Systematic Review of Magnetic Resonance Imaging Characteristics That Affect Treatment Decision Making and Predict Clinical Outcome in Patients With Cervical Spondylotic Myelopathy
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVE: To determine whether there are magnetic resonance imaging (MRI) characteristics in patients with cervical spondylotic myelopathy that affect treatment decisions or predict postsurgical outcomes or adverse events. SUMMARY OF BACKGROUND DATA: Although the role of MRI in confirming the clinical diagnosis of cervical spondylotic myelopathy and directing surgical management is well established, its potential value as a prognostic tool is largely unknown. METHODS: A systematic search was conducted using PubMed and the Cochrane Collaboration Library for articles published between January 1, 1956, and November 20, 2012. The overall body of evidence with respect to each clinical question was determined on the basis of precepts outlined by the Grading of Recommendation Assessment, Development and Evaluation Working Group and recommendations made by the Agency for Healthcare Research and Quality. RESULTS: The initial search yielded 268 citations. Twenty publications met all inclusion criteria and were included in the review. Three of these assessed MRI predictors of clinical deterioration in the case of conservative treatment and 17 evaluated MRI anatomic or cord characteristics that could predict surgical outcome or adverse events. There is low evidence suggesting that a high signal intensity (SI) grade on T2WI is not associated with patient deterioration during conservative treatment. High SI grade on T2WI, along with compression ratio and canal diameter, was not an important predictor of outcome. There is low evidence identifying number of high SI segments on T2WI, low SI segments on T1WI, combined T1/T2 SI, and SI ratio as important negative predictors of surgical outcome. CONCLUSION: On the basis of this review and on low-quality evidence, we have identified 3 important negative predictors of surgical outcome: number of high SI segments on T2WI, combined T1/T2 signal change, and SI ratio.EVIDENCE-BASED CLINICAL RECOMMENDATIONS: RECOMMENDATION 1: We suggest that when clinically feasible, surgeons rely on MRI to confirm the diagnosis of CSM and rely on clinical history and examination to determine progression and severity of disease. OVERALL STRENGTH OF EVIDENCE: Low. STRENGTH OF RECOMMENDATION: Weak. RECOMMENDATION 2: T2 signal may be a useful prognostic indicator when used in combination with low SI change on T1WI, or as a ratio comparing compressed with noncompressed segments, or as a ratio of T2 compared with T1WI. We suggest that if surgeons use MRI signal intensity to estimate the risk of a poor outcome after surgery, they use high SI change on T2WI in combination with other signal intensity parameters, and not in isolation. OVERALL STRENGTH OF EVIDENCE: Low. StrENGTH OF RECOMMENDATION: Weak.
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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 | 0.009 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".