How Does Self‐Declared Chronic Pain Compare to Other Definitions? A Prospective Multicenter Study
Bibliographic record
Abstract
Background: Self‐declared chronic pain has not been compared to existing definitions. Our objective was to evaluate the agreement between self‐declared chronic pain and different chronic pain definitions, three months after an emergency department (ED) visit. Methods: In this planned substudy of a prospective multicenter cohort study, we included consecutive patients aged ≥ 18 years with an acute pain condition discharged from the ED with an opioid prescription. Three months after their ED visit, participants were asked about their pain intensity, pain frequency, pain disability, and self‐declared chronic pain. Agreement between self‐declared chronic pain and five other definitions were calculated with kappas. Results: A total of 1411 participants were included; mean age was 52 (±16) years, and 53% were female. Prevalence of self‐declared chronic pain was 23.0% and varied from 16.9% to 45.3% for other definitions. Agreement of self‐declared chronic pain was moderate (0.57–0.60) with most definitions but lower with the pain intensity ≥ 1 definition (0.47). The proportion of chronic pain participants using opioids ( ⁓20%) or other analgesics (⁓80%) was similar with all definitions except for the pain intensity ≥ 1 definition which was associated with a lower proportion of analgesic use (11%, 64%). Conclusion: In summary, self‐declared chronic pain displayed moderate agreement with other chronic pain definitions and similar analgesic consumption but lower with the pain intensity ≥ 1 definition. Nonetheless, chronic pain prevalence varied greatly depending on how it was defined. Self‐declared chronic pain might be a more patient‐centered outcome and could be easily applied to standardize chronic pain definition. Trial Registration: ClinicalTrials.gov identifier: NCT03953534
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".