Dispensing Error Leading to Alendronate Ingestion
Bibliographic record
Abstract
OBJECTIVE: To report a case of medication dispensing error by administration of similarly packaged drugs. CASE SUMMARY: A 6-year-old East Indian boy with asthma was mistakenly given alendronate, a bisphosphonate, for 3 months instead of montelukast, a leukotriene-receptor antagonist. Symptoms of esophageal irritation developed and disappeared on discontinuation of alendronate. DISCUSSION: Alendronate and montelukast have very similar packaging and are available in dosages that also can be similar for some patients. Alendronate caused symptoms of irritative gastritis in this child before the error was identified. This case report emphasizes one of the possible sources of medication dispensing errors: a mistaken identification due to similar packaging (confirmation bias). Manufacturers can help to prevent medication errors in many ways; in this case, more distinct packaging would have decreased the risk of error. A standard bar-coding scheme among manufacturers could lead to an important improvement in the safety of medication dispensation. Practitioners are also encouraged to report such errors to the United States Pharmacopoeia Medication Errors Reporting Program. CONCLUSIONS: With increased awareness of medication errors, healthcare practitioners, manufacturers, and patients should take precautionary steps to prevent dispensing errors and their consequences.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".