In-depth characterization of a mouse model of postoperative atrial fibrillation
Bibliographic record
Abstract
Introduction: Postoperative atrial fibrillation (POAF), characterized as AF that arises 1-3 days after surgery, occurs after 30%-40% of cardiac and 10%-20% of non-cardiac surgeries, and is thought to arise due to transient surgery-induced triggers acting on a preexisting vulnerable atrial substrate often associated with inflammation and autonomic nervous system dysfunction. Current experimental studies often rely on human atrial tissue samples, collected during surgery prior to arrhythmia development, or animal models such as sterile pericarditis and atriotomy, which have not been robustly characterized. Aim: To characterize the demographic, electrophysiologic, and inflammatory properties of a POAF mouse model. Methods and Results: A total of 131 wild-type C57BL/6J mice were included in this study. A total of 86 (65.6%) mice underwent cardiothoracic surgery (THOR), which consisted of bi-atrial pericardiectomy with 20 s of aortic cross-clamping; 45 (34.3%) mice underwent a sham procedure consisting of dissection down to but not into the thoracic cavity. Intracardiac pacing, performed 72 h after surgery, was used to assess AF inducibility. THOR mice showed greater AF inducibility (38.4%) compared to Sham mice (17.8%, P = 0.027). Stratifying the cohort by tertiles of age showed that the greatest risk of POAF after THOR compared to Sham occurred in the 12-19-week age group. Stratifying by sex showed that cardiothoracic (CT) surgery increased POAF risk in females but had no significant effect in males. Quantitative polymerase chain reaction of atrial samples revealed upregulation of transforming growth factor beta 1 (TGF-β1) and interleukin 6 (IL6) and 18 (IL18) expression in THOR compared to Sham mice. Conclusion: Here, we demonstrate that the increased POAF risk associated with CT surgery is most pronounced in female and 12-19-week-old mice, and that the expression of inflammatory cytokines is upregulated in the atria of THOR mice prone to inducible AF. One sentence summary: We developed a mouse model of POAF that replicates key features of this condition in humans in terms of incidence and inflammatory indices. We demonstrated that female mice have a greater POAF risk than males, highlighting the importance of considering biological sex in future POAF mouse studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".