Alexandre Costa Souza et al. Bruna de Mattos Ivo Junqueira Stephanie de Azevedo Drubi Priscila Pinheiro … Laila Caroline Gomes Pedro Henrique Correia Filgueiras Ricardo André Sales Pereira Guedes Marco André Moraes Sales Yuri Xavier de Carvalho Carolina Thê Macêdo
Abstract
Background
Identifying atrial etiology in patients with mitral regurgitation remains challenging because the diagnosis is often established by exclusion. The use of a multivariable model may enhance diagnostic accuracy in the context of atrial functional mitral regurgitation.
Objective
To develop and validate a multivariable logistic regression model based on clinical and echocardiographic characteristics to predict atrial functional mitral regurgitation.
Methods
This cross-sectional study included patients with significant mitral regurgitation diagnosed by transesophageal echocardiography. The dataset was randomly divided into a training set (70%) and a validation set (30%). Statistical analyses were performed using a significance level of 5%.
Results
A total of 203 patients were included. The median age was 79 years in the atrial group and 72 years in the non-atrial group (p = 0.0022). Receiver operating characteristic curve analysis demonstrated good discriminative performance, with an area under the curve of 0.896 (95% CI, 0.845-0.947) in the training set. In the validation set, the model achieved an area under the curve of 0.946 (95% CI, 0.89-1.00), which indicates high predictive accuracy. Model calibration assessed by the Hosmer-Lemeshow test (chi-square test = 5.197; df = 8; p = 0.736) demonstrated good agreement between predicted and observed outcomes.
Conclusion
A multivariable model was derived and validated as a useful tool for predicting atrial etiology in patients with mitral regurgitation, potentially reducing diagnostic variability in clinical practice.
