Disentangling the Effects of Comorbidity and Polypharmacy on Cognitive Function and Physical Frailty in Individuals With HIV
Bibliographic record
Abstract
OBJECTIVE: To estimate the extent to which comorbidity, polypharmacy, and anticholinergic/sedative burden interrelate to influence cognitive ability, perceived cognitive deficits (PCD), and physical frailty in people living with HIV. DESIGN: Cross-sectional Structural Equation Modeling of data from 824 older people living with HIV in Canada, participating in the Positive Brain Health Now study. METHOD: Structural Equation Modeling was used to link observed variables, including comorbidity, polypharmacy, anticholinergic, and sedative burden, to cognitive ability and 2 latent constructs-physical frailty and PCD. The model was adjusted for age, sex, education, nadir CD4, duration of HIV, and symptoms of anxiety/depression. Maximum Likelihood with Robust standard errors and bootstrapping were used to test the robustness and significance of the model's indirect effects. RESULTS: Anticholinergic burden had a direct significant negative relationship with cognitive ability (βstd = -0.21, P < 0.05) and indirect effect on PCD (βstd = 0.16, P < 0.01) and frailty (βstd = 0.06, P < 0.01) through sedative burden. Sedative burden was directly associated with PCD (βstd = 0.18, P < 0.01) and indirectly with frailty through PCD (βstd = 0.07, P < 0.01). Comorbidity and polypharmacy exerted indirect effects on PCD and physical frailty through anticholinergic and sedative burden. The model fits the data well (CFI: 0.97, TLI: 0.94, RMSEA: 0.05, SRMR: 0.04). CONCLUSIONS: Anticholinergic and sedative burden function as a pathway through which polypharmacy and comorbidities influence physical frailty and PCD. Reducing the use of anticholinergic and sedative medications could help prevent and manage cognitive impairment and frailty in older people living with HIV.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".