Psychotropic medication use pre and post-diagnosis of cluster B personality disorder: a Quebec’s health services register cohort
Bibliographic record
Abstract
Background: Cluster B personality disorders (PDs) are considered some of the most severe mental health conditions. Scarce evidence exists about the real-world utilization of psychotropics for cluster B PD individuals. Objective: We aimed to uncover trends and patterns of psychotropic medication use among individuals diagnosed with cluster B PD in the year before and after their diagnosis and to identify factors associated with medication use in a large cohort of individuals newly diagnosed with cluster B PDs. Methods: We conducted a population-based observational study using Quebec's health services register. We identified Quebec residents aged ≥14 years and insured with the provincial drug plan with a first diagnosis of cluster B PD recorded between April 1, 2002, and March 31, 2019. Cluster B PD was defined with ICD-9/10 diagnostic codes. We retrieved all claims for the main psychotropic medication classes: antipsychotics, antidepressants, anxiolytics, mood stabilizers, and attention-deficit/hyperactivity disorder (ADHD) medications. We calculated the proportion of individuals exposed to these medication classes and analyzed trends over the years using robust Poisson regression models, adjusting for potential confounders. We used robust Poisson regression to identify factors associated with medication class use. Results: We identified 87,778 new cases of cluster B PD, with a mean age of 44.5 years; 57.5% were women. Most frequent psychiatric comorbidities in the five years before cluster B PD diagnosis were depression (50.9%), anxiety (49.7%), and psychotic disorders (37.5%). Most individuals (71.0%) received at least one psychotropic during the year before cluster B PD diagnosis, and 78.5% received at least one of these medications in the subsequent year. The proportion of users increased after the diagnosis for antidepressants (51.6-54.7%), antipsychotics (35.9-45.2%), mood stabilizers (14.8-17.0%), and ADHD medications (5.1-5.9%), and remained relatively stable for anxiolytics (41.4-41.7%). Trends over time showed statistically significant increased use of antipsychotics and ADHD medications, decreased use of anxiolytics and mood stabilizers, and a stable use of antidepressants. Conclusion: Psychotropic medication use is highly prevalent among cluster B PD individuals. We observed an increase in medication use in the months following the diagnosis, particularly for antipsychotics, antidepressants, and mood stabilizers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".