Mental health and chronic medical conditions: schizophrenia, its treatment, risk of metabolic complications, and health care utilization
Bibliographic record
Abstract
Objective - To assess the relationship between schizophrenia and cardiovascular disease by evaluating metabolic risk associated with treatment for schizophrenia, prevalence of cardiovascular risk factors (CV-RF) and disease (CV-D), and health care utilization in people with schizophrenia compared to the non-schizophrenic population. Methods – Four studies were completed to evaluate the dissertation objectives. A systematic review was completed to quantify the change in metabolic parameters associated with use of atypical antipsychotic agents. The second study utilized a period prevalence design to compare prevalence of CV-RF (diabetes, hypertension, dyslipidemia) and CV-D in people with and without schizophrenia using the administrative databases of Alberta Health and Wellness. General and cardiac specialist health care utilization was evaluated in people with schizophrenia using data from Alberta Health and Wellness. Lastly, results from the Canadian Community Health Survey were used to evaluate prevalence of CV-RF and CV-D while controlling for important lifestyle and demographic variables unavailable in the databases of Alberta Health and Wellness. Results – Use of atypical agents, particularly clozapine, resulted in statistically significant weight gain and increases in total cholesterol and blood glucose compared to typical agents. Having schizophrenia was associated with a significantly higher prevalence of diabetes, obesity, smoking, and CV-D compared to people without schizophrenia. Individuals with schizophrenia visited a general practitioner and the emergency department more often, and were more likely to be hospitalized than those without schizophrenia. Despite having a higher prevalence of coronary artery disease, individuals with schizophrenia were significantly less likely to visit a cardiologist or undergo revascularization compared to people with coronary artery disease who did not have schizophrenia. Conclusion – Individuals with schizophrenia have a considerable burden of cardiovascular disease compared to people without schizophrenia. This is likely a result of a number of factors, including medications used to treat schizophrenia, the increased prevalence of smoking and other unhealthy lifestyle factors, and the increased prevalence of cardiovascular risk factors in people with schizophrenia. Individuals with schizophrenia utilize the general health care system more frequently than their non-schizophrenic counterparts, therefore the opportunity exists for monitoring for and management of modifiable cardiovascular risk factors in this vulnerable population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".