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Record W4408657628 · doi:10.3389/fimmu.2025.1528414

Patient-reported outcomes with subcutaneous immunoglobulin in secondary immunodeficiency

2025· review· en· W4408657628 on OpenAlexaff
Juthaporn Cowan, Il‐Kang Na, André Gladiator, Marta Kamieniak, S. Shahzad Mustafa

Bibliographic record

VenueFrontiers in Immunology · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePrimary immunodeficiencyIntensive care medicineQuality of life (healthcare)Patient satisfactionImmunodeficiencyCohortDiseasePediatricsInternal medicineSurgeryImmunologyImmune system

Abstract

fetched live from OpenAlex

Subcutaneous (SCIG) and intravenous immunoglobulin (IVIG) replacement are both used to prevent infections in patients with secondary immunodeficiency (SID). Compared with IVIG, SCIG has fewer systemic side effects and, additionally, facilitates home-based treatment. Shared decision-making practice should include discussion of aspects such as patient preference as well as the associated risks and benefits of treatment. We review the available evidence for the use of SCIG treatment in patients with SID, focusing on patient-reported outcomes (PROs). In most studies, there were improvements to health-related quality of life with SCIG treatment, compared with before initiating SCIG without prior IVIG treatment, or after switching to SCIG from IVIG treatment, or a no-SCIG/IVIG cohort. Treatment satisfaction with SCIG was similar between patients with SID and primary immunodeficiency disease. Patient preference and perception assessments highlighted the benefits of SCIG compared with IVIG, such as ease of use and administration, convenience, and time-effectiveness. In addition, many patients self-administered SCIG at home. Such aspects may be of specific benefit to patients with SID and hematological malignancy by reducing the risk of infection exposure in clinical settings. PRO data may be useful during shared decision-making discussions with patients with SID.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0030.004
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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes1
Has abstractyes

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