Predictors of Outcome After Surgical Decompression for mild degenerative Cervical Myelopathy -A Systematic Review
Bibliographic record
Abstract
STUDY DESIGN: Systematic Reviews. OBJECTIVES: To investigate predictors of surgical outcomes for mild Degenerative Cervical Myelopathy (DCM) by reviewing all related studies conducted at this point. METHODS: An electronic search was carried out in PubMed, EMBASE, Scopus, and Web of Science until June 23, 2021. Full-text articles reporting surgical outcome predictors of mild DCM cases were eligible. We included studies with mild DCM which was defined as a modified Japanese Orthopaedic Association score of 15 to 17 or a Japanese Orthopaedic Association score of 13 to 16. Independent reviewers screened all the records, and discrepancies between the reviewers were solved in a session with the senior author. For risk of bias assessment, RoB 2 tool was used for randomized clinical trials and ROBINS-I for non-randomized studies. RESULTS: After screening 6 087 manuscripts, only 8 studies met the inclusion criteria. Lower pre-operative mJOA scores and quality-of-life measurement scores were reported by multiple studies to predict better surgical outcomes compared to other groups. High-intensity pre-operative T2 magnetic resonance imaging (MRI) was also reported to predict poor outcomes. Neck pain before intervention resulted in improved patient-reported outcomes. Two studies also reported motor symptoms prior to surgery as outcome predictors. CONCLUSION: Lower quality of life before surgery, neck pain, lower pre-operative mJOA scores, motor symptoms before surgery, female gender, gastrointestinal comorbidities, surgical procedure and surgeon's experience with specific techniques, and high signal intensity of cord in T2 MRI were the surgical outcome predictors reported in the literature. Lower Quality of Life (QoL) score and neck prior to surgery were reported as predictors of the more improved outcome, but high cord signal intensity in T2 MRI was reported as an unfavorable outcome predictor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".