Development of a Uniform Apheresis Case Report Form for Standardized Collection of Apheresis Data
Bibliographic record
Abstract
Apheresis is performed worldwide for an increasing number of indications. The development of common data elements (CDE) for apheresis related areas may facilitate conduct of new research, enhance quality initiatives including benchmarking, and improve patient care. This report describes the systematic development of the Uniform Apheresis Case Report Form (UACRF) as part of the Apheresis in the United States (ApheresUS) program. A consensus panel of 17 diverse experts in apheresis, related specialties, and electronic case report form (eCRF), and database development was assembled. The panel met via online conferencing from November 17, 2020 to December 1, 2021. A draft document was posted online for public comment from October 11, 2021 to November 10, 2021. Feedback was collected using an online survey tool. The consensus panel revised the UACRF. This version was converted to an eCRF with additional changes made to improve usability in this format. The final version of the UACRF was created on August 24, 2023. The UACRF contains 16 modules: procedure and subject eligibility, patient demographics, general procedure information, laboratory parameters, vascular access, common procedure elements, eight procedure specific modules (mononuclear cell collection and seven therapeutic modalities), outcomes, and site information. A total of 137 data elements were created, including 57 with one or more subelements. The UACRF is the first systematic attempt to develop CDE for therapeutic apheresis and white blood cell collections. Further validation of the UACRF is necessary to confirm the tool's ability to collect the relevant data elements and determine the usability of the form.
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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 | 0.123 | 0.210 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 0.023 |
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".