Physical activity and disability in patients with noncardiac chest pain: a longitudinal cohort study
Bibliographic record
Abstract
Abstract Background Noncardiac chest pain (NCCP) is one of the leading reasons for emergency department visits and significantly limits patients’ daily functioning. The protective effect of physical activity has been established in a number of pain problems, but its role in the course of NCCP is unknown. This study aimed to document the level of physical activity in patients with NCCP and its association with NCCP-related disability in the 6 months following an emergency department visit. Methods In this prospective, longitudinal, cohort study, participants with NCCP were recruited in two emergency departments. They were contacted by telephone for the purpose of conducting a medical and sociodemographic interview, after which a set of questionnaires was sent to them. Participants were contacted again 6 months later for an interview aimed to assess their NCCP-related disability. Results The final sample consisted of 279 participants (57.0% females), whose mean age was 54.6 (standard deviation = 15.3) years. Overall, the proportion of participants who were physically active in their leisure time, based on the Actimètre questionnaire criteria, was 22.0%. Being physically active at the first measurement time point was associated with a 38% reduction in the risk of reporting NCCP-related disability in the following 6 months (ρ = .047). This association remained significant after controlling for confounding variables. Conclusions Being physically active seems to have a protective effect on the occurrence of NCCP-related disability in the 6 months following an emergency department visit with NCCP. These results point to the importance of further exploring the benefits of physical activity in this population.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".