Clinical outcome measures and their evidence base in degenerative cervical myelopathy: a systematic review to inform a core measurement set (AO Spine RECODE-DCM)
Bibliographic record
Abstract
OBJECTIVES: To evaluate the measurement properties of outcome measures currently used in the assessment of degenerative cervical myelopathy (DCM) for clinical research. DESIGN: Systematic review DATA SOURCES: MEDLINE and EMBASE were searched through 4 August 2020. ELIGIBILITY CRITERIA: Primary clinical research published in English and whose primary purpose was to evaluate the measurement properties or clinically important differences of instruments used in DCM. DATA EXTRACTION AND SYNTHESIS: Psychometric properties and clinically important differences were both extracted from each study, assessed for risk of bias and presented in accordance with the Consensus-based Standards for the selection of health Measurement Instruments criteria. RESULTS: Twenty-nine outcome instruments were identified from 52 studies published between 1999 and 2020. They measured neuromuscular function (16 instruments), life impact (five instruments), pain (five instruments) and radiological scoring (five instruments). No instrument had evaluations for all 10 measurement properties and <50% had assessments for all three domains (ie, reliability, validity and responsiveness). There was a paucity of high-quality evidence. Notably, there were no studies that reported on structural validity and no high-quality evidence that discussed content validity. In this context, we identified nine instruments that are interpretable by clinicians: the arm and neck pain scores; the 12-item and 36-item short form health surveys; the Japanese Orthopaedic Association (JOA) score, modified JOA and JOA Cervical Myelopathy Evaluation Questionnaire; the neck disability index; and the visual analogue scale for pain. These include six scores with barriers to application and one score with insufficient criterion and construct validity. CONCLUSIONS: This review aggregates studies evaluating outcome measures used to assess patients with DCM. Overall, there is a need for a set of agreed tools to measure outcomes in DCM. These findings will be used to inform the development of a core measurement set as part of AO Spine RECODE-DCM.
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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 | 0.027 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".