Examination of drug removal profiles in patients undergoing therapeutic plasma exchange: A retrospective study
Bibliographic record
Abstract
INTRODUCTION: Therapeutic plasma exchange (TPE) eliminates disease-contributing substances but may also affect drug concentrations. This study aimed to assess the prevalence of prescription drugs removable via TPE by reviewing patient medication histories. METHODS: A retrospective, single-center study was conducted from January 1, 2021 to December 31, 2022. The study included 244 patients undergoing 1087 TPE sessions. Drugs prescribed to patients on TPE days were categorized as "yes" (probably removable), "maybe" (possibly removable), and "no" (unlikely removable) regarding their removability via TPE. RESULTS: Among 3966 prescriptions, 556 (14.0%) were analyzed, with 21.8%, 36.5%, and 41.7% falling into the "yes," "maybe," and "no" categories for removability. Although only 14.0% were categorized, 83.6% of patients received at least one analyzable drug. Among them, 83.8% had at least one potentially removable drug. CONCLUSION: Real-world data highlights the need for caution in drug treatments during TPE to ensure optimal therapeutic outcomes, particularly for specific drugs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".