E.08 Subcutaneous vs. intravenous immunoglobulins for chronic inflammatory demyelinating polyneuropathy and multifocal motor neuropathy
Bibliographic record
Abstract
Background: Background: High-dose intravenous immunoglobulin (IV-Ig) is an evidence-based treatment for chronic inflammatory demyelinating polyneuropathy (CIDP) and multifocal motor neuropathy (MMN). Recently, subcutaneous Ig (SC-Ig) has received increasing attention. We performed a meta-analysis to assess the efficacy of SC-Ig versus IV-Ig. Methods: Methods: We searched PubMed, Embase, and Scopus from January, 1990 to December, 2015 for publications comparing IV-Ig vs. SC-Ig in patients with CIDP or MMN. We performed fixed-effects meta-analyses for strength changes as measured by the Medical Research Council sum score changes (MRC-SS). Results: Results: A total of 8 studies comprising 138 patients (88 with CIDP and 50 with MMN) were included in the meta-analysis. Considering the total population the use of SC-Ig showed slightly better results for MRC-SS (ES=-1.78, 95%CI=-3.45 to -0.11, I 2 <0.001%). However, when CIDP and MMN were compared separately, there were no differences between treatments (CIDP: ES=-0.28, 95%CI=-0.57 to 0.02, I 2 <0.001%; MMN: ES=-0.34, 95%CI=-3.99 to 3.31, I 2 <0.001%). Conclusions: Conclusions: We found comparable efficacy between SC and IV-Ig administrations for CIDP and MMN. These results suggest that SC-Ig is a suitable alternative treatment method, especially when other situations (e.g. convenience, safety profile) warrant its use. Further studies are needed to explore the efficacy of SC-Ig for CIDP and MMN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".