Phosphorylcholine-Coated Circuits Improve Preservation of Platelet Count and Reduce Expression of Proinflammatory Cytokines in CABG: A Prospective Randomized Trial
Bibliographic record
Abstract
BACKGROUND: The interaction of blood with foreign artificial surfaces during cardiopulmonary bypass (CPB) has been recognized as a major stimulus in evoking a systemic inflammatory and metabolic response. Phosphorylcholine (PC) is a new-generation coating material designed to ameliorate biocompatibility and thereby to reduce the detrimental interactions of CPB. We studied the effects of PC-coated perfusion circuits on platelet function and the humoral and cellular response to CPB. METHODS: Thirty patients undergoing coronary artery bypass grafting were randomized to PC-coated (PC group, n = 15) and noncoated (control group, n = 15) circuit groups. Clinical data, total blood loss, and pre- and postoperative platelet counts were recorded and IL-6 and TNF-alpha, CD41a, CD42b, and CD62p were measured at induction of anesthesia, after the initiation of CPB and at termination of CPB. RESULTS: There was a significantly improved preservation of platelet count following CPB in the PC group (p = 0.028), which was sustained over a period of 72 hours. The use of PC-coated circuits further resulted in a significant attenuation of TNF-alpha and IL-6 expression (p < 0.05 and p < 0.01); however, we were unable to detect any differences in clinical outcomes. CONCLUSIONS: Despite similar clinical outcome, the obvious reduction of cytokine expression and improved preservation of platelet count suggest superior biocompatibility of PC-coated circuits.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".