Instruments for pain assessment in patients with advanced dementia: A systematic review of the evidence for Latin America
Bibliographic record
Abstract
OBJECTIVE: Pain treatment is an essential component of care for elderly patients with advanced dementia. The objective of this study was to identify and analyze the different scales used for pain assessment in elderly persons diagnosed with dementia, in the literature available at the Latin American level. METHOD: A systematic review was performed on the existing scales for pain assessment in elderly people diagnosed with Alzheimer's disease, vascular dementia, and dementia with Lewy bodies. RESULTS: 226 articles were retrieved from the PUBMED, BIREME, and Scielo databases, of which a total of 10 articles entered the systematic review. The instruments identified in these publications were PAINAD, Abbey, McGill, and PACSLAC, while the Colored Pain Scale, Faces Pain Scale, and VAS scales were used as the silver standard. In Spanish, the Abbey scale, and in Portuguese, the PACSLAC scale showed the best reliability and validity coefficients. SIGNIFICANCE OF RESULTS: It is concluded that there are only two appropriate scales for the assessment of pain in people with dementia in the region of interest of this study. It is recommended to generate more evidence for a more accurate assessment of pain in people with dementia.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".