Atorvastatin Reduces the Incidence of Postoperative Atrial Fibrillation in Statin-Naive Patients Undergoing Isolated Heart Valve Surgery
Bibliographic record
Abstract
BACKGROUND: Atorvastatin has been demonstrated to reduce the incidence of postoperative atrial fibrillation (POAF) in patients undergoing cardiac surgery, but its effect on isolated heart valve surgery is unknown. METHODS: In a randomized, double-blinded, placebo-controlled trial, 58 patients who underwent isolated heart valve surgery supported by on-pump cardiopulmonary bypass were randomly assigned to receive either placebo (n = 29) or 40 mg of atorvastatin once daily starting 3 days preoperatively and continuing within 5 days postoperatively (n = 29). A continuous monitoring tool and an electrocardiographic Holter monitoring were used for detecting the POAF (Clinical Trial Registration: www.clinicaltrials.gov; Unique Identifier: NTC02084069). RESULTS: The patients' median age was 49 years, and 67% were female. In all, 6 (21%) and 13 (45%) cases of POAF were observed in the atorvastatin and placebo groups, respectively (P = .050). The duration of AF before re-establishment of sinus rhythm was significantly lower in the atorvastatin group than in the placebo group (median of 70 vs 132 minutes, P = .026). The lengths of intensive care unit and hospital stay were comparable between the groups. The increase in postoperative white blood cell count was significantly lower in the atorvastatin group than in the placebo group (median of 1.5 vs 2.3 × 10(3)/µL, respectively, P = .019). After adjustment, the atorvastatin treatment was associated with a decrease in the risk of developing POAF (odds ratio 0.122, 95% confidence interval 0.027-0.548, P = .006). CONCLUSION: Perioperative treatment with 40 mg of atorvastatin is useful to decrease the incidence of POAF in the statin-naive patients undergoing isolated heart valve surgery.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".