Thyrotoxicosis due to 1000-fold error in compounded liothyronine: A case elucidated by mass spectrometry
Bibliographic record
Abstract
Thyrotoxicosis attributable exclusively to triiodothyronine (T3) is, by necessity, caused by accidental or intentional ingestion of pharmaceutical preparations. The clinical presentation of T3 overdose appears to differ from classic thyroid storm. A 30-year-old female patient presented serially to the emergency department with headache, nausea and vomiting. Neurological work-up was negative and she was treated for presumed viral gastroenteritis. Eventually she developed confusion and was admitted. Laboratory investigations showed a suppressed TSH and a free T3 above the linear range (>30 pmol/L), estimated by dilution in normal serum to be 330 pmol/L. She was diagnosed with thyrotoxicosis secondary to recently prescribed compounded liothyronine and was treated with seven rounds of plasmapheresis. Using a rapidly developed mass spectrometric method for T3, it was determined that compounding pharmacy had dispensed liothyronine at a concentration ≃1000-times the prescribed dosage. The clinical and mass spectrometry laboratories played an essential role in the diagnosis of thyroid storm in this case of T3 overdose as the expected clinical features of hyperpyrexia, tachycardia and hypertension were initially absent.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".