Designing an experimental method for assessing biocompatibility of circuit coatings using biomarkers for platelet activation during cardiopulmonary bypass
Bibliographic record
Abstract
INTRODUCTION: Cardiopulmonary bypass is an essential component of cardiothoracic surgeries. However, significant complications such as systemic inflammatory response syndrome (SIRS) resulting from cardiopulmonary bypass (CPB) are a common occurrence due to contact between circulating blood and foreign surfaces that leads to platelet activation. It is suggested that different available CPB circuit coatings can potentially reduce platelet activation. However, there have been no published evidence-based reports confirming these claims. In addition, there is no well-established protocol for studying platelet activation biomarkers during CPB in vitro in a laboratory setting. METHODS: Surface by Terumo. Fresh bovine blood samples were collected and circulated through the CPB circuit following the standard protocol used in the operation rooms. Blood samples were then collected at 5 min, 30 min, and 55 min during the circulation. Blood plasmas were separated and subjected to enzyme-linked immunosorbent assay to measure most established platelet activation markers P-selectin, Platelet Factor 4 (PF4), Glycoprotein IIb/IIIa (GPIIb/IIIa), and β-thromboglobulin (β-TG) at different time points. RESULTS: The biomarker values at 30 min and 55 min were compared to the base values at 5 min for each type of CPB circuit. The results of the means from all measured biomarkers showed data measurements that indicated no significant variability within each coating. All collected data points fell within ±2 SD of the means, which was considered acceptable variations across technical replicates. Conclusion: In this study, we were able to establish an in vitro protocol in the laboratory setting that is precise and reliable with minimum intra-variability. This established protocol will allow for future studies in which different coated CPB circuits can be compared for their effectiveness in blocking platelet activation during the CPB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".