Polypharmacy and Potentially Inappropriate Medication Use in Older Adults With Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence and potential risk factors for polypharmacy and prescribing of the potentially inappropriate medications, opioids and benzodiazepines/Z-drugs, in older adults with systemic lupus erythematosus (SLE). METHODS: The study population comprised adults age ≥50 years meeting American College of Rheumatology or Systemic Lupus International Collaborating Clinics classification criteria followed at a tertiary care rheumatology clinic. Information on prescriptions filled in the 4 months preceding chart review was obtained from the Manitoba Drug Program Information Network. Clinical data, including age, sex, Charlson Comorbidity Index (CCI) score, Systemic Lupus Erythematosus Disease Activity Index 2000 score, prednisone use, SLE duration, and rural residence were abstracted from electronic medical records. Logistic regression analyses were performed to assess any association between polypharmacy (using 2 definitions: ≥5 and ≥10 medications), potentially inappropriate medication use, and clinical features. RESULTS: A total of 206 patients (mean age 62 years, 91% female, 36% rural) were included: 148 (72%) filled ≥5 medications, 71 (35%) filled ≥10 medications, 63 (31%) used benzodiazepines/Z-drugs, and 50 (24%) used opioids. Among the 77 patients age ≥65 years, 57 (74%) filled ≥5 medications, and 26 (34%) filled ≥10 medications, compared to 30% and 4%, respectively, of Manitobans age ≥65 years (National Prescription Drug Utilization Information System, 2016). The odds of polypharmacy were greater with prednisone use (adjusted odds ratio [OR] 3.70 [95% confidence interval (95% CI) 1.40-9.79] for ≥5 medications), CCI score (adjusted OR 1.62 [95% CI 1.20-2.17]), and rural residence (adjusted OR 2.05 [95% CI 1.01-4.18]). Odds of benzodiazepine/Z-drug use were increased with polypharmacy (adjusted OR 4.35 [95% CI 1.69-11.22]), and odds of opioid use were increased with polypharmacy (adjusted OR 6.75 [95% CI 1.93-23.69]) and CCI score (adjusted OR 1.29 [95% CI 1.08-1.54]). CONCLUSION: The prevalence of polypharmacy in this SLE cohort was higher than in the general Manitoban population. Polypharmacy is a strong marker for use of prescription benzodiazepines/Z-drugs and opioids.
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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 | 0.000 | 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 | 0.000 |
| 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".