The Global Spine Care Initiative: care pathway for people with spine-related concerns
Bibliographic record
Abstract
PURPOSE: The purpose of this report is to describe the development of an evidence-based care pathway that can be implemented globally. METHODS: The Global Spine Care Initiative (GSCI) care pathway development team extracted interventions recommended for the management of spinal disorders from six GSCI articles that synthesized the available evidence from guidelines and relevant literature. Sixty-eight international and interprofessional clinicians and scientists with expertise in spine-related conditions were invited to participate. An iterative consensus process was used. RESULTS: After three rounds of review, 46 experts from 16 countries reached consensus for the care pathway that includes five decision steps: awareness, initial triage, provider assessment, interventions (e.g., non-invasive treatment; invasive treatment; psychological and social intervention; prevention and public health; specialty care and interprofessional management), and outcomes. The care pathway can be used to guide the management of patients with any spine-related concern (e.g., back and neck pain, deformity, spinal injury, neurological conditions, pathology, spinal diseases). The pathway is simple and can be incorporated into educational tools, decision-making trees, and electronic medical records. CONCLUSION: A care pathway for the management of individuals presenting with spine-related concerns includes evidence-based recommendations to guide health care providers in the management of common spinal disorders. The proposed pathway is person-centered and evidence-based. The acceptability and utility of this care pathway will need to be evaluated in various communities, especially in low- and middle-income countries, with different cultural background and resources. These slides can be retrieved under Electronic Supplementary Material.
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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 | 0.064 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".