A novel nomogram model for diagnosing isolated atrial functional mitral regurgitation in patients with significant...

Atrial functional mitral regurgitation (AFMR) is a recently identified subtype of functional mitral regurgitation (MR), which necessitates a distinct therapeutic approach to that of traditional functional MR. However, diagnosing AFMR remains a complex challenge. Thus, this study aimed to establish a straightforward and effective method for the accurate diagnosis of AFMR using a nomogram.

In total, 489 patients with clinically significant (moderate-to-severe or severe) functional MR who were admitted to the Sun Yat-sen Memorial Hospital of Sun Yat-sen University from January 2020 to May 2023 were enrolled in the study. The patients were randomly divided into training and validation groups at a 7:3 ratio. The predictors for AFMR were screened out by uni- and multivariate logistic regression analyses, and a nomogram model was constructed. The model's predictive accuracy and discriminative capacity were subsequently assessed.

The multivariate logistic regression analysis revealed that the following factors were independent predictors of AFMR: left atrial diameter (LAd) [odds ratio (OR): 1.14, 95% confidence interval (CI): 1.04-1.24, P=0.004], left ventricular diastolic diameter (LVDd) (OR: 0.73, 95% CI: 0.65-0.82, P<0.001), left ventricular ejection fraction (LVEF) (OR: 1.21, 95% CI: 1.13-1.29, P<0.001), previous atrial fibrillation (AF) (OR: 9.34, 95% CI: 2.89-30.45, P<0.001), and myocardial infarction (MI) (OR: 0.04, 95% CI: 0.00-0.40, P=0.007). These factors were integrated into the diagnostic nomogram model. The area under the curve (AUC) values of the model were 0.993 and 0.979 in the training and testing cohorts, respectively.

This study developed a simple way to diagnose AFMR using a nomogram model that incorporated the LAd, LVDd, LVEF, AF, and MI. This model could help cardiologists in treatment determination and prognosis evaluation.