MRI Quantification of Spinal Cord Atrophy in Multiple Sclerosis: A Systematic Review and Meta-Analysis (P3.016)
Bibliographic record
Abstract
Objective: To perform a systematic review and meta-analysis of spinal cord(SC) atrophy in multiple sclerosis(MS). Background: SC atrophy is emerging as an important imaging outcome measure in MS given its significant correlation with clinical disability, particularly in progressive MS. However, to date, a comprehensive review of reference ranges for SC atrophy in MS has not been reported, which would support its use in clinical trial settings. Methods: We performed a systematic review and meta-analysis using multiple literature databases in line with widely-accepted PRISMA guidelines. A search protocol was developed using Medical Subject headings(MeSH) and key words focused on upper-cervical SC cross-sectional area(SC-CSA) as a measure of SC atrophy in MS with studies published between 1/1/1977-6/1/2015. Two reviewers independently assessed and abstracted titles/abstracts, and data. Meta-analysis used random-effects modelling to compare pooled estimates of SC atrophy between MS subtypes and healthy controls(HCs). Heterogeneity was assessed using DerSimonian and Laird’s Q-test. Results: 78 eligible studies(59 cross-sectional, 19 longitudinal) met inclusion and exclusion criteria. Using SC-CSA, atrophy was more prominent in MS vs. HCs, and in progressive vs. relapsing-remitting MS(RRMS). Specifically, the pooled estimated mean SC-CSA in HCs, RRMS, and progressive MS was 81.1mm2 (95[percnt] CI: 80.7-81.4), 77.6mm2 (95[percnt] CI: 77.4-77.8), and 69.9mm2 (95[percnt] CI: 69.7-70.1) respectively (both comparisons p<0.001). SC atrophy correlated well with the Expanded Disability Status Scale score(r-value range: -0.75 to -0.22). In longitudinal studies, SC atrophy rates were greater in MS vs. HCs, and in progressive vs. relapsing MS, with annualized rates of atrophy ranging from -0.27[percnt] to -4.26[percnt]. Conclusions: SC atrophy reliably differentiates between MS and HCs and between MS subtypes, and correlates strongly with clinical disability. Our findings support the validity of SC atrophy as an imaging outcome measure in clinical trial settings and suggests that this measure may eventually be a viable clinical prognostic tool.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.046 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".