Neuroleptic Malignant Syndrome in a Patient With Anti-N-Methyl-D-Aspartate Receptor Encephalitis: Case Report and Review of Related Literature
Bibliographic record
Abstract
INTRODUCTION: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe but treatable disease that presents with symptoms similar to neuroleptic malignant syndrome (NMS). CASE REPORT: We describe a 28-year old female who initially presented with headaches, behavioral changes, anxiety, lip tremors, and rigidity of extremities. She was prescribed with olanzapine and later manifested with neuroleptic malignant syndrome symptoms such as decrease in sensorium, muscle rigidity, hyperthermia and tachycardia. Further investigation showed presence of bilateral ovarian teratoma and anti-NMDAR antibodies in her serum and cerebrospinal fluid. Symptoms resolved after intravenous high-dose methylprednisolone, bilateral oophoro-cystectomy, and intravenous immunoglobulin administration. Overlapping pathological mechanisms of anti- NMDAR encephalitis and NMS were discussed. Ten patients with anti- NMDAR encephalitis and NMS were noted in a review of literature. Prognosis was favorable and intervention ranged from supportive to methylprednisolone and intravenous immunoglobulin administration, plasma exchange and teratoma resection. CONCLUSION: Anti- NMDAR encephalitis patients are at risk for NMS due to antipsychotic intolerance and other interrelated pathophysiological mechanisms. The overlap between the signs and symptoms of anti-NMDAR encephalitis and NMS poses a diagnostic dilemma and warrants a careful investigation and 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".