Prognostic value of magnetic resonance imaging in patients with clinically isolated syndrome conversion to multiple sclerosis: A meta-analysis
Bibliographic record
Abstract
BACKGROUND: Numerous studies have investigated the associations of brain or spinal cord MRI with the risk of developing Multiple Sclerosis (MS) in people with Clinically Isolated Syndrome (CIS), however, the findings are uncertain. Therefore, we performed a meta-analysis based on 24 publications to comprehensively evaluate such associations. MATERIALS AND METHODS: The databases of EMBASE and MEDLINE (January 1980-August 2011) were searched electronically for all relevant studies. Data were extracted from each study independently by both reviewers using a predefined structured spreadsheet. The quality of each study was assessed independently by two reviewers according to Newcastle-Ottawa Scale for reading cohort study proposed by Deeks et al. The meta-analysis including 24 qualified studies was performed by using the Cochrane Collaborations RevMan5.0 software. RESULTS: Twenty-four identified studies met the inclusion criteria and minimum quality threshold. A meta-analysis of cohort studies indicated that the CISs having MRI lesions did have significantly increased risk for MS (risk ratio [RR] = 3.71, 95% confidence interval [CI], 3.27-4.21, P < 0.00001). In the subgroup analysis (according to the number of T2 lesions at baseline), the risk of developing MS in CIS patients with the medium MRI burden (4-9 lesions) was higher than with the low MRI burden (1-3 lesions) (RR = 0.66,95% CI, 0.45-0.95, P < 0.00001). While, no correlation was found in group between the medium MRI burden and the high MRI burden(>9 lesions) (RR = 0.97, 95% CI, 0.82-1.15, P = 0.72). Meanwhile, the CIS patients with abnormal baseline MRI, especially with infratentorial lesions, had a high risk of conversion to MS compared to patients without the such infratentorial lesions (RR = 1.37, % CI, 1.09-1.73, P = 0.0008). CONCLUSIONS: Despite some limitations, this meta-analysis established solid statistical evidence for an association between the presence or absence of MRI lesions within the brain or spinal cord MRI and the risk of developing MS, particularly for studies with large sample size. The CIS patients with abnormal baseline MRI, especially with infratentorial lesions, had a high risk of conversion to MS. However, this association warrants additional validation in larger and well designed studies.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.058 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".