Are any biocompatible coatings capable of attenuating the deleterious effects of cardiopulmonary bypass?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Biocompatible circuits (BCC) are intended to decrease the activation of blood to the artificial cardiopulmonary bypass (CPB) surface. Typically, the coatings are made of various inert substances or molecules physiologically similar to endothelium. Thromboelastography (TEG) graphically represents clot formation, strength of clotting and fibrinolysis. TEG analysis was undertaken to determine if coagulation could be preserved by the BCC. METHODS: Five different BCC were studied in clinical applications. These five coated circuits were then compared to an identical circuit where only the oxygenator was coated. A pre- and post-bypass TEG was done for comparison. Six well-studied parameters of TEG analysis were compared: R time, angle, K, maximum amplitude (MA), LY30% and Clot Index (CI). Postoperative bleeding and transfusion requirements were compared to TEG results for comparison. RESULTS: All postoperative TEG results were significantly different from preoperative parameters except LY30%. No BCC circuit was able to prevent the significant disruption of the observed TEG coagulation parameters R, K, angle, MA and CI. Of note, the postoperative TEG parameters resulting from the Control and Trillium groups--which had the same type of oxygenator - were practically identical. The oxygenator, which represents the largest surface area in the CPB circuit, is the single most important factor influencing coagulation. CONCLUSION: While not harmful, BCC are ineffective in preserving TEG coagulation parameters post CPB. Clinical findings support laboratory TEG results in that there were no differences in bleeding or transfusion requirements between groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it