Development and validation of a nomogram superior to CHADS2 and CHA2DS2-VASc models for predicting left atrial appendage dense spontaneous echo contrast/left atrial appendage thrombus.

ABSTRACT

Background: Atrial fibrillation (AF) is one of the most frequently encountered arrhythmias in clinical practice, with stroke triggered by detachment of left atrial appendage thrombus (LAAT) after AF being its most critical complication. The purpose of this study was to construct a nomogram model for forecasting left atrial appendage (LAA) dense spontaneous echo contrast (SEC) and LAAT to accurately identify patients at high risk for stroke. Methods: A retrospective analysis was conducted on 433 patients with AF receiving transesophageal echocardiography (TEE) in the First Affiliated Hospital of Soochow University from October 2019 to July 2022. These patients were assigned into a non-dense SEC/LAAT group or a dense SEC/LAAT group. We constructed a nomogram model dependent on the odds ratios (ORs) of logistic regression and subsequently compared its performance with two models, CHADS2 and CHA2DS2-VASc. Results: Female gender, high D-dimer level, low left ventricular ejection fraction, low left atrial ejection fraction, and low left atrial reservoir strain rate were found to be independent factors for predicting LAA SEC/LAAT, with OR values and 95% confidence intervals of 2.811 (1.445-5.469), 2.460 (1.230-4.921), 0.961 (0.927-0.996), 0.950 (0.932-0.967), and 0.173 (0.035-0.848), respectively. The consistency statistic of the nomogram based on these given predictive factors was 0.921, and the calibrated consistency statistic was 0.903. According to receiver operation curve analysis and decision curve analysis, the nomogram was demonstrated to be superior to the CHADS2 and CHA2DS2-VASc models in predicting LAA dense SEC/LAAT. The net reclassification improvement and integrated discrimination improvement of the nomogram were 0.449 (0.324-0.575) and 0.461 (0.408-0.515), when compared with the CHADS2 model, and were 0.521 (0.411-0.632), and 0.432 (0.400-0.504), respectively, when compared with the CHA2DS2-VASc models. Conclusions: The nomogram model constructed in this study demonstrated excellent performance in predicting LAA dense SEC/LAAT, displaying a superior ability to that of the CHADS2 and CHA2DS2-VASc models.