Correlation of Endogenous Pain Modulation Function with Physical Activity in Elders Having Chronic Pain
Bibliographic record
Abstract
Context: Chronic pain is a major predicament of the elderly population and lacks appropriate treatment. In normal healthy individuals, physical activity (PA) shows an effect on endogenous pain modulation (EPM) function by producing central opioids and producing exercise-induced analgesia. Aims: This study aimed to determine a correlation between EPM function and PA of the elderly having chronic pain. Methodology: This was a cross-sectional study of 45 elderly individuals who were between 60 and 80 years of age, suffering from chronic pain. The EPM function was tested using conditioned pain modulation test and PA levels were obtained using Yale Physical Activity Survey (YPAS). In addition, we collected demographic details, duration of pain, and site of pain from the study population. Descriptive statistics was depicted in terms of frequency. Categorical variables were indicated as the mean and standard error of mean. The Spearman's rank correlation ( r ) test was used to find the correlation between conditioned pain modulation (CPM) and YPAS score. Results: A positive moderate correlation was found between EPM function and PA of elderly having chronic pain ( r = 0.05; P = 0.0002). Analysis of EPM function based on the gender of the study population showed that both females (22.54 ± 23.92) and males (6.24 ± 29.19) had similar EPM function values. YPAS score was found as a significant predictor of CPM ( P = 0.0003). Conclusion: There is a positive moderate correlation between EPM function and PA levels of elderly having chronic pain.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".