Ancillary Outcome Measures for Assessment of Individuals With Cervical Spondylotic Myelopathy
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVE: To identify suitable outcome measures that can be used to quantify neurological and functional impairment in the management of cervical spondylotic myelopathy (CSM). SUMMARY OF BACKGROUND DATA: CSM is the leading cause of acquired spinal cord disability, causing varying degrees of neurological impairment which impact on independence and quality of life. Because this impairment can have a heterogeneous presentation, a single outcome measure cannot define the broad range of deficits seen in this population. Therefore, it is necessary to define outcome measures that characterize the deficits with greater validity and sensitivity. METHODS: This review was conducted in 3 stages. Stage I: To evaluate the current use of outcome measures in CSM, PubMed was searched using the name of the outcome measure and the common abbreviation combined with "CSM" or "myelopathy." Stage II: Having identified a lack of appropriate outcome measures, we constructed criteria by which measures appropriate for assessing the various aspects of CSM could be identified. Stage III: A second literature search was then conducted looking at specified outcomes that met these criteria. All literature was reviewed to determine specificity and psychometric properties of outcomes for CSM. RESULTS: Nurick grade, modified Japanese Orthopaedic Association Scale, visual analogue scale (VAS) for pain, Short Form (36) Health Survey (SF-36), and Neck Disability Index were the most commonly cited measures. The Short-Form 36 Health Survey and Myelopathy Disability Index have been validated in the CSM population with multiple studies, whereas the modified Japanese Orthopaedic Association Scale score, Nurick grade, and European Myelopathy Scale each had only one study assessing psychometric characteristics. No validity, reliability, or responsiveness studies were found for the VAS or Neck Disability Index in the CSM population. CONCLUSION: We recommend that the modified Japanese Orthopaedic Association Scale, Nurick grade, Myelopathy Disability Index, Neck Disability Index, and 30-Meter Walk Test are most appropriate for the assessment of CSM. However, 6 additional outcome measures (QuickDASH, Berg Balance Scale, Graded Redefined Assessment of Strength Sensibility and Prehension, Grip Dynamometer, and GAITRite Analysis) were identified, which provide complementary assessments for CSM. SUMMARY STATEMENTS: There does not exist a single or composite of outcome instruments that measures myelopathy impairment, function/disability, and participation that have also demonstrated reliability, validity, and responsiveness in a CSM population. More work in the development and psychometric evaluation of new or existing measures is necessary to identify the ideal composite of measures to be used in the clinical and research settings. The mJOA, Nurick grade, NDI, MDI, and 30MWT should be adopted in any clinical practice that treats CSM both for screening and clinical follow-up. We propose that clinicians and researchers consider using the ancillary measures identified, such as the QuickDASH, Berg Balance Scale, GRASSP version 1.0, Grip Strength, and GAITRite Analysis. It is highly recommended that baseline and follow-up measurements should be performed in patients with CSM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| 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".