Adopting Clinical Practice Guidelines for Pharmacologic Management of Acute Spinal Cord Injury from a Developed World Context to a Developing Global Region
Bibliographic record
Abstract
BACKGROUND: Proper utilization of high-quality clinical practice guidelines (CPGs) eliminates the dependence of patients' outcomes on the ability and knowledge of "individual" health care providers and reduces unwarranted variation in care. The aim of this study was to adapt/adopt two CPGs for pharmacologic management of acute spinal cord injury (SCI) using guideline adaptation methods. METHODS: This study was conducted based on the ADAPTE process. Following establishment of an organizing committee and choosing the health topics, we appraised the quality of the CPGs using the Appraisal of Clinical Guidelines for Research & Evaluation II (AGREE II). Then, the authors extracted and categorized suggestions according to Population, Intervention, Professions, Outcomes and Health care setting (PIPOH). The decision-making process was based on systemic evaluation of each suggestion, utilizing a combination of AGREE II scores, the quality of supporting evidence for or against each suggestion and the triad of feasibility, acceptance and adoptability for the Iranian health-care context. RESULTS: Two guidelines were included in the adaptation process. Based on high-quality of these guidelines and the feasibility and adoptability evaluation of the organizing committee, we decided to adopt the suggestion of both guidelines. Overall, seven suggestions were extracted from the source guidelines. CONCLUSION: This work provides a framework to apply guidelines for acute SCI to the developing regions of the world. Attempts should be made to implement these suggestions in order to improve the health outcomes of Iranian SCI patients.
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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 | 0.055 | 0.138 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".