Development and Validation of Weight, Height and Age Bands to Guide the Prescription of Fixed-Dose Dispersible Tablet Formulations
Bibliographic record
Abstract
OBJECTIVES: Conversion of pediatric essential drugs from syrup to dispersible tablet formulations would require fixed dose options guided by the weight band in which a child falls or a proxy for weight, such as height or age. The purpose of this study was to determine whether weight, height, or age bands can be created that would lead to greater than 95% of children receiving a therapeutic dose of 6 commonly prescribed essential drugs, including paracetamol, iron sulfate, amoxicillin, co-trimoxazole (i.e., trimethoprim/sulfamethoxazole), ciprofloxacin, and co-artemether (i.e., artemether/lumefantrine). METHODS: Using World Health Organization growth standards, we created 4 weight bands and then matched them to height and age 50th percentile growth curves. The resulting weight, height, and age bands were then applied to Ugandan and Bangladeshi anthropometric data sets, and the percentage of children who would have received a correct therapeutic dose based upon weight, height, or age was determined. This percentage was interpreted as acceptable if >95%, marginal if 90% to 95% and unacceptable if <90%. RESULTS: Applying the 4 weight bands to the 6 selected drugs, greater than 95% of children would have received an acceptable therapeutic dose across the 4 weight bands for each of the 6 drugs tested. None of the drugs tested would deliver an acceptable therapeutic dose across all bands based upon height or age among Ugandan children, and only co-trimoxazole would have been delivered at acceptable therapeutic levels based upon these bands in Bangladeshi children. CONCLUSIONS: For the 6 drugs tested, dispersible tablets prescribed on the basis of a 4-dose regimen determined by weight bands would deliver an acceptable therapeutic dose greater than 95% of the time. Substituting weight for age or height bands would result in unacceptable levels of under- or overdosing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".