Outcomes of Severe Methanol Intoxication Treated with Hemodialysis: Report of Seven Cases and Review of Literature
Bibliographic record
Abstract
To identify factors associated with the outcome of severe methanol intoxication treated with hemodialysis, we analyzed the clinical course of 7 patients admitted with serum methanol level higher than 50 mg/dL, and therefore requiring hemodialysis. Four patients (group A) had adverse outcomes (1 death, 3 severe neurological deficits and/or blindness) and 3 patients (group B) had no adverse outcomes. Compared to group B, group A appeared to have a longer delay between ingestion of methanol and arrival at the emergency department (ED), a longer wait in the ED until ethanol infusion was started (3.6 ± 2.7 vs 1.3 ± 0.9 hr, p < 0.05), and, on admission, higher serum methanol (504 ± 219 vs 321 ± 228 mg/dL, p < 0.05), higher serum osmolality (460.5 ± 98.2 vs 397.6 ± 52.3 mOsm/kg, p < 0.05), higher serum osmolal gap (162.6 ± 76.7 vs 105.6 ± 52.9 mOsm/kg, p < 0.05), lower arterial pH (6.86 ± 0.08 vs 7.38 ± 0.16, p < 0.01), lower serum bicarbonate (4.6 ± 1.6 vs 19.9 ± 5.7 mmol/L, p < 0.01), and higher serum anion gap (36.5 ± 1.3 vs 14.3 ± 6.7 mEq/L, p < 0.01). Delay in the ED until hemodialysis was started did not differ (group A 6.4 ± 2.6 hr, group B 5.3 ± 3.5 hr), while duration of hemodialysis until serum methanol levels became permanently undetectable was longer in group A (15.0 ± 0.5 vs 8.4 ± 4.4 hr, p < 0.01). The ingested dose of methanol and the delay between ingestion and initiation of therapy to block methanol metabolism (ethanol infusion) and remove methanol from the body (hemodialysis) appear to be the critical factors influencing the outcome of methanol intoxication. Early diagnosis and initiation of treatment before substantial parts of the ingested methanol have been metabolized are of paramount importance in ensuring a favorable outcome.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".