Lithium Poisoning From a Poison Control Center Perspective
Bibliographic record
Abstract
The purpose of this study was to evaluate the severity of lithium poisoning from a poison control center-based population and the correlation of the Hansen and Amdisen classification with outcome and lithium levels in that setting. All lithium overdoses brought to the attention of the poison control center were prospectively observed during 1 year. Demographic data, amount ingested, coingestants, symptoms and signs, lithium levels, treatment, and outcome were recorded. There were 12 acute lithium overdoses: 5, 5, and 2 with grade 0, 1, and 2, respectively. No patients required hemodialysis or had sequelae or died. There were 174 acute-on-chronic overdoses: 66, 85, 15, and 8 with grade 0, 1, 2, and 3, respectively. Six patients underwent hemodialysis; none had sequelae but one died. There were 19 chronic poisonings: 9, 9, and 1 with grade 1, 2, and 3, respectively. Three patients underwent hemodialysis; one had sequelae and one died. Patients classified as grade 2 had higher lithium levels than those with grade 1 in patients with only lithium poisoning (3.08 +/- 0.77 vs. 2.09 +/- 0.91 mmol/L P = 0.03). The study concluded that morbidity (0.5%) and mortality (1%) associated with lithium poisoning are rarely observed. The Hansen and Amdisen classification does not appear to be a useful clinical tool to predict either morbidity or mortality and does not correlate well with lithium levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".