Extracorporeal treatments for isoniazid poisoning: Systematic review and recommendations from the EXTRIP workgroup
Bibliographic record
Abstract
Abstract Isoniazid toxicity from self‐poisoning or dosing errors remains common in regions of the world where tuberculosis is prevalent. Although the treatment of isoniazid poisoning is centered on supportive care and pyridoxine administration, extracorporeal treatments (ECTRs), such as hemodialysis, have been advocated to enhance elimination of isoniazid. No systematic reviews or evidence‐based recommendations currently exist on the benefit of ECTRs for isoniazid poisoning. The Extracorporeal Treatments in Poisoning (EXTRIP) workgroup systematically collected and rated the available evidence on the effect of and indications for ECTRs in cases of isoniazid poisoning. We conducted a systematic review of the literature, screened studies, extracted data on study characteristics, outcomes, and measurement characteristics, summarized findings, and formulated recommendations following published EXTRIP methods. Forty‐three studies (two animal studies, 34 patient reports or patient series, and seven pharmacokinetic studies) met inclusion criteria. Toxicokinetic or pharmacokinetic analysis was available for 60 patients, most treated with hemodialysis ( n = 38). The workgroup assessed isoniazid as “Moderately Dialyzable” by hemodialysis for patients with normal kidney function (quality of evidence = C) and “Dialyzable” by hemodialysis for patients with impaired kidney function (quality of evidence = A). Clinical data for ECTR in isoniazid poisoning were available for 40 patients. Mortality of the cohort was 12.5%. Historical controls who received modern standard care including appropriately dosed pyridoxine generally had excellent outcomes. No benefit could be extrapolated from ECTR, although there was evidence of added costs and harms related to the double lumen catheter insertion, the extracorporeal procedure itself, and the extracorporeal removal of pyridoxine. The EXTRIP workgroup suggests against performing ECTR in addition to standard care (weak recommendation, very low quality of evidence) in patients with isoniazid poisoning. If standard dose pyridoxine cannot be administered, we suggest performing ECTR only in patients with seizures refractory to GABA A receptor agonists (weak recommendation, very low quality of evidence).
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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 | 0.024 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".