Be Careful, Mom and Doc: Hepatotoxicity Associated with Prescribed Medications in Young Infants
Bibliographic record
Abstract
Accidental poisonings in young infants are relatively uncommon, and the careless caregiver is usually the culprit. We report two cases of hepatotoxicity due to prescribed medications. An infant was given 15 mL instead of 1.5 mL of paracetamol by his mother because she omitted the decimal point on the label of the drug bottle. The infant became symptomatic, and liver enzyme and clotting profile were abnormal, necessitating treatment with N-acetyl cysteine. Another infant was prescribed oral ketoconazole for thrush, resulting in elevation of liver enzymes. The serum alanine aminotransferase levels were transiently elevated but returned to normal, and both infants recovered uneventfully. This report serves to alert the doctor to avoid using decimal points in drug labeling and to avoid prescribing excessive amount of drug for trivial acute illness. Thrush in infancy is common and usually treated with oral nystatin. Other oral antifungals such as ketoconazole may be associated with liver derangement and should be avoided in infants.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".