Baseline anticholinergic burden from medications predicts poorer baseline and long‐term health‐related quality of life in 16 675 men and women of <scp>EPIC‐Norfolk</scp> prospective population‐based cohort study
Bibliographic record
Abstract
PURPOSE: Previous studies investigating the association between anticholinergic burden (ACB) and health-related quality of life (HRQoL) showed conflicting results and focused on older adults or specific patient groups only. METHODS: Participants from the European Prospective Investigation of Cancer-Norfolk study were divided into three groups according to their ACB from medications at baseline, representing ACB scores of 0, 1 and ≥2. Outcomes of interest were the physical and mental component summary scores (PCS and MCS) of the Short Form-36, collected at 18 months from the baseline and again after a mean 13 years of follow-up. Linear regression and logistic regression for cross-sectional and longitudinal associations between ACB and HRQoL were constructed adjusting for potential confounders. RESULTS: A total of 16 675 participants, mean age 58.9 ± 9.1 years (55.6% female) and 7133 participants, mean age at follow-up 69.1 ± 8.7 years (56.8% female), were included in the cross-sectional and longitudinal analyses, respectively. In cross-sectional analysis, higher anticholinergic burden was associated with higher odds of being in the lowest quartile of PCS (ACB = 1; OR, 1.85[1.64, 2.09] and ACB ≥ 2:2.19[1.85, 2.58] and MCS (ACB = 1:1.47[1.30, 1.66] and ACB ≥ 2:1.68[1.42, 1.98]). In longitudinal analysis, higher anticholinergic burden was similarly associated with higher odds of being in the lowest quartile of PCS (ACB = 1:1.56[1.24, 1.95] and ACB ≥ 2:1.48[1.07, 2.03]) compared with ACB 0 group. The association with MCS scores did not reach statistical significance. CONCLUSION: The use of anticholinergic medications is associated with both short and long-term poorer physical functions but association with mental functioning appears more short-term.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".