Effect of Anticholinergic Drugs on the Efficacy of Activated Charcoal
Bibliographic record
Abstract
BACKGROUND: Although it is a commonly held belief that the ingestion of drugs with an anticholinergic action would prolong the duration of time after drug ingestion for effective gastrointestinal decontamination, data are lacking to support this belief. The purpose of this study is to determine whether activated charcoal is more effective in the presence of concurrent anticholinergic activity. METHODS: A three-limbed randomized crossover study in 10 healthy volunteers was completed to determine the ability of a 50 g dose of activated charcoal to reduce the bioavailability of a simulated overdose of acetaminophen (12 x 325 mg tablets) in the presence and absence of a concurrently present anticholinergic drug, atropine (0.01 mg/kg I. M. administered 15 min prior to the acetaminophen ingestion). RESULTS: After the acetaminophen ingestion, median Cmax occurred at 1 h for all three exposures but was lower in the atropine-treated study arm (31+/-19 mg/L) than in the control or charcoal alone intervention arms (49+/-13 and 51+/-16 mg/L, respectively) (P<0.05). Compared to the control area under the serum concentration vs. time curve, a single dose of activated charcoal 1 h after drug ingestion reduced acetaminophen bioavailability by 20% (95% CI 4-36%) and by 47% (95% CI 35-59%) in the presence of atropine (P<0.05 atropine plus charcoal vs. charcoal alone). CONCLUSIONS: Our data support the belief that activated charcoal is more effective in the presence of anticholinergic activity. Additional study is required to determine whether in patients with anticholinergic drug overdose, activated charcoal is effective at times beyond the recommendation for overdoses of drugs without this pharmacodynamic effect.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".