Cognitive impact of anticholinergic and sedative burden in people with HIV
Bibliographic record
Abstract
OBJECTIVE: This study aims to estimate the extent to which anticholinergic and sedative burden is associated with cognitive ability and self-reported cognitive difficulties (SCD) in middle-aged and older adults living with HIV. DESIGN: This cross-sectional analysis examined data from the inaugural visit of participants enrolled in the Positive Brain Health Now (BHN) study. METHODS: Cognitive ability was measured using the Brief Cognitive Ability Measure (B-CAM; higher is better) and SCD using the Perceived Deficits Questionnaire (PDQ; higher is worse). Medication burden was quantified using several scoring systems, including the Anticholinergic Cognitive Burden (ACB), Anticholinergic and Sedative Burden Catalog (ACSBC), Anticholinergic Drug Scale (ADS), Anticholinergic Risk Scale (ARS), and the Sedative Load Model (SLM). Multivariable Ordinary Least Squares and quantile regression were utilized to estimate average effects and distribution-specific impacts, respectively. RESULTS: Of 824 participants (mean age 53 years, 84.7% men), 41.4% used anticholinergics (ACSBC) and 39% used sedatives (SLM). High anticholinergic burden was linked to worse cognitive ability [ β = -3.81; 95% confidence interval (CI): -7.16, -0.46] and SCD ( β = 3.89; 95% CI: 1.08, 6.71). Using three or more anticholinergics worsened cognitive ability ( β = -4.45; 95% CI: -8.54, -0.35), and using three or more sedatives increased SCD ( β = 4.35; 95% CI: 0.92-7.78). Stronger negative associations were observed in participants with lower cognitive ability and more difficulties. CONCLUSIONS: These results suggest that anticholinergic and sedative burden may contribute to cognitive impairment in people with HIV. Personalized medication management and regular cognitive assessments could mitigate these adverse effects.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".