A comparison of the metabolic side-effects of the second-generation antipsychotic drugs risperidone and paliperidone in animal models
Bibliographic record
Abstract
BACKGROUND: The second generation antipsychotic drugs represent the most common form of pharmacotherapy for schizophrenia disorders. It is now well established that most of the second generation drugs cause metabolic side-effects. Risperidone and its active metabolite paliperidone (9-hydroxyrisperidone) are two commonly used antipsychotic drugs with moderate metabolic liability. However, there is a dearth of preclinical data that directly compares the metabolic effects of these two drugs, using sophisticated experimental procedures. The goal of the present study was to compare metabolic effects for each drug versus control animals. METHODS: Adult female rats were acutely treated with either risperidone (0.1, 0.5, 1, 2, 6 mg/kg), paliperidone (0.1, 0.5, 1, 2, 6 mg/kg) or vehicle and subjected to the glucose tolerance test; plasma was collected to measure insulin levels to measure insulin resistance with HOMA-IR. Separate groups of rats were treated with either risperidone (1, 6 mg/kg), paliperidone (1, 6 mg/kg) or vehicle, and subjected to the hyperinsulinemic euglycemic clamp. RESULTS: Fasting glucose levels were increased by all but the lowest dose of risperidone, but only with the highest dose of paliperidone. HOMA-IR increased for both drugs with all but the lowest dose, while the three highest doses decreased glucose tolerance for both drugs. Risperidone and paliperidone both exhibited dose-dependent decreases in the glucose infusion rate in the clamp, reflecting pronounced insulin resistance. CONCLUSIONS: In preclinical models, both risperidone and paliperidone exhibited notable metabolic side-effects that were dose-dependent. Differences between the two were modest, and most notable as effects on fasting glucose.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".