Characteristics and complexity of chronic pain patients referred to a community-based multidisciplinary chronic pain clinic
Bibliographic record
Abstract
BACKGROUND: Community-based care fills an important service gap for patients living with chronic pain. Better understanding of unmet patient needs in the community may inform improved policy and resource allocation. AIMS: The aim of this study was to describe patients presenting to a community-based, multidisciplinary chronic pain clinic in Vancouver, British Columbia. METHODS: This is a retrospective cross-sectional study of 935 unique consecutive patients who completed an intake questionnaire between January 2016 and March 2017. All data were patient reported. RESULTS: Nine hundred thirty-five patient records were analyzed for descriptive characteristics. The mean age of the population was 49.5 (SD = 14.9) years; 70% were female. Approximately 50% of patients lived below the poverty line in Vancouver; 30% were not working due to disability, 51% had pain for more than 5 years, and 63% reported severe functional impairment. CONCLUSIONS: Substantial unmet need is demonstrated in this patient population accessing a community-based chronic pain clinic. The population described is mainly of working age with significant functional impairment, reflecting a high level of need due to severity and duration of symptoms, poverty, and other characteristics described.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".