Psychiatric and non-psychiatric polypharmacy among older adults with schizophrenia: Trends from a population-based study between 2000 and 2016
Bibliographic record
Abstract
Background: Schizophrenia is a severe psychiatric disorder associated with multiple psychiatric and non-psychiatric comorbidities. As adults with schizophrenia age, they may use many medications, i.e., have polypharmacy. While psychiatric polypharmacy is well documented, little is known about trends and patterns of global polypharmacy. This study aimed to draw a portrait of polypharmacy among older adults with schizophrenia from 2000 to 2016. Methods: This population-based cohort study was conducted using the data of the Quebec Integrated Chronic Disease Surveillance System of the National Institute of Public Health of Quebec to characterize recent trends and patterns of medication use according to age and sex. We identified all Quebec residents over 65 years with an ICD-9 or ICD-10 diagnosis of schizophrenia between 2000 and 2016. We calculated the total number of medications used by every individual each year and the age-standardized proportion of individuals with polypharmacy, as defined by the usage of 5+, 10+, 15+, and 20+ different medications yearly. We identified the clinical and socio-demographic factors associated with polypharmacy using robust Poisson regression models considering the correlation of the responses between subjects and analyzed trends in the prevalence of different degrees of polypharmacy. Results: From 2000 to 2016, the median number of medications consumed yearly rose from 8 in 2000 to 11 in 2016. The age-standardized proportion of people exposed to different degrees of polypharmacy also increased from 2000 to 2016: 5+ drugs: 76.6%–89.3%; 10+ drugs: 36.9%–62.2%; 15+: 13.3%–34.4%; 20+: 3.9%–14.4%. Non-antipsychotic drugs essentially drove the rise in polypharmacy since the number of antipsychotics remained stable (mean number of antipsychotics consumed: 1.51 in 2000 vs. 1.67 in 2016). In the multivariate regression, one of the main clinically significant factor associated with polypharmacy was the number of comorbidities (e.g., Polypharmacy-10+: RR[2 VS. 0–1] = 1.4; 99% IC:1.3–1.4, RR[3–4] = 1.7 (1.7–1.8); RR[5+] = 2.1 (2.1–2.2); Polypharmacy-15+: RR[2 VS 0–1] = 1.6; 99% IC:1.5–1.7, RR[3–4] = 2.5 (2.3–2.7); RR[5+] = 4.1 (3.8–4.5). Conclusion: There was a noticeable increase in polypharmacy exposure among older adults with schizophrenia in recent years, mainly driven by non-antipsychotic medications. This raises concerns about the growing risks for adverse effects and drug-drug interactions in this vulnerable population.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".