Expert Consensus Guidelines for Stocking of Antidotes in Hospitals That Provide Emergency Care
Bibliographic record
Abstract
We provide recommendations for stocking of antidotes used in emergency departments (EDs). An expert panel representing diverse perspectives (clinical pharmacology, medical toxicology, critical care medicine, hematology/oncology, hospital pharmacy, emergency medicine, emergency medical services, pediatric emergency medicine, pediatric critical care medicine, poison centers, hospital administration, and public health) was formed to create recommendations for antidote stocking. Using a standardized summary of the medical literature, the primary reviewer for each antidote proposed guidelines for antidote stocking to the full panel. The panel used a formal iterative process to reach their recommendation for both the quantity of antidote that should be stocked and the acceptable timeframe for its delivery. The panel recommended consideration of 45 antidotes; 44 were recommended for stocking, of which 23 should be immediately available. In most hospitals, this timeframe requires that the antidote be stocked in a location that allows immediate availability. Another 14 antidotes were recommended for availability within 1 hour of the decision to administer, allowing the antidote to be stocked in the hospital pharmacy if the hospital has a mechanism for prompt delivery of antidotes. The panel recommended that each hospital perform a formal antidote hazard vulnerability assessment to determine its specific need for antidote stocking. Antidote administration is an important part of emergency care. These expert recommendations provide a tool for hospitals that offer emergency care to provide appropriate care of poisoned patients.
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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 | 0.049 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".