Processed residual pump blood in cardiac surgery: the Processed Residual Blood in Cardiac surgery trial
Bibliographic record
Abstract
BACKGROUND: Processing residual cardiopulmonary bypass (CPB) volume via ultrafiltration may improve hemostasis and reduce transfusion through clearing activated complement, activated coagulation components, and proinflammatory cytokines. We sought to establish if processing residual CPB volume with ultrafiltration reduces homologous blood transfusion and bleeding. STUDY DESIGN AND METHODS: Adult patients undergoing isolated coronary artery bypass grafting (CABG) surgery were randomly assigned to receive processed (n = 99) or unprocessed (control; n = 98) residual CPB volume in this single-center randomized controlled trial. The intensive care unit team, patients, and assessors were blinded to treatment assignment and a transfusion protocol was followed. Surgeons were permitted to use retrograde autologous priming to minimize crystalloid pump prime. RESULTS: The processed study bag was of a smaller volume (280 [0, 550] mL vs. 590 [215, 726] mL; p < 0.01) but a higher hematocrit (29% [0%, 34%] vs. 23% [20%, 25%]; p < 0.01) than control. The rate of transfusion with homologous blood was 39% in both groups (p = 0.92). There was no difference in the volume transfused (processed 323 ± 585 mL vs. control 276 ± 520 mL; p = 0.56). There was also no difference in the proportion of patients transfused with any blood product (processed 44% vs. control 45%; p = 0.95) or in the volume of chest tube output (processed 600 [500, 940] mL vs. control 670 [490, 932] mL; p = 0.62). CONCLUSION: Ultrafiltration of residual CPB volume in adults undergoing isolated CABG surgery does not reduce the need for transfusion or bleeding.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".