Predictors of response following standardized education and self-management recommendations for low back pain stratified by dominant pain location
Bibliographic record
Abstract
BACKGROUND: Low back pain (LBP) is a leading cause of disability globally. Risk-stratification systems (e.g. STarT Back) have been proposed to guide treatment, but with varying success. We investigated factors associated with poor response to standardized LBP education and self-management recommendations stratified by dominant pain location (back or leg). METHODS: LBP patients underwent a standardized primary care model of care of education and self-management recommendations. Poor response was defined as an Oswestry Disability Index (ODI) change score <10 units by 6 months. Multivariable logistic regression was used to identify poor response risk factors, stratified by back-dominant and leg-dominant back pain. Baseline factors: age, sex, body mass index, ODI, LBP/leg-pain intensity, LBP/leg-pain duration, STarT Back chronicity-risk, smoking, comorbidity count, and self-efficacy. RESULTS: The sample consisted of 767 patients (443 back-dominant, 324 leg-dominant). Mean age was 53 years, and 59% were female. Females accounted for 66% of back-dominant and 50% of leg-dominant patients. Chronicity risk was 'high' for 18% of back-dominant and 29% of leg-dominant patients. Poor response was higher in back- (57%) compared to leg-dominant (42%) patients. Adjusted stratified analyses: female sex, moderate or high chronicity-risk, and increasing age were associated with increased risk of poor response, and greater self-efficacy with favourable response, in leg-dominant patients; these were not the cases among back-dominant patients. Increased comorbidity count was associated with poor response in back dominant patients. In both patient groups, higher baseline ODI score was associated with favorable response, and smoking and longer pain duration with poor response. CONCLUSIONS: Differences in the influence of sex and chronicity risk in particular on outcome by dominant pain location suggests that considering these patients as a single group may not be appropriate. Furthermore, findings suggest that stratification by pain dominance may enhance the use of established risk stratification tools such as the STarT Back.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".