Anticholinergic burden and poor oral health are associated with frailty in geriatric patients undergoing inpatient rehabilitation: A cross‐sectional study
Bibliographic record
Abstract
BACKGROUND: Poor oral health is known to be associated with frailty in geriatric populations. Recent exposure to anticholinergic medications is responsible for features of poor oral health. Anticholinergic medications pose a cumulative risk for frailty. METHODS: We studied 115 geriatric inpatients (aged >65 years and recruited over a 3-month period from October to December 2017). Patients who were severely agitated, cognitively impaired, from a non-English speaking background and with severe sensory impairment were excluded. Frailty and oral health were assessed using the Reported Edmonton Frailty Scale and the Oral Health Assessment Test, respectively. Exposure to anticholinergic medications was assessed using the Anticholinergic Burden Scale. RESULTS: The mean age was 80 (range from 66 to 101). Only 44 patients (38.3%) were not exposed to any anticholinergic medication. Nearly two-thirds of patients were taking anticholinergic medications, with 25% classified as having a high anticholinergic burden (ACB ≥ 4). Approximately one-third of severely frail patients were exposed to a high anticholinergic burden. Patients with a high anticholinergic burden were more than twice as likely to have severe frailty (OR 2.21; 95% confidence interval 1.05-4.6). Poor oral health was associated with frailty (OR 1.24; 95% CI 1.02-1.49). CONCLUSION: High anticholinergic burden was found to be a risk marker for severe frailty independent of its effect on oral health. Poor oral health was associated with all levels of frailty. This study highlights a need for a review of medications with anticholinergic properties in older patients. Further research should be directed at whether deprescribing could prevent poor oral health or slow the progression of frailty.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".