Influence of dementia on multiple components of pain
Bibliographic record
Abstract
Experimental findings on the influence of dementia on pain have so far been conflicting. There is evidence for a decreased, an unchanged and even for an increased pain processing in patients with dementia. The present study was conducted to add on the description of the impact of dementia on pain processing by assessing multiple components of pain (subjective, facial, motor reflex and autonomic responses) in parallel in one group of demented patients. Subjective (rating scale), facial (FACS), motor reflex (NFR) and autonomic (SSR, heart rate) responses to noxious electrical stimulation were assessed in 35 demented patients and 46 aged-matched healthy controls. Stimulus intensities were tailored to the individual NFR threshold. Demented patients rated the stimuli similarly painful as healthy controls did; however, the ability to provide these self-report ratings was markedly diminished in demented patients. Facial responses to noxious stimulation were significantly increased in demented patients. In line with this the NFR threshold was markedly decreased in the patient group. Autonomic responses on the other hand tended to be diminished in patients with dementia. In conclusion, dementia tends to affect different pain components in different ways. Therefore, the assessment of pain in patients with dementia should be based on the measurement of multiple components of pain and not solely on subjective self-report ratings. Furthermore, taking into account our findings on facial responses and the NFR, we think that there is sufficient evidence suggesting a rather intensified processing of noxious stimulation in this patient group.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".