Use of the anion gap and intermittent hemodialysis following continuous hemodiafiltration in extremely high dose acute‐on‐chronic lithium poisoning: A case report
Bibliographic record
Abstract
A 35-year-old woman intentionally took 40,000 mg of lithium carbonate, and she was transferred to our hospital with nausea, vomiting, and diarrhea. She was diagnosed as having bipolar disorder 10 years ago and was receiving oral lithium therapy. Blood test results on arrival were remarkable for a negative anion gap of -2.1 and later, the serum lithium level turned out to be as high as 15.4 mEq/L. Intubation was required because of disrupted consciousness, and continuous hemodiafiltration (CHDF) was immediately started in the intensive care unit to obtain constant removal of lithium. After adding intermittent hemodialysis (IHD) twice during the daytime to accelerate the lithium clearance, CHDF became unnecessary on day 4, and she was extubated on day 6 with complete recovery of consciousness. Close monitoring of the patient data showed recovery of the decreased anion gap as indicator of the serum lithium level reduction. On day 36, she was discharged without any complication and sequela. The current case highlighted the effective use of CHDF between IHD sessions to prevent the rebound elevation of lithium and the role of the anion gap as a surrogate marker of serum lithium concentration during the treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".