A comparison of measles-rubella-zoster reaction, oligoclonal IgG bands, oligoclonal kappa free light chains and kappa index in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: To evaluate the diagnostic performance of the measles-rubella-zoster reaction (MRZR) in a large real-world multiple sclerosis (MS) cohort. Second, to compare MRZR with the determination of oligoclonal IgG bands (OCB), oligoclonal kappa free light chain bands (oKFLC), and the KFLC index. METHODS: A single-center retrospective study was conducted at the University Hospital Ostrava (Czech Republic). Patients were eligible if aged ≥18 years with a determined clinical diagnosis. IgG antibodies against measles (M), rubella (R), and varicella zoster (Z) viruses were determined in paired CSF and serum using ELISA and MRZR indicated as positive if at least two components had an antibody index >1.4. OCB and oKFLC were detected by means of isoelectric focusing, and KFLC CSF and serum concentrations for calculation of the KFLC index were determined immunochemically. RESULTS: A total of 1,751 patients were included in the analyzed data set, which comprised 379 MS patients and 1,372 non-MS controls. The frequency of positive MRZR was higher in MS than in non-MS cases (MS 32.2 % vs non-MS 2.8 %; p < 0.001). This corresponded to a specificity of 97.2 % (95 % CI 96.1-98.0) and sensitivity of 32.2 % (95 % CI 27.5-37.2) and overall accuracy of 83.1 % (95 % CI 81.3-84.8). In comparison, the highest sensitivity of 95.6% (95 % CI 93.0-97.5) was for OCB with specificity of 86.9 % (95 % CI 84.9-88.7), followed by oKFLC with sensitivity and specificity of 94.7 % (95 % CI 91.5-96.9) and 78.4% (95 % CI 75.7-80.8), respectively, and the KFLC index with sensitivity of 92.5 % (95 % CI 86.6-96.3) and specificity of 93.5 % (95 % CI 90.5-95.9). DISCUSSION: MRZR remains a very specific test for the diagnosis of MS but has low sensitivity, which disallows its independent use. In contrast, OCB showed the highest sensitivity and thus remains the gold standard for the diagnosis of MS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".