Medication-induced acute dystonic reaction: the challenge of diagnosing movement disorders in the intensive care unit
Bibliographic record
Abstract
A 62-year-old man presented with left middle cerebral artery stroke. 1 h postadministration of tissue plasminogen activator, he received a total of 4 mg of haloperidol for combativeness. He developed partial complex status epilepticus, requiring benzodiazepines, phenytoin, propofol and intubation. 5 h later, he developed recurrent stereotyped tonic movements involving arching of the back, extension of the arms and contraction of opposing muscle groups. Repeat CT scan of the head showed evolving insular infarct. Differential diagnoses for these movements included tonic/clonic seizures, extensor (decerebrate) posturing from haemorrhagic conversion, neuroleptic malignant syndrome, or dystonic reaction. Given the lack of response to antiseizure medications, the recent administration of haloperidol, and the prompt resolution of movements following diphenhydramine administration, an acute dystonic reaction was considered. This atypical case of a critically ill patient with stroke highlights the fact that these patients may have multiple abnormal movements requiring careful analysis to guide diagnosis-specific management.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| 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".