Frontiers in cardiovascular medicine · 2026
Diagnostic value of left atrial three-dimensional strain for paroxysmal atrial fibrillation in patients with acute ischemic stroke.
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Wu Yanni, Li Xueyi, Tang Chao, Lv Xiaorui, Zhang Xia, Li Hui
Аннотация
OBJECTIVE: To investigate the diagnostic and incremental value of left atrial three-dimensional (3D) strain parameters for paroxysmal atrial fibrillation (PAF) detected by short-term in-hospital cardiac monitoring and early Holter recording in patients with acute ischemic stroke (AIS).
METHODS: A total of 340 consecutive AIS patients were enrolled and divided into non-PAF (n = 282) and PAF (n = 58) groups. A base diagnostic model was constructed using univariable logistic regression and least absolute shrinkage and selection operator (LASSO) regression. The optimal 3D strain parameter was selected via receiver operating characteristic (ROC) curve analysis and added to the base model. Incremental value was assessed using C-index, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Model robustness was validated with bootstrap resampling.
RESULTS: All 3D left atrial strain parameters showed diagnostic value for PAF [all area under the curve (AUC) > 0.6]. The base model incorporating age, sex, B-type natriuretic peptide (BNP, log-transformed), and left atrial maximum volume index (LAVI) yielded a C-index of 0.910. After adding left atrial reservoir-phase circumferential strain (LASr-c), the C-index increased to 0.932, with a continuous NRI of 0.8638 and IDI of 0.0973. Bootstrap validation confirmed model robustness (bias-corrected C-index = 0.919). DCA showed that the new model provided greater net clinical benefit across most risk threshold ranges.
CONCLUSION: Left atrial 3D strain has good diagnostic value for in-hospital detected PAF in AIS patients. Adding LASr-c may improve PAF risk stratification and inform subsequent targeted rhythm monitoring.
METHODS: A total of 340 consecutive AIS patients were enrolled and divided into non-PAF (n = 282) and PAF (n = 58) groups. A base diagnostic model was constructed using univariable logistic regression and least absolute shrinkage and selection operator (LASSO) regression. The optimal 3D strain parameter was selected via receiver operating characteristic (ROC) curve analysis and added to the base model. Incremental value was assessed using C-index, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Model robustness was validated with bootstrap resampling.
RESULTS: All 3D left atrial strain parameters showed diagnostic value for PAF [all area under the curve (AUC) > 0.6]. The base model incorporating age, sex, B-type natriuretic peptide (BNP, log-transformed), and left atrial maximum volume index (LAVI) yielded a C-index of 0.910. After adding left atrial reservoir-phase circumferential strain (LASr-c), the C-index increased to 0.932, with a continuous NRI of 0.8638 and IDI of 0.0973. Bootstrap validation confirmed model robustness (bias-corrected C-index = 0.919). DCA showed that the new model provided greater net clinical benefit across most risk threshold ranges.
CONCLUSION: Left atrial 3D strain has good diagnostic value for in-hospital detected PAF in AIS patients. Adding LASr-c may improve PAF risk stratification and inform subsequent targeted rhythm monitoring.