Bibliographic record
Abstract
A case history of a 31-year-old male schizophrenic patient is presented. The man was treated with olanzapine for three weeks before he died. After one week on a 10 mg daily dose of olanzapine, his fasting blood glucose was elevated to 11.3 mmol/L (203 mg/dL). In order to treat more aggressively his psychosis, the olanzapine dose was raised to 20 mg daily resulting in his fasting blood glucose climbing to 15.8 mmol/l (284 mg/dL). On the days preceding his death, he became progressively weaker, and developed polydipsia with polyuria. He had no personal or family history of diabetes mellitus and he was on no other medication at the time of his death. Postmortem blood, vitreous humor, and urine glucose concentrations were 53 mmol/L (954 mg/dL), 49 mmol/L (882 mg/dL), and 329 mmol/L (5922 mg/dL), respectively. Drug screen on urine and blood indicated only a small amount or olanzapine and no alcohols. Peripheral blood olanzapine concentration was within therapeutic limits, 45 ng/mL. Analysis of vitreous humor and urine revealed severe dehydration with small amounts of ketones. Death was attributed to hyperosmolar nonketotic diabetic coma, and olanzapine was felt most likely to be the cause. Another atypical neuroleptic, clozapine, has also been associated with the development and exacerbation of diabetes mellitus or diabetic ketoacidosis. We recommend including vitreous glucose and beta-hydroxybutyrate analysis as part of postmortem toxicology work up when the drug screen reveals the presence of either olanzapine or clozapine.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".