Off-label drug use in pediatric anesthesia and intensive care according to official and pediatric reference formularies L'emploi non conforme de medicaments en anesthesie et en soins intensifs pediatriques selon les formulaires de reference officiels et pediatriques
Bibliographic record
Abstract
Purpose In pediatric practice, the official drug label often does not accurately reflect the contemporary use of many drugs prescribed to children. Therefore, clinicians frequently use contemporary drug references as a source of prescribing information instead of national formularies. The objective of this study was to compare drug prescriptions between two national formularies and two commnly used contemporary pediatric reference guidelines in the operating room/postanesthetic care unit (OR/ PACU), pediatric intensive care unit (PICU), and neonatal intensive care unit (NICU). Methods We performed a retrospective chart review of patients admitted over a one-month period to the NICU and PICU, and for one week during the same month, we reviewed charts of patients in the OR/PACU. The data collected included patients’ demographic information, drugs prescribed, and dosage information. We assessed conformity with two national formularies, the Canadian Compendium of Pharmaceuticals and Specialties (CPS) and France’s 2009 Dictionnaire Vidal (Vidal), and two contemporary pediatric references, the Hospital for Sick Children Handbook and Formulary and the Lexi-Comp Pediatric Dosage Handbook. Results Across the three clinical units, 59.7% (95% confidence interval [CI] 57.1-62.1%) of prescriptions were identified as being off-label, as defined by the CPS formulary. The odds of having an off-label prescription would have been substantially lower if the contemporary pediatric references (odds ratio [OR] = 0.074; 95% CI 0.0650.084) or Vidal (OR = 0.70; 95% CI 0.63-0.77) had been used to define the label (both P 0.001 compared with the
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 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".