When do the aminotransferases rise after acute acetaminophen overdose?
Bibliographic record
Abstract
CONTEXT: Rising aminotransferases (ATs) [either aspartate aminotransferase (AST) or alanine aminotransferase (ALT) are one of the first signs of hepatotoxicity following acetaminophen (APAP)] overdose (OD). However, the timing and speed of such rises are not well characterized, hampering early risk prediction. OBJECTIVE: To describe the kinetics of AT release in acute APAP OD patients who develop hepatotoxicity despite treatment. METHODS: A descriptive study of acute APAP OD patients with peak AT > 1,000 IU/L taken from the derivation subset of the Canadian Acetaminophen Overdose Study (CAOS), a large, multicenter retrospective cohort of patients hospitalized for APAP poisoning. RESULTS: Of 2,488 hospital admissions for acute APAP OD, 94 met inclusion criteria. Treatment with acetylcysteine, mostly intravenously, was begun in all cases within 24 h of ingestion. The initial AT concentration was already elevated in most patients at presentation [median 211 (IQR 77-511) IU/L obtained at 15.3 (12.1-19.2) h postingestion], and exceeded 100 IU/L in almost all patients within 24 h of ingestion. Serum AT concentrations rose rapidly [doubling time 9.5 h (95% CI: 8.7-10.4 h)], especially in patients who developed AT > 1,000 IU/L within 48 h of ingestion. Coagulopathy was worse in these patients and in those with an AT > 250 IU/L during the first 12 h of treatment with acetylcysteine. DISCUSSION AND CONCLUSIONS: An abnormal and rapidly doubling AT at presentation is more typical in severely poisoned patients, as judged by the effects on clotting. These data suggest that risk prediction instruments may be improved by incorporating both the serum AT concentration at initiation of antidotal therapy and its rate of change. Further studies using such an approach are warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".