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Record W4414360730 · doi:10.1017/cjn.2025.10428

Feasibility of Subcutaneous Immunoglobulin Therapy as the Maintenance Therapy in Patients with Autoimmune Neuromuscular Disease: A Prospective Study

2025· article· en· W4414360730 on OpenAlexaffvenue
Syed F. Hussain, Zaeem A. Siddiqi

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2025
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaintenance therapyProspective cohort studyAntibodyRegimenDosingCAR T-cell therapy

Abstract

fetched live from OpenAlex

Long-term immunoglobulin therapy is crucial for several neuromuscular disorders (NMD). Recently, subcutaneous immunoglobulin (SCIg) has become an alternate to intravenous immunoglobulin (IVIg) for maintenance therapy to address limitations. This prospective study assessed the feasibility of SCIg as maintenance therapy for various NMDs after transitioning from IVIg. Overall, the mean monthly immunoglobulin dose remained stable or reduced after transition while maintaining efficacy. Participants reported significantly fewer side effects (29.2 % vs. 66.7%) with SCIg. Compliance with self-infusion and dosing regimen with SCIg was high, with no product wastage. The study shows SCIg therapy has distinct advantages over IVIg and should be considered for NMD patients requiring maintenance therapy.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.267
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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