The longitudinal relationships between pain severity and disability versus health-related quality of life and costs among chronic low back pain patients
Bibliographic record
Abstract
PURPOSE: Previous studies found higher levels of pain severity and disability to be associated with higher costs and lower health-related quality of life. However, these findings were based on cross-sectional data and little is known about the longitudinal relationships between pain severity and disability versus health-related quality of life and costs among chronic low back pain patients. This study aims to cover this knowledge gap by exploring these longitudinal relationships in a consecutive cohort. METHODS: Data of 6316 chronic low back pain patients were used. Measurements took place at 3, 6, 9, and 12 months. Pain severity (Numeric pain rating scale; range: 0-100), disability (Oswestry disability index; range: 0-100), health-related quality of life (EQ-5D-3L: range: 0-1), societal and healthcare costs (cost questionnaire) were measured. Using linear generalized estimating equation analyses, longitudinal relationships were explored between: (1) pain severity and health-related quality of life, (2) disability and health-related quality of life, (3) pain severity and societal costs, (4) disability and societal costs, (5) pain severity and healthcare costs, and (6) disability and healthcare costs. RESULTS: Higher pain and disability levels were statistically significantly related with poorer health-related quality of life (pain intensity: - 0.0041; 95% CI - 0.0043 to - 0.0039; disability: - 0.0096; 95% CI - 0.0099 to - 0.0093), higher societal costs (pain intensity: 7; 95% CI 5 to 8; disability: 23; 95% CI 20 to 27) and higher healthcare costs (pain intensity: 3; 95% CI 2 to 4; disability: 9; 95% CI 7 to 11). CONCLUSION: Pain and disability were longitudinally related to health-related quality of life, societal costs, and healthcare costs. Disability had a stronger association with all outcomes compared to 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".