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Updated: May 5, 2026
The WATCHMAN Left Atrial Appendage Closure Device for Atrial Fibrillation
Published on: February 28, 2012
Development and validation of a nomogram superior to CHADS2 and CHA2DS2-VASc models for predicting left atrial
Shikun Sun1, Changsheng Ma1, Ying Li2
1Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Insights
This study developed a novel nomogram to predict left atrial appendage thrombus in atrial fibrillation patients, outperforming existing risk scores. The model identifies high-risk individuals for stroke, improving clinical decision-making.
Area of Science:
- Cardiology
- Medical Imaging
- Predictive Modeling
Background:
- Atrial fibrillation (AF) is a common arrhythmia with stroke as its critical complication, often caused by left atrial appendage thrombus (LAAT).
- Accurate identification of patients at high risk for LAAT is crucial for stroke prevention.
Purpose of the Study:
- To construct and validate a nomogram model for predicting left atrial appendage (LAA) dense spontaneous echo contrast (SEC) and LAAT.
- To compare the predictive performance of the novel nomogram against established risk stratification models (CHADS₂ and CHA₂DS₂-VASc).
Main Methods:
- A retrospective analysis of 433 AF patients who underwent transesophageal echocardiography (TEE).
- Logistic regression was used to identify independent predictors for LAA dense SEC/LAAT.
- A nomogram was constructed and its performance evaluated using consistency, receiver operating characteristic (ROC), and decision curve analyses.
Main Results:
- Female gender, elevated D-dimer, reduced left ventricular ejection fraction, reduced left atrial ejection fraction, and decreased left atrial reservoir strain rate were significant predictors of LAA dense SEC/LAAT.
- The developed nomogram demonstrated high consistency (0.921) and calibrated consistency (0.903).
- The nomogram significantly outperformed the CHADS₂ and CHA₂DS₂-VASc models in predicting LAA dense SEC/LAAT, showing superior net reclassification and integrated discrimination improvements.
Conclusions:
- The novel nomogram offers excellent performance in predicting LAA dense SEC/LAAT in AF patients.
- This tool provides a superior alternative to the CHADS₂ and CHA₂DS₂-VASc models for identifying high-risk individuals.
- The nomogram can aid clinicians in more accurate stroke risk stratification and management for AF patients.
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.
