Effects of N-acetyl cysteine and melatonin on early reperfusion injury in patients undergoing coronary artery bypass grafting
Bibliographic record
Abstract
OBJECTIVES: This study assessed the efficacy of oral consumption of N-acetyl cysteine (NAC) and melatonin (ML) in reducing early reperfusion injury and acute oxidative stress in patients undergoing coronary artery bypass grafting (CABG) with respect to the measurements of cardiac troponin I, lactate, malondealdehyde (MDA), and tumor necrosis factor-α (TNF-α) levels in the blood. METHODS: This study was a randomized, open-label, placebo-controlled trial. Eighty eight patients, aged between 39 to 76 years and eligible for CABG, were recruited and randomly assigned into 3 intervention groups through a simple randomization method and underwent CABG surgery. Blood samples were withdrawn from arterial line, before the induction of anesthesia (before the start of surgery), after incision (before aortic cross-clamping), during global ischemia (during aortic cross-clamping), after aortic cross-clamping (on set of reperfusion), 15 minutes after reperfusion, and after recovery at the intense care unit. The blood samples were analyzed for troponin I, lactate, MDA and TNF-α levels. RESULTS: There was no significant difference in influencing variables among the groups at the baseline. Overall mean troponin I, lactate, and TNF- α levels were significantly different between the intervention groups (all P < .001) at the recovery phase. Post-hoc pairwise comparisons showed that the differences of mean serum levels between ML and control groups were statistically significant for MDA, TNF- α, lactate, and troponin I (P < .001, P = .001, and P = .001, respectively). The differences between NAC and control groups and between ML and NAC groups were only significant for mean lactate level (P < .001). CONCLUSION: The current study revealed that ML and NAC are potent antioxidants with similar efficacy in terms of reducing CABG related cardiac injury and oxidative stress with the dosage employed for the intervention.
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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 | 0.001 |
| 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 | 0.000 | 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".