학술논문
A novel method of calculating stroke volume using point-of-care echocardiography
Document Type
Academic Journal
Author
Source
Cardiovascular Ultrasound. August 20, 2020, Vol. 18 Issue 1
Subject
Language
English
Abstract
Author(s): Ehson Aligholizadeh[sup.1], William Teeter[sup.1], Rajan Patel[sup.2], Peter Hu[sup.2], Syeda Fatima[sup.1], Shiming Yang[sup.2], Gautam Ramani[sup.3], Sami Safadi[sup.4], Peter Olivieri[sup.5], Thomas Scalea[sup.1] and Sarah Murthi[sup.1] Background Accurate hemodynamic monitoring is vital [...]
Background Point-of-care transthoracic echocardiography (POC-TTE) is essential in shock management, allowing for stroke volume (SV) and cardiac output (CO) estimation using left ventricular outflow tract diameter (LVOTD) and left ventricular velocity time integral (VTI). Since LVOTD is difficult to obtain and error-prone, the body surface area (BSA) or a modified BSA (mBSA) is sometimes used as a surrogate (LVOTD.sup.BSA, LVOTD.sup.mBSA). Currently, no models of LVOTD based on patient characteristics exist nor have BSA-based alternatives been validated. Methods Focused rapid echocardiographic evaluations (FREEs) performed in intensive care unit patients over a 3-year period were reviewed. The age, sex, height, and weight were recorded. Human expert measurement of LVOTD (LVOTD.sup.HEM) was performed. An epsilon-support vector regression was used to derive a computer model of the predicted LVOTD (LVOTD.sup.CM). Training, testing, and validation were completed. Pearson coefficient and Bland-Altman were used to assess correlation and agreement. Results Two hundred eighty-seven TTEs with ideal images of the LVOT were identified. LVOTD.sup.CM was the best method of SV measurement, with a correlation of 0.87. LVOTD.sup.mBSA and LVOTD.sup.BSA had correlations of 0.71 and 0.49 respectively. Root mean square error for LVOTD.sup.CM, LVOTD.sup.mBSA, and LVOTD.sup.BSA respectively were 13.3, 37.0, and 26.4. Bland-Altman for LVOTD.sup.CM demonstrated a bias of 5.2. LVOTD.sup.CM model was used in a separate validation set of 116 ideal images yielding a linear correlation of 0.83 between SV.sup.HEM and SV.sup.CM. Bland Altman analysis for SV.sup.CM had a bias of 2.3 with limits of agreement (LOAs) of - 24 and 29, a percent error (PE) of 34% and a root mean square error (RMSE) of 13.9. Conclusions A computer model may allow for SV and CO measurement when the LVOTD cannot be assessed. Further study is needed to assess the accuracy of the model in various patient populations and in comparison to the gold standard pulmonary artery catheter. The LVOTD.sup.CM is more accurate with less error compared to BSA-based methods, however there is still a percentage error of 33%. BSA should not be used as a surrogate measure of LVOTD. Once validated and improved this model may improve feasibility and allow hemodynamic monitoring via POC-TTE once it is validated. Keywords: Echocardiography, POCUS, Hemodynamic monitoring, Cardiac output, Fluid resuscitation
Background Point-of-care transthoracic echocardiography (POC-TTE) is essential in shock management, allowing for stroke volume (SV) and cardiac output (CO) estimation using left ventricular outflow tract diameter (LVOTD) and left ventricular velocity time integral (VTI). Since LVOTD is difficult to obtain and error-prone, the body surface area (BSA) or a modified BSA (mBSA) is sometimes used as a surrogate (LVOTD.sup.BSA, LVOTD.sup.mBSA). Currently, no models of LVOTD based on patient characteristics exist nor have BSA-based alternatives been validated. Methods Focused rapid echocardiographic evaluations (FREEs) performed in intensive care unit patients over a 3-year period were reviewed. The age, sex, height, and weight were recorded. Human expert measurement of LVOTD (LVOTD.sup.HEM) was performed. An epsilon-support vector regression was used to derive a computer model of the predicted LVOTD (LVOTD.sup.CM). Training, testing, and validation were completed. Pearson coefficient and Bland-Altman were used to assess correlation and agreement. Results Two hundred eighty-seven TTEs with ideal images of the LVOT were identified. LVOTD.sup.CM was the best method of SV measurement, with a correlation of 0.87. LVOTD.sup.mBSA and LVOTD.sup.BSA had correlations of 0.71 and 0.49 respectively. Root mean square error for LVOTD.sup.CM, LVOTD.sup.mBSA, and LVOTD.sup.BSA respectively were 13.3, 37.0, and 26.4. Bland-Altman for LVOTD.sup.CM demonstrated a bias of 5.2. LVOTD.sup.CM model was used in a separate validation set of 116 ideal images yielding a linear correlation of 0.83 between SV.sup.HEM and SV.sup.CM. Bland Altman analysis for SV.sup.CM had a bias of 2.3 with limits of agreement (LOAs) of - 24 and 29, a percent error (PE) of 34% and a root mean square error (RMSE) of 13.9. Conclusions A computer model may allow for SV and CO measurement when the LVOTD cannot be assessed. Further study is needed to assess the accuracy of the model in various patient populations and in comparison to the gold standard pulmonary artery catheter. The LVOTD.sup.CM is more accurate with less error compared to BSA-based methods, however there is still a percentage error of 33%. BSA should not be used as a surrogate measure of LVOTD. Once validated and improved this model may improve feasibility and allow hemodynamic monitoring via POC-TTE once it is validated. Keywords: Echocardiography, POCUS, Hemodynamic monitoring, Cardiac output, Fluid resuscitation