CHANGE-Rx: frailty, falls, polypharmacy, and inappropriate medication use in a Canadian cohort of people aged 65 years and older with HIV
Bibliographic record
Abstract
OBJECTIVE: To characterize the prevalence of polypharmacy, use of potentially inappropriate medications (PIMs), anticholinergic burden (ACB), and sedative burden and their association with the risk of frailty and falls in a Canadian cohort of older people with HIV. DESIGN: CHANGE-Rx is a cross-sectional analysis of baseline data from CHANGE-HIV, a prospective Canadian cohort of people with HIV aged 65 years and older. METHODS: Information on prescription, over-the-counter/natural-health product use, comorbidities, HIV-specific factors, frailty, and fall history were assessed at the baseline visit at cohort entry. Proportion of people with polypharmacy (≥5 non-antiretroviral drugs), severe polypharmacy (≥10 non-antiretroviral drugs), PIMs, ACB, and sedative burden were determined. Chi-square tests and multivariate regression analysis were used to assess the association between medication factors and the risk of frailty and falls. RESULTS: Four hundred forty participants were included: median age 69 years (range: 65-89), 16.4% were classified as frail, 20.7% experienced a fall (last 6 months), 53.8% had polypharmacy, 14.6% had severe polypharmacy, 49.3% had at least one 1 PIM. For prescribed comedications, 16.5 and 55.7% of participants had high ACB and sedative burden, respectively. The odds ratios (ORs) for frailty were 3.3, 2.6, and 2.9 among patients with high ACB, high sedative burden, and severe polypharmacy, respectively. The OR for falls were 1.9 and 1.8 for patients with high sedative burden and at least one PIM, respectively. CONCLUSION: Polypharmacy, PIMs, and high ACB and sedative burden are common among older adults with HIV in Canada. It remains to be determined if interventions addressing polypharmacy/PIMs would reduce falls and frailty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".