PB1348 Thrombopoietin Receptor Agonist and Rituximab Combination Therapy in Patients with Refractory Primary Immune Thrombocytopenia. A Single-Center Study
Bibliographic record
Abstract
Background: Immune thrombocytopenia (ITP) is a disorder characterized by immune-mediated platelet destruction and impaired platelet production that can be treated with intravenous immunoglobin (IVIg).By understanding the use of IVIg in ITP, we can identify gaps to develop a regional best practice guideline or educational initiatives to optimize use.Aims: (1) Evaluate practice patterns of IVIg use among physicians treating ITP locally, and (2) Evaluate the appropriateness of use according to IWG guidelines.Methods: We performed a retrospective data analysis using Alberta Health Services Provincial Laboratory Services; dynaLife; Sunrise Clinical Manager, and Transfusion Medicine records, which was supplemented by patient chart review.Inclusion criteria were patients 18 years of age and older diagnosed with ITP based on ICD-10 codes between 2012-2017 in Calgary and who received IVIg.We assessed the responsiveness, and appropriateness by indication according to the IWG guidelines (Ethics approval REB18-1798).Results: There were 158 patients included who were diagnosed with ITP and received IVIg (Table 1).There were 80.1% of patients who achieved an early response with IVIg therapy and 58.2% of patients who achieved a complete remission.The mean number of days until repeat IVIg therapy was 60.4 days.The use of IVIg in managing ITP was appropriate in 67.6% of cases.Indications for IVIg use for ITP varied, with bleeding being the most common indication followed by need for rapid platelet increase and then physician preference.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".