Prevalence, mortality and healthcare utilization of cluster B personality disorders in Quebec: A province cohort study, 2001–2012
Bibliographic record
Abstract
Background Cluster B personality disorder (PD) is a highly prevalent mental health condition in general population (1 to 6% depending on the subtype and study). Patients affected are known to be heavier users of both mental and medical healthcare than other clinical conditions such as depression. Few studies have highlighted their elevated mortality rate compared to general population. Methods The estimates were produced using data from the integrated monitoring system for chronic disease of Quebec. It provides annual and life prevalence, mortality rate, years of and healthcare utilization profile Quebec inhabitants. Results A total of 7,995,963 people were included in the study. The life prevalence of cluster B PD is 2.6%. The mean years of lost life is 13 for men and 9 for women when they are compared to general population. The 3 most important causes of death are: suicide (20.4%), cardiovascular diseases (19.1%) and cancers (18.6%). The standardized mortality ratio (SMR) for each medical condition is superior in cluster B personality disorders than general population. The most important SMR is for suicide (male: 10.2 and female: 21). In the year 2011–2012, 78% had consulted a general practitioner, 62% a psychiatrist, 41% were admitted in an emergency department and 21% were hospitalized. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 |
| 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".