Sarcopenia, chronic pain, and perceived health of older: a cross-sectional study
Bibliographic record
Abstract
Abstract Introduction Aging is a dynamic and progressive process that can be associated with the presence of morbidities, such as chronic diseases, and functional decline, characteristic of sarcopenia, which directly affects the self-perceived health of the older. Objective To test the hypothesis that there is an association between sarcopenia, chronic pain, and perceived health in the older. Methods The study used a quantitative approach and enrolled 43 sarcopenic elderly individuals registered in the University of The Third Age Program (UATI) at Universidade do Estado da Bahia, in Brazil, between November and December 2019. Data included patients’ sociodemographic and anthropometric characteristics, self-reported morbidities, multimorbidity, history of chronic pain and perceived health. The data were subjected to descriptive statistical analyses. Crossing of data was performed using Pearson’s chi-square test, and the correlation coefficient was assessed using Cramer’s Phi and V tests. Results There was an association of sarcopenia with chronic pain (p = 0.027) and with age group (p = 0.016), however not with perceived health (p = 0.09). There was also no association between age range and chronic pain (p > 0.05). Conclusion According to the findings of this study, it can be concluded that sarcopenia is associated with the presence of chronic pain and the age of the elderly, not being associated with the perception of health. However, the age of the elderly was not associated with the presence of 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".