Rapid bedside identification of high-risk population in heart failure with reduced ejection fraction by acoustic cardiography |
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Authors: | Shang Wang Fang FangMing Liu Yat Yin LamJing Wang Qing ShangJing Ping Sun John E. SandersonCheuk Man Yu |
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Affiliation: | Division of cardiology, Department of Medicine and Therapeutics, Prince of Wales Hospital, Li Ka Shing Institute of Health and Sciences, Institute of Vascular Medicine, The Chinese University of Hong Kong, Hong Kong, China |
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Abstract: | BackgroundLow left ventricular ejection fraction (LVEF) and the presence of restrictive LV filling pattern are poor prognosticators in heart failure patients with reduced EF (HFREF). We sought to investigate whether acoustic cardiography can identify these high-risk HFREF subgroups.MethodsA total of 127 HFREF patients (EF < 50%) were enrolled into our study. All patients underwent acoustic cardiographic and echocardiographic examinations. Acoustic cardiographic parameters included S3 score (probability that the third heart sound exists), electromechanical activation time (EMAT, interval from Q wave to the first heart sound; %EMAT is the proportion of cardiac cycle that EMAT occupies), and systolic dysfunction index (SDI, a derived variable from the combination of %EMAT, S3 score, QRS duration and QR interval). Receiver operating characteristic curves were used to determine diagnostic utility of acoustic cardiography.ResultsSDI discriminated (area under curve [AUC], 0.79; 95% confidence interval [CI], 0.71–0.87) patients with severely impaired EF (EF ≤ 35%) from those with moderately impaired EF (35% < EF < 50%) with an SDI > 5 that yielded 87% sensitivity and 60% specificity. An S3 score > 4 identified patients with restrictive LV filling pattern with 0.76 AUC (95% CI, 0.67–0.84), 81% sensitivity and 55% specificity.ConclusionsSDI and S3 score obtained by acoustic cardiography identified HFREF patients with severely impaired systolic and diastolic function, respectively. This simple, bedside technology may be used as a screening tool to identify the sickest HFREF patients for more intensive therapy. |
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Keywords: | Acoustic cardiography Heart failure Diagnosis |
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