Development of the Canadian Spinal Cord Injury Best Practice (Can-SCIP) Guideline: Methods and overview
Bibliographic record
Abstract
Introduction Spinal cord injury (SCI) is a life-altering injury that leads to a complex constellation of changes in an individual’s sensory, motor, and autonomic function which is largely determined by the level and severity of cord impairment. Available SCI-specific clinical practice guidelines (CPG) address specific impairments, health conditions or a segment of the care continuum, however, fail to address all the important clinical questions arising throughout an individual’s care journey. To address this gap, an interprofessional panel of experts in SCI convened to develop the Canadian Spinal Cord Injury Best Practice (Can-SCIP) Guideline. This article provides an overview of the methods underpinning the Can-SCIP Guideline process.Methods The Can-SCIP Guideline was developed using the Guidelines Adaptation Cycle. A comprehensive search for existing SCI-specific CPGs was conducted. The quality of eligible CPGs was evaluated using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument. An expert panel (n = 52) convened, and groups of relevant experts met to review and recommend adoption or refinement of existing recommendations or develop new recommendations based on evidence from systematic reviews conducted by the Spinal Cord Injury Research Evidence (SCIRE) team. The expert panel voted to approve selected recommendations using an online survey tool.Results The Can-SCIP Guideline includes 585 total recommendations from 41 guidelines, 96 recommendations that pertain to the Components of the Ideal SCI Care System section, and 489 recommendations that pertain to the Management of Secondary Health Conditions section. Most recommendations (n = 281, 48%) were adopted from existing guidelines without revision, 215 (36.8%) recommendations were revised for application in a Canadian context, and 89 recommendations (15.2%) were created de novo.Conclusion The Can-SCIP Guideline is the first living comprehensive guideline for adults with SCI in Canada across the care continuum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.071 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".