P.031 Intravenous immunoglobulins (IVIG) therapy in chronic inflammatory demyelinating polyneuropathy (CIDP): time to maximal recovery
Bibliographic record
Abstract
Background: The response of Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) to Intravenous Immunoglobulins (IVIG) treatment is well established . However, determination if patients not responding to 2 IVIG treatments or those whose condition stabilizes (ICE Trial) may benefit from additional doses remains unclear. We aim to identify time period required to reach maximal strength gains from IVIG treatment. Methods: Retrospective chart review of 14 patients with CIDP was performed. Change in Grip strength (GS), Knee extension (KE), Elbow Flexion (EF) and Dorsflexion(DF) was analyzed with a dynamometer during IVIG therapy. Averages for : percent change from baseline(Max%Δ),cumulative grams(g) of IVIG and time in weeks(w) required for maximal strength recovery was determined per function (+/−SEM).Anciliary therapy for all patients was recorded. Results: Strongest improvement was observed for DF(124+/−30%,p<0.001), followed by KE(113+/−19%,p<0.01),GS(100+/−21%,p<0.001) and EF(98+/−14%p<0.05).GS improved the fastest(19.1+/−3w) followed by DF(29.5+/−7w),KE(29.6+/−4w) and EF(31+/−6w). Cumulative IVIG dose to reach Max%Δ was highest for EF(869+/−201g) and lowest for GS(573+/−78g). Conclusions: Our study has demonstrated effectiveness of multiple treatments with IVIG to reach significant improvement in strength. Different muscle groups manifested different time-dependency ,reflecting variable amounts of IVIG required. Improvement was identified to be present on a ongoing basis ,with therapy lasting between 19.1-31 weeks,requiring between 869-573g of IVIG.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".