Comparison of the Extracorporeal Treatments in Poisoning (EXTRIP) and Paris Criteria for Lithium Poisoned Patients
Bibliographic record
Abstract
Aim: Two recommendations for hemodialysis in lithium poisoning, one from the Extracorporeal TReatments in Poisoning (EXTRIP) workgroup and a single center retrospective one (Paris), differ. We compared outcomes in lithium poisoning based on these criteria with a primary outcome of worsening neurological symptoms in patients where EXTRIP and Paris criteria were discordant. Methods: Poison center data were queried for lithium poisoned patients for whom hemodialysis was either recommended or performed. Patients were categorized according to EXTRIP and Paris criteria and excluded if the peak lithium concentration was <1.2 mmol/L or if neurological follow-up was unavailable. Comparative analyses were only performed when both criteria could be assessed. Results: 219 patients were analyzed. Paris criteria were applied in 70 and EXTRIP criteria in 178. 42 patients were excluded because Paris criteria could not be applied. When Paris and EXTRIP both supported hemodialysis, 50/57 (88%) of patients who received hemodialysis improved, as did all 3 who did not receive hemodialysis. When Paris and EXTRIP opposed hemodialysis, all non-dialyzed patients did well. Among the 86 patients for whom EXTRIP supported hemodialysis but Paris did not, 4/19 (21%) patients not dialyzed deteriorated (p=0.02; OR=8.7, 95%CI=1.5-51.8), one of whom died. All 8 patients for whom Paris criteria supported hemodialysis but EXTRIP did not were dialyzed and improved. Conclusion: When the EXTRIP and Paris criteria are discordant, EXTRIP criteria outperforms the Paris criteria at identifying potentially ill patients who might benefit from hemodialysis.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".