Age-Dependent Metabolic Effects of Second-Generation Antipsychotics in Second-Generation Antipsychotic-Naïve French Canadian Patients
Bibliographic record
Abstract
BACKGROUND: Patients receiving second-generation antipsychotics (SGAs) may experience secondary metabolic effects such as weight gain, as well as changes in lipid and glucose metabolism. These effects are well documented in adults; however, fewer studies are available concerning their occurrence and their evolution in children and adolescents. OBJECTIVE: The aim of this study was to determine if there is an age-dependent variation in the metabolic effects of SGAs in a drug-naïve population. METHODS: Charts of 232 French Canadian patients participating in a program monitoring the metabolic effects of SGAs were retrospectively reviewed. A total of 85 SGA-naïve patients were selected, including 58 youths and 27 adults. Changes, relative to baseline, in weight, body mass index, lipid metabolism (total cholesterol, low-density lipoprotein, high-density lipoprotein, and triglyceride), and fasting blood glucose were assessed, with follow-up at 3, 6, 12, and 24 months. RESULTS: With respect to weight gain, in both the youth and adult groups, body mass index significantly increased from baseline at 3 months (10.1% [p < 0.0001] and 12.2% [p < 0.0001], respectively) and 6 months (11.8% [p < 0.0001] and 13.1% [p < 0.0001], respectively). With respect to lipid metabolism, in the youth group, there was no significant change. In the adult group, there was a significant increase at 3 and 6 months in total cholesterol (24.0% [p = 0.004] and 24.1% [p = 0.0006], respectively), low-density lipoprotein (26.8% [p = 0.019] and 30.1% [p = 0.010], respectively), and high-density lipoprotein (10.2% [p = 0.04] and 17.1% [p = 0.005], respectively). There was no significant change in triglyceride and glucose metabolism in both groups. CONCLUSIONS: Our results confirm the age-independent effects of SGA on weight gain. However, more data are needed to explore the age effect on glucose and lipid metabolism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".