A Predictive Model and Scoring System for All-Cause Mortality in Patients With Atrial Fibrillation Combined With...

The high prevalence and mortality rate of combined atrial fibrillation (AF) and obstructive sleep apnea syndrome (OSAS) impose a significant disease burden on public healthcare systems. However, there is currently a lack of risk-assessment tools for all-cause mortality in patients with both AF and OSAS. Therefore, this study utilized clinical data from patients at the First Affiliated Hospital of Xinjiang Medical University to establish a predictive model and address this gap.

This study included 408 patients with AF and OSAS, randomly divided into a training set (n = 285) and a validation set (n = 123). Subsequently, the training set was split into deceased and surviving groups to analyze in-hospital indicators.

A total 10 variables were selected from an initial 64 variables in patients with AF and OSAS identified through Lasso regression screening, including hypoxemia, catheter ablation (CA), red blood cell count (RBC), lymphocyte count, basophil granulocyte count, total bile acids, D-dimer, free triiodothyronine, N-terminal pro-brain natriuretic peptide (NT-proBNP), and chronic obstructive pulmonary disease. Variables identified as significant in the univariate logistic regression analysis were included in the multivariable logistic regression analysis, which revealed that CA (odds ratio (OR) = 0.21) was an independent protective factor. In contrast, moderate-to-severe hypoxemia (OR = 11.11), RBC <3.8 × 10¹²/L (OR = 20.70), and D-dimer ≥280 ng/mL (OR = 7.07) were independent risk factors. Based on this, receiver operating characteristic (ROC) curves were plotted, showing area under the curve (AUC) values of 0.96 for the training set and 0.91 for the validation set, indicating the model exhibited good predictive ability. A risk-scoring system was developed to assess the overall mortality risk of patients with AF and OSAS. The percentage bar chart demonstrated an increase in mortality rate and a decrease in survival rate as the risk level increased.

The predictive model and risk scoring system developed in this study exhibit good predictive abilities in evaluating all-cause mortality in patients with AF and OSAS, providing valuable clinical guidance and reference.