Management of toxic alcohol poisoning in New South Wales: a retrospective study
Bibliographic record
Abstract
Context Toxic alcohol poisoning causes significant morbidity and mortality, especially when treatment is delayed. We describe the epidemiology, management and outcomes of clinically significant toxic alcohol poisonings in New South Wales. We also evaluate the frequency and choice of antidotal therapies (fomepizole versus ethanol) and complications of poisoning and treatment.Methods We searched databases of the New South Wales Poisons Information Centre, and six tertiary clinical toxicology services. We included toxic alcohol poisonings referred to a clinical toxicologist, which met the indications for treatment. Data extracted included demographics, exposures, management, and outcomes.Results Among 259 patients presenting with suspected toxic alcohol poisoning between 2015 and 2023, 39 fulfilled the inclusion criteria. Ingestions included ethylene glycol (n = 31), diethylene glycol (n = 5), and methanol (n = 3). The median time to presentation was 4 h (IQR: 2–10 h; n = 23). The median time from hospital presentation to initiating alcohol dehydrogenase inhibition was 4 h (IQR: 2–6 h; n = 33). Five patients received fomepizole and 28 received ethanol therapy. In 23 patients receiving ethanol for ≥24 h, 10 (43%) had at least two subtherapeutic ethanol concentrations. Twenty-five patients received extracorporeal treatments, initiated within a median of 7 h (IQR: 4–11 h; n = 24). Twenty-two patients (56%) developed complications: acute kidney injury (n = 21), neurotoxicity (n = 10), and death (n = 4). In 18 ethanol-treated patients (64%), the use of fomepizole could have been advantageous, including avoiding intensive care admission (n = 8), simplifying monitoring during transport (n = 11), and delaying and/or foregoing extracorporeal treatment (n = 7).Discussion Most patients treated for toxic alcohol poisoning had proven poisonings, biochemically or by history. Complications were common for multiple reasons, including possible delays in diagnosis and treatment.Conclusion The management of patients with toxic alcohol poisonings is resource-intensive, and toxicity is associated with clinically significant morbidity and mortality. Delays in presentation, diagnosis and treatment initiation appear to be associated with the development of complications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".