Evaluation of a Personalized Subcutaneous Immunoglobulin Treatment Program for Neurological Patients
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Subcutaneous immunoglobulin (SCIg) treatment has been shown to control symptoms and improve overall satisfaction in patients with neurological disorders. However, a large injection volume can be overwhelming and a barrier to successful SCIg treatment. We established a nurse-led individualized approach program to facilitate a smooth and successful treatment transition from intravenous immunoglobulin (IVIg) to SCIg. The program involved a lead nurse to provide two or more individual educational sessions on SCIg administration, establish a written transition plan, and liaise care with physicians. OBJECTIVES: We aimed to evaluate the impact of our program to a successful transition defined as SCIg retention or adherence without a need to restart IVIg by six or twelve months. METHODS: We reviewed medical charts of all patients with immune-mediated neuromuscular disorders who were in our program during January 2010 to Dec 2016. RESULTS: Nineteen patients were identified. Mean IVIg treatment duration was 31.5 months (range 4-98) before the transition. Mean steady state SCIg dosage was 26.2 g/week (SD 10.3). All patients were initially able to switch to SCIg, with a retention rate of 17/19 (89.5%) at six months and 15/19 (78.9%) at twelve months. Two patients reverted back to IVIg treatment due to worsening of their symptoms at two and three months, while two required supplemental IVIg infusions. There were no major adverse events reported during the twelve-month period, but one minor cutaneous adverse event (redness around the injection site). CONCLUSIONS: Successful treatment transition may be achieved with the nurse led individualized approach program.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it