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Record W4298126023 · doi:10.1186/s13223-022-00726-7

A clinician’s guide for administration of high-concentration and facilitated subcutaneous immunoglobulin replacement therapy in patients with primary immunodeficiency diseases

2022· review· en· W4298126023 on OpenAlexvenueno aff
Kristin Epland, Daniel Suez, Kenneth Paris

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsnot available
FundersTakeda Pharmaceuticals U.S.A.
KeywordsMedicinePrimary immunodeficiencyIntensive care medicineImmunodeficiencyAdverse effectAntibodyQuality of life (healthcare)ImmunologyInternal medicineNursing

Abstract

fetched live from OpenAlex

Immunoglobulin replacement therapy is the standard-of-care treatment for patients with primary immunodeficiency diseases who have impaired antibody production and function. Clinicians and patients may consider intravenous immunoglobulin (IVIG) or subcutaneous immunoglobulin (SCIG) options, and each route may offer different benefits for the individual. IVIG requires fewer infusion sites and less frequent infusions than some formulations of SCIG. However, SCIG does not require venous access, is associated with fewer systemic adverse infusion reactions than IVIG, and can independently be self-administered at home. Importantly, tailoring treatment experiences to the needs of the individual may improve treatment adherence and quality of life for patients with primary immunodeficiency diseases who often rely on long-term or lifelong treatment. This review aims to educate United States (US) healthcare providers on the administration process of SCIG, with a focus on more concentrated formulations of SCIG and facilitated SCIG. It provides practical guidance on initiating, optimizing, and monitoring SCIG therapy. The advantages and disadvantages of the different treatment options are also presented for discussion between the patient and clinician.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 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

Citations23
Published2022
Admission routes1
Has abstractyes

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