BACKGROUND: Measurement of left atrial (LA) volume (LAV) is recommended for quantification of LA size. Only LA anteroposterior diameter (LAd) is available in a number of large cohorts, trials, or registries. The aim of this study was to evaluate whether LAV may be reasonably estimated from LAd. METHODS: One hundred forty consecutive patients referred to our outpatient clinics were prospectively enrolled to measure LAd from the long-axis view on two-dimensional echocardiography. LA orthogonal dimensions were also taken from apical four- and two-chamber views. LAV was measured using the Simpson, area-length, and ellipsoid (LAVe) methods. The first 70 patients were the learning series and the last 70 the testing series (TeS). In the learning series, best-fitting regression analysis of LAV-LAd was run using all LAV methods, and the highest values of F were chosen among the regression equations. In the TeS, the best-fitting regressions were used to estimate LAV from LAd. RESULTS: In the learning series, the best-fitting regression was linear for the Spearman method (r2 = 0.62, F = 111.85, P = .0001) and area-length method (r2 = 0.62, F = 112.24, P = .0001) and powered for the LAVe method (r2 = 0.81, F = 288.41, P = .0001). In the TeS, the r2 value for LAV prediction was substantially better using the LAVe method (r2 = 0.89) than the Simpson (r2 = 0.72) or area-length (r2 = 0.70) method, as was the intraclass correlation (ρ = 0.96 vs ρ = 0.89 and ρ = 0.89, respectively). In the TeS, the sensitivity and specificity of LA dilatation by the estimated LAVe method were 87% and 90%, respectively. CONCLUSIONS: LAV can be estimated from LAd using a nonlinear equation with an elliptical model. The proposed method may be used in retrospective analysis of existing data sets in which determination of LAV was not programmed.
BACKGROUND: Measurement of left atrial (LA) volume (LAV) is recommended for quantification of LA size. Only LA anteroposterior diameter (LAd) is available in a number of large cohorts, trials, or registries. The aim of this study was to evaluate whether LAV may be reasonably estimated from LAd. METHODS: One hundred forty consecutive patients referred to our outpatient clinics were prospectively enrolled to measure LAd from the long-axis view on two-dimensional echocardiography. LA orthogonal dimensions were also taken from apical four- and two-chamber views. LAV was measured using the Simpson, area-length, and ellipsoid (LAVe) methods. The first 70 patients were the learning series and the last 70 the testing series (TeS). In the learning series, best-fitting regression analysis of LAV-LAd was run using all LAV methods, and the highest values of F were chosen among the regression equations. In the TeS, the best-fitting regressions were used to estimate LAV from LAd. RESULTS: In the learning series, the best-fitting regression was linear for the Spearman method (r2 = 0.62, F = 111.85, P = .0001) and area-length method (r2 = 0.62, F = 112.24, P = .0001) and powered for the LAVe method (r2 = 0.81, F = 288.41, P = .0001). In the TeS, the r2 value for LAV prediction was substantially better using the LAVe method (r2 = 0.89) than the Simpson (r2 = 0.72) or area-length (r2 = 0.70) method, as was the intraclass correlation (ρ = 0.96 vs ρ = 0.89 and ρ = 0.89, respectively). In the TeS, the sensitivity and specificity of LA dilatation by the estimated LAVe method were 87% and 90%, respectively. CONCLUSIONS: LAV can be estimated from LAd using a nonlinear equation with an elliptical model. The proposed method may be used in retrospective analysis of existing data sets in which determination of LAV was not programmed.
Authors: Maria Angela Losi; Massimo Imbriaco; Grazia Canciello; Filomena Pacelli; Carlo Di Nardo; Raffaella Lombardi; Raffaele Izzo; Costantino Mancusi; Andrea Ponsiglione; Serena Dell'Aversana; Alberto Cuocolo; Giovanni de Simone; Bruno Trimarco; Emanuele Barbato Journal: J Cardiovasc Transl Res Date: 2019-09-05 Impact factor: 4.132
Authors: Maria V Manzi; Costantino Mancusi; Maria Lembo; Giovanni Esposito; Maria A E Rao; Giovanni de Simone; Carmine Morisco; Valentina Trimarco; Raffaele Izzo; Bruno Trimarco Journal: ESC Heart Fail Date: 2022-04-28
Authors: Giovanni de Simone; Costantino Mancusi; Roberta Esposito; Nicola De Luca; Maurizio Galderisi Journal: High Blood Press Cardiovasc Prev Date: 2018-05-02
Authors: Daniele Massera; Mo Hu; Joseph A Delaney; Traci M Bartz; Megan E Bach; Stephen J Dvorak; Christopher R DeFilippi; Bruce M Psaty; John S Gottdiener; Jorge R Kizer; Sanjiv J Shah Journal: Heart Date: 2021-07-13 Impact factor: 5.994
Authors: Giovanni de Simone; Wenyu Wang; Lyle G Best; Fawn Yeh; Raffaele Izzo; Costantino Mancusi; Mary J Roman; Elisa T Lee; Barbara V Howard; Richard B Devereux Journal: Cardiovasc Diabetol Date: 2017-05-12 Impact factor: 9.951
Authors: Maria Lembo; Valentina Trimarco; Maria Virginia Manzi; Costantino Mancusi; Giovanni Esposito; Salvatore Esposito; Carmine Morisco; Raffaele Izzo; Bruno Trimarco Journal: Front Cardiovasc Med Date: 2022-07-28