Multiplying the serum aminotransferase by the acetaminophen concentration to predict toxicity following overdose
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Bibliographic record
Abstract
CONTEXT: The first available predictors of hepatic injury following acetaminophen (APAP) overdose are the serum APAP and aminotransferases [AT, i.e., aspartate (AST) aminotransferase or alanine (ALT) aminotransferase]. OBJECTIVE: We describe the initial value, rate of change, and interrelationship between these biomarkers in patients who develop hepatotoxicity despite treatment following acute overdose. A new parameter, the APAP × AT multiplication product, is proposed for early risk stratification. METHODS: We conducted a descriptive study of individuals selected from a multicenter retrospective cohort of patients hospitalized for APAP poisoning. We selected those acute APAP overdose patients who subsequently developed AT > 1,000 IU/L. Rising serum AT values were compared to simultaneously measured (or estimated) falling serum APAP. The APAP × AT was expressed relative to initiation of acetylcysteine therapy and grouped by time to meeting hepatotoxicity criteria. RESULTS: In the 94 cases studied, serum APAP concentrations were still appreciable [median 570 (interquartile range (IQR) 314-983) μmol/L] at the time of the first measured AT [211 (77-511) IU/L at 15.3 (12.1-19.2) h post-ingestion], yielding an initial APAP × AT of 99,000 (52,000-240,000) μmol × IU/L(2). Because serum AT rose rapidly (doubling time 9.5 h ) and APAP fell slowly (half-life 4.8 h), the multiplication product remained elevated during the first 12-24 h of antidotal therapy, especially among patients who developed earlier hepatotoxicity (AT > 1,000 IU/L). DISCUSSION AND CONCLUSIONS: The APAP × AT multiplication product, calculated at the time of presentation and after several h of antidotal therapy, holds promise as a new risk predictor following APAP overdose. It requires neither graphical interpretation nor accurate time of ingestion, two limitations to current risk stratification.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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 it