FP475PREDICTION AND VALIDATION OF HEMODIALYSIS DURATION IN INTENTIONAL METHANOL POISONING
Bibliographic record
Abstract
Introduction and Aims: Acidosis and methanol monitoring is essential in determination of hemodialysis (HD) duration in cases of methanol poisoning (MP). However, methanol monitoring is not easily available, leading to undue extension of HD. Accuracy and safety of prediction models for HD duration have never been validated in large number of cases of MP in the era of high-efficiency HD. The goal of the present study was to determine methanol elimination half-life, use a training set of cases for proposing a half-life based approach to determining HD duration, and finally to validate our approach in a validation set of MP. Methods: In a retrospective cohort study, we identified 71 episodes of MP in 55 subjects that were treated by alcohol dehydrogenase blockade, folinic acid and HD. All HD sessions were performed with high-efficiency filters with a surface area > 2.0 m2 and a dialysate flow of 750 ml/min. Using methanol levels during HD, we calculated methanol elimination T1/2 for individual episodes of MP through a one phase decay exponential regression analysis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".