In:
Clinical Cardiology, Wiley, Vol. 44, No. 3 ( 2021-03), p. 407-414
Abstract:
A predictive model using left atrial function indexes obtained by real‐time three‐dimensional echocardiography (RT‐3DE) and the blood B‐type natriuretic peptide (BNP) level was constructed, and its value in predicting recurrence in patients with early persistent atrial fibrillation (AF) after radiofrequency ablation was explored. Methods A total of 228 patients with early persistent AF who were scheduled to receive the first circular pulmonary vein ablation (CPVA) were enrolled. Clinical data of patients were collected: (1) The blood BNP level was measured before radiofrequency ablation; (2) RT‐3DE was used to obtain the left atrial (LA) time‐volume curve; (3) The clinical characteristics, BNP level and LA function parameters were compared, and logistic regression was used to construct a prediction model with combined parameters; (4) The receiver operating characteristic (ROC) curve was used to examine the diagnostic efficacy of the model. Results (1) 215 patients with early persistent AF completed CPVA and the follow‐up. After 3–6 months of follow‐up, the patients were divided into sinus rhythm group (160 cases) and recurrence group (55 cases); (2) The recurrence group showed higher minimum LA volume index, diastolic ejection index, and preoperative BNP (all p ≤ .001), while the sinus rhythm group exhibited higher expansion index (PI) and left atrial appendage peak emptying velocity ( p ≤ .001); (3) In univariate analysis, BNP level had the best diagnostic performance in predicting the recurrence of AF(AUC = 0.703). We constructed a model based on LA function and BNP level to predict the recurrence of persistent AF after CPVA. This combined model was better than BNP alone in predicting the recurrence of persistent AF after CPVA (AUC: 0.814 vs. 0.703, z = 2.224, p = .026). Conclusion The combined model of LA function and blood BNP level has good predictive value for the recurrence of early persistent AF after CPVA.
Type of Medium:
Online Resource
ISSN:
0160-9289
,
1932-8737
Language:
English
Publisher:
Wiley
Publication Date:
2021
detail.hit.zdb_id:
2048223-1
