ArticleFrontiers in cardiovascular medicine2022
A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Prediction Models for Postoperative Atrial Fibrillation After Cardiac Surgery: A Systematic Review and Critical Appraisal.Journal of clinical medicine · 2026Review
- Risk factors analysis and prediction models of atrial fibrillation/flutter after esophagectomy.Journal of cardiothoracic surgery · 2026Article
- Using preoperative four-dimensional automated left atrial quantification echocardiography to predict postoperative atrial fibrillation in patients undergoing cardiac surgery.Quantitative imaging in medicine and surgery · 2025Article
- Prediction Model for POstoperative atriaL fibrillAtion in caRdIac Surgery: The POLARIS Score.Journal of clinical medicine · 2025Article
- Association of Preoperative Leukocyte-to-Albumin Ratio with Short- and Long-Term Outcomes After Valvular Heart Surgery: A Retrospective Cohort Study.Journal of inflammation research · 2025Article
- An Evaluation of Four Predictive Scores for New Onset Atrial Fibrillation After Cardiac Surgery in a Tertiary Cardiac Centre.ANZ journal of surgeryArticle
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Authors and funding
6 authors.
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Abstract
Background: Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model. Methods: This retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram. Results: A total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595-5.206; Conclusion: Cardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions.
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