The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis

The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis Omar Aldalati, Mehdi Eskandari, Montasir H Ali, Rita Cabaco, Jonathan Byrne, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4200318/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Studies utilising invasive pressure‒volume loops offer valuable insights into left ventricular (LV) contractility, yet their availability remains limited. Conversely, noninvasive indices are accessible and reproducible; however, their validation in patients with aortic stenosis (AS) is lacking. We sought to validate the noninvasive indices of PVL studies in a group of symptomatic severe AS patients. We recruited patients with symptomatic severe AS admitted for transcatheter aortic valve implantation (TAVI) for invasive PVL studies. Noninvasive PVL indices were measured with three-dimensional (3D) echocardiography with a prespecified protocol. The agreement between invasive and noninvasive calculation methods was assessed. Results: Eleven patients (11) were recruited for this pilot study. The noninvasive end-systolic pressure‒volume relationship (ESPVR) determined by Kelly's method (Ees (sb) = 0.9 × systolic blood pressure/end-systolic volume (ESV)) had the best agreement with the invasive ESPVR (limits of agreement -1.7 to 2.1 with a percentage error of 24%, one sample T test p =0.504). Systolic blood pressure, as measured by the brachial blood pressure cuff, had the best agreement with end-systolic pressure in severe aortic stenosis (limits of agreement -60 to 60 with a percentage error of 3%, one sample T test p =0.959). Conclusion: Measurement of the single-beat estimate of ventricular elastance (Ees (sb) ) is possible in patients with severe aortic stenosis. Kelly's method (Ees (sb) = 0.9 × SBP/ESV) had the best agreement with the invasive measurement of left ventricular elastance (Ees). Systolic blood pressure, as measured by the brachial blood pressure cuff, has the best agreement with end-systolic pressure in severe aortic stenosis. Severe aortic stenosis Invasive pressure‒volume loop indices Noninvasive pressure‒volume loop indices Ventricular elastance Validation Figures Figure 1 Figure 2 Background: There is growing interest in early intervention for severe aortic stenosis (AS). The left ventricular (LV) ejection fraction (EF) has been used for the assessment of LV function. The assessment of LV EF, regardless of the modality used, has inherent limitations. Advanced tools for assessing LV mechanics, such as myocardial deformation, have been developed for the early detection of subclinical LV dysfunction. Pressure‒volume loop (PVL) indices, mainly left ventricular elastance (Ees; also known as the end-systolic pressure‒volume relationship (ESPVR)), are considered the gold standard measures of LV systolic function 3 . Invasive PV loop measurement requires left ventricular conductance catheter placement, inferior vena cava (IVC) balloon occlusion for load variation, and a pulmonary artery catheter for calibration. The invasive nature of such a procedure renders it a research tool rather than a day-to-day investigation 4 . As a result, several single-beat noninvasive echocardiography-based methods have been developed and validated for measuring Ees in clinical practice; the majority of these methods were derived from animal-based research 9 . To the authors’ knowledge, none of the validated single-beat noninvasive methods have included patients with severe AS. In this pilot study, we sought to assess the agreement between invasive and noninvasive PVL indices in severe AS patients. We also sought to compare the methods of single-beat estimates of Ees and the agreement between the other invasive and noninvasive indices of contractility. Methods: We recruited eleven ( 11 ) consecutive patients for invasive PV loop studies during transcatheter aortic valve implantation (TAVI) procedures. The patients had symptomatic severe AS and were deemed by the heart team appropriate and in need of TAVI. The recruited patients had to meet the following inclusion criteria: In sinus rhythm Suitability for transfemoral access In stable clinical conditions Absence of coexisting severe valvular heart disease Normal right ventricular function Able to give informed consent Invasive pressure‒volume loop studies: The TAVI procedures were performed as per routine clinical care. After crossing the aortic valve, a 4 Fr or 7 Fr high-fidelity conductance catheter (CD Leycom, Netherlands) was placed in the LV, either over the guidewire or with the help of a destination catheter. The conductance catheter was then connected to a dual-field conductance processor (Inca, CD Leycom, Netherlands). Under fluoroscopic guidance, the conductance catheter position was optimised along the long LV axis with the help of live PV loop recording. For calibration purposes, a pulmonary artery catheter (Swan–Ganz catheter, 6 Fr, Edwards Lifesciences Corp., Irvine, USA) was placed in the pulmonary artery under fluoroscopy guidance from the right median cubital vein. Calibration was performed using the parallel conductance method. Cardiac output was measured first with the thermodilution technique (SV calibration; repeated three times), followed by the injection of 10 ml of 10% saline into the pulmonary artery (EFcal; repeated twice). After calibration, we waited for several minutes to ensure cardiovascular stability. The conductance catheter position was reassessed by fluoroscopy once again before acquiring live PV loop data. Three-dimensional transthoracic echocardiography: All recruited patients underwent two- and three-dimensional transthoracic echocardiography (2D and 3D TTE) approximately 90 minutes before TAVI (Epic CVx, Best, Netherland). 3D LV end-systolic and end-diastolic volumes (Qlab version 12, Philips, Best, Netherlands), preejection period (PEP), ejection time (ET) and total systolic time (TST) were calculated. Brachial blood pressure was recorded at the time of the 3D TTE study for all patients. The following formula was used to calculate the noninvasive Ees: The acquired TTE data were used to calculate the noninvasive Ees (sb) using the following formulas: Formula Name Formula Chen's method 7 Ees (Chen) = DBP – (ENDest × SBP × 0.9)/(SV × ENDest) Kelly's method 10 Ees (Kelly) = (0.9 × SBP)/ESV Tanoue's method 6 Ees (Tanoue) = MAP/ESV Yamashita's method 11 Ees (Yamashita) = corrected MAP/ESV Kim's method Ees (Kim) = (DBP – 0.9 × SBP + α × (DBP – EDP) X (ET/PEP))/SV Shishido's method 5 Ees (Shishido) = (DBP + (DBP – EDP)/PEP × ET × α – 0.9 × SBP)/SV Bombardini's method 12 Ees (Bombardini) = (0.9 × SBP) + Mg/ESV Systolic blood pressure method 13 Ees (SBP) = SBP/ESV Ees = ventricular elastance, DBP = diastolic blood pressure, SBP = systolic blood pressure, ENDest = noninvasively estimated normalised elastance at the onset of ejection, SV = stroke volume, ESV = end systolic volume, MAP = mean arterial pressure, EDP = end diastolic pressure, ET = ejection time, PEP = preejection period, Mg = mean gradient (measured by transthoracic echocardiogram). The sonographers and clinicians reporting the TTE were blinded to the invasive PV loop study results. Similarly, the cardiac physiologist and the clinician reporting the PV loop studies were blinded to the results of the 3D TTE studies. Statistical analysis: The agreement between the invasive and noninvasive indices was tested using Bland‒Altman plots, linear regression, Wilcoxon's test, Pearson's correlation and the percentage error between the corresponding indices. Statistical analysis was performed with SPSS statistical software (IBM SPSS Statistics for Windows, Version 22.0. Results: Eleven consecutive patients ( 11 ) were recruited for this study. The mean age was 84 ± 8 years; the majority were females (73%). All recruited patients had severe AS with a mean aortic valve area (AVA) of 0.72 cm2 ± 0.2, a mean gradient of 42 ± 16 mmHg and a dimensionless index of 0.21 ± 0.06, as shown in Table 1 . The measured indices from the invasive PVL studies and TTE are summarised in Table 2 and Table 3 , respectively. Table 1 Baseline characteristics Variable AS patients ( 11 ) Age (years ± SD) 84 ± 8 Female 8 (73%) Body mass index (kg/m2 ± SD) 29 ± 7 Body surface area (m 2 ± SD) 1.79 ± 0.22 NYHA class II 5 (45%) III 6 (55%) Systolic blood pressure (mmHg ± SD) 137 ± 19 Diastolic blood pressure (mmHg ± SD) 73 ± 12 Never smoked 9 (81%) Hypertension (Yes) 8 (73%) Diabetes (Yes) 4 (37%) Peripheral vascular disease (Yes) 3 (28%) Previous myocardial infarction (Yes) 1 (9%) Previous cardiac surgery (Yes) 1 (9%) Creatinine (µmol/l ± SD) 101 ± 25 Haemoglobin (mmol/l ± SD) 124 ± 9 QRS duration (ms ± SD) 84 ± 18 General anaesthesia (Yes) 6 (54%) Echocardiography Characteristics Ejection fraction (% ±SD) 53 ± 12 RWMA 1 (9%) Mean gradient (mmHg) 42 ± 16 Peak gradient (mmHg) 75 ± 25 Aortic valve area (cm2) 0.72 ± 0.2 Dimensionless index 0.21 ± 0.06 AS: aortic stenosis, RWMA: regional wall motion abnormality, SD: standard deviation, NYHA: New York Heart Association Table 2 Pressure-volume loop invasive measures Variable Mean ± SD Median (IQR) 95% Confidence Interval Lower Bound Upper Bound Heart rate (bpm) 67 ± 16 64 ( 18 ) 56 78 Ejection fraction (%) 60 ± 12 61 ( 16 ) 52 69 Cardiac output (L/min) 4.7 ± 1.5 5 (2.7) 3.6 5.8 Stroke volume (ml) 78 ± 26 82 (56) 59 97 Stroke work (ml.mmHg) 8155 ± 2895 7766 (4089) 6210 10099 Diastolic Indices End-diastolic volume (ml) 110 ± 41 107 (78) 82 138 End-diastolic pressure (mmHg) 9.5 ± 5.5 7.8 ( 10 ) 5.8 13 dp/dt minimum (mmHg/s) -1194 ± 469 -1419 (532) -1510 -879 TAU (ms) 33 ± 6 32 ( 12 ) 29 38 EDPVR (mmHg/ml) 0.1008 ± 0.06 0.1014 (0.12) 0.0583 0.1432 Systolic Indices End-systolic volume (ml) 58 ± 30 59 (58) 38 79 End-systolic pressure (mmHg) 138 ± 27 144 (44) 119 159 dp/dt maximum (mmHg/s) 1277 ± 362 1272 (537) 1034 1520 ESPVR (mmHg/ml) 3.25 ± 2.1 2.54 (4.5) 1.81 4.69 SCI (mmHg/ml/s) 14.1 ± 8 10.5 ( 14 ) 8.5 19.7 PRSW (mmHG) 82 ± 52 67.9 (49) 47 117 PVA (mmHg.ml) 12152 ± 3543 12061 (6545) 9771 14532 Arterial elastance (mmHg/ml) 2.06 ± 1 1.74 (1.4) 1.35 2.77 VA coupling (Ea/ESPVR) 0.76 ± 0.33 0.69 (0.26) 0.53 0.98 ZVA invasive 3.6 ± 1.6 2.8 (2.7) 2.48 4.74 bpm: beat per minute, dp/dt minimum: the minimum rate of change of ventricular pressure, EDPVR: End-diastolic pressure volume relationship, ESPVR: End-systolic pressure volume relationship, PRSW: Pre-load recruitable stroke work, PVA: pressure volume area, SCI: Starling contractility index, TAU: left ventricular time constant (diastolic index), VA Coupling: ventriculo-arterial coupling, ZVA = valvulo-arterial impedance (mmHg/ml/m2). Table 3 The required non-invasive measures to calculate Ees single beat estimates, the calculated Ees and the other non-invasive measures of contractility Variable Mean ± SD Median (IQR) 95% Confidence Interval Lower Bound Upper Bound End-diastolic volume (ml)* 96 ± 38 89 (88) 70 122 End-systolic volume (ml)* 48 ± 29 28 (54) 28 68 Stroke volume (ml)* 48 ± 14 44 (25) 39 58 Ejection fraction (%)* 53 ± 12 56 ( 15 ) 45 61 Pre-ejection period (ms) 70 ± 17 80 ( 20 ) 59 82 Ejection time (ms) 326 ± 56 310 (60) 288 364 Total systolic time (ms) 397 ± 46 390 (50) 365 428 PEP/ET (ratio) 0.22 ± 0.07 0.25 (0.11) 0.17 0.27 Calculated Non-Invasive Ees Ees by Chen et al 2.89 ± 0.7 3 (0.8) 2.4 3.3 Ees by Kim et al 3.1 ± 1.5 2.8 (1.6) 2 4.1 Ees by Shishido et al 11 ± 4 9.9 ( 6 ) 8.2 13.7 Ees by Tanuoue et al 3.48 ± 1.8 3.5 (3.8) 2.25 4.71 Ees as suggested by Bombardini et al 4.6 ± 2.2 5.5 ( 5 ) 3.1 6.1 Other Calculated Non-Invasive Indices Arterial elastance (Ea) 2.7 ± 0.8 2.8 (1.4) 2.18 3.31 Ea as suggested by Bombardini et al 3.6 ± 1 4.1 ( 2 ) 2.9 4.3 PRSW (mmHg) 50 ± 11 51 ( 16 ) 42 58 ZVA non-invasive 7 ± 2 6.5 (2.7) 5.7 8.4 *based on 3D echocardiography. Ea: arterial elastance, Ees: ventricular elastance (ESPVR), PEP/ET: pre-ejection period/ejection time, PRSW: Pre-load recruitable stroke work, PVA: pressure volume area, SCI: Starling contractility index, ZVA = valvulo-arterial impedance (mmHg/ml/m 2 ). Agreement between invasive and noninvasive Ees (ventricular elastance): As shown in Table 4 , the Chen method (considered the most reliable) did not differ from invasive ventricular elastance (Ees) compared with the one-sample T test and the Wilcoxon test. However, the correlation coefficient reached statistical significance, suggesting a proportion bias. The Bland‒Altman plot shows a clear systematic difference between the two methods. The fitted regression line suggests that for low values, Ees (Chen) overestimates the invasive Ees, and the opposite is true for higher values (Fig. 1 ). Table 4 The agreement between invasive and non-invasive indices Non-Invasive Index Mean difference to invasive index One sample T-test Wilcoxon’s test Pearson’s Correlation Correlation coefficient Limits of agreement Percentage error & Ees by Chen -0.359 0.511 0.722 0.670* -1.136* -3.7 to 3 21% Ees by Kelly 0.227 0.504 1 0.862* -0.174 -1.7 to 2.1 24% Ees by SBP 0.614 0.094 0.110 0.862* -0.072 -1.5 to 2.75 38% Ees by Tanoue -0.605 0.138 0.091 0.841* -0.309 -2.9 to 1.7 -4% Ees by Yamashita 0.076 0.846 0.790 0.808* -0.167 -2.2 to 2.4 23% Ees by Kim -0.146 0.859 0.477 0.002 -0.641 -5.2 to 4.9 47% Ees by Shishido 7.74 < 0.001 0.003 -0.050 1.191 -1.5 to 16.9 400% Ees by Bombardini 1.358 0.008 0.003 0.809* -0.641 -1.2 to 3.9 71% Components of The Above Formulas LV ESP by Kelly -14 0.153 0.182 0.160 -0.719 -72 to 40 -7% LV ESP as SBP -0.5 0.959 0.929 0.463 -0.050 -60 to 60 3% LV ESP by Bombardini 28 0.008 0.013 0.296 -0.604 -26 to 82 24% LV ESP as MAP -43 < 0.001 0.003 0.207 -0.707* -98 to 11.8 -29% LV ESP as corrected MAP -18 0.049 0.050 0.305 -0.462 -79 to 34.9 -10% End-diastolic volume £ -13 0.059 0.093 0.861* -0.078 -54 to 28 -11% End-systolic volume £ -10 0.273 0.350 0.477 0.135 -68 to 48 -11% Stroke volume £ -29 0.001 0.003 0.710* -0.506* -68 to 10 -33% Other Indices Ejection fraction (%) 7.4 0.111 0.091 0.335 0.042 -20 to 38 10% PRSW (mmHg) -32 0.037 0.010 0.742* -1.367* -118 to 54 -26% Arterial elastance 0.684 0.025 0.041 0.611* -0.272 -0.9 to 2.3 48% Ea by Yamashita 2.66 < 0.001 0.003 0.625* 0.282 0.7 to 4.6 150% Ea by Bombardini 1.621 < 0.001 0.003 0.632* 0.005 0.1 to 3.7 99% VA coupling* 0.200 0.176 0.131 -0.324 -0.585 -0.6 to 1 55% VA coupling $ 0.225 0.199 0.050 0.346 0.547* -0.8 to 2.1 40% ZVA 3.4 < 0.001 0.003 0.606* 0.250 0.264 to 6.5 110% *VA coupling = Ea/Ees = (0.9 × SBP/ SV) / Ees(Chen), $VA coupling = Ea/Ees = (0.9 × SBP/ SV) / (0.9 × SBP / ESV), £unit = ml, &Percentage error = (mean difference / invasive reference index) × 100, Ees = ventricular elastance (mmHg/ml), SBP = systolic blood pressure, MAP = mean arterial pressure, ESP = end-systolic pressure, PRSW = pre-load recruitable stroke work, Ea = arterial elastance (mmHg/ml), VA coupling = ventriculo-arterial coupling, ZVA = valvulo-arterial impedance (mmHg/ml/m2 Kelly’s method, which is by far the most widely used method in noninvasive studies, has a low mean difference (0.227) that does not reach statistical significance compared to zero when tested with a one-sample t test. It was also not different from the invasive Ees when compared using the Wilcoxon test. It had the highest correlation with the invasive Ees and the lowest correlation coefficient (-0.174), which did not reach statistical significance. The percentage error was also small (24%), with the narrowest 95% confidence interval of all methods. The Bland‒Altman plot and the fitted regression line showed a homogenous data distribution around the mean, excluding any systematic difference between the two methods (Fig. 2 ). Substituting the LV ESP with SBP with the formula Ees = (ESP/ESV) ≈ (SBP/ESV) yielded similar results to those of Kelly's method. The Tanoue and Yamashita methods had good agreement with the invasive methods but were less accurate than was Kelly's method, as shown in Table 4 (supplemental Fig. 1). The Kim method did not differ from the invasive Ees method but had a weak correlation with the invasive Ees method, and the percentage error was 47%. The Bland‒Altman plot shows more considerable variability than the other two methods (supplemental Fig. 2). The Shishido and Bombardini methods had weak agreement with the invasive Ees method. The method of Shishido had the greatest mean difference from that of invasive Ees. Both methods were significantly different compared to invasive Ees, and the difference reached statistical significance compared with the one-sample T test. The Bland‒Altman plots also show considerable variability with these methods (supplemental Figs. 3 and 4). The Bland‒Altman plot was significantly different when Shishido's method was used. The Shishido method seems to overestimate the true Ees at high values. The agreement among the components of the single-beat estimate formulas for Ees: Using Kelly's method, the difference in the LV ESP between the invasive and noninvasive measurements did not reach statistical significance (Table 4 ). However, the agreement between the two measures was poor, as suggested by the wide confidence intervals and Bland‒Altman plots (Supplemental Fig. 5). Systolic blood pressure (SBP) had comparable confidence intervals and a smaller mean difference, correlation coefficient and percentage error than invasive LV ESP (Table 4 ). The LV ESP by Bombardini, mean arterial pressure (MAP) and corrected MAP methods were significantly different from the invasive ESP, as shown in Table 4 , indicating poor agreement. The noninvasive measurements of the EDV and ESV by 3D echocardiography showed good agreement with the invasive measurements according to the one-sample T test and Wilcoxon test. The correlation coefficients were small and did not reach statistical significance, indicating the absence of proportional bias. The Bland‒Altman plots also showed a reasonably homogenous data distribution around the mean. The SV difference between the two methods showed poor agreement, as shown in Table 4 . Discussion: The quest to develop and validate an index that facilitates the surveillance of left ventricular function and the determination of the optimal time for intervention in patients with aortic stenosis is evident in the recently published literature 15 . Lee et al. studied subclinical ventricular deterioration in aortic stenosis (cardiac magnetic resonance study (CMR)) 16 . One of the study's rationales is the reduced sensitivity of the left ventricular ejection fraction (LVEF) as a marker of myocardial damage. LVEF has inherent limitations irrespective of the method and modality employed. On the other hand, the European Society of Cardiology (ESC) recommends early intervention in patients with asymptomatic severe aortic stenosis and an LV EF < 50% 17 . A decrease in LVEF is a late marker and is usually suggestive of advanced myocardial damage, which might be irreversible in some patients 16 . Pressure‒volume loop indices, namely, the LV elastance (Ees), are considered the gold standard for assessing LV function 3 . The invasive nature of such procedures limits their clinical utility. While several noninvasive methods for single-beat estimates of Ees have been developed and utilised in clinical practice, none have been validated for aortic stenosis. 12 The Achilles heel in the noninvasive assessment of Ees is twofold: the measurement of LV ESP (LV end-systolic pressure) and the measurement of V0 (the maximal LV volume at which pressure is still zero). Estimation of LV end-systolic pressure: One of the main challenges in aortic stenosis is the estimation of noninvasive LV ESP. 12 LV ESP in patients with no trans-aortic valve gradient, as developed by Kelly et al., is estimated as LV ESP = 0.9 × SBP, where SBP is the brachial systolic blood pressure measured by a mercury sphygmomanometer. 10,18 Kelly et al. studied ten patients (simultaneously invasive and noninvasive studies) in an attempt to calculate arterial elastance (Ea). They showed an accurate prediction of LV ESP using correlation; they did not gauge the agreement between the two methods. They also assessed another formula, LV ESP ≈ (SBP × 2 + DBP)/3, to estimate LV ESP. Both formulas had similar accuracies for predicting the LV ESP (r 2 = 0.97 and 0.96, respectively). 18 Researchers such as Chen et al. and Kim et al. accepted this assumption (LV ESP = 0.9 × SBP) and used it in their single-beat estimates of Ees (sb) . 7,8 Tanoue et al. substituted LV ESP with MAP and showed a strong correlation between invasive and noninvasive Ees in an animal model of 24 mongrel dogs. 6 However, correlation does not always mean that there is agreement between the two methods. Moreover, the substitution of LV ESP with MAP has not been validated in humans. Chemla et al. showed that LV ESP strongly correlates with SBP but is less strongly correlated with MAP. 19 As such, this particular formula (MAP/ESV) has not been widely used in noninvasive studies for measuring Ees. Bombardini et al., in their noninvasive studies, substituted LV ESP with systolic blood pressure (noninvasive Ees(sb) = SBP/ESV). 12,13 In aortic stenosis, the above assumptions fall short due to the presence of a gradient across the stenotic aortic valve (AV), i.e., the substitution of the LV ESP with a derivative of the brachial SBP would underestimate the LV ESP and, as a result, the Ees(sb). Yamashita et al. (coauthored by Tanoue) recognised this flaw among patients with aortic stenosis and substituted MAP with the "corrected MAP". 11 The corrected MAP incorporated the AV peak gradient as measured by TTE. 11 However, this assumption has not been validated in humans or in the context of AS. On the other hand, Bombardini et al. recommended the addition of the pressure drop to the brachial systolic blood pressure to estimate LV ESP. 12 In this study, we showed that invasive LV ESP had the best agreement with Kelly's method for LV ESP when substituted with SBP (LV ESP = 0.9 × SBP). As a substitute, SBP had the smallest mean difference and the closest correlation coefficient to zero. The other methods (MAP, corrected MAP and the Bombardini suggestion) had weak agreement with the LV ESP, as evidenced by one sample t test and the Wilcoxon test. Estimation of V0: To calculate the ESPVR, V0, which is the maximal volume at which the pressure is still zero (the ESPVR volume axis intercept), should be measured (estimated). It is considered constant and load independent. V0 cannot be directly measured in clinical practice, but it can be estimated once the slope of the ESPVR (Ees) is known. 7 Assuming that Ees is linear, two points from the regression line that represents Ees will be sufficient to estimate Ees (the slope) and, hence, V0. 20 To generate these two points, researchers in the past altered the LV loading conditions with inferior vena cava (IVC) occlusion and repeated the PV loop measurements. The two measures of Ees (at normal loading conditions and reduced loading conditions) constituted the two points required to estimate Ees (the slope of change in the ESPVR). However, the above assumption is not entirely correct because ESPVR is nonlinear under high contractile states and low loading conditions. 7 In large mammals, it is typically concave. 21 Considering that the ESPVR is nonlinear under many conditions, V0 becomes load dependent. Chen et al., in their study to develop a single-beat estimate of Ees, and Maurer et al., in an echocardiography-based noninvasive survey, reported a negative V0. 7,22 Nonetheless, the above assumptions have been generally accepted. The generated indices of contractility were still accurate, sensitive and reproducible. Chen et al. also wrote in their study: "importantly, the behaviour of the ESPVR in the physiologic loading range defines the relevant haemodynamic responses; so Ees assessed in this range is most important". 7 Single-beat estimates of Ees generate a single figure of Ees. Researchers such as Shishido et al., Chen et al., and Kim et al. have attempted to account for this fact. 5,7,8 The formulas used were based on time-varying elastance [E(t)] during the isovolumic contraction phase and ejection phase. 9 As such, the need for two Ees estimates at two different loading conditions has been negated. Shishido et al. then used the following formula to estimate V0: V0 (sb) = end systolic volume (Ves) – end systolic pressure (Pes)/Ees (sb) . 5 The simplified single-beat estimate of Ees, such as Ees (sb) = 0.9 × SBP/ESV, assumes V0 = zero. In this study, to simplify the research protocol to include otherwise lengthy and risky procedures, we measured the invasive ESPVR as Ees = ESP/ESV, i.e., we assumed V0 = zero. The agreement between invasive Ees and noninvasive Ees(sb): The single-beat estimate of Ees (Ees(sb)) formulas can be divided into two groups: the group that attempts to measure V0 and assumes that LV ESP = 0.9 × SBP, such as (Shishido, Chen and Kim), and the second group that assumes that V0 = zero but substitutes for LV ESP differently (Kelly, Tanoue, Yamashita and Bombardini). Chowdhury et al. studied the agreement between invasively measured Ees and noninvasive Ees(sb) among children. 3 Their research methodology mandated vena cava balloon occlusion. They compared four different methods of estimating Ees(sb): Chen, Kim, Shishido and Tanoue. Notably, they calculated Tanoue Ees as "Ees(sb4) = 0.9 × SBP/ESV". In their original publication, Tanoue et al. used the MAP as a substitute for the LV ESP, not 0.9 × SBP. They concluded the following: Chen's, Shishido's and Kim's methods overestimated the true Ees, and only the following formula, Ees(sb) = 0.9 × SBP/ESV, had good agreement with invasive Ees. Notably, patients with LV outflow obstruction, including patients with severe AS, were excluded. In 2014, Yotti et al. studied 27 patients with various loading conditions (eight patients with dilated cardiomyopathy, ten normal EF patients and nine patients with end-stage liver failure). Their research methodology also mandated vena cava balloon occlusion. They concluded that Chen's method (r2 = -0.05, p > 0.05) failed to correlate with invasive Ees, while Kelly's method (Ees = 0.9 × SBP/ESV) had only a poor correlation (r2 = 0.38, p < 0.05). 23 Kelly's method (Ees(sb) = 0.9 × SBP/ESV) and the SBP method (Ees(sb) = SBP/ESV) had the best agreement with the invasive Ees (allowing for the abovementioned assumptions). The methods that fell into group one had poor agreement with invasive Ees. Likewise, the methods that assumed V0 = zero (group two) but attempted to account for the gradient across the AV also showed poor agreement compared to Kelly's method. It seems that a simplified formula, such as Ees(sb) = 0.9 × SBP/ESV or Ees(sb) = SBP/ESV, has the best agreement with the invasively measured Ees. The above conclusion holds true regardless of the method used to estimate the invasive Ees (with or without load variation) or the studied clinical condition, including severe AS. The number of assumptions made to assemble these complex formulas is likely the reason behind these findings. As Chen et al. suggested, ultimately, the sensitivity and specificity of a specific index determine its clinical utility. All being equal, it is the simplest method that should be used. Conclusion: Measurement of the single-beat estimate of ventricular elastance (Ees(sb)) is possible in patients with severe aortic stenosis. Kelly's method (Ees(sb) = 0.9 × SBP/ESV) has the best agreement with the invasive measurement of left ventricular elastance (ESPVR). Systolic blood pressure, as measured by the brachial blood pressure cuff, has the best agreement with end-systolic pressure in severe aortic stenosis. Further studies are warranted to evaluate the efficacy of noninvasive Ees (end-systolic elastance) as a marker of left ventricular function in predicting clinical outcomes. Study limitations: In many prior invasive PV loop studies, protocols involved IVC occlusion to vary the load and estimate the Ees, a method we did not employ in this pilot study. It is worth noting that there is a trend among other laboratories conducting these studies to simplify invasive PVL studies. More importantly, every preceding study, irrespective of the approach used to estimate invasive Ees, indicated that Kelly's method (Ees = 0.9 × SBP/ESV) had the best agreement with invasive Ees. This aligns our findings well and bolsters their external validity. The discrepancy observed between invasive and noninvasive SV measurements underscores concerns regarding sample size and the placement of the conductance catheter within the left ventricle. To address this issue, our study meticulously optimised catheter positioning via fluoroscopy and real-time PV loop acquisition. We ensured measurement accuracy by collecting data after obtaining at least two high-quality PV loop segments. We did not factor in the medications administered during the TAVI procedures, including painkillers, sedatives, intravenous fluids, or, in a subset of patients, the peripheral use of vasoconstrictors such as metaraminol bitartrate. Finally, only a few patients experienced MR. Therefore, we were unable to noninvasively estimate the Starling contractility index (SCI) = dp/dt Max/EDV. Abbreviations: • AS • Aortic stenosis • EDV • End-diastolic volume • Ees • Left ventricular elastance • Ees(sb) • Single-beat estimate of left ventricular elastance • EF • Ejection fraction • ESPVR • End-systolic pressure‒volume relationship – also known as left ventricular elastance • ESV • End-systolic volume • LV • Left ventricle • LVEF • Left ventricular ejection fraction • LV ESP • Left ventricular end-systolic pressure • MAP • Mean arterial pressure • PVL • Pressure‒volume loop • TAVI • Transcatheter aortic valve implantation • TTE • Transthoracic echocardiography • V0 • The maximal LV volume at which pressure is still zero Declarations: Ethics approval and consent to participate: The study complied with the Declaration of Helsinki, and approvals of the original study design and subsequent amendments were all granted by the London Dulwich Research Ethics Committee with the reference number 13/LO/1542 IRAS project ID: 123464. All study participants provided written consent. The manuscript submission conforms to the guidelines set forth in the “Recommendations for the Conduct, Reporting, Editing and Publication of Scholarly Work in Medical Journals (ICMJE Recommendation)”. Consent for publication: Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported fully by King’s College Charity and in part by a National Institute for Health Research Biomedical Research Centre award to Guy's & St Thomas' Hospital and King's College London in partnership with King's College Hospital. Authors' contributions OA and ME contributed to the study conception, design, data acquisition and analysis, and interpretation of the data and drafted, revised and finalised the manuscript. MA, RC, JB and MM contributed to the study conception, study design, data acquisition and analysis and manuscript revision. BB and NK contributed to the data acquisition, analysis and revision of the manuscript. AS, RD and PM contributed to the conception and design of the study, interpretation of the data and revision of the manuscript. Acknowledgements Not applicable References: Lam W, Pontana F, Vassiliou V, Prasad S. Severe aortic stenosis with high valvulo-arterial impedance (Zva) has more adverse cardiac changes on cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2016;18. Pibarot P, Garcia D, Dumesnil JG. Energy loss index in aortic stenosis: from fluid mechanics concept to clinical application. Circulation [Internet]. 2013 [cited 2019 Dec 21];127:1101–4. http://www.ncbi.nlm.nih.gov/pubmed/23479666 . Chowdhury SM, Butts RJ, Taylor CL, Bandisode VM, Chessa KS, Hlavacek AM, Shirali GS, Baker GH. Validation of Noninvasive Measures of Left Ventricular Mechanics in Children: A Simultaneous Echocardiographic and Conductance Catheterisation Study. J Am Soc Echocardiogr. 2016;29:640–7. Burkhoff D. Chasing the Elusive Pressure–Volume Relationships⁎⁎Editorials published in JACC: Cardiovascular Imaging reflect the views of the authors and do not necessarily represent the views of JACC: Cardiovascular Imaging or the American College of Cardiology. JACC Cardiovasc Imaging. 2009;2:1282–4. Shishido T, Hayashi K, Shigemi K, Sato T, Sugimachi M, Sunagawa K. Single-beat estimation of end-systolic elastance using bilinearly approximated time-varying elastance curve. Circulation [Internet]. 2000 [cited 2019 Dec 21];102:1983–9. http://www.ncbi.nlm.nih.gov/pubmed/11034949 . Tanoue Y, Sese A, Ueno Y, Joh K, Hijii T. Bidirectional Glenn Procedure Improves the Mechanical Efficiency of a Total Cavopulmonary Connection in High-Risk Fontan Candidates. Circulation [Internet]. 2001 [cited 2019 Dec 21];103:2176–2180. https://www.ahajournals.org/doi/ 10.1161/01.CIR.103.17.2176 . Chen-Huan C, Barry F, Erez N, Carlos ER, Kuan-Rau C, Phillip YD, Miho K, David AK. Noninvasive Single-Beat Determination of Left Ventricular End-Systolic Elastance in Humans. J Am Coll Cardiol. 2001;38. Kim YJ, Jones M, Greenberg NL, Popovic ZB, Sitges M, Bauer F, Thomas JD, Shiota T. Evaluation of Left Ventricular Contractile Function Using Noninvasively Determined Single-beat End-systolic Elastance in Mitral Regurgitation: Experimental Validation and Clinical Application. J Am Soc Echocardiogr. 2007;20:1086–92. Senzaki H, Chen CH, Kass DA. Single-beat estimation of end-systolic pressure–volume relation in humans: A new method with the potential for noninvasive application. Circulation. 1996;94:2497–506. Kelly R, Ting C, Yang T, Liu C, Maughan W, Chang M, Kass D, Kelly RP, Ting C-T, Yang T-M, Liu C-P, Lowell Maughan W, Chang M-S, Kass DA. Effective Arterial Elastance as Index of Arterial Vascular Load in Humans. 2010; http://www.lww.com/reprints . Yamashita Y, Tanoue Y, Sonoda H, Ushijima T, Kimura S, Oishi Y, Tatewaki H, Hiasa K, Arita T, Shiose A. Comparison of cardiac energetics after transcatheter and surgical aortic valve replacements. Interact Cardiovasc Thorac Surg. 2019;28:587–93. Bombardini T, Zoppè M, Ciampi Q, Cortigiani L, Agricola E, Salvadori S, Loni T, Pratali L, Picano E. Myocardial contractility in the stress echo lab: From pathophysiological toy to clinical tool. Cardiovasc Ultrasound. 2013;11. Bombardini T, Gemignani V, Bianchini E, Venneri L, Petersen C, Pasanisi E, Pratali L, Pianelli M, Faita F, Giannoni M, Picano E. Cardiac reflections and natural vibrations: Force-frequency relation recording system in the stress echo lab. Cardiovasc Ultrasound. 2007;5:1–17. Giavarina D. Understanding Bland Altman analysis. Biochem Med. 2015;25:141–51. Hachicha Z, Dumesnil JG, Pibarot P. Usefulness of the Valvuloarterial Impedance to Predict Adverse Outcome in Asymptomatic Aortic Stenosis. J Am Coll Cardiol [Internet]. 2009 [cited 2019 Sep 25];54:1003–1011. https://linkinghub.elsevier.com/retrieve/pii/S0735109709020592 . Lee SP, Park SJ, Kim YJ, Chang SA, Park EA, Kim HK, Lee W, Lee SC, Park SW, Sohn DW, Choe YH. Early detection of subclinical ventricular deterioration in aortic stenosis with cardiovascular magnetic resonance and echocardiography. J Cardiovasc Magn Reson. 2013;15. What is new for general cardiologists in the. 2017 ESC Guidelines on valvular hea [Internet]. [cited 2019 Dec 21]; https://www.escardio.org/Journals/E-Journal-of-Cardiology-Practice/Volume-15/What-is-new-for-general-cardiologists-in-the-2017-ESC-Guidelines-on-valvular-heart-disease . Kelly RP, Ting CT, Yang TM, Liu CP, Maughan WL, Chang MS, Kass DA. Effective arterial elastance as index of arterial vascular load in humans. Circulation. 1992;86:513–21. Chemla D, Antony I, Lecarpentier Y, Nitenberg A. Contribution of systemic vascular resistance and total arterial compliance to effective arterial elastance in humans. Am J Physiol - Hear Circ Physiol. 2003;285. Burkhoff D, Mirsky I, Suga H. Assessment of systolic and diastolic ventricular properties via pressure–volume analysis: a guide for clinical, translational, and basic researchers. Am J Physiol Circ Physiol. 2005;289:H501–12. Foëx P, Leone BJ. Pressure–volume loops: A dynamic approach to the assessment of ventricular function. J Cardiothorac Vasc Anesth. 1994;8:84–96. Maurer MS, King DL, El-Khoury Rumbarger L, Packer M, Burkhoff D. Left heart failure with a normal ejection fraction: Identification of different pathophysiologic mechanisms. J Card Fail. 2005;11:177–87. Yotti R, Bermejo J, Benito Y, Sanz-Ruiz R, Ripoll C, Martínez-Legazpi P, Del Villar CP, Elízaga J, González-Mansilla A, Barrio A, Bañares R, Fernández-Avilés F. Validation of noninvasive indices of global systolic function in patients with normal and abnormal loading conditions a simultaneous echocardiography pressure–volume catheterisation study. Circ Cardiovasc Imaging. 2014;7:164–72. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4200318","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287814648,"identity":"90cdc94e-86bd-4df1-829c-0f261f64de21","order_by":0,"name":"Omar Aldalati","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABG0lEQVRIie2RMUsDMRTHXwjcLWm7SQ6p/QopWRwUv8oFoV1uKS4dSgkI6WbXk0r9ChVBHAsP2iXiB7jlimDXFkE6VXOz10M3h/yGF8LL7+UfAuDx/F9OiQ7dEvcB6sWeaFdYpcKJpu5cbAGCvynE/EJpHOH7Bga8Ob6m63w1xVYQjnLaex6CsPNSJZp0ZAoLLlMM2lo9YdswK+itRRAvulQRWSxdGK40QqFkxPAEaM3MQbyWBxNZ9wNgz9U9hlut7rIL01rnThlWKIkEN1nNkLlbdKYMB+EUejBYNEmuQN1w+YCsl8aLr0vDEoE1gyw68PzGcfcRNp9nzelyNNvuBp3zcbhcvblgJ3Ublycr+NEqxld/pMfj8Xgq+QbU5F5TJpujOgAAAABJRU5ErkJggg==","orcid":"","institution":"University Hospital of Wales","correspondingAuthor":true,"prefix":"","firstName":"Omar","middleName":"","lastName":"Aldalati","suffix":""},{"id":287814649,"identity":"85a5c801-588e-4003-a604-ad301a28a247","order_by":1,"name":"Mehdi Eskandari","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Eskandari","suffix":""},{"id":287814650,"identity":"d55eecec-522a-443f-9363-8648fdb40ecd","order_by":2,"name":"Montasir H Ali","email":"","orcid":"","institution":"University Hospital of Wales","correspondingAuthor":false,"prefix":"","firstName":"Montasir","middleName":"H","lastName":"Ali","suffix":""},{"id":287814651,"identity":"ec7b47b1-9218-4cc4-be4d-8f2278c0bd31","order_by":3,"name":"Rita Cabaco","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rita","middleName":"","lastName":"Cabaco","suffix":""},{"id":287814652,"identity":"f1ef31c0-96cd-4029-bb6a-aafeb1020146","order_by":4,"name":"Jonathan Byrne","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Byrne","suffix":""},{"id":287814653,"identity":"4f4d7c70-ca77-44e1-895c-ab70717c9d74","order_by":5,"name":"Mark Monaghan","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Monaghan","suffix":""},{"id":287814654,"identity":"295aec11-6aa2-4fd5-93fb-b279e75ccee6","order_by":6,"name":"Bobit Lukban","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bobit","middleName":"","lastName":"Lukban","suffix":""},{"id":287814655,"identity":"8d562086-f3d1-4c98-8e98-bcfe6cbe1421","order_by":7,"name":"Nicola Kennedy","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nicola","middleName":"","lastName":"Kennedy","suffix":""},{"id":287814656,"identity":"439a3048-e32b-4080-a3da-6eb3eacfc2b6","order_by":8,"name":"Ajay Shah","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ajay","middleName":"","lastName":"Shah","suffix":""},{"id":287814657,"identity":"47105a10-01d3-45ea-807d-61634e2ad869","order_by":9,"name":"Rafal Dworakowski","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rafal","middleName":"","lastName":"Dworakowski","suffix":""},{"id":287814658,"identity":"553d50e9-55d3-4d67-884b-6c710e7a27c7","order_by":10,"name":"Philip MacCarthy","email":"","orcid":"","institution":"King’s College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"","lastName":"MacCarthy","suffix":""}],"badges":[],"createdAt":"2024-04-01 11:31:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4200318/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4200318/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54393942,"identity":"440bc132-0acd-48b2-bf52-3e67b940bd29","added_by":"auto","created_at":"2024-04-09 21:09:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29161,"visible":true,"origin":"","legend":"\u003cp\u003eBland‒Altmanplot ofthe agreement between Chen Ees (sb) and invasive Ees measurements.\u003c/p\u003e\n\u003cp\u003eThe plot shows a clear systematic difference between the two methods. The fitted regression line suggests that for low values, Ees(Chen) overestimates the invasive Ees, and the opposite is true for higher values.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4200318/v1/0256cf7e447f9bb43317e320.png"},{"id":54393943,"identity":"cec41c18-9ad0-4797-935e-bdada9f7f146","added_by":"auto","created_at":"2024-04-09 21:09:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":29556,"visible":true,"origin":"","legend":"\u003cp\u003eBland‒Altmanplot showingthe agreement between Kelly Ees (sb) and invasive Ees measurements.\u003c/p\u003e\n\u003cp\u003eThe plot and the fitted regression line show a homogenous data distribution around the mean, excluding any systematic difference between the two methods.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4200318/v1/77bc69ca13a506cd8cb35e71.png"},{"id":58221757,"identity":"ce9f8259-db46-4d4d-aedc-d6df917c5752","added_by":"auto","created_at":"2024-06-12 16:37:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1292741,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4200318/v1/270a6e32-a50b-4ea7-a7cb-90797b6e4a4c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis","fulltext":[{"header":"Background:","content":"\u003cp\u003eThere is growing interest in early intervention for severe aortic stenosis (AS). The left ventricular (LV) ejection fraction (EF) has been used for the assessment of LV function. The assessment of LV EF, regardless of the modality used, has inherent limitations. Advanced tools for assessing LV mechanics, such as myocardial deformation, have been developed for the early detection of subclinical LV dysfunction.\u003c/p\u003e \u003cp\u003ePressure‒volume loop (PVL) indices, mainly left ventricular elastance (Ees; also known as the end-systolic pressure‒volume relationship (ESPVR)), are considered the gold standard measures of LV systolic function\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInvasive PV loop measurement requires left ventricular conductance catheter placement, inferior vena cava (IVC) balloon occlusion for load variation, and a pulmonary artery catheter for calibration. The invasive nature of such a procedure renders it a research tool rather than a day-to-day investigation\u003csup\u003e4\u003c/sup\u003e. As a result, several single-beat noninvasive echocardiography-based methods have been developed and validated for measuring Ees in clinical practice; the majority of these methods were derived from animal-based research\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo the authors\u0026rsquo; knowledge, none of the validated single-beat noninvasive methods have included patients with severe AS. In this pilot study, we sought to assess the agreement between invasive and noninvasive PVL indices in severe AS patients. We also sought to compare the methods of single-beat estimates of Ees and the agreement between the other invasive and noninvasive indices of contractility.\u003c/p\u003e"},{"header":"Methods:","content":"\u003cp\u003eWe recruited eleven (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) consecutive patients for invasive PV loop studies during transcatheter aortic valve implantation (TAVI) procedures. The patients had symptomatic severe AS and were deemed by the heart team appropriate and in need of TAVI. The recruited patients had to meet the following inclusion criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIn sinus rhythm\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSuitability for transfemoral access\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIn stable clinical conditions\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAbsence of coexisting severe valvular heart disease\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNormal right ventricular function\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAble to give informed consent\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eInvasive pressure‒volume loop studies:\u003c/p\u003e \u003cp\u003eThe TAVI procedures were performed as per routine clinical care. After crossing the aortic valve, a 4 Fr or 7 Fr high-fidelity conductance catheter (CD Leycom, Netherlands) was placed in the LV, either over the guidewire or with the help of a destination catheter. The conductance catheter was then connected to a dual-field conductance processor (Inca, CD Leycom, Netherlands). Under fluoroscopic guidance, the conductance catheter position was optimised along the long LV axis with the help of live PV loop recording.\u003c/p\u003e \u003cp\u003eFor calibration purposes, a pulmonary artery catheter (Swan\u0026ndash;Ganz catheter, 6 Fr, Edwards Lifesciences Corp., Irvine, USA) was placed in the pulmonary artery under fluoroscopy guidance from the right median cubital vein. Calibration was performed using the parallel conductance method. Cardiac output was measured first with the thermodilution technique (SV calibration; repeated three times), followed by the injection of 10 ml of 10% saline into the pulmonary artery (EFcal; repeated twice).\u003c/p\u003e \u003cp\u003eAfter calibration, we waited for several minutes to ensure cardiovascular stability. The conductance catheter position was reassessed by fluoroscopy once again before acquiring live PV loop data.\u003c/p\u003e \u003cp\u003eThree-dimensional transthoracic echocardiography:\u003c/p\u003e \u003cp\u003eAll recruited patients underwent two- and three-dimensional transthoracic echocardiography (2D and 3D TTE) approximately 90 minutes before TAVI (Epic CVx, Best, Netherland). 3D LV end-systolic and end-diastolic volumes (Qlab version 12, Philips, Best, Netherlands), preejection period (PEP), ejection time (ET) and total systolic time (TST) were calculated. Brachial blood pressure was recorded at the time of the 3D TTE study for all patients.\u003c/p\u003e \u003cp\u003eThe following formula was used to calculate the noninvasive Ees:\u003c/p\u003e \u003cp\u003eThe acquired TTE data were used to calculate the noninvasive Ees\u003csub\u003e(sb)\u003c/sub\u003e using the following formulas:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormula Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChen's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e7\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Chen)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;DBP \u0026ndash; (ENDest \u0026times; SBP \u0026times; 0.9)/(SV \u0026times; ENDest)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKelly's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e10\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Kelly)\u003c/sub\u003e = (0.9 \u0026times; SBP)/ESV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTanoue's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Tanoue)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;MAP/ESV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYamashita's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e11\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Yamashita)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;corrected MAP/ESV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKim's method\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Kim)\u003c/sub\u003e = (DBP \u0026ndash; 0.9 \u0026times; SBP\u0026thinsp;+\u0026thinsp;α \u0026times; (DBP \u0026ndash; EDP) X (ET/PEP))/SV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eShishido's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e5\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Shishido)\u003c/sub\u003e = (DBP + (DBP \u0026ndash; EDP)/PEP \u0026times; ET\u0026thinsp;\u0026times;\u0026thinsp;α \u0026ndash; 0.9 \u0026times; SBP)/SV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBombardini's method\u003c/em\u003e\u003csup\u003e\u003cem\u003e12\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(Bombardini)\u003c/sub\u003e = (0.9 \u0026times; SBP)\u0026thinsp;+\u0026thinsp;Mg/ESV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSystolic blood pressure method\u003c/em\u003e\u003csup\u003e\u003cem\u003e13\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEes\u003csub\u003e(SBP)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;SBP/ESV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEes\u0026thinsp;=\u0026thinsp;ventricular elastance, DBP\u0026thinsp;=\u0026thinsp;diastolic blood pressure, SBP\u0026thinsp;=\u0026thinsp;systolic blood pressure, ENDest\u0026thinsp;=\u0026thinsp;noninvasively estimated normalised elastance at the onset of ejection, SV\u0026thinsp;=\u0026thinsp;stroke volume, ESV\u0026thinsp;=\u0026thinsp;end systolic volume, MAP\u0026thinsp;=\u0026thinsp;mean arterial pressure, EDP\u0026thinsp;=\u0026thinsp;end diastolic pressure, ET\u0026thinsp;=\u0026thinsp;ejection time, PEP\u0026thinsp;=\u0026thinsp;preejection period, Mg\u0026thinsp;=\u0026thinsp;mean gradient (measured by transthoracic echocardiogram).\u003c/p\u003e \u003cp\u003eThe sonographers and clinicians reporting the TTE were blinded to the invasive PV loop study results. Similarly, the cardiac physiologist and the clinician reporting the PV loop studies were blinded to the results of the 3D TTE studies.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003e The agreement between the invasive and noninvasive indices was tested using Bland‒Altman plots, linear regression, Wilcoxon's test, Pearson's correlation and the percentage error between the corresponding indices. Statistical analysis was performed with SPSS statistical software (IBM SPSS Statistics for Windows, Version 22.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results:","content":"\u003cp\u003eEleven consecutive patients (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e) were recruited for this study. The mean age was 84\u0026thinsp;\u0026plusmn;\u0026thinsp;8 years; the majority were females (73%). All recruited patients had severe AS with a mean aortic valve area (AVA) of 0.72 cm2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2, a mean gradient of 42\u0026thinsp;\u0026plusmn;\u0026thinsp;16 mmHg and a dimensionless index of 0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06, as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The measured indices from the invasive PVL studies and TTE are summarised in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, respectively.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAS patients (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index (kg/m2\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody surface area (m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u0026thinsp;\u003cstrong\u003e\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNYHA class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic blood pressure (mmHg\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiastolic blood pressure (mmHg\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever smoked\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeripheral vascular disease (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious myocardial infarction (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious cardiac surgery (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (\u0026micro;mol/l\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHaemoglobin (mmol/l\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQRS duration (ms\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral anaesthesia (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchocardiography Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEjection fraction (% \u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRWMA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean gradient (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak gradient (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAortic valve area (cm2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDimensionless index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eAS: aortic stenosis, RWMA: regional wall motion abnormality, SD: standard deviation, NYHA: New York Heart Association\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePressure-volume loop invasive measures\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower Bound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper Bound\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart rate (bpm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEjection fraction (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiac output (L/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke volume (ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke work (ml.mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8155\u0026thinsp;\u0026plusmn;\u0026thinsp;2895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7766 (4089)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiastolic Indices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-diastolic volume (ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110\u0026thinsp;\u0026plusmn;\u0026thinsp;41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 (78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-diastolic pressure (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.8 (\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edp/dt minimum (mmHg/s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1194\u0026thinsp;\u0026plusmn;\u0026thinsp;469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1419 (532)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTAU (ms)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEDPVR (mmHg/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1008\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1014 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic Indices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-systolic volume (ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-systolic pressure (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138\u0026thinsp;\u0026plusmn;\u0026thinsp;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e144 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edp/dt maximum (mmHg/s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1277\u0026thinsp;\u0026plusmn;\u0026thinsp;362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1272 (537)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1520\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eESPVR (mmHg/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.54 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCI (mmHg/ml/s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.5 (\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRSW (mmHG)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.9 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePVA (mmHg.ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12152\u0026thinsp;\u0026plusmn;\u0026thinsp;3543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12061 (6545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14532\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eArterial elastance (mmHg/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.74 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVA coupling (Ea/ESPVR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZVA invasive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003ebpm: beat per minute, dp/dt minimum: the minimum rate of change of ventricular pressure, EDPVR: End-diastolic pressure volume relationship, ESPVR: End-systolic pressure volume relationship, PRSW: Pre-load recruitable stroke work, PVA: pressure volume area, SCI: Starling contractility index, TAU: left ventricular time constant (diastolic index), VA Coupling: ventriculo-arterial coupling, ZVA\u0026thinsp;=\u0026thinsp;valvulo-arterial impedance (mmHg/ml/m2).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe required non-invasive measures to calculate Ees single beat estimates, the calculated Ees and the other non-invasive measures of contractility\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower Bound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper Bound\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-diastolic volume (ml)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u0026thinsp;\u0026plusmn;\u0026thinsp;38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-systolic volume (ml)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke volume (ml)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEjection fraction (%)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-ejection period (ms)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEjection time (ms)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e326\u0026thinsp;\u0026plusmn;\u0026thinsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e310 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal systolic time (ms)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e397\u0026thinsp;\u0026plusmn;\u0026thinsp;46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e390 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e428\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePEP/ET (ratio)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalculated Non-Invasive Ees\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Chen et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Kim et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Shishido et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.9 (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Tanuoue et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes as suggested by Bombardini et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 (\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Calculated Non-Invasive Indices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eArterial elastance (Ea)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEa as suggested by Bombardini et al\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRSW (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZVA non-invasive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e*based on 3D echocardiography.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eEa: arterial elastance, Ees: ventricular elastance (ESPVR), PEP/ET: pre-ejection period/ejection time, PRSW: Pre-load recruitable stroke work, PVA: pressure volume area, SCI: Starling contractility index, ZVA\u0026thinsp;=\u0026thinsp;valvulo-arterial impedance (mmHg/ml/m\u003csup\u003e2\u003c/sup\u003e).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAgreement between invasive and noninvasive Ees (ventricular elastance):\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, the Chen method (considered the most reliable) did not differ from invasive ventricular elastance (Ees) compared with the one-sample T test and the Wilcoxon test. However, the correlation coefficient reached statistical significance, suggesting a proportion bias. The Bland‒Altman plot shows a clear systematic difference between the two methods. The fitted regression line suggests that for low values, Ees\u003csub\u003e(Chen)\u003c/sub\u003e overestimates the invasive Ees, and the opposite is true for higher values (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe agreement between invasive and non-invasive indices\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-Invasive\u003c/p\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean difference to\u003c/p\u003e\n \u003cp\u003einvasive index\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOne sample T-test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWilcoxon\u0026rsquo;s test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePearson\u0026rsquo;s\u003c/p\u003e\n \u003cp\u003eCorrelation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCorrelation\u003c/p\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLimits of agreement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage error\u003csup\u003e\u0026amp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Chen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.670*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.136*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.7 to 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Kelly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.862*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.7 to 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by SBP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.862*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.5 to 2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Tanoue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.841*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.9 to 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Yamashita\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.808*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.2 to 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Kim\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.2 to 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Shishido\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.5 to 16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEes by Bombardini\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.809*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.2 to 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eComponents of The Above Formulas\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV ESP by Kelly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-72 to 40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV ESP as SBP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-60 to 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV ESP by Bombardini\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-26 to 82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV ESP as MAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.707*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-98 to 11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV ESP as corrected MAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-79 to 34.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-diastolic volume\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026pound;\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.861*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-54 to 28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnd-systolic volume\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026pound;\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-68 to 48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke volume\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026pound;\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.710*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.506*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-68 to 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-33%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Indices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEjection fraction (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-20 to 38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRSW (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.742*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.367*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-118 to 54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-26%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eArterial elastance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.611*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.9 to 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEa by Yamashita\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.625*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7 to 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEa by Bombardini\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.632*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1 to 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVA coupling*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.6 to 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVA coupling\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e$\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.547*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.8 to 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZVA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.606*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.264 to 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e*VA coupling\u0026thinsp;=\u0026thinsp;Ea/Ees = (0.9 \u0026times; SBP/ SV) / Ees(Chen), $VA coupling\u0026thinsp;=\u0026thinsp;Ea/Ees = (0.9 \u0026times; SBP/ SV) / (0.9 \u0026times; SBP / ESV), \u0026pound;unit\u0026thinsp;=\u0026thinsp;ml, \u0026amp;Percentage error = (mean difference / invasive reference index) \u0026times; 100, Ees\u0026thinsp;=\u0026thinsp;ventricular elastance (mmHg/ml), SBP\u0026thinsp;=\u0026thinsp;systolic blood pressure, MAP\u0026thinsp;=\u0026thinsp;mean arterial pressure, ESP\u0026thinsp;=\u0026thinsp;end-systolic pressure, PRSW\u0026thinsp;=\u0026thinsp;pre-load recruitable stroke work, Ea\u0026thinsp;=\u0026thinsp;arterial elastance (mmHg/ml), VA coupling\u0026thinsp;=\u0026thinsp;ventriculo-arterial coupling, ZVA\u0026thinsp;=\u0026thinsp;valvulo-arterial impedance (mmHg/ml/m2\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eKelly\u0026rsquo;s method, which is by far the most widely used method in noninvasive studies, has a low mean difference (0.227) that does not reach statistical significance compared to zero when tested with a one-sample t test. It was also not different from the invasive Ees when compared using the Wilcoxon test. It had the highest correlation with the invasive Ees and the lowest correlation coefficient (-0.174), which did not reach statistical significance. The percentage error was also small (24%), with the narrowest 95% confidence interval of all methods. The Bland‒Altman plot and the fitted regression line showed a homogenous data distribution around the mean, excluding any systematic difference between the two methods (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Substituting the LV ESP with SBP with the formula Ees = (ESP/ESV) \u0026asymp; (SBP/ESV) yielded similar results to those of Kelly\u0026apos;s method.\u003c/p\u003e\n\u003cp\u003eThe Tanoue and Yamashita methods had good agreement with the invasive methods but were less accurate than was Kelly\u0026apos;s method, as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e (supplemental Fig. 1). The Kim method did not differ from the invasive Ees method but had a weak correlation with the invasive Ees method, and the percentage error was 47%. The Bland‒Altman plot shows more considerable variability than the other two methods (supplemental Fig. 2).\u003c/p\u003e\n\u003cp\u003eThe Shishido and Bombardini methods had weak agreement with the invasive Ees method. The method of Shishido had the greatest mean difference from that of invasive Ees. Both methods were significantly different compared to invasive Ees, and the difference reached statistical significance compared with the one-sample T test. The Bland‒Altman plots also show considerable variability with these methods (supplemental Figs.\u0026nbsp;3 and 4). The Bland‒Altman plot was significantly different when Shishido\u0026apos;s method was used. The Shishido method seems to overestimate the true Ees at high values.\u003c/p\u003e\n\u003cp\u003eThe agreement among the components of the single-beat estimate formulas for Ees:\u003c/p\u003e\n\u003cp\u003eUsing Kelly\u0026apos;s method, the difference in the LV ESP between the invasive and noninvasive measurements did not reach statistical significance (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). However, the agreement between the two measures was poor, as suggested by the wide confidence intervals and Bland‒Altman plots (Supplemental Fig. 5). Systolic blood pressure (SBP) had comparable confidence intervals and a smaller mean difference, correlation coefficient and percentage error than invasive LV ESP (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe LV ESP by Bombardini, mean arterial pressure (MAP) and corrected MAP methods were significantly different from the invasive ESP, as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, indicating poor agreement.\u003c/p\u003e\n\u003cp\u003eThe noninvasive measurements of the EDV and ESV by 3D echocardiography showed good agreement with the invasive measurements according to the one-sample T test and Wilcoxon test. The correlation coefficients were small and did not reach statistical significance, indicating the absence of proportional bias. The Bland‒Altman plots also showed a reasonably homogenous data distribution around the mean. The SV difference between the two methods showed poor agreement, as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion:","content":"\u003cp\u003eThe quest to develop and validate an index that facilitates the surveillance of left ventricular function and the determination of the optimal time for intervention in patients with aortic stenosis is evident in the recently published literature\u003csup\u003e15\u003c/sup\u003e. Lee et al. studied subclinical ventricular deterioration in aortic stenosis (cardiac magnetic resonance study (CMR))\u003csup\u003e16\u003c/sup\u003e. One of the study's rationales is the reduced sensitivity of the left ventricular ejection fraction (LVEF) as a marker of myocardial damage. LVEF has inherent limitations irrespective of the method and modality employed. On the other hand, the European Society of Cardiology (ESC) recommends early intervention in patients with asymptomatic severe aortic stenosis and an LV EF\u0026thinsp;\u0026lt;\u0026thinsp;50%\u003csup\u003e17\u003c/sup\u003e. A decrease in LVEF is a late marker and is usually suggestive of advanced myocardial damage, which might be irreversible in some patients\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePressure‒volume loop indices, namely, the LV elastance (Ees), are considered the gold standard for assessing LV function\u003csup\u003e3\u003c/sup\u003e. The invasive nature of such procedures limits their clinical utility. While several noninvasive methods for single-beat estimates of Ees have been developed and utilised in clinical practice, none have been validated for aortic stenosis.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Achilles heel in the noninvasive assessment of Ees is twofold: the measurement of LV ESP (LV end-systolic pressure) and the measurement of V0 (the maximal LV volume at which pressure is still zero).\u003c/p\u003e \u003cp\u003eEstimation of LV end-systolic pressure:\u003c/p\u003e \u003cp\u003eOne of the main challenges in aortic stenosis is the estimation of noninvasive LV ESP.\u003csup\u003e12\u003c/sup\u003e LV ESP in patients with no trans-aortic valve gradient, as developed by Kelly et al., is estimated as LV ESP\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP, where SBP is the brachial systolic blood pressure measured by a mercury sphygmomanometer.\u003csup\u003e10,18\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eKelly et al. studied ten patients (simultaneously invasive and noninvasive studies) in an attempt to calculate arterial elastance (Ea). They showed an accurate prediction of LV ESP using correlation; they did not gauge the agreement between the two methods. They also assessed another formula, LV ESP \u0026asymp; (SBP \u0026times; 2\u0026thinsp;+\u0026thinsp;DBP)/3, to estimate LV ESP. Both formulas had similar accuracies for predicting the LV ESP (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.97 and 0.96, respectively).\u003csup\u003e18\u003c/sup\u003e Researchers such as Chen et al. and Kim et al. accepted this assumption (LV ESP\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP) and used it in their single-beat estimates of Ees\u003csub\u003e(sb)\u003c/sub\u003e.\u003csup\u003e7,8\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTanoue et al. substituted LV ESP with MAP and showed a strong correlation between invasive and noninvasive Ees in an animal model of 24 mongrel dogs.\u003csup\u003e6\u003c/sup\u003e However, correlation does not always mean that there is agreement between the two methods. Moreover, the substitution of LV ESP with MAP has not been validated in humans. Chemla et al. showed that LV ESP strongly correlates with SBP but is less strongly correlated with MAP.\u003csup\u003e19\u003c/sup\u003e As such, this particular formula (MAP/ESV) has not been widely used in noninvasive studies for measuring Ees. Bombardini et al., in their noninvasive studies, substituted LV ESP with systolic blood pressure (noninvasive Ees(sb)\u0026thinsp;=\u0026thinsp;SBP/ESV).\u003csup\u003e12,13\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn aortic stenosis, the above assumptions fall short due to the presence of a gradient across the stenotic aortic valve (AV), i.e., the substitution of the LV ESP with a derivative of the brachial SBP would underestimate the LV ESP and, as a result, the Ees(sb). Yamashita et al. (coauthored by Tanoue) recognised this flaw among patients with aortic stenosis and substituted MAP with the \"corrected MAP\".\u003csup\u003e11\u003c/sup\u003e The corrected MAP incorporated the AV peak gradient as measured by TTE.\u003csup\u003e11\u003c/sup\u003e However, this assumption has not been validated in humans or in the context of AS. On the other hand, Bombardini et al. recommended the addition of the pressure drop to the brachial systolic blood pressure to estimate LV ESP.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study, we showed that invasive LV ESP had the best agreement with Kelly's method for LV ESP when substituted with SBP (LV ESP\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP). As a substitute, SBP had the smallest mean difference and the closest correlation coefficient to zero. The other methods (MAP, corrected MAP and the Bombardini suggestion) had weak agreement with the LV ESP, as evidenced by one sample t test and the Wilcoxon test.\u003c/p\u003e \u003cp\u003eEstimation of V0:\u003c/p\u003e \u003cp\u003eTo calculate the ESPVR, V0, which is the maximal volume at which the pressure is still zero (the ESPVR volume axis intercept), should be measured (estimated). It is considered constant and load independent. V0 cannot be directly measured in clinical practice, but it can be estimated once the slope of the ESPVR (Ees) is known.\u003csup\u003e7\u003c/sup\u003e Assuming that Ees is linear, two points from the regression line that represents Ees will be sufficient to estimate Ees (the slope) and, hence, V0.\u003csup\u003e20\u003c/sup\u003e To generate these two points, researchers in the past altered the LV loading conditions with inferior vena cava (IVC) occlusion and repeated the PV loop measurements. The two measures of Ees (at normal loading conditions and reduced loading conditions) constituted the two points required to estimate Ees (the slope of change in the ESPVR). However, the above assumption is not entirely correct because ESPVR is nonlinear under high contractile states and low loading conditions.\u003csup\u003e7\u003c/sup\u003e In large mammals, it is typically concave.\u003csup\u003e21\u003c/sup\u003e Considering that the ESPVR is nonlinear under many conditions, V0 becomes load dependent. Chen et al., in their study to develop a single-beat estimate of Ees, and Maurer et al., in an echocardiography-based noninvasive survey, reported a negative V0.\u003csup\u003e7,22\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNonetheless, the above assumptions have been generally accepted. The generated indices of contractility were still accurate, sensitive and reproducible. Chen et al. also wrote in their study: \"importantly, the behaviour of the ESPVR in the physiologic loading range defines the relevant haemodynamic responses; so Ees assessed in this range is most important\".\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSingle-beat estimates of Ees generate a single figure of Ees. Researchers such as Shishido et al., Chen et al., and Kim et al. have attempted to account for this fact.\u003csup\u003e5,7,8\u003c/sup\u003e The formulas used were based on time-varying elastance [E(t)] during the isovolumic contraction phase and ejection phase.\u003csup\u003e9\u003c/sup\u003e As such, the need for two Ees estimates at two different loading conditions has been negated. Shishido et al. then used the following formula to estimate V0: V0\u003csub\u003e(sb)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;end systolic volume (Ves) \u0026ndash; end systolic pressure (Pes)/Ees\u003csub\u003e(sb)\u003c/sub\u003e.\u003csup\u003e5\u003c/sup\u003e The simplified single-beat estimate of Ees, such as Ees\u003csub\u003e(sb)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV, assumes V0\u0026thinsp;=\u0026thinsp;zero. In this study, to simplify the research protocol to include otherwise lengthy and risky procedures, we measured the invasive ESPVR as Ees\u0026thinsp;=\u0026thinsp;ESP/ESV, i.e., we assumed V0\u0026thinsp;=\u0026thinsp;zero.\u003c/p\u003e \u003cp\u003eThe agreement between invasive Ees and noninvasive Ees(sb):\u003c/p\u003e \u003cp\u003eThe single-beat estimate of Ees (Ees(sb)) formulas can be divided into two groups: the group that attempts to measure V0 and assumes that LV ESP\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP, such as (Shishido, Chen and Kim), and the second group that assumes that V0\u0026thinsp;=\u0026thinsp;zero but substitutes for LV ESP differently (Kelly, Tanoue, Yamashita and Bombardini).\u003c/p\u003e \u003cp\u003eChowdhury et al. studied the agreement between invasively measured Ees and noninvasive Ees(sb) among children.\u003csup\u003e3\u003c/sup\u003e Their research methodology mandated vena cava balloon occlusion. They compared four different methods of estimating Ees(sb): Chen, Kim, Shishido and Tanoue. Notably, they calculated Tanoue Ees as \"Ees(sb4)\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV\". In their original publication, Tanoue et al. used the MAP as a substitute for the LV ESP, not 0.9 \u0026times; SBP. They concluded the following: Chen's, Shishido's and Kim's methods overestimated the true Ees, and only the following formula, Ees(sb)\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV, had good agreement with invasive Ees. Notably, patients with LV outflow obstruction, including patients with severe AS, were excluded.\u003c/p\u003e \u003cp\u003eIn 2014, Yotti et al. studied 27 patients with various loading conditions (eight patients with dilated cardiomyopathy, ten normal EF patients and nine patients with end-stage liver failure). Their research methodology also mandated vena cava balloon occlusion. They concluded that Chen's method (r2 = -0.05, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) failed to correlate with invasive Ees, while Kelly's method (Ees\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV) had only a poor correlation (r2\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003csup\u003e23\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eKelly's method (Ees(sb)\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV) and the SBP method (Ees(sb)\u0026thinsp;=\u0026thinsp;SBP/ESV) had the best agreement with the invasive Ees (allowing for the abovementioned assumptions). The methods that fell into group one had poor agreement with invasive Ees. Likewise, the methods that assumed V0\u0026thinsp;=\u0026thinsp;zero (group two) but attempted to account for the gradient across the AV also showed poor agreement compared to Kelly's method.\u003c/p\u003e \u003cp\u003eIt seems that a simplified formula, such as Ees(sb)\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV or Ees(sb)\u0026thinsp;=\u0026thinsp;SBP/ESV, has the best agreement with the invasively measured Ees. The above conclusion holds true regardless of the method used to estimate the invasive Ees (with or without load variation) or the studied clinical condition, including severe AS. The number of assumptions made to assemble these complex formulas is likely the reason behind these findings.\u003c/p\u003e \u003cp\u003eAs Chen et al. suggested, ultimately, the sensitivity and specificity of a specific index determine its clinical utility. All being equal, it is the simplest method that should be used.\u003c/p\u003e"},{"header":"Conclusion:","content":"\u003cp\u003eMeasurement of the single-beat estimate of ventricular elastance (Ees(sb)) is possible in patients with severe aortic stenosis. Kelly's method (Ees(sb)\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV) has the best agreement with the invasive measurement of left ventricular elastance (ESPVR). Systolic blood pressure, as measured by the brachial blood pressure cuff, has the best agreement with end-systolic pressure in severe aortic stenosis. Further studies are warranted to evaluate the efficacy of noninvasive Ees (end-systolic elastance) as a marker of left ventricular function in predicting clinical outcomes.\u003c/p\u003e\n\u003ch3\u003eStudy limitations:\u003c/h3\u003e\n\u003cp\u003eIn many prior invasive PV loop studies, protocols involved IVC occlusion to vary the load and estimate the Ees, a method we did not employ in this pilot study. It is worth noting that there is a trend among other laboratories conducting these studies to simplify invasive PVL studies.\u003c/p\u003e \u003cp\u003eMore importantly, every preceding study, irrespective of the approach used to estimate invasive Ees, indicated that Kelly's method (Ees\u0026thinsp;=\u0026thinsp;0.9 \u0026times; SBP/ESV) had the best agreement with invasive Ees. This aligns our findings well and bolsters their external validity.\u003c/p\u003e \u003cp\u003eThe discrepancy observed between invasive and noninvasive SV measurements underscores concerns regarding sample size and the placement of the conductance catheter within the left ventricle. To address this issue, our study meticulously optimised catheter positioning via fluoroscopy and real-time PV loop acquisition. We ensured measurement accuracy by collecting data after obtaining at least two high-quality PV loop segments.\u003c/p\u003e \u003cp\u003eWe did not factor in the medications administered during the TAVI procedures, including painkillers, sedatives, intravenous fluids, or, in a subset of patients, the peripheral use of vasoconstrictors such as metaraminol bitartrate.\u003c/p\u003e \u003cp\u003eFinally, only a few patients experienced MR. Therefore, we were unable to noninvasively estimate the Starling contractility index (SCI)\u0026thinsp;=\u0026thinsp;dp/dt Max/EDV.\u003c/p\u003e"},{"header":"Abbreviations:","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; AS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Aortic stenosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; EDV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; End-diastolic volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; Ees\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Left ventricular elastance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; Ees(sb)\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Single-beat estimate of left ventricular elastance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; EF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; ESPVR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; End-systolic pressure‒volume relationship \u0026ndash; also known as left ventricular elastance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; ESV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; End-systolic volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; LV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Left ventricle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; LVEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Left ventricular ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; LV ESP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Left ventricular end-systolic pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; MAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Mean arterial pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; PVL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Pressure‒volume loop\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; TAVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Transcatheter aortic valve implantation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; TTE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; Transthoracic echocardiography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; V0\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e\u0026bull; The maximal LV volume at which pressure is still zero\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations:","content":"\u003ch3\u003eEthics approval and consent to participate:\u003c/h3\u003e\n\u003cp\u003eThe study\u0026nbsp;complied\u0026nbsp;with the Declaration of\u0026nbsp;Helsinki,\u0026nbsp;and approvals of the original study design and subsequent amendments were all granted by\u0026nbsp;the\u0026nbsp;London Dulwich Research Ethics Committee with the reference number 13/LO/1542 IRAS project ID: 123464. All study participants\u0026nbsp;provided\u0026nbsp;written consent.\u003c/p\u003e\n\u003cp\u003eThe manuscript submission conforms to the guidelines set forth in the \u0026ldquo;Recommendations for the Conduct, Reporting, Editing and Publication of Scholarly Work in Medical Journals (ICMJE Recommendation)\u0026rdquo;.\u003c/p\u003e\n\u003ch3\u003eConsent for publication:\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author\u0026nbsp;upon\u0026nbsp;reasonable request.\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis study was supported fully by King\u0026rsquo;s College Charity and in part by a National Institute for Health Research Biomedical Research Centre award to Guy\u0026apos;s \u0026amp; St Thomas\u0026apos; Hospital and King\u0026apos;s College London in partnership with King\u0026apos;s College Hospital.\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; contributions\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003eOA and ME contributed to the\u0026nbsp;study\u0026nbsp;conception, design, data acquisition and analysis,\u0026nbsp;and\u0026nbsp;interpretation of\u0026nbsp;the\u0026nbsp;data and drafted, revised and finalised the manuscript.\u003c/li\u003e\n \u003cli\u003eMA, RC, JB and MM contributed to the\u0026nbsp;study\u0026nbsp;conception,\u0026nbsp;study design, data acquisition and analysis and manuscript\u0026nbsp;revision.\u003c/li\u003e\n \u003cli\u003eBB and NK contributed to the data acquisition, analysis and revision of the manuscript.\u003c/li\u003e\n \u003cli\u003eAS, RD and PM contributed to the conception\u0026nbsp;and\u0026nbsp;design of the\u0026nbsp;study, interpretation of\u0026nbsp;the\u0026nbsp;data and\u0026nbsp;revision of\u0026nbsp;the manuscript.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eAcknowledgements\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References:","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLam W, Pontana F, Vassiliou V, Prasad S. 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J Am Coll Cardiol [Internet]. 2009 [cited 2019 Sep 25];54:1003\u0026ndash;1011. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://linkinghub.elsevier.com/retrieve/pii/S0735109709020592\u003c/span\u003e\u003cspan address=\"https://linkinghub.elsevier.com/retrieve/pii/S0735109709020592\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SP, Park SJ, Kim YJ, Chang SA, Park EA, Kim HK, Lee W, Lee SC, Park SW, Sohn DW, Choe YH. Early detection of subclinical ventricular deterioration in aortic stenosis with cardiovascular magnetic resonance and echocardiography. J Cardiovasc Magn Reson. 2013;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhat is new for general cardiologists in the. 2017 ESC Guidelines on valvular hea [Internet]. [cited 2019 Dec 21]; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.escardio.org/Journals/E-Journal-of-Cardiology-Practice/Volume-15/What-is-new-for-general-cardiologists-in-the-2017-ESC-Guidelines-on-valvular-heart-disease\u003c/span\u003e\u003cspan address=\"https://www.escardio.org/Journals/E-Journal-of-Cardiology-Practice/Volume-15/What-is-new-for-general-cardiologists-in-the-2017-ESC-Guidelines-on-valvular-heart-disease\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly RP, Ting CT, Yang TM, Liu CP, Maughan WL, Chang MS, Kass DA. Effective arterial elastance as index of arterial vascular load in humans. Circulation. 1992;86:513\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChemla D, Antony I, Lecarpentier Y, Nitenberg A. 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J Card Fail. 2005;11:177\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYotti R, Bermejo J, Benito Y, Sanz-Ruiz R, Ripoll C, Mart\u0026iacute;nez-Legazpi P, Del Villar CP, El\u0026iacute;zaga J, Gonz\u0026aacute;lez-Mansilla A, Barrio A, Ba\u0026ntilde;ares R, Fern\u0026aacute;ndez-Avil\u0026eacute;s F. Validation of noninvasive indices of global systolic function in patients with normal and abnormal loading conditions a simultaneous echocardiography pressure\u0026ndash;volume catheterisation study. Circ Cardiovasc Imaging. 2014;7:164\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Severe aortic stenosis, Invasive pressure‒volume loop indices, Noninvasive pressure‒volume loop indices, Ventricular elastance, Validation","lastPublishedDoi":"10.21203/rs.3.rs-4200318/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4200318/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground:\u003c/p\u003e\n\u003cp\u003eStudies utilising invasive pressure‒volume loops offer valuable insights into left ventricular (LV) contractility, yet their availability remains limited. Conversely, noninvasive indices are accessible and reproducible; however, their validation in patients with aortic stenosis (AS) is lacking.\u003cstrong\u003e \u003c/strong\u003eWe sought to validate the noninvasive indices of PVL studies in a group of symptomatic severe AS patients.\u003c/p\u003e\n\u003cp\u003eWe recruited patients with symptomatic severe AS admitted for transcatheter aortic valve implantation (TAVI) for invasive PVL studies. Noninvasive PVL indices were measured with three-dimensional (3D) echocardiography with a prespecified protocol. The agreement between invasive and noninvasive calculation methods was assessed.\u003c/p\u003e\n\u003cp\u003eResults:\u003c/p\u003e\n\u003cp\u003eEleven patients (11) were recruited for this pilot study. The noninvasive end-systolic pressure‒volume relationship (ESPVR) determined by Kelly's method (Ees\u003csub\u003e(sb)\u003c/sub\u003e = 0.9 × systolic blood pressure/end-systolic volume (ESV)) had the best agreement with the invasive ESPVR (limits of agreement -1.7 to 2.1 with a percentage error of 24%, one sample T test p =0.504). Systolic blood pressure, as measured by the brachial blood pressure cuff, had the best agreement with end-systolic pressure in severe aortic stenosis (limits of agreement -60 to 60 with a percentage error of 3%, one sample T test p =0.959).\u003c/p\u003e\n\u003cp\u003eConclusion:\u003c/p\u003e\n\u003cp\u003eMeasurement of the single-beat estimate of ventricular elastance (Ees\u003csub\u003e(sb)\u003c/sub\u003e) is possible in patients with severe aortic stenosis. Kelly's method (Ees\u003csub\u003e(sb)\u003c/sub\u003e = 0.9 × SBP/ESV) had the best agreement with the invasive measurement of left ventricular elastance (Ees). Systolic blood pressure, as measured by the brachial blood pressure cuff, has the best agreement with end-systolic pressure in severe aortic stenosis.\u003c/p\u003e","manuscriptTitle":"The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-09 21:09:47","doi":"10.21203/rs.3.rs-4200318/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f0c5764-d5bb-4159-a80c-2758c10772e7","owner":[],"postedDate":"April 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T23:23:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-09 21:09:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4200318","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4200318","identity":"rs-4200318","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}