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Record W2522235699 · doi:10.1002/mus.25409

Subcutaneous versus intravenous immunoglobulin for chronic autoimmune neuropathies: A meta‐analysis

2016· review· en· W2522235699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMuscle & Nerve · 2016
Typereview
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMultifocal motor neuropathyMismatch negativityChronic inflammatory demyelinating polyneuropathyMedicineConfidence intervalInternal medicinePolyradiculoneuropathyAntibodyRelative riskAdverse effectGastroenterologyMeta-analysisImmunologyGuillain-Barre syndromeElectroencephalography

Abstract

fetched live from OpenAlex

INTRODUCTION: High-dose intravenous immunoglobulin (IVIg) is an evidence-based treatment for multifocal motor neuropathy (MMN) and chronic inflammatory demyelinating polyneuropathy (CIDP). Recently, subcutaneous immunoglobulin (SC-Ig) has received increasing attention. METHODS: We performed a meta-analysis of reports of efficacy and safety of SC-Ig versus IVIg for inflammatory demyelinating polyneuropathies. RESULTS: A total of 8 studies comprising 138 patients (50 with MMN and 88 with chronic CIDP) were included in the meta-analysis. There were no significant differences in muscle strength outcomes in MMN and CIDP with Sc-Ig (MMN: effect size [ES] = 0.65, 95% confidence interval [CI] = -0.31-1.61; CIDP: ES = 0.84, 95% CI = -0.01-1.69). Additionally SC-Ig had a 28% reduction in relative risk (RR) of moderate and/or systemic adverse effects (95% CI = 0.11-0.76). CONCLUSIONS: The efficacy of SC-Ig is similar to IVIg for CIDP and MMN and has a significant safety profile. Muscle Nerve 55: 802-809, 2017.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.336
Teacher spread0.260 · 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