de hierro en Argentina
Bibliographic record
Abstract
OBJECTIVES: To estimate the direct and indirect cost of iron deficiency (ID) and iron-deficiency anemia (IDA) in Argentina and compare it with the cost of a prevention and treatment program. METHODS: Analysis of a prior scenario to gage the relative cost-benefit of an IDA prevention and treatment program for all low-income children and expectant mothers without social coverage/benefits in Argentina. The economic consequences of ID and IDA were estimated as direct (cost of care for premature birth) and indirect costs (future lost productivity due to poor cognitive development due of children with ID and current reduced productivity of adults with IDA) employing the specific methodology designed by The Micronutrient Initiative (Ottawa, Canada). The interventions were defined according the practical clinical guidelines in use in Argentina and the item costs were taken from Ministry of Health price lists. RESULTS: Each US$ 1.00 invested in an ID and IDA prevention and treatment program, assuming 90% coverage of breastfeeding/pregnant uninsured low-income mothers, would save US$ 33.40 by preventing the economic losses that would otherwise result from these conditions. CONCLUSIONS: DH interventions not only significantly improve the health status of the population, but also offer a considerable savings.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".