Development and validation of a nomogram superior to CHADS₂ and CHA₂DS₂-VASc models for predicting left atrial...

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.