A critical appraisal of clinical practice guidelines for diagnostic imaging in the spinal cord injury
Bibliographic record
Abstract
BACKGROUND CONTEXT: Spinal cord injury (SCI) is a serious health problem which carries a heavy economic burden. Imaging technologies play an important role in the diagnosis of SCI. Although several organizations have developed guidelines for diagnostic imaging of SCI, their quality has not yet been systematically assessed. PURPOSE: We aim to conduct a systematic review to appraise SCI guidelines and summarize their recommendations for diagnostic imaging of SCI. STUDY DESIGN: Systematic review. METHODS: We searched Embase, Medline, Web of Science, Cochrane, some guideline-specific databases (eg, Scottish Intercollegiate Guidelines Network) and Google Scholar from January 2000 to January 2022. We included guidelines developed by nationally recognized organizations. If multiple versions could be obtained, we included the latest one. We appraised included guidelines using the Appraisal of Guidelines for Research and Evaluation, 2nd edition instrument which contains six domains (eg, scope and purpose). We also extracted recommendations and assessed their supporting evidence using levels of evidence (LOE). The evidence was categorized as A (the best quality), B, C, and D (the worst quality). RESULTS: Seven guidelines (2008-2020) were included. They all received the lowest scores in the domain of applicability. All guidelines (7/7, 100%) recommended magnetic resonance imaging (MRI) in patients with SCI or SCI without radiographic abnormality (SCIWORA). A total of 12 recommendations involving patient age (eg, adult and child patients), timing of MRI (eg, as soon as possible and in the acute period), symptoms indicated for MRI (eg, a stiff spine and midline tenderness, suspected disc and posterior ligamentous complex injury, and neurological deficit), and types of MRI (eg, T2-weighted imaging and diffusion tensor imaging) were extracted. Among them, the LOE was C in nine (75%) recommendations and D in three (25%) recommendations. CONCLUSIONS: Seven guidelines were included in the present systematic review, and all of them showed the worst applicability scores in the Appraisal of Guidelines for Research and Evaluation, 2nd edition instrument. They all weakly recommended MRI for patients with suspected SCI or SCIWORA based on a low LOE.
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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 | 0.029 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".