The impact on neurological outcomes with the new-generation membrane oxygenators with integrated arterial filters
Bibliographic record
Abstract
Background: This study aims to compare the neurocognitive effects of two different oxygenator systems, i.e. membrane oxygenator with or without integrated arterial filters, used during cardiopulmonary bypass in patients undergoing coronary artery bypass grafting. Methods: This prospective, randomized study included a total of 40 patients (36 males, 4 females; mean age 60.0±8.5 years; range 43 to 75 years) who underwent elective coronary artery bypass grafting between January 2015 and December 2015. The patients were divided into two groups by block randomization using the sealed envelope technique. In group 1, non-integrated arterial filter membrane oxygenators and, in group 2, integrated arterial filter membrane oxygenators were used. Near-infrared spectroscopy was used to assess the cerebral oxygenation intraoperatively in all patients. Cranial diffusion-weighted magnetic resonance imaging was performed 2-4 days before and after the surgical procedure. Cognitive functions were evaluated using the Montreal Cognitive Assessment at the postoperative one month. Results: Eleven patients in the non-integrated group and seven patients in the integrated group had new lesions in the diffusion-weighted magnetic resonance imaging. The mean pre- and postoperative total Montreal Cognitive Assessment scores were 27.9±3.3 vs 28.1±3.4 and 26.2±3.1 vs 26.8±3, respectively, in the non-integrated and integrated groups. There were no statistically significant differences between the two groups in terms of the number of new lesions, the near-infrared spectroscopy findings, and the Montreal Cognitive Assessment scores. Conclusion: Membrane oxygenators with integrated arterial filters do not seem to offer a significant advantage over those without integrated arterial filters in terms of neurocognitive outcomes in patients undergoing coronary artery bypass grafting.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".