Correlation between plasma brain natriuretic peptide levels and left atrial appendage flow velocity in patients with non-valvular atrial fibrillation and normal left ventricular systolic function

Harada, Masahiko; Tabako, Satoshi; Fujii, Yuichiro; Takarada, Yuichi; Hayashi, Kyoko; Ohara, Hiroshi; Hara, Fumihiko; Ikeda, Takanori

doi:10.1007/s12574-017-0362-4

Cited by 10 publications

(11 citation statements)

References 44 publications

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“…This can also explain the view that some scholars believe that LAD can predict the risk of stroke[ 32 ]. However, similar to the study of Harada M et al [ 33 ], the multiple linear regression analysis did not prove that LAD is an independent factor of the LAAFV. Therefore, this needs more research to confirm.…”

Section: Discussionsupporting

confidence: 50%

“…The reason may be that the population included in our study is mainly NVAF patients with normal LVEF. So far, studys on the relationship between LVMI and LAA are rare, and there seems to be some controversy [ 33 , 35 ]. Our study showed that LAAFV was negatively correlated with LVMI, and the multiple linear regression analysis proved that LVMI is an independent factor of the LAAFV, which is similar to the study of Harada M et al [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

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Left atrial appendage orifice area and morphology is closely associated with flow velocity in patients with nonvalvular atrial fibrillation

Chen

et al. 2021

BMC Cardiovasc Disord

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Background Thromboembolic events are the most serious complication of atrial fibrillation (AF), and the left atrial appendage (LAA) is the most important site of thrombosis in patients with AF. During the period of COVID-19, a non-invasive left atrial appendage detection method is particularly important in order to reduce the exposure of the virus. This study used CT three-dimensional reconstruction methods to explore the relationship between LAA morphology, LAA orifice area and its mechanical function in patients with non-valvular atrial fibrillation (NVAF). Methods A total of 81 consecutive patients with NVAF (36 cases of paroxysmal atrial fibrillation and 45 cases of persistent atrial fibrillation) who were planned to undergo catheter radiofrequency ablation were enrolled. All patients were examined by transthoracic echocardiography (TTE), TEE, and computed tomography angiography (CTA) before surgery. The LAA orifice area was obtained according to the images of CTA. According to the left atrial appendage morphology, it was divided into chicken wing type and non-chicken wing type. At the same time, TEE was performed to determine left atrial appendage flow velocity (LAAFV), and the relationship between the left atrial appendage orifice area and LAAFV was analyzed. Results The LAAFV in Non-chicken wing group was lower than that in Chicken wing group (36.2 ± 15.0 cm/s vs. 49.1 ± 22.0 cm/s, p-value < 0.05). In the subgroup analysis, the LAAFV in Non-chicken wing group was lower than that in Chicken wing group in the paroxysmal AF (44.0 ± 14.3 cm/s vs. 60.2 ± 22.8 cm/s, p-value < 0.05). In the persistent AF, similar results were observed (29.7 ± 12.4 cm/s vs. 40.8 ± 17.7 cm/s, p-value < 0.05). The LAAFV in persistent AF group was lower than that in paroxysmal AF group (34.6 ± 15.8 cm/s vs. 49.9 ± 20.0 cm/s, p-value < 0.001). The LAAFV was negatively correlated with left atrial dimension (R = − 0.451, p-value < 0.001), LAA orifice area (R= − 0.438, p-value < 0.001) and left ventricular mass index (LVMI) (R= − 0.624, p-value < 0.001), while it was positively correlated with LVEF (R = 0.271, p-value = 0.014). Multiple linear regression analysis showed that LAA morphology (β = − 0.335, p-value < 0.001), LAA orifice area (β = − 0.185, p-value = 0.033), AF type (β = − 0.167, p-value = 0.043) and LVMI (β = − 0.465, p-value < 0.001) were independent factors of LAAFV. Conclusions The LAA orifice area is closely related to the mechanical function of the LAA in patients with NVAF. The larger LAA orifice area and LVMI, Non-chicken wing LAA and persistent AF are independent predictors of decreased mechanical function of LAA, and these parameters might be helpful for better management of LA thrombosis.

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Section: Discussionsupporting

confidence: 50%

Section: Discussionmentioning

confidence: 99%

Left atrial appendage orifice area and morphology is closely associated with flow velocity in patients with nonvalvular atrial fibrillation

Chen

et al. 2021

BMC Cardiovasc Disord

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“…Previous studies [ 38 , 39 ] found that elevated BNP was associated with LAA disfunction, and a high plasma brain natriuretic polypeptide level was a marker of risk for thromboembolism in patients with nonvalvular atrial fibrillation [ 40 ]. Harada et al also found that higher plasma BNP was associated with a lower LAA flow velocity in patients with nonvalvular AF and normal LV systolic function [ 17 ]. Therefore, in addition to diagnosing heart failure, the serum level of NT-pro BNP could, to a certain degree, reflect the function of left atrium and left atrial appendage.…”

Section: Discussionmentioning

confidence: 99%

“…Predictors in our model included demographics (age and sex), previous medical history (history of atrial fibrillation, hypertension, heart failure, diabetes, stroke, and vascular diseases), anticoagulant drugs and left atrial (LA) diameter. In addition, many studies have proved the correlation between NT-proBNP and LAA flow velocity [ 15 , 16 , 17 ]. Therefore, we chose BNP as one of the predictors.…”

Section: Methodsmentioning

confidence: 99%

Machine Learning Model-Based Simple Clinical Information to Predict Decreased Left Atrial Appendage Flow Velocity

Li¹,

Dou

Ding

et al. 2022

JPM

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Background: Transesophageal echocardiography (TEE) is the first technique of choice for evaluating the left atrial appendage flow velocity (LAAV) in clinical practice, which may cause some complications. Therefore, clinicians require a simple applicable method to screen patients with decreased LAAV. Therefore, we investigated the feasibility and accuracy of a machine learning (ML) model to predict LAAV. Method: The analysis included patients with atrial fibrillation who visited the general hospital of PLA and underwent transesophageal echocardiography (TEE) between January 2017 and December 2020. Three machine learning algorithms were used to predict LAAV. The area under the receiver operating characteristic curve (AUC) was measured to evaluate diagnostic accuracy. Results: Of the 1039 subjects, 125 patients (12%) were determined as having decreased LAAV (LAAV < 25 cm/s). Patients with decreased LAAV were fatter and showed a higher prevalence of persistent AF, heart failure, hypertension, diabetes and stroke, and the decreased LAAV group had a larger left atrium diameter and a higher serum level of NT-pro BNP than the control group (p < 0.05). Three machine-learning models (SVM model, RF model, and KNN model) were developed to predict LAAV. In the test data, the RF model performs best (R = 0.608, AUC = 0.89) among the three models. A fivefold cross-validation scheme further verified the predictive ability of the RF model. In the RF model, NT-proBNP was the factor with the strongest impact. Conclusions: A machine learning model (Random Forest model)-based simple clinical information showed good performance in predicting LAAV. The tool for the screening of decreased LAAV patients may be very helpful in the risk classification of patients with a high risk of LAA thrombosis.

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“…When atrial fibrillation occurs, the left atrium cannot contract effectively, the damage of left ventricular diastolic function and the increase of left ventricular filling pressure can lead to left atrial blood stasis, presenting as SEC, and increase the risk of LAA thrombosis (21,22). Studies have shown that BNP can predict the risk of atrial fibrillation (23), thromboembolism (22,(24)(25)(26)(27), and general cardiovascular risk (28)(29)(30). Recent studies have suggested that BNP is not only a predictor of AF, but also an early predictor of cerebral embolism in patients with AF (31).…”

Section: Main Findingsmentioning

confidence: 99%

A Study of Cardiogenic Stroke Risk in Non-valvular Atrial Fibrillation Patients

Song

et al. 2020

Front. Cardiovasc. Med.

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Correlation between plasma brain natriuretic peptide levels and left atrial appendage flow velocity in patients with non-valvular atrial fibrillation and normal left ventricular systolic function

Abstract: This study showed that a higher plasma BNP was associated with a lower LAA flow velocity in patients with NV-AF and normal LV systolic function. The plasma BNP may complement the role of the CHADS score in predicting lower LAA flow velocity.

Cited by 10 publications

References 44 publications

Left atrial appendage orifice area and morphology is closely associated with flow velocity in patients with nonvalvular atrial fibrillation

Left atrial appendage orifice area and morphology is closely associated with flow velocity in patients with nonvalvular atrial fibrillation

Machine Learning Model-Based Simple Clinical Information to Predict Decreased Left Atrial Appendage Flow Velocity

A Study of Cardiogenic Stroke Risk in Non-valvular Atrial Fibrillation Patients

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