Associations between plasma clozapine/N-desmethylclozapine ratio, insulin resistance and cognitive performance in patients with co-morbid obesity and ultra-treatment resistant schizophrenia
Bibliographic record
Abstract
Clozapine (CLZ), the sole antipsychotic with superior efficacy for ultra-treatment resistant schizophrenia (TRS), is limited by adverse effects, including metabolic dysregulation. Clozapine's main metabolite, N-desmethylclozapine (NDMC), has potent 5-HT2C antagonist properties which may explain this metabolic dysfunction, thus the CLZ:NDMC ratio is of particular interest. High insulin resistance states could be associated with CYP1A2 induction and lower CLZ:NDMC ratios. Additionally, lower CLZ:NDMC ratios have been associated with better cognitive, but worse metabolic functioning. This study investigated associations between metabolic and cognitive parameters with the CLZ/NDMC ratio. Primary outcomes included relationships between the CLZ:NDMC ratio to the homeostatic model assessment for insulin resistance (HOMA-IR) and Brief Assessment of Cognition in Schizophrenia (BACS) composite z-scores. Secondary outcomes assessed relationships between CLZ:NDMC ratios to fasting insulin, BMI, weight, fasting glucose, and BACS digit sequencing z-scores. 38 patients who were overweight or obese with schizophrenia or schizoaffective disorder completed fasting bloodwork, anthropometric, psychopathological, and cognitive assessments. Multivariate regressions found a statistically significant inverse association between the CLZ/NDMC ratio and HOMA-IR (B = - 1.028, SE B = .473, β = - 0.348 p = 0.037), which may have been driven by fasting insulin levels (B = - 27.124, SE B = 12.081, β = - 0.351 p = 0.031). The CLZ/NDMC ratio may predict insulin resistance/metabolic comorbidity among patients with TRS receiving clozapine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".