La prise en charge des surdoses d’acétaminophène à l’urgence : sujet étonnamment complexe !
Bibliographic record
Abstract
L’acétaminophène (APAP) est l’une des molécules les plus consommées par la population. Les infirmier.ères d’urgence doivent donc évaluer quotidiennement des personnes exposées à ce type de molécule, que la dose ingérée soit toxique ou non. Plusieurs conséquences, trop souvent sous-estimées, mais pouvant être fatales, sont associées aux surdoses à l’APAP. L’évaluation initiale dès le triage s’avère donc importante afin d’estimer le risque d’hépatotoxicité, puis de déterminer le besoin de traitement. L’objectif de cet article est donc de guider le personnel infirmier d’urgence lors de l’évaluation des personnes potentiellement intoxiquées à l’APAP et de démystifier la molécule, les types d’exposition, l’analyse des résultats de laboratoire, l’approche thérapeutique appropriée et les critères d’initiation et de cessation du traitement selon le contexte.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".