Malignant Catatonia in a Patient with Bipolar Disorder, B12 Deficiency, and Neuroleptic Malignant Syndrome
Bibliographic record
Abstract
A Case is presented of a 23-year-old woman with progressive onset of paranoid psychosis and catatonia, who was ultimately found to have both vitamin B12 deficiency and a family history of bipolar disorder. The patient was initially diagnosed with schizophrenia and treated with the antipsychotic medication ziprasidone. Her condition rapidly worsened to a state consistent with either neuroleptic malignant syndrome or malignant catatonia. Work-up then revealed vitamin B12 deficiency and a family history of bipolar disorder. Her symptoms improved rapidly but partially with benzodiazepines and electrocon-vulsive therapy, and completely with addition of valproic acid, vitamin B12 replacement, and re-introduction of antipsychotic medication in the form of olanzapine. The authors discuss the differential diagnosis of catatonia as reflecting a high likelihood of underlying mood disorder; the evaluation and management of malignant catatonia and malignant neuroleptic syndrome; and the role of vitamin B12 deficiency in precipitating psychotic symptoms. The case also illustrates the problems of diagnosing and managing a multifactorial disorder with psychiatric, general medical, and perhaps iatrogenic components.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".