BMC Cardiovascular Disorders (Jul 2022)

A nomogram to predict left atrial appendage thrombus and spontaneous echo contrast in non-valvular atrial fibrillation patients

  • Shikun Sun,
  • Bo Su,
  • Jia Lin,
  • Caiming Zhao,
  • Changsheng Ma

DOI
https://doi.org/10.1186/s12872-022-02737-z
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 10

Abstract

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Abstract Background Non-valvular atrial fibrillation (NVAF) significantly increases the risk of stroke. Although there is availability of prediction models, their ability to predict the risk of stroke in NVAF patients remains suboptimal. Therefore, there is need to improve prediction of high-risk individuals, which is critical for efficient management of patients with NVAF. Objective The objective of our paper is to develop a nomogram for predicting the risk of left atrial appendage thrombus (LAAT) and spontaneous echo contrast (SEC), thereby replacing the risk of stroke in NVAF patients. Design This was a retrospective cohort study that analyzed clinical data and echocardiographic indices of 387 patients with NVAF from October 2018 to June 2021. Multivariable logistic regression was used to evaluate independent factors that were used to construct the prediction nomogram. Analysis The discriminative ability and calibration of the nomogram to predict LAAT/SEC were tested using C-statistic and calibration plot. The performance of the nomogram was assessed against the CHA2DS2 score, CHA2DS2-VASc score and ATRIA score using the receiver operating characteristic curve (ROC), decision curve analysis (DCA), integrated discrimination index (IDI) and net reclassification index (NRI). Result Out of the total 387 patients enrolled in this study, 232 had LAAT/SEC. Multivariable analyses demonstrated that N-terminal pro-B-type natriuretic peptide (NT-proBNP), albumin (ALB), LAA ejection fraction (LAAEF) and LAA global peak longitudinal strain (LAA GPLS) were independent predictors of LAAT/SEC. The constructed nomogram had good discriminative (C = 0.886) and calibration (0.876) abilities after bias correction by the C-index. Compared with other models, the decision curve analyses demonstrated that the nomogram had greater net benefits. Besides, the nomogram had significant improvement in predictive performance, sensitivity and reclassification for LAAT/SEC compared with the CHA2DS2 [(c-index: 0.886 vs. 0.576, p < 0.05), (NRI: 0.539, p < 0.05), (IDI: 0.432, p < 0.05)], CHA2DS2-VASc [(c-index: 0.886 vs0.579, p < 0.05), (NRI: 0.513, p < 0.05), (IDI: 0.432, p < 0.05)] or ATRIA [(c-index: 0.886 vs0.583, p < 0.05), (NRI: 0.546, p < 0.05), (IDI: 0.432, p < 0.05)]. Conclusion Taken together, our data demonstrated that the developed nomogram was effective and had potential clinical application in the prediction of LAAT/SEC in patients with NVAF.

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