Establishing an institutional therapeutic apheresis registry
Bibliographic record
Abstract
Apheresis was first performed as a therapeutic procedure in the 1950s. The first national therapeutic apheresis (TA) registry was established in Canada in 1981 and other national registries followed, including two attempts at establishing an international TA registry. There is no national registry in the United States. Our large, academic, tertiary hospital has a very active TA service. We created a TA database to track all procedures performed by the apheresis service by transferring data from paper appointment logs and the electronic medical records into a Microsoft Access database. Retrospective data from each TA procedure performed at UAB from January 1, 2003 through December 31, 2012 were entered, including the type of procedure, indication, date, and patient demographics. Microsoft Excel was used for data analysis. During the 10-year period, our TA service treated 1,060 patients and performed 11,718 procedures. Of these patients, 70% received therapeutic plasma exchange (TPE), 21% received extracorporeal photopheresis (ECP), 4.5% received red cell exchange (RCE), 4.2% received leukocytapheresis, and 0.6% underwent platelet depletion. Among the procedures, 54% were TPEs, 44% were ECPs, 1.3% were RCEs, 0.5% were leukocytaphereses, and 0.1% were platelet depletions. According to the current literature, national and international TA use is underreported. We believe that the UAB TA registry provides useful information about TA practices in our region and can serve as a model for other institutions. Furthermore, data from multiple institutional registries can be used for clinical research to increase the available evidence for the role of TA in various conditions. J. Clin. Apheresis 31:516-522, 2016. © 2015 Wiley Periodicals, Inc.
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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 | 0.026 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".