Development of Cardiometabolic Health indicators to advance the quality of spinal cord injury rehabilitation: SCI-High Project
Bibliographic record
Abstract
Context: Spinal cord injury or disease (SCI/D) leads to unchanged low-density lipoprotein and cholesterol, very low high-density lipoprotein a form of dyslipidemia and physical inactivity which combine to increase risk of morbidity and mortality from cardiometabolic disease. Herein, we describe the selection of structure, process and outcome indicators for adults in the first 18 months post-SCI/D rehabilitation admission.Methods: A Pan-Canadian Cardiometabolic Health Working Group was formed to develop a construct definition. Cardiometabolic risk factors were summarized in a Driver diagram. Release of the Paralyzed Veterans of America “Identification and Management of Cardiometabolic Risk after Spinal Cord Injury” and the International Scientific Exercise Guidelines: “Evidence-based scientific exercise guidelines for adults with spinal cord injury”, informed the group’s focus on prevention strategies to advance this Domain of rehabilitation admission.Results: The structure indicator identifies during rehabilitation the presence of appropriate time and resources for physical exercise prescription. Process indicators are lipid profile assessment at rehabilitation admission and documented exercise prescriptions prior to discharge. The outcome indicators track patient’s knowledge retention regarding exercise prescription at discharge, current exercise adherence and lipid status 18 months after rehabilitation discharge.Conclusion: Routine national implementation of these indicators at the specified time points will enhance efforts to detect dyslipidemia and assure routine participation in endurance exercise. These indicators align with international initiatives to improve cardiometabolic health through interventions targeting modifiable risk factors specifically endurance exercising and optimal lipid profiles, crucial to augmenting cardiometabolic health after SCI/D.
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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 | 0.026 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".