A critical appraisal of clinical practice guidelines on surgical treatments for spinal cord injury
Bibliographic record
Abstract
BACKGROUND CONTEXT: Spinal cord injury (SCI) is a global health problem with a heavy economic burden. Surgery is considered as the cornerstone of SCI treatment. Although various organizations have formulated different guidelines on surgical treatment for SCI, the methodological quality of these guidelines has still not been critically appraised. PURPOSE: We aim to systematically review and appraise the current guidelines on surgical treatments of SCI and summarize the related recommendations with the quality evaluation of supporting evidence. STUDY DESIGN: Systematic review. METHODS: Medline, Cochrane library, Web of Science, Embase, Google Scholar, and online guideline databases were searched from January 2000 to January 2022. The most updated and recent guidelines containing evidence-based or consensus-based recommendations and established by authoritative associations were included. The Appraisal of Guidelines for Research and Evaluation, 2nd edition instrument containing 6 domains (eg, applicability) was used to appraise the included guidelines. An evidence-grading scale (ie, level of evidence, LOE) was utilized to evaluate the quality of supporting evidence. The supporting evidence was categorized as A (the best quality), B, C, and D (the worst quality). RESULTS: Ten guidelines from 2008 to 2020 were included, however, all of them acquired the lowest scores in the domain of applicability among all the six domains. Fourteen recommendations (eight evidence-based recommendations and six consensus-based recommendations) were totally involved. The SCI types of the population and timing of surgery were studied. Regarding the SCI types of the population, eight guidelines (8/10, 80%), two guidelines (2/10, 20%), and three guidelines (3/10, 30%) recommended surgical treatment for patients with SCI without further clarification of characteristics, incomplete SCI, and traumatic central cord syndrome (TCCS), respectively. Besides, one guideline (1/10, 10%) recommended against surgery for patients with SCI without radiographic abnormality. Regarding the timing of surgery, there were eight guidelines (8/10, 80%), two guidelines (2/10, 20%), and two guidelines (2/10, 20%) with recommendations for patients with SCI without further clarification of characteristics, incomplete SCI, and TCCS, respectively. For patients with SCI without further clarification of characteristics, all eight guidelines (8/8, 100%) recommended for early surgery and five guidelines (5/8, 62.5%) recommended for the specific timing, which ranged from within 8 hours to within 48 hours. For patients with incomplete SCI, two guidelines (2/2, 100%) recommended for early surgery, without specific time thresholds. For patients with TCCS, one guideline (1/2, 50%) recommended for surgery within 24 hours, and another guideline (1/2, 50%) simply recommended for early surgery. The LOE was B in eight recommendations, C in three recommendations, and D in three recommendations. CONCLUSIONS: We remind the reader that even the highest quality guidelines often have significant flaws (eg, poor applicability), and some of the conclusions are based on consensus recommendations which is certainly less than ideal. With these caveats, we found most included guidelines (8/10, 80%) recommended early surgical treatment for patients after SCI, which was consistent between evidence-based recommendations and consensus-based recommendations. Regarding the specific timing of surgery, the recommended time threshold did vary, but it was usually within 8 to 48 hours, where the LOE was B to 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 | 0.229 | 0.557 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.044 | 0.023 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".