Out-of-hospital assessment and triage of paracetamol (acetaminophen) exposure in the United States and Canada: a consensus guideline
Bibliographic record
Abstract
INTRODUCTION: Consensus guidelines for out-of-hospital assessment and triage of paracetamol (acetaminophen) exposure were published in 2006. Changes in the healthcare system, paracetamol ingestion trends, and availability of paracetamol-containing products necessitate an update to these guidelines. Updated guidelines were created for out-of-hospital management of paracetamol exposure in the United States and Canada. METHODS: A modified Delphi consensus methodology was used to create a decision framework to evaluate clinical aspects of care related to paracetamol overdose in the out-of-hospital setting. Twenty-one panelists were selected by four clinical toxicology societies (America's Poison Centers®, American Academy of Clinical Toxicology, American College of Medical Toxicology, and Canadian Association for Poison Centres and Clinical Toxicology) to participate as panelists. Guidelines were collected from most poison centers in the United States and Canada, and systematic collection and review of medical literature was conducted. RESULTS: The panel developed a guideline for out-of-hospital management of paracetamol exposure that encompasses acute and repeated supratherapeutic ingestion patterns. Acute ingestion is defined as any ingestion presenting within 24 h of initial ingestion, regardless of ingestion pattern. Repeated supratherapeutic ingestion is defined as an exposure that occurs over a period of 24 h or more. This guideline emphasizes the importance of obtaining accurate history. When ingestion history is determined as accurate, dosage and ingestion pattern are used to decide treatment referral. It is recommended that patients be referred to the emergency department if their ingestion amount is: (1) ≥200 mg/kg or 10 g (whichever is less) within 24 h; (2) ≥150 mg/kg/24 h or 6 g/day (whichever is less) within 48 h; (3) ≥100 mg/kg/24 h or 4 g/day (whichever is less) for more than 48 h. DISCUSSION: The need for standardizing the out-of-hospital assessment and triage of paracetamol exposure is pressing. Despite the availability of acetylcysteine, some patients develop fatal liver failure due to missed diagnoses and delays in treatment. Failure to recognize cases requiring acetylcysteine is associated with significant morbidity and mortality. CONCLUSION: This consensus statement provides evidence-based guidance for out-of-hospital management of paracetamol ingestion to standardize healthcare facility referral criteria for paracetamol exposed patients.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".