Abstract
Left ventricular (LV) systolic dysfunction is an acknowledged perioperative risk factor and should be identified before surgery. Conventional echocardiographic assessment of LV ejection fraction (LVEF) obtained by biplane LV volumes is the gold standard to detect LV systolic dysfunction. However, this modality needs extensive training and is time consuming. Hence, a feasible point-of-care screening method for this purpose is warranted. The aim of this study was to evaluate 3 point-of-care echocardiographic methods for identification of LV systolic dysfunction in comparison with biplane LVEF. One hundred elective surgical patients, with a mean age of 63 ± 12 years and body mass index of 27 ± 4 kg/m2, were consecutively enrolled in this prospective observational study. Transthoracic echocardiography was conducted 1-2 hours before surgery. LVEF was obtained by automatic two-dimensional (2D) biplane ejection fraction (EF) software. We evaluated if Tissue Doppler Imaging peak systolic myocardial velocities (TDISm), anatomic M-mode E-point septal separation (EPSS), and conventional M-mode mitral annular plane systolic excursion (MAPSE) could discriminate LV systolic dysfunction (LVEF <50%) by calculating accuracy, efficiency, correlation, positive (PPV) respective negative predictive (NPV) values, and area under the receiver operating characteristic curve (AUROC) for each point-of-care method. LVEF<50% was identified in 22% (21 of 94) of patients. To discriminate an LVEF <50%, AUROC for TDISm (mean <8 cm/s) was 0.73 (95% confidence interval [CI], 0.62-0.84; P < .001), with a PPV of 47% and an NPV of 90%. EPSS with a cutoff value of >6 mm had an AUROC 0.89 (95% CI, 0.80-0.98; P < .001), with a PPV of 67% and an NPV of 96%. MAPSE (mean <12 mm) had an AUROC 0.80 (95% CI, 0.70-0.90; P < 0.001) with a PPV of 57% and an NPV of 98%. All 3 point-of-care methods performed reasonably well to discriminate patients with LVEF <50%. The clinician may choose the most suitable method according to praxis and observer experience.
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