A clinician’s guide for administration of high-concentration and facilitated subcutaneous immunoglobulin replacement therapy in patients with primary immunodeficiency diseases
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.032 |
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".