The Impact of Remote Ischemic Preconditioning on Inflammation Markers in Patients Undergoing Coronary Artery Bypass Grafting
Bibliographic record
Abstract
Background: This study aimed to investigate if remote ischemic preconditioning reduces the inflammatory process on patients undergoing coronary artery bypass grafting (CABG). Methods: We conducted a case-control study involving 80 patients, half of whom underwent ischemic preconditioning for severe coronary artery disease (CAD) and subsequently underwent CABG. We assessed interleukin (IL)-1 and IL-6 levels using the enzyme-linked immunosorbent assay (ELISA) method, high-sensitivity troponin I (hsTnI) using chemiluminescent immunoassay (CLIA), and C-reactive protein (CRP) using the turbidimetric method at three key time points: before surgery (visit 1 or V1), immediately postoperatively (visit 2 or V2), and 1 week postoperatively (visit 3 or V3) in all subjects. Results: Ischemic preconditioned patients showed a significant decrease in proinflammatory markers (IL-1, IL-6) but not in CRP or hsTnI. Conclusions: This study demonstrated that remote ischemic preconditioning significantly reduced the levels of specific proinflammatory markers (IL-1 and IL-6), which may suggest general systemic protection. However, it did not demonstrate cardioprotection per se , as evidenced by the absence of a statistically significant decrease in hsTnI level. Cardiol Res. 2024;15(5):369-376 doi: https://doi.org/10.14740/cr1702
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".