Chronic immunoglobulin maintenance therapy in myasthenia gravis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Long-term treatment of myasthenia gravis (MG) includes symptomatic and course-modifying therapies that target the immune system. Recently, both intravenous immunoglobulin (IVIG) and subcutaneous immunoglobulin (SCIG) have emerged as viable options for chronic therapy, considering the favourable safety-efficacy profile and possible immunosuppressant sparing properties. The aim was to investigate the outcomes of the long-term care of generalized MG with immunoglobulin (Ig). METHODS: This is a retrospective, repeated-measures design study. Charts of generalized MG patients, treated with IVIG/SCIG for at least 6 months, from January 2015 to January 2020, were analysed. The primary outcome was the mean change in Myasthenia Gravis Impairment Index (MGII) after treatment with Ig, comparing baseline to IVIG and SCIG treatment periods. Secondary outcomes included the changes in pyridostigmine, immunosuppressive medications and patient-reported outcome 'percentage of normal' (0%-100%). RESULTS: Thirty-four patients were treated with chronic Ig therapy (30 IVIG/SCIG, three SCIG, one IVIG). The mean durations of IVIG and SCIG periods were 21.8 ± 19.4 (range 3-64) months and 19.5 ± 11.3 (range 5-45) months respectively. There was a significant reduction in MGII scores (27.7 ± 15.7 baseline; 22.0 ± 17.4 IVIG period; 19.5 ± 18.1 SCIG period; F = 17.9; d.f. = 1.7; P < 0.01), pyridostigmine and immunosuppressant use (P = 0.00). The outcome 'percentage of normal' had a significant positive association with both treatments (P = 0.00). CONCLUSION: Our study results suggest that patients can be successfully transitioned to IVIG and from IVIG to SCIG in the chronic treatment of generalized MG with reductions in impairments and use of other medications and improvement in overall status with Ig therapy. Prospective, randomized studies are needed to clarify costs and comparative effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".