Higher Processed Blood Volume of Granulocyte and Monocyte Adsorption Apheresis Ameliorates Long-Term Disease Activity in Ulcerative Colitis Patients
Bibliographic record
Abstract
Background: Granulocyte and monocyte adsorption apheresis (GMA) is a therapeutic option for remission induction in the active ulcerative colitis (UC) patients. Effects of high processed blood volume of GMA as remission induction therapy on the long-term prognosis of UC patients have remained unclear. For this study, we investigated the relation between re-exacerbation of UC and the processed blood volume of GMA performed as induction therapy. Methods: Data from UC patients treated using a total of 10 GMA sessions as remission induction therapy during 2012 - 2022 were retrospectively collected and analyzed. The relation between the GMA dose, processed blood volume of GMA divided by body weight, and UC re-exacerbation requiring inpatient treatment within 1 year was evaluated. Results: This study examined data of 72 active UC patients, with median age of 44.4 years (65% male) and median GMA dose of 34.2 mL/kg/session. Kaplan-Meier analysis showed the 1-year exacerbation-free rate was significantly higher in the higher GMA dose group than in the lower GMA dose group (P = 0.008). Cox proportional hazards regression analyses revealed a higher GMA dose as inversely associated with the re-exacerbation of UC within 1 year (hazard ratio: 0.36, 95% confidence interval: 0.17 - 0.78). Extended treatment time of GMA session beyond 60 min contributed to achieving the higher GMA dose and did not increase unexpected treatment termination because of clotting. Conclusion: Greater processed blood volume of GMA per patient body weight may be associated with a lower 1-year exacerbation rate in UC patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".