An interdisciplinary clinical practice model for the management of low-back pain in primary care: the CLIP project
Bibliographic record
Abstract
BACKGROUND: Low-back pain is responsible for significant disability and costs in industrialized countries. Only a minority of subjects suffering from low-back pain will develop persistent disability. However, this minority is responsible for the majority of costs and has the poorest health outcomes. The objective of the Clinic on Low-back pain in Interdisciplinary Practice (CLIP) project was to develop a primary care interdisciplinary practice model for the clinical management of low-back pain and the prevention of persistent disability. METHODS: Using previously published guidelines, systematic reviews and meta-analyses, a clinical management model for low-back pain was developed by the project team. A structured process facilitating discussions on this model among researchers, stakeholders and clinicians was created. The model was revised following these exchanges, without deviating from the evidence. RESULTS: A model consisting of nine elements on clinical management of low-back pain and prevention of persistent disability was developed. The model's two core elements for the prevention of persistent disability are the following: 1) the evaluation of the prognosis at the fourth week of disability, and of key modifiable barriers to return to usual activities if the prognosis is unfavourable; 2) the evaluation of the patient's perceived disability every four weeks, with the evaluation and management of barriers to return to usual activities if perceived disability has not sufficiently improved. CONCLUSION: A primary care interdisciplinary model aimed at improving quality and continuity of care for patients with low-back pain was developed. The effectiveness, efficiency and applicability of the CLIP model in preventing persistent disability in patients suffering from low-back pain should be assessed.
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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 | 0.074 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".