Prevalence of Analgesic Use and Pain in People with and without Dementia or Cognitive Impairment in Aged Care Facilities: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Pain is a frequent cause of discomfort and distress in residents in residential aged care facilities (RACFs). Despite the benefits of adequate pain management, there is inconsistency in the literature regarding analgesic use and pain in residents with dementia. The aim of this systematic review was to determine the prevalence of analgesic drug use among residents with and without dementia or cognitive impairment in RACFs. A systematic search of MEDLINE and EMBASE (inception to January 2014) was conducted using Medical Subject Headings and Emtree terms, respectively. Studies were included if they reported prevalence of analgesic use for residents both with and without dementia within the same study. Data extraction and quality assessment was performed independently by two investigators. Data on the prevalence of analgesic use, pain and painful conditions were extracted. Meta-analyses were performed using random effect models. The 7 included studies were of high quality (≥ 5 out of 7 on the adapted Newcastle-Ottawa Scale). Analgesic use in residents with and without dementia or cognitive impairment ranged from 20.2% to 61.2% and 38.8% to 79.6%, respectively. Paracetamol was the most prevalent analgesic in people with and without dementia. Residents with dementia or cognitive impairment had a significantly lower prevalence of analgesic use (odds ratio [OR] 0.576, 95% confidence interval [CI] = 0.406-0.816) and of self-reported and clinician-observed pain (OR 0.355, 95% CI = 0.278-0.454) than residents without cognitive impairment, despite a comparable prevalence of painful conditions. These findings may indicate under-reporting and under-detection of pain in persons with dementia, and subsequent suboptimal treatment.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".