Long-Term Metabolic Monitoring of Youths Treated with Second-Generation Antipsychotics 5 Years after Publication of the CAMESA Guidelines Are We Making Progress? Surveillance Métabolique à Long Terme des Jeunes Traités par Antipsychotiques de Deuxième Génération, Cinq ans Après la publication des Lignes Directrices Camesa: Faisons-Nous des Progrès?
Bibliographic record
Abstract
OBJECTIVE: The potential metabolic adverse effects of second-generation antipsychotics (SGA) need to be monitored. The Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics (CAMESA) offers guidelines for this purpose. We aimed to evaluate the long-term rates of youths receiving monitoring in mental health clinics and document the factors that may influence them. METHOD: The charts of 180 patients (13.3 ± 3.1 years, 54.4% males) receiving SGA treatment for the first time between January 2016 and June 2018 were reviewed. Monitoring was divided into baseline and 1- to 6-month and 9- to 24-month periods. Population under study was stratified into children (4 to 12 years) and adolescents (13 to 18 years). Sociodemographic characteristics, psychiatric diagnosis and comorbidities, prescribed SGAs and comedications, anthropometric measures (AM), blood pressure (BP), blood tests (BT), electrocardiogram, and the psychiatrist's years of practice were collected. Cross tables were used to present the monitoring rates. Categories were compared by covariate analysis. Rates of patients monitored across categories were compared using Fisher exact test. RESULTS: Monitoring rates for AM, BT, and BP were 55%, 47.8%, and 46.7% at baseline; 50%, 41.7%, and 45.2% at 1 to 6 months; and 47.2%, 41.5%, and 40.6% at 9 to 24 months, respectively. Higher monitoring rates were significantly associated with adolescent status (baseline, 1 to 6 months), a diagnosis of psychotic and/or affective disorder (baseline, 1 to 6 months, 9 to 24 months), having ≤1 psychiatric comorbidities (1 to 6 months), high SGA dose (baseline, 1 to 6 months), and clinician's experience (baseline, 9 to 24 months). Significantly lower monitoring rates were associated with the psychostimulant/atomoxetine comedication (baseline, 1 to 6 months, 9 to 24 months). CONCLUSION: Five years after publication of the CAMESA guidelines, metabolic monitoring is conducted for less than half of patients. In our sample, age, diagnostic category, psychiatric comorbidities, SGA dose, clinician's experience, and comedications influenced the monitoring rates. Major progress still needs to be made before reaching a satisfactory level of monitoring.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".