Paraneoplastic neuropsychiatric syndrome presenting as delirium
Bibliographic record
Abstract
Delirium in patients with cancer is associated with poor outcomes, but reversible causes need to be ruled out. We report the case of a 59-year-old woman who was presented with behavioural and cognitive changes over 2 weeks. She was non-verbal and combative, requiring involuntary admission and declaration of incompetence to make healthcare treatment decisions. Infectious and metabolic investigations and initial brain imaging were unremarkable. She was diagnosed with limited-stage small cell lung cancer and a paraneoplastic neuropsychiatric syndrome. Owing to the patient's delirium, chemotherapy delivery required pharmacological and physical restraints. After 2 cycles of chemotherapy, she could participate in the decision process and was discharged home. She completed radical chemo-radiotherapy and has remained free of disease progression for 18 months. Paraneoplastic neuropsychiatric syndromes, although rare, are potentially treatable and need to be excluded as a cause of delirium.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".