JCM, Vol. 15, Pages 255: C-Reactive Protein-to-Albumin Ratio (CAR) and Left Atrial Diameter Predicts New-Onset Atrial Fibrillation in Chronic Coronary Syndrome: A Retrospective Cohort Study
Journal of Clinical Medicine doi: 10.3390/jcm15010255
Authors:
Xiaoying Xie
Jingjing Chen
Liangying Lin
Ximei Zhang
Baoshun Hao
Shujie Yu
Yesheng Ling
Xiaoxian Qian
Shaojie Lai
Yong Liu
Lin Wu
Bin Zhou
Background/Objectives: New-onset atrial fibrillation (NOAF) frequently develops in patients with chronic coronary syndrome (CCS) and is associated with adverse cardiovascular outcomes. The C-reactive protein–to–albumin ratio (CAR) reflects systemic inflammation, whereas left atrial diameter (LAD) indicates structural cardiac remodeling. Their combined predictive role for NOAF in CCS remains uncertain. This study evaluated the predictive value of combined CAR and LAD for NOAF in CCS patients. Methods: We retrospectively analyzed 2431 CCS patients treated at the Third Affiliated Hospital of Sun Yat-sen University between 2012 and 2019. The primary endpoint was NOAF occurrence during follow-up. Receiver operating characteristic (ROC) analysis determined exploratory cutoff values for CAR (0.0429) and LAD (33.96 mm). Patients were categorized into four groups: Group 1 (low CAR–low LAD), Group 2 (high CAR–low LAD), Group 3 (low CAR–high LAD), and Group 4 (high CAR–high LAD). Cox proportional hazards, Kaplan-Meier, and subgroup analyses were conducted to evaluate associations with NOAF risk. Results: During a median follow-up of 4.96 years, 93 NOAF events were identified. Compared with the Group 1, patients with higher CAR and LAD showed significantly elevated NOAF risk (HR = 2.67, 95%CI 1.99–3.57, p < 0.001). The combined CAR–LAD model demonstrated superior predictive accuracy (AUC = 0.731, 95% CI = 0.654–0.765; p < 0.001) and consistent effects across most subgroups. Decision curve analysis confirmed greater net clinical benefit for the combined model. Conclusions: The integration of CAR and LAD serves as a simple, non-invasive, and effective tool for predicting NOAF in CCS patients. This dual-marker model facilitates early identification of high-risk individuals and support personalized preventive strategies in clinical practice.
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Xiaoying Xie www.mdpi.com
