Changes in quality of life scores with intravenous immunoglobulin or plasmapheresis in patients with myasthenia gravis
Bibliographic record
Abstract
BACKGROUND: Intravenous immunoglobulin (IVIG) and plasmapheresis (plasma exchange (PLEX)) have comparable efficacy in reducing the Quantitative Myasthenia Gravis Score for disease severity (QMGS) in patients with moderate to severe myasthenia gravis (MG). OBJECTIVE: To determine if the improvement in the quality of life (QOL) after immunomodulation is comparable with either IVIG or PLEX. METHODS: 62 patients participated in the MG-QOL-60 study, completing the questionnaire at baseline and at day 14 after treatment. The MG-QOL-15 scores were computed from the MG-QOL-60 questionnaire responses. We analysed the change in the QOL scores from baseline to day 14 in both treatment groups. RESULTS: The scores in both QOL scales decreased at day 14 in the IVIG and PLEX groups, without significant difference between groups (QOL-15: IVIG -5.7 ± 8.5, PLEX: -7.0 ± 7.6, p=0.52; QOL-60: IVIG -13.3 ± 16.9, PLEX -18.5 ± 22.0, p = 0.41). The improvement in QOL showed a good correlation with the decrease in QMGS. There was an excellent correlation between the MG-QOL-15 and MG-QOL-60 scores at baseline and at day 14. CONCLUSIONS: This study of MG-QOL changes supports recent findings that IVIG and PLEX are comparable in the treatment of patients with moderate to severe MG and worsening symptoms. Furthermore, our study supports the use of the MG-QOL-15 as a secondary outcome measure in future clinical trials in MG.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".