The Accuracy and Influencing Factors of Doppler Echocardiography in Estimating Pulmonary Artery Systolic Pressure: Comparison With Right Heart Catheterization : A Retrospective Cross-sectional Study

The Accuracy and Influencing Factors of Doppler Echocardiography in Estimating Pulmonary Artery Systolic Pressure: Comparison With Right Heart Catheterization : A Retrospective Cross-sectional Study | 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 Accuracy and Influencing Factors of Doppler Echocardiography in Estimating Pulmonary Artery Systolic Pressure: Comparison With Right Heart Catheterization : A Retrospective Cross-sectional Study Guangjie Lv, Aili Li, Xincao Tao, Yanan Zhai, Yu Zhang, Jieping Lei, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1087290/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background: Noninvasive assessment of pulmonary artery systolic pressure by Doppler echocardiography (sPAP ECHO ) has been widely adopted to screen for pulmonary hypertension (PH). But high proportion of overestimation or underestimation of sPAP ECHO still remained. So we aimed to explore the accuracy and influencing factors of sPAP ECHO with right heart catheterization (RHC) as reference. Methods: A total of 218 highly suspected pulmonary hypertension (PH) patients who underwent RHC and echocardiography within 7 days were included. The correlation and consistency between tricuspid regurgitation (TR) derived parameters and RHC results were tested by Pearson and Bland-Altaman methods. With mPAP ≥25mmHg measured by RHC as the standard diagnostic criteria of PH, ROC curve was used to compared the diagnostic efficacy of sPAP ECHO with other TR related methods. The ratio of (sPAP ECHO -sPAP RHC )/sPAP RHC was calculated and divided into three groups, namely, the underestimation group, accurate group and overestimation group by ±10% as the boundary. The influencing factors of sPAP ECHO were analyzed by ordinal regression analysis. Results: sPAP ECHO had the greatest correlation coefficient (r=0.781, P<0.001), best diagnostic efficiency (AUC=0.98) and lowest bias (mean bias= 0.07mmHg, 95% limits of agreement: -32.08 to +32.22mmHg) compared with other TR related methods. Ordinal regression analysis showed that TR signal quality, PAWP and sPAP RHC level affected the accuracy of sPAP ECHO (P < 0.05). The OR value of PAWP was 0.94 (95%CI: 0.89, 0.99). Compared with high sPAP RHC level, the OR value of low and medium sPAP RHC level were 21.56 (95%CI: 9.57, 48.55) and 5.13 (95%CI: 2.55, 10.32) , respectively. Relative to the signal quality of type A, the OR value of type B and C signal quality were 0.26 (95%CI: 0.14, 0.48) and 0.23 (95%CI: 0.07, 0.73), respectively. While TR severity and right ventricular systolic function had no significant effect on the accuracy of sPAP ECHO . Conclusions: sPAP ECHO was superior to other TR-related methods in PH screening, and was often overestimated in patients with pre-capillary PH at low sPAP RHC level, even with good TR signal quality. Trial registration: This is a retrospectively registered study. Medical Genetics Doppler echocardiography Pulmonary hypertension Right heart catheterization Tricuspid regurgitation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Right heart catheter is recognized as the gold standard for measuring pulmonary artery pressure, but its invasiveness limits its general applicability. While Doppler echocardiography can non-invasively assess pulmonary artery pressure in a variety of methods, such as peak velocity of tricuspid regurgitation (TR Vmax) and its derived parameters including TR pressure gradient (TR-PG), TR mean pressure gradient (TR-mPG), estimated mean pulmonary artery pressure (mPAP ECHO ) and pulmonary artery systolic pressure (sPAP ECHO ). But until now, there is no consensus on which echocardiographic method is better. The current guideline recommend TR Vmax to avoid extra error of the estimated right atrial pressure (RAP) [ 1 ] . Research has also found mPAP is superior than TR Vmax in identifying pulmonary hypertension (PH). However, mPAP ECHO is obtained by tracing the Doppler-derived velocity-time integral of TR which is time-consuming and closely dependent on TR signal quality. While sPAP ECHO as the most well-adopted approach in pulmonary hypertension (PH) screening has proved to be a reliable method [ 3 ] . But whether sPAP ECHO is superior to other parameters in determining the probability of PH was not examined previously. sPAP ECHO can also provide valuable information in evaluating treatment response and even predicting prognosis [ 4 , 5 ] . But high proportion of overestimation or underestimation of sPAP ECHO still remained [ 6 ] . In order to evaluate PH patients’ condition appropriately and improve doctor’s diagnostic confidence, we need to understand in what kind of situation that sPAP ECHO will be under or overestimated. Based on clinical experience and review of previous literature, we assumed that right ventricular systolic function, pulmonary artery pressure level, TR severity and signal quality would affect the accuracy of sPAP ECHO . In addition, as a important parameter to distinguish pre-capillary and post-capillary PH, pulmonary artery wedge ressure (PAWP) was also included into analysis to see if there was any difference in the accuracy of sPAP ECHO . Therefore, the first aim of this study was to compare the efficiency of sPAP ECHO with other parameters in PH screening. And the second goal was to find influencing factors that account for the inaccuracy of sPAP ECHO . Methods From October 2015 and October 2020, a total of 430 patients with known or suspected PH admitted to our center were evaluated. Inclusion criteria included: age ≥18 years old; the interval between echocardiography and RHC ≤7 days; Exclusion criteria included: patients without TR, pulmonary artery stenosis or right ventricular outflow tract stenosis, poor image quality which are not suitable for analysis, ventricular septal defect or patent ductus arteriosus. Patient’s demographic and clinical data were obtained from the departmental electronic medical record. The institutional review board of the China-Japan Friendship Hospital waived the need for written patient informed consent as this study involved the retrospective analysis of clinically acquired data. The data underlying this article will be shared on reasonable request to the corresponding author. Baseline assessment of eligible patients including WHO functional class, the level of N-terminal pro B-type natriuretic peptide (NT-proBNP) and 6-minute walk test (6MWT) were recorded. Right heart catheterization Haemodynamic measurements were performed with a 7F Swan-Ganz catheter Philips Allura X-PER FD20 flat-plate angiography system (Baxter Inc). The system was zeroed and referenced at patients’ heart level as previously described [7] . Right atrial pressure (RAP), pulmonary systolic artery pressure (sPAP RHC ) and PAWP were recorded at end expiration in baseline over at least 3 heart cycles. Cardiac output (CO) was obtained using Fick’s method. Pulmonary vascular resistance (PVR), cardiac index, stroke volume, pulse pressure and diastolic pressure gradient were calculated using standard formulas. According to the tertiles of sPAP RHC , PH was classified into low, medium and high levels. Echocardiography Echocardiographic images were acquired using a GE Vivid E95 machine (GE Healthcare, General Electric Healthcare) equipped with M5S phased-array transducers. Analysis was performed independently by two blinded investigators using EchoPAC software (GE Healthcare version 201). Two-dimensional and Doppler echocardiography (DE) were performed on the basis of current guidelines. TR-PG was calculated from the TR Vmax obtained from continuous-wave Doppler by the simplified Bernoulli equation: TR-PG = 4 (TR Vmax) 2 . TR-mPG was obtained by tracing the time-velocity integral of TR. sPAP ECHO and mPAP ECHO were calculated by adding the estimated RAP to TR-PG and TR-mPG, respectively. RAP is divided into three categories (3, 8, and 15 mmHg) based on the inferior vena cava (IVC) diameter and its respiratory variation [1] . Noninvasive assessment of sPAP ECHO was obtained by adding the right ventricle-right atrium pressure gradient (RV-RA PG) to the estimated RAP. The ratio of (sPAP ECHO -sPAP RHC )/sPAP RHC was calculated and divided into three groups, namely, the underestimation group, accurate group and overestimation group by ±10% as the boundary. The severity of TR was classified into 3 grades by comprehensively evaluating the regurgitation jet area and vena contracta (VC) width. The mild group was defined as jet area <5 cm 2 , VC TR ≤ 3 mm; the moderate group as jet area 5–10 cm 2 , 3 mm 10 cm 2 , VC TR ≥7 mm. The quality of the TR signal was classified into 3 types according to envelope visibility ( Fig 1 , type A, complete envelope; type B, partial envelope but prone to extrapolation; and type C, unreliable envelope) as previously reported [6] . RV systolic function was assessed using multiple parameters, including RV wall thickness (RV WT), tricuspid annular plane systolic excursion (TAPSE), systolic annular tissue velocity of the lateral tricuspid annulus (S’) and RV fractional area change (FAC). All parameters were repeatedly measured and averaged. To determine the reproducibility of sPAP ECHO measurements, a total of 34 randomly selected examinations were analyzed twice by a first investigator at a 1-week interval and once by a second investigator. Statistical Analysis Standard statistical software (SPSS version 26 for Windows, SPSS, Chicago, IL, USA) was used for the statistical analysis. Data are expressed as mean±standard deviation for quantitative variables with normal distribution or as median (interquartile range) for variables without normal distribution. The correlation and consistency between TR derived parameters and RHC results were tested by Pearson and Bland-Altaman methods. With mPAP ≥ 25mmHg measured by RHC as the standard diagnostic criteria of PH, ROC curve was used to compared the diagnostic efficacy of sPAP ECHO with other TR related methods. The influencing factors of sPAP ECHO were analyzed by ordinal regression analysis. The intraclass correlation coefficient was used to determine inter- and intra-observer reproducibility for sPAP E CHO from 34 randomly selected patients using an identical cine-loop for each view. For all statistical tests, a P value <0.05 was used to indicate significance. Results Patients characteristics A total of 218 patients were finally identified and analyzed, as shown in Fig. 2 . Baseline demographics and clinical characteristics are described in Table 1 . The mean age of patients was 50.9±13.3 years old, 40.3% were male, 197 (90.4%) patients had PH. No patient experienced major cardiac event between DE and RHC examinations. Table 2 lists the DE and RHC variables grouped by estimated accuracy. Table 1 Clinical and demographic characteristics Variables Value Age (years) 50.9±13.3 Males(%) 90(41.3) BMI 1.67 (1.57, 1.84) Systolic BP(mmHg) 120(108, 132) Diastolic BP(mmHg) 77(70, 87) Heart rate (bpm) 76(68.65, 80) Interval between TTE and RHC, days 2.5(1, 5) NT-pro BNP (pg/ml) 451 (175, 1043) 6M WT (m) 365.5±104.6 WHO functional class I Class(%) 20(9.2) II Class(%) 93(42.7) III Class(%) 89(40.8) IV Class(%) 16(7.3) PH (n) 197 (90.4%) Idiopathic, heritable, drug and toxic induced 37 Associated with Connective tissue disease 25 Portal hypertension 2 Congenital heart disease 8 PH due to left heart disease 6 PH due to lung disease and/or hypoxia 6 Chronic thromboembolic PH 95 PH with unclear and/or multifactorial mechanisms 13 Pulmonary veno-occlusive disease and/or pulmonary capillary haemangiomatosis 5 Non-PH (n) 21 (9.6%) Values are presented as mean ± SD, median (IQR), or n (%). BMI, body mass index; TTE, transthoracic echocardiography; RHC, right heart catheterization; BP, blood pressure; NT-pro BNP, N-terminal pro B-type natriuretic peptide; 6M WT, 6-minutes walk test; PH, pulmonary hypertension. Table 2 Univariable and multivariable ordered analysis for accuracy of sPAP ECHO Variables Overestimation (n=79) Accurate (n=81) Underestimation (n=58) Univariable analysis Multivariable analysis P OR (95% CI) P OR (95% CI) Echocardiographic parameters RAD (mm) 49.1±10.2 49.9±11.1 49.4±10.0 0.816 0.997(0.974, 1.021) RVDD (mm) 45.4±7.3 46.2±7.6 46.5±6.5 0.323 0.984(0.952,1.016) RV WT (mm) 5.3±1.5 5.4±1.4 5.8±1.6 0.055 0.845(0.712,1.003) TAPSE(mm) 16.8±3.9 16.3±3.4 15.9±3.7 0.110 1.057(0.988,1.130) FAC(%) 30.6±9.3 29.8±8.3 27.7±7.6 0.064 1.029(0.998,1.061) TR severity 0.546 mild 44 (20.2%) 51 (23.5%) 36(16.5%) 0.944 1.031(0.441,2.408) moderate 28(12.8%) 22(10.1%) 16(7.3%) 0.480 1.386(0.560,3.431) severe 7(3.2%) 8(3.7%) 6(2.8%) TR signal quality 0.020 A 53(24.3%) 49(22.5%) 25(11.5%) B 23(10.6%) 26(11.9%) 27 (12.4%) 0.017 0.525(0.309,0.892) 0.000 0.258(0.138,0438) C 3 (1.4%) 6 (2.8%) 6 (2.8%) 0.055 0.375(0.138,1.020) 0.013 0.233(0.074,0.734) Catheterization parameters sPAP RHC level 0.000 mild 43 (19.7%) 25 (111.5%) 2 (0.9%) 0.000 15.574(7.563,31.961) 0.000 21.561(9.574,48.554) moderate 30 (13.8%) 27 (12.4%) 17 (7.9%) 0.000 5.279(2.752.10.125) 0.000 5.125 (2.545,10.321) severe 6 (2.8%) 29 (13.3%) 39 (17.9%) sPAP RHC (mmHg) 60.5±19.6 74.4±23.1 92.4±23.1 0.000 0.958(0.947,0.970) RAP (mmHg) 2.2±4.2 3.3±4.7 5.2±6.1 0.002 0.921(0.875,0.970) PVR(Wood Units) 8.4±5.9 11.2±6.2 14.0±8.5 0.000 0.912(0.878,0.947) PAWP (mmHg) 6.9±5.2 7.5±5.2 10.1±7.0 0.003 0.932(0.889,0.977) 0.018 0.939(0.892,0.989) mPAP (mmHg) 38.6±35.6 43.3±14.7 53.9±15.5 0.000 0.961(0.944,0.978) Clinical parameters 6M WT (m) 370.9±105.7 355.9±123.0 367.8±84.1 0.868 1.000(0.996,1.005) WHO functional class 0.907 I 5 (2.3%) 10 (4.6%) 5 (2.3%) 0.805 0.858(0.256,2.880) II 38 (17.4%) 29 (13.3%) 26 (11.9%) 0.745 1.176(0.443,3.127) III 30 (13.8%) 37 (17.0%) 22 (10.1%) 0.919 1.052(0.395,2.805) VI 6 (2.8%) 5 (2.3%) 5 (2.3%) RAD, right atrial diameter; RVDD, right ventricle diastolic diameter; RV WT, right ventricle wall thickness; TAPSE, tricuspid annular plane systolic excursion ; RV FAC, right ventricle fractional area change; RAP, right atrial pressure; PVR, pulmonary vascular resistance; PAWP, pulmonary artery wedge pressure; mPAP, mean pulmonary artery pressure. 6M WT, 6-minute walk test. Observer Variability Of Spap Estimation The intraclass correlation coefficient for inter-observer reproducibility of sPAP ECHO was 0.988 (95% confidence interval 0.977–0.994) and the intraclass correlation coefficient for intra-observer reproducibility of sPAP ECHO was 0.992 (95% confidence interval 0.984–0.996). Association Between Invasively Determined Parameters And Tr Derived Parameters All the TR derived parameters including TR Vmax, TR-PG, TR-mPG, mPAP ECHO and sPAP ECHO showed positive correlation with related RHC results (Fig. 3 ). sPAP ECHO had the greatest correlation coefficient (r=0.782, P < 0.001). Bland-Altman analysis demonstrated low bias between RHC and echocardiographic results with wide limits of agreements (Fig. 4 ). The bias of sPAP ECHO (mean bias= 0.07mmHg, 95% limits of agreement: -32.08 to +32.22mmHg) was lower than that of TR-PG (mean bias= 5.87mmHg, 95% limits of agreement: -26.46 to +38.21mmHg). The mean deviation between mPAP ECHO , TR-mPG with mPAP RHC were -2.59mmHg (95% limits of agreement -26.29 to +21.11mmHg) and 3.32mmHg ( 95% limits of agreement -20.07 to +26.70mmHg), respectively. Performance Of Different Tr Methods For Predicting Ph The ROC analysis showed TR Vmax, TR-PG, TR-mPG, mPAP ECHO and sPAP ECHO had similar diagnostic performance for determining the possibility of PH (Table 3 ). There was no significant difference among the AUCs of these TR methods ( P ༞0.05). However, the predictive efficiency and sensitivity of sPAP ECHO were better than other methods. Of note, using Youden index quantification, the optimal cutoff value for our cohort was 55.5 mmHg for the sPAP ECHO method. Table 3 Receiver Operating Characteristic Curve Analysis of DE Parameters for Detecting PH (mPAP≥ 25mmHg) AUC Cut-off value sensitivity (%) specificity (%) accuracy(%) PPV(%) NPV(%) sPAP ECHO 0.981 55.5 mmHg 90.86 100.00 91.74 100.00 53.85 TR Vmax 0.977 361.5cm/s 88.83 100.00 89.91 100.00 48.84 TR-PG 0.978 52.5mmHg 87.82 100.00 88.99 100.00 46.67 mPAP ECHO 0.956 30.6 mmHg 94.38 84.62 93.72 98.82 52.38 TR-mPG 0.945 27.6mmHg 92.70 84.62 92.15 98.80 45.83 PPV: Positive predictive value; NPV: Negative predictive value. sPAP ECHO : pulmonary systolic pressure estimated by echocardiography; TR Vmax: maximum velocity of tricuspid regurgitation; TR-PG: tricuspid regurgitation pressure gradient; mPAP ECHO : mean pulmonary artery pressure estimated by echocardiography; TR-mPG: tricuspid regurgitation mean pressure gradient. Factors Affecting The Accuracy Of Spap Estimation There were 79 patients (36.2%) in overestimated group, 81 patients (37.2%) in accurate group and 58 patients (26.6%) in underestimated group. sPAP RHC was divided into three levels according to its tertile (63mmHg, 85mmHg). Univariable ordinal analysis demonstrated that RV WT, FAC, TR signal quality, sPAP RHC level, RAP, PVR, PAWP and mPAP were associated with inaccuracy of sPAP ECHO estimation (Table 2 ). After multivariate ordinal regression analysis, it was found that TR signal quality, PAWP and sPAP RHC level affected the accuracy of sPAP ECHO significantly (P < 0.05). The OR value of PAWP was 0.94 (95%CI: 0.89, 0.99). Compared with high sPAP RHC level, the OR value of low and medium sPAP RHC level were 21.56 (95%CI: 9.57, 48.55) and 5.13 (95%CI: 2.55, 10.32), respectively. Relative to the signal quality of type A, the OR value of type B and C signal quality were 0.26 (95%CI: 0.14, 0.48) and 0.23 (95%CI: 0.07, 0.73), respectively. While TR severity, RV systolic function parameters such as TAPSE, S’ and FAC didn’t remain in the final equation. Discussion Key findings of our study: (1) Compared with TR Vmax and its derived parameters, sPAP ECHO showed better sensitivity for predicting PH while maintaining similar specificity. (2) Patients with lower PAWP tends to overestimate sPAP ECHO at lower sPAP RHC level, even with good TR signal quality. Performance of sPAP ECHO in PH screening In our study, sPAP ECHO exhibited best correlation with sPAP RHC and was superior to TR Vmax and its derived methods in PH screening. Compared with mPAP ECHO , sPAP ECHO is more convenient to measure. As a derived variables of TR Vmax, sPAP ECHO didn’t amplify measurement errors in assessing pulmonary artery pressure as indicated by the currents guideline, on the contrary, it showed better sensitivity while maintaining similar specificity. Relative to TR-PG and TR-mPG, sPAP ECHO contains more information from RAP which may accounts for its better accuracy and lower bias. RAP would elevate with the increase of RV overload [8] , it is an important measurement that provides heart failure and prognostic information [9] . Hellenkamp’s study on mPAP ECHO also supported RAP is of additional diagnostic value in predicting PH [2] . In a word, sPAP ECHO as a simple and reliable parameter is more suitable than other TR related methods for clinical practice in PH screening. Reasons for inaccuracy of sPAP ECHO estimation First, our data suggested patients with lower PAWP tended to overestimate sPAP ECHO . Finkelhor et al also found PAWP had a strong inverse correlation with the difference between sPAP RHC and sPAP ECHO too [2] . They speculated that elevated left atrial pressure can be transmitted to the right atrium via the shared inter-atrial septum as well as through pericardial constraint and limit TR velocities, thus the accuracy of sPAP ECHO will be affected. Even though the mechanism of how PAWP affects pulmonary artery pressure is still unclear, interestingly, more and more studies are beginning to notice this phenomenon. Amsallem et al found patients with higher PAWP is associated with lower sPAP ECHO thresholds for PH diagnosis [11] . Our result supported this view in the opposite way. Pre-capillary PH patients with lower PAWP accounted for 85.8% of our population, and the optimal cut-off value of our cohort was 55.5 mmHg which is higher than previous studies focusing on post-capillary PH patients with higher PAWP [12, 13] . We speculated the underestimation of sPAP ECHO due to high PAWP leads to lower sPAP ECHO threshold for post-capillary PH. In contrast, the higher sPAP ECHO threshold of pre-capillary PH might be associated with overestimation of sPAP ECHO because of lower PAWP. Therefore, a higher sPAP ECHO threshold for determining pre-capillary PH is more appropriate. Second, for the effect of sPAP RHC level on the accuracy of sPAP ECHO , Groh et al found DE inaccurately estimated right ventricular pressure in children with elevated right heart pressure [14] . Our results provided further evidence that DE tended to overestimate sPAP RHC at low sPAP RHC level and increasingly underestimated the sPAP RHC with the advance of sPAP RHC level. We assumed that the coupling mechanism between RV contractility and its load may account for this phenomenon. sPAP RHC is mildly elevated during the initial phase of PH, RV coupling is maintained by a 4- to 5-fold increase in contractility through muscle hypertrophy as well as changes in muscle properties [15] . The compensatory enhancement of RV contractility [16] would make TR Vmax become higher, sPAP RHC will be overestimated by DE, while the pulmonary artery pressure is still in the normal range due to the natural vascular elasticity. As sPAP RHC increased moderately, the compensatory contractility of RV would halt and the stroke volume would decrease, but CO is maintained by increasing heart rate. At this stage of PH, the estimation of sPAP RHC by DE is relatively reliable. However, sPAP RHC would become higher with the development of PH, when RV uncoupling occurs, CO would reduce which will result in increasing of RV preload. The elevated RV preload and RAP would lead to a decreased right atrial-ventricular pressure gradient, thus DE would underestimate the sPAP RHC . sPAP RHC level may affect the accuracy of sPAP ECHO through coupling mechanism between RV contractility and its load, but studies with larger sample sizes are needed test this hypothesis. Third, our finding confirmed previous reports that the TR signal quality would affect the accuracy of sPAP ECHO [17] . Except poor signal quality of TR leads to underestimation of sPAP ECHO , we also found good signal quality also brings overestimation of sPAP ECHO for some cases. As in our cohort, 41% of patients who obtained type A signal quality of TR still overestimated sPAP ECHO . After further analysis, we found lower sPAP RHC level and PAWP were significantly associated with overestimation of sPAP ECHO for patients with type A signal quality. This phenomenon suggests we cannot simply rely on good signal quality, attention should also be given to patients with pre-capillary PH, especially during the initial stage of disease, cause TR signal quality, sPAP RHC level and PAWP work together to affect the accuracy of sPAP ECHO . Furthermore, there is no consensus on how TR severity would interfere the accuracy of the sPAP ECHO . Hioka et al reported that echocardiography increasingly overestimated the TR PG with the advance of TR severity, as was theoretically predicted by the pressure recovery phenomenon associated with the laminar regurgitant flow [18] . But Parasuraman et al reported that severe TR could cause equalisation of right atrial and ventricular pressures which may cause the TR Doppler envelope to be cut short, leading to underestimation of sPAP ECHO [19] . Our study differed from other studies in that the TR severity did not significantly affect the accuracy of sPAP ECHO . On the one hand, only 9.6% of patients in our cohort had severe TR which is in line with the actual clinical situation that severe TR only appears in the minority of the total patients. On the other hand, patients with mild or moderate TR could also obtained type A signal quality and estimate sPAP ECHO appropriately ( Fig 5 ) . TR severity was also affected by RV contractility and dimension. So the overall impact of TR severity to the accuracy of sPAP ECHO is not as significant as TR signal quality. At last, we didn’t find RV systolic parameters have significant impact on the accuracy of sPAP ECHO neither. Theoretically, RV systolic function will gradually decrease [20] , but the RV can remain coupled for the large increase in load by increasing contractility until heart failure [15] . Therefore, RV systolic parameters are relatively stable before the end stage of PH. In addition, the heart movement and measurement angle dependence also affect the accuracy of the relevant parameters. Although RV systolic parameters had clinical significance for the assessment of PH, they didn’t have significant effect on the accuracy of sPAP ECHO . Limitations: This study has several limitations that merits emphasis. First, this is a retrospective research with a small sample size. 90.5% had PH and 47.7% of them were due to chronic pulmonary thromboembolism, the sample size of other type PH was relatively small. Thus we couldn’t give specific suggestion for each type of PH. Furthermore, we included patients who underwent RHC and echocardiography within 7 days due to the restriction of clinical actual conditions. But the average interval time was 3 days in this study, and the majority of our patients have pre-capillary PH which indicates the patient's hemodynamics are relatively stable and wouldn’t change dramatically during this short time. At last, the single-center nature of the present study limited generalization. Conclusions sPAP ECHO was superior to other TR-related methods in PH screening, and was often overestimated in patients with pre-capillary PH at low sPAP RHC level, even with good TR signal quality. Abbreviations Abbreviation Full Title PH Pulmonary Hypertension RHC Right Heart Catheterization DE Doppler Echocardiography TR Tricuspid Regurgitation sPAP RHC Pulmonary Artery Systolic Pressure measured by RHC sPAP ECHO Pulmonary Artery Systolic Pressure estimated by DE mPAP Mean Pulmonary Artery Pressure measured by RHC mPAP ECHO Mean Pulmonary Artery Pressure estimated by DE PAWP Pulmonary Artery Wedge Pressure RAP Right Atrial Pressure CO Cardiac output TR PG TR Pressure Gradient TR-mPG TR Mean Pressure Gradient PVR Pulmonary Vascular Resistance RV Right Ventricle RV WT RV Wall Thickness TAPSE Tricuspid Annular Plane Systolic Excursion S’ Systolic Annular Tissue Velocity of the Lateral Tricuspid Annulus FAC RV Fractional Area Change IVC Inferior Vena Cava Declarations Acknowledgements None. Funding Funding : This study was supported by grants from the National Natural Key Clinical Specialty Construction Project (2020-QTL-009) and the Capital Health Development Research Project (2020-2-4063). Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Consent for publication Not applicable Ethics approval and consent to participate This study complied with the Declaration of Helsinki. Ethical approval number was 2020-95-K59. The protocol was approved by the Ethic Committee of China-Japan Friendship Hospital. The institutional review board of the China-Japan Friendship Hospital waived the need for written patient informed consent as this study involved the retrospective analysis of clinically acquired data. Competing interests The authors declare that they have no competing interests. Authors ’contributions All authors contributed to the study conception and design. Aili Li searched relevant literature and conceived the study. Zhenguo Zhai, Xincao Tao and Wanmu Xie were involved in research Implementation. Material preparation and data collection were performed by Qian Gao, Yu Zhan and Yanan Zhai. Jieping Lei was involved interpreted the results. Guangjie Lv analyzed the data and drafted the paper. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Author details 1 Department of Cardiology, China-Japan Friendship Hospital, Beijing 100029, China; 2 Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing 100029, China; 3 National Clinical Research Center for Respiratory Diseases, Beijing 100029, China; 4 Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing 100029, China. 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Circ Cardiovasc Imaging, 2015,8(11):e3521, e3521. Austin C, Alassas K, Burger C, et al. Echocardiographic assessment of estimated right atrial pressure and size predicts mortality in pulmonary arterial hypertension[J]. Chest, 2015,147(1):198–208. Finkelhor R S, Scrocco J D, Madmani M, et al. Discordant Doppler right heart catheterization pulmonary artery systolic pressures: importance of pulmonary capillary wedge pressure[J]. Echocardiography, 2014,31(3):279–284. Amsallem M, Tedford R J, Denault A, et al. Quantifying the Influence of Wedge Pressure, Age, and Heart Rate on the Systolic Thresholds for Detection of Pulmonary Hypertension[J]. J Am Heart Assoc, 2020,9(11):e16265. Sawada N, Kawata T, Daimon M, et al. Detection of Pulmonary Hypertension with Systolic Pressure Estimated by Doppler Echocardiography[J]. Int Heart J, 2019,60(4):836–844. Greiner S, Jud A, Aurich M, et al. Reliability of noninvasive assessment of systolic pulmonary artery pressure by Doppler echocardiography compared to right heart catheterization: analysis in a large patient population[J]. J Am Heart Assoc, 2014,3(4):e1103. Groh G K, Levy P T, Holland M R, et al. Doppler echocardiography inaccurately estimates right ventricular pressure in children with elevated right heart pressure[J]. J Am Soc Echocardiogr, 2014,27(2):163–171. Vonk N A, Westerhof B E, Westerhof N. The Relationship Between the Right Ventricle and its Load in Pulmonary Hypertension[J]. J Am Coll Cardiol, 2017,69(2):236–243. Margonato D, Ancona F, Ingallina G, et al. Tricuspid Regurgitation in Left Ventricular Systolic Dysfunction: Marker or Target?[J]. Front Cardiovasc Med, 2021,8:702589. Amsallem M, Sternbach J M, Adigopula S, et al. Addressing the Controversy of Estimating Pulmonary Arterial Pressure by Echocardiography[J]. J Am Soc Echocardiogr, 2016,29(2):93–102. Hioka T, Kaga S, Mikami T, et al. Overestimation by echocardiography of the peak systolic pressure gradient between the right ventricle and right atrium due to tricuspid regurgitation and the usefulness of the early diastolic transpulmonary valve pressure gradient for estimating pulmonary artery pressure[J]. Heart Vessels, 2017,32(7):833–842. Parasuraman S, Walker S, Loudon B L, et al. Assessment of pulmonary artery pressure by echocardiography-A comprehensive review[J]. Int J Cardiol Heart Vasc, 2016,12:45–51. Kong D, Shu X, Pan C, et al. Evaluation of right ventricular regional volume and systolic function in patients with pulmonary arterial hypertension using three-dimensional echocardiography[J]. Echocardiography, 2012,29(6):706–712. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 27 Jan, 2022 Reviews received at journal 31 Dec, 2021 Reviewers agreed at journal 29 Dec, 2021 Reviewers agreed at journal 22 Dec, 2021 Reviewers agreed at journal 07 Dec, 2021 Reviewers agreed at journal 03 Dec, 2021 Reviewers agreed at journal 01 Dec, 2021 Reviewers invited by journal 24 Nov, 2021 Editor assigned by journal 24 Nov, 2021 Editor invited by journal 18 Nov, 2021 Submission checks completed at journal 18 Nov, 2021 First submitted to journal 16 Nov, 2021 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. 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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-1087290","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":64481915,"identity":"08796dcd-4765-4cef-9997-22b584aae355","order_by":0,"name":"Guangjie Lv","email":"","orcid":"","institution":"Department of Cardiology, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guangjie","middleName":"","lastName":"Lv","suffix":""},{"id":64481916,"identity":"23ebb8c8-0e42-40c4-b9b1-4d219a854ecc","order_by":1,"name":"Aili Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYFACHiA2sODhZ2Y+/IAULRI8ku1saQYkaGGQYDA4z6MgQZQGfvazBx/8KJCQMT7Mw2DAUGMTTVCLZE9esmEP0GFmh3kPPGA4lpbbQEiLwQ0eMwkesBa+BAPGhsOEtdgDtUj+AWoxbgZqJEoLyHxpkC0GzMRqkTiTY2wsA9QicRgYyAnE+IW//Yzhwzd/bOz5+w8ffvChxoawFlSQQJryUTAKRsEoGAW4AACf6TMRdu+9PgAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Cardiology, China-Japan Friendship Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Aili","middleName":"","lastName":"Li","suffix":""},{"id":64481917,"identity":"b78802ee-b43f-42d2-bebc-5fe7f260eff3","order_by":2,"name":"Xincao Tao","email":"","orcid":"","institution":"Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xincao","middleName":"","lastName":"Tao","suffix":""},{"id":64481918,"identity":"c5cd5b78-1331-4a51-a72a-09a9ce1053b0","order_by":3,"name":"Yanan Zhai","email":"","orcid":"","institution":"Department of Cardiology, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanan","middleName":"","lastName":"Zhai","suffix":""},{"id":64481919,"identity":"93cb7d26-c183-42ad-b293-2d1ff9bfa324","order_by":4,"name":"Yu Zhang","email":"","orcid":"","institution":"Department of Cardiology, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zhang","suffix":""},{"id":64481920,"identity":"97d74e37-9567-4e74-8876-e729ebb17e87","order_by":5,"name":"Jieping Lei","email":"","orcid":"","institution":"Institute of Clinical Medical Sciences, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jieping","middleName":"","lastName":"Lei","suffix":""},{"id":64481921,"identity":"3bd25725-15ab-4117-98c3-4d95ba645d3f","order_by":6,"name":"Qian Gao","email":"","orcid":"","institution":"Department of Cardiology, China-Japan Friendship Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Gao","suffix":""},{"id":64481922,"identity":"61fe58c3-1b86-4ea5-9734-d2da5d7f416f","order_by":7,"name":"Wanmu Xie","email":"","orcid":"","institution":"National Clinical Research Center for Respiratory Diseases","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wanmu","middleName":"","lastName":"Xie","suffix":""},{"id":64481923,"identity":"41724a2b-5c5c-4651-804f-9c73272ccd22","order_by":8,"name":"Zhenguo Zhai","email":"","orcid":"","institution":"National Clinical Research Center for Respiratory Diseases","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhenguo","middleName":"","lastName":"Zhai","suffix":""}],"badges":[],"createdAt":"2021-11-17 00:44:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1087290/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1087290/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16023713,"identity":"d05864d6-2df9-43eb-aeeb-21ffecf58a19","added_by":"auto","created_at":"2021-11-30 15:54:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":197982,"visible":true,"origin":"","legend":"Classification of the TR signal quality using continuous-wave Doppler. Type A, complete envelope; Type B, partial envelope but prone to extrapolation; Type C, unreliable envelope or no signal.","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/3ae6bdb9ad2ad9901b29ea0b.png"},{"id":16024241,"identity":"dd84c894-b176-4c8f-b428-dad4f21b24dd","added_by":"auto","created_at":"2021-11-30 15:57:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21267,"visible":true,"origin":"","legend":"Flow chart of patient screening","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/b57ef93fad7666bedbf9c89e.png"},{"id":16023758,"identity":"7adfaa63-8ad0-47ce-a1e4-aee8b8fac684","added_by":"auto","created_at":"2021-11-30 15:54:31","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":781519,"visible":true,"origin":"","legend":"Correlation of invasively determined parameters with TR derived parameters. pearson’s rank correlation coefficients are presented with 95% CI in brackets.","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/ec079c6c15bb6459ef6f95bf.jpeg"},{"id":16023715,"identity":"e9c14f5e-0dd1-46bf-a001-64b4a4914d04","added_by":"auto","created_at":"2021-11-30 15:54:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":117064,"visible":true,"origin":"","legend":"Bland–Altman plot showing the relationship between invasively determined parameters with TR derived parameters.","description":"","filename":"Fig04.png","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/3505ca7b8236c18e28c7e4b9.png"},{"id":16023748,"identity":"cf99916c-3c7b-4eac-92ac-5aef14e4fbfd","added_by":"auto","created_at":"2021-11-30 15:54:31","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":143762,"visible":true,"origin":"","legend":"Examples of different severity of TR with type A signal quality and accurate sPAPECHO.\nThe upper image presents a 40 years old female with mild TR whose sPAPECHO and sPAPRHC were 59 and 61 mmHg, respectively. The medium image shows a 50 years old female with moderate TR whose sPAPECHO and sPAPRHC were 60 and 60 mmHg, respectively. The lower image demonstrates a 34 years old female with severe TR whose sPAPECHO and sPAPRHC were 71 and 73 mmHg, respectively. \n\n","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/dd4807c5c85fc7a1d8e36361.jpeg"},{"id":16024252,"identity":"b790930f-3463-4d69-9832-e21d9c4e7ec0","added_by":"auto","created_at":"2021-11-30 15:57:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1133284,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1087290/v1/bfc34d3e-57d2-4652-b249-22e6629c8a55.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Accuracy and Influencing Factors of Doppler Echocardiography in Estimating Pulmonary Artery Systolic Pressure: Comparison With Right Heart Catheterization : A Retrospective Cross-sectional Study\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eRight heart catheter is recognized as the gold standard for measuring pulmonary artery pressure, but its\u003c/p\u003e \u003cp\u003einvasiveness limits its general applicability. While Doppler echocardiography can non-invasively assess pulmonary artery pressure in a variety of methods, such as peak velocity of tricuspid regurgitation (TR Vmax) and its derived parameters including TR pressure gradient (TR-PG), TR mean pressure gradient (TR-mPG), estimated mean pulmonary artery pressure (mPAP\u003csub\u003eECHO\u003c/sub\u003e) and pulmonary artery systolic pressure (sPAP\u003csub\u003eECHO\u003c/sub\u003e). But until now, there is no consensus on which echocardiographic method is better. The current guideline recommend TR Vmax to avoid extra error of the estimated right atrial pressure (RAP)\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Research has also found mPAP is superior than TR Vmax in identifying pulmonary hypertension (PH). However, mPAP\u003csub\u003eECHO\u003c/sub\u003e is obtained by tracing the Doppler-derived velocity-time integral of TR which is time-consuming and closely dependent on TR signal quality. While sPAP\u003csub\u003eECHO\u003c/sub\u003e as the most well-adopted approach in pulmonary hypertension (PH) screening has proved to be a reliable method\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. But whether sPAP\u003csub\u003eECHO\u003c/sub\u003e is superior to other parameters in determining the probability of PH was not examined previously. sPAP\u003csub\u003eECHO\u003c/sub\u003e can also provide valuable information in evaluating treatment response and even predicting prognosis\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. But high proportion of overestimation\u003c/p\u003e \u003cp\u003eor underestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e still remained\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In order to evaluate PH patients\u0026rsquo; condition appropriately and improve doctor\u0026rsquo;s diagnostic confidence, we need to understand in what kind of situation that sPAP\u003csub\u003eECHO\u003c/sub\u003e will be under or overestimated. Based on clinical experience and review of previous literature, we assumed that right ventricular systolic function, pulmonary artery pressure level, TR severity and signal quality would affect the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e. In addition, as a important parameter to distinguish pre-capillary and post-capillary PH, pulmonary artery wedge ressure (PAWP) was also included into analysis to see if there was any difference in the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e. Therefore, the first aim of this study was to compare the efficiency of sPAP\u003csub\u003eECHO\u003c/sub\u003e with other parameters in PH screening. And the second goal was to find influencing factors that account for the inaccuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eFrom October 2015 and October 2020, a total of 430 patients with known or suspected PH admitted to our center were evaluated. Inclusion criteria included: age \u0026ge;18 years old; the interval between echocardiography and RHC \u0026le;7 days; Exclusion criteria included: patients without TR, pulmonary artery stenosis or right ventricular outflow tract stenosis, poor image quality which are not suitable for analysis, ventricular septal defect or patent ductus arteriosus. Patient\u0026rsquo;s demographic and clinical data were obtained from the departmental electronic medical record. The institutional review board of the China-Japan Friendship Hospital waived the need for written patient informed consent as this study involved the retrospective analysis of clinically acquired data. The data underlying this article will be shared on reasonable request to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBaseline assessment of eligible patients including WHO functional class, the level of N-terminal pro B-type natriuretic peptide (NT-proBNP) and 6-minute walk test (6MWT) were recorded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRight heart catheterization\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHaemodynamic measurements were performed with a 7F Swan-Ganz catheter Philips Allura X-PER FD20 flat-plate angiography system (Baxter Inc). The system was zeroed and referenced at patients\u0026rsquo; heart level as previously described\u003csup\u003e[7]\u003c/sup\u003e. Right atrial pressure (RAP), pulmonary systolic artery pressure (sPAP\u003csub\u003eRHC\u003c/sub\u003e) and PAWP were recorded at end expiration in baseline over at least 3 heart cycles. Cardiac output (CO) was obtained using Fick\u0026rsquo;s method. Pulmonary vascular resistance (PVR), cardiac index, stroke volume, pulse pressure and diastolic pressure gradient were calculated using standard formulas. According to the tertiles of sPAP\u003csub\u003eRHC\u003c/sub\u003e, PH was classified into low, medium and high levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEchocardiography\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEchocardiographic images were acquired using a GE Vivid E95 machine (GE Healthcare, General Electric Healthcare) equipped with M5S phased-array transducers. Analysis was performed independently by two blinded investigators using EchoPAC software (GE Healthcare version 201).\u0026nbsp;Two-dimensional and Doppler echocardiography (DE) were performed on the basis of current guidelines. TR-PG was calculated from the TR Vmax obtained from continuous-wave Doppler by the simplified Bernoulli equation: TR-PG = 4 (TR Vmax)\u003csup\u003e2\u003c/sup\u003e.\u0026nbsp;TR-mPG\u0026nbsp;was obtained by tracing the time-velocity integral of TR. sPAP\u003csub\u003eECHO\u003c/sub\u003e and mPAP\u003csub\u003eECHO\u003c/sub\u003e were calculated by adding the estimated RAP to TR-PG and TR-mPG, respectively. RAP is divided into three categories (3, 8, and 15 mmHg) based on the inferior vena cava (IVC) diameter and its respiratory variation\u003csup\u003e[1]\u003c/sup\u003e. Noninvasive assessment of sPAP\u003csub\u003eECHO\u003c/sub\u003e was obtained by adding the right ventricle-right atrium pressure gradient (RV-RA PG) to the estimated RAP. The ratio of (sPAP\u003csub\u003eECHO\u003c/sub\u003e-sPAP\u003csub\u003eRHC\u003c/sub\u003e)/sPAP\u003csub\u003eRHC\u003c/sub\u003e was calculated and divided into three groups, namely, the underestimation group, accurate group and overestimation group by \u0026plusmn;10% as the boundary. The severity of TR was classified into 3 grades by comprehensively evaluating the regurgitation jet area and vena contracta (VC) width. The mild group was defined as jet area \u0026lt;5 cm\u003csup\u003e2\u003c/sup\u003e, VC TR \u0026le; 3 mm; the moderate group as jet area 5\u0026ndash;10 cm\u003csup\u003e2\u003c/sup\u003e, 3 mm \u0026lt; VCTR＜7 mm and severe group as jet area \u0026gt;10 cm\u003csup\u003e2\u003c/sup\u003e, VC TR \u0026ge;7 mm. The quality of the TR signal was classified into 3 types according to envelope visibility (\u003cstrong\u003eFig 1\u003c/strong\u003e, type A, complete envelope; type B, partial envelope but prone to\u0026nbsp;extrapolation; and type C,\u0026nbsp;unreliable envelope) as previously reported\u003csup\u003e[6]\u003c/sup\u003e. RV systolic function was assessed using multiple parameters, including RV wall thickness (RV WT), tricuspid annular plane systolic excursion (TAPSE), systolic annular tissue velocity of the lateral tricuspid annulus (S\u0026rsquo;) and RV fractional area change (FAC). All\u0026nbsp;parameters were repeatedly measured and averaged.\u0026nbsp;To determine the reproducibility of sPAP\u003csub\u003eECHO\u003c/sub\u003e measurements, a total of 34 randomly selected examinations were analyzed twice by a first investigator at a 1-week interval and once by a second investigator.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStandard statistical software (SPSS version 26 for Windows, SPSS, Chicago, IL, USA) was used for the statistical analysis. Data are expressed as mean\u0026plusmn;standard deviation for quantitative variables with normal distribution or as median (interquartile range) for variables without normal distribution. The correlation and consistency between TR derived parameters and RHC results were tested by Pearson and Bland-Altaman\u0026nbsp;methods. With mPAP \u0026ge; 25mmHg measured by RHC as the standard diagnostic criteria of PH, ROC curve was used to compared the diagnostic efficacy of sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003ewith other TR related methods. The influencing factors of sPAP\u003csub\u003eECHO\u003c/sub\u003e were analyzed by ordinal regression analysis. The intraclass correlation coefficient was used to determine inter- and intra-observer reproducibility for sPAP\u003csub\u003eE\u003c/sub\u003e\u003csub\u003eCHO\u003c/sub\u003e from 34 randomly selected patients using an identical cine-loop for each view. For all statistical tests, a \u003cem\u003eP\u003c/em\u003e value \u0026lt;0.05 was used to indicate significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatients characteristics\u003c/h2\u003e \u003cp\u003eA total of 218 patients were finally identified and analyzed, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Baseline demographics and clinical characteristics are described in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of patients was 50.9\u0026plusmn;13.3 years old, 40.3% were male, 197 (90.4%) patients had PH. No patient experienced major cardiac event between DE and RHC examinations. Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e lists the DE and RHC variables grouped by estimated accuracy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical and demographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.9\u0026plusmn;13.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90(41.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.67 (1.57, 1.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic BP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120(108, 132)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic BP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77(70, 87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76(68.65, 80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval between TTE and RHC, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5(1, 5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-pro BNP (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e451 (175, 1043)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6M WT (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e365.5\u0026plusmn;104.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO functional class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI Class(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII Class(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(42.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII Class(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89(40.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV Class(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(7.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (90.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdiopathic, heritable, drug and toxic induced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssociated with Connective tissue disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortal hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH due to left heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH due to lung disease and/or hypoxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic thromboembolic PH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH with unclear and/or multifactorial mechanisms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary veno-occlusive disease and/or pulmonary capillary haemangiomatosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-PH (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eValues are presented as mean \u0026plusmn; SD, median (IQR), or n (%).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eBMI, body mass index; TTE, transthoracic echocardiography; RHC, right heart catheterization; BP, blood pressure; NT-pro BNP, N-terminal pro B-type natriuretic peptide; 6M WT, 6-minutes walk test; PH, pulmonary hypertension.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable ordered analysis for accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverestimation (n=79)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAccurate\u003c/p\u003e \u003cp\u003e(n=81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUnderestimation (n=58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eUnivariable analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMultivariable analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEchocardiographic parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAD (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.1\u0026plusmn;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.9\u0026plusmn;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.4\u0026plusmn;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.997(0.974, 1.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVDD (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.4\u0026plusmn;7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.2\u0026plusmn;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.5\u0026plusmn;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.984(0.952,1.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV WT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.3\u0026plusmn;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4\u0026plusmn;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u0026plusmn;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.845(0.712,1.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAPSE(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.8\u0026plusmn;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.3\u0026plusmn;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.9\u0026plusmn;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.057(0.988,1.130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAC(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.6\u0026plusmn;9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8\u0026plusmn;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.7\u0026plusmn;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.029(0.998,1.061)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTR severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.031(0.441,2.408)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.386(0.560,3.431)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTR signal quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.525(0.309,0.892)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.258(0.138,0438)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.375(0.138,1.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.233(0.074,0.734)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCatheterization parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esPAP\u003csub\u003eRHC\u003c/sub\u003e level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (111.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.574(7.563,31.961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.561(9.574,48.554)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.279(2.752.10.125)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.125 (2.545,10.321)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esPAP\u003csub\u003eRHC\u003c/sub\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.5\u0026plusmn;19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.4\u0026plusmn;23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.4\u0026plusmn;23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.958(0.947,0.970)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u0026plusmn;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u0026plusmn;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.2\u0026plusmn;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.921(0.875,0.970)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVR(Wood Units)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4\u0026plusmn;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.2\u0026plusmn;6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0\u0026plusmn;8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.912(0.878,0.947)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAWP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.9\u0026plusmn;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.5\u0026plusmn;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.1\u0026plusmn;7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.932(0.889,0.977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.939(0.892,0.989)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emPAP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.6\u0026plusmn;35.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.3\u0026plusmn;14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.9\u0026plusmn;15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.961(0.944,0.978)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6M WT (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e370.9\u0026plusmn;105.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e355.9\u0026plusmn;123.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e367.8\u0026plusmn;84.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.000(0.996,1.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO functional class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.858(0.256,2.880)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.176(0.443,3.127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.052(0.395,2.805)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eRAD, right atrial diameter; RVDD, right ventricle diastolic diameter; RV WT, right ventricle wall thickness; TAPSE, tricuspid annular plane systolic excursion ; RV FAC, right ventricle fractional area change; RAP, right atrial pressure; PVR, pulmonary vascular resistance; PAWP, pulmonary artery wedge pressure; mPAP, mean pulmonary artery pressure. 6M WT, 6-minute walk test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eObserver Variability Of Spap Estimation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe intraclass correlation coefficient for inter-observer reproducibility of sPAP\u003csub\u003eECHO\u003c/sub\u003e was 0.988 (95% confidence interval 0.977\u0026ndash;0.994) and the intraclass correlation coefficient for intra-observer reproducibility of sPAP\u003csub\u003eECHO\u003c/sub\u003e was 0.992 (95% confidence interval 0.984\u0026ndash;0.996).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation Between Invasively Determined Parameters And Tr Derived Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the TR derived parameters including TR Vmax, TR-PG, TR-mPG, mPAP\u003csub\u003eECHO\u003c/sub\u003e and sPAP\u003csub\u003eECHO\u003c/sub\u003e showed positive correlation with related RHC results (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). sPAP\u003csub\u003eECHO\u003c/sub\u003e had the greatest correlation coefficient (r=0.782, P \u0026lt; 0.001). Bland-Altman analysis demonstrated low bias between RHC and echocardiographic results with wide limits of agreements (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The bias of sPAP\u003csub\u003eECHO\u003c/sub\u003e (mean bias= 0.07mmHg, 95% limits of agreement: -32.08 to +32.22mmHg) was lower than that of TR-PG (mean bias= 5.87mmHg, 95% limits of agreement: -26.46 to +38.21mmHg). The mean deviation between mPAP\u003csub\u003eECHO\u003c/sub\u003e, TR-mPG with mPAP\u003csub\u003eRHC\u003c/sub\u003e were -2.59mmHg (95% limits of agreement -26.29 to +21.11mmHg) and 3.32mmHg ( 95% limits of agreement -20.07 to +26.70mmHg), respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerformance Of Different Tr Methods For Predicting Ph\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ROC analysis showed TR Vmax, TR-PG, TR-mPG, mPAP\u003csub\u003eECHO\u003c/sub\u003e and sPAP\u003csub\u003eECHO\u003c/sub\u003e had similar diagnostic performance for determining the possibility of PH (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). There was no significant difference among the AUCs of these TR methods (\u003cem\u003eP\u003c/em\u003e༞0.05). However, the predictive efficiency and sensitivity of sPAP\u003csub\u003eECHO\u003c/sub\u003e were better than other methods. Of note, using Youden index quantification, the optimal cutoff value for our cohort was 55.5 mmHg for the sPAP\u003csub\u003eECHO\u003c/sub\u003e method. \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceiver Operating Characteristic Curve Analysis of DE Parameters for Detecting PH (mPAP\u0026ge; 25mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCut-off\u0026nbsp;value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003esensitivity\u0026nbsp;(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003especificity\u0026nbsp;(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eaccuracy(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePPV(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNPV(%)\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\u003esPAP\u003csub\u003eECHO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.5\u0026nbsp;mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTR\u0026nbsp;Vmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e361.5cm/s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTR-PG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.5mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emPAP\u003csub\u003eECHO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.6\u0026nbsp;mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e93.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTR-mPG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.6mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.83\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\"\u003ePPV: Positive predictive value; NPV: Negative predictive value. sPAP\u003csub\u003eECHO\u003c/sub\u003e: pulmonary systolic pressure estimated by echocardiography; TR Vmax: maximum velocity of tricuspid regurgitation; TR-PG: tricuspid regurgitation pressure gradient; mPAP\u003csub\u003eECHO\u003c/sub\u003e: mean pulmonary artery pressure estimated by echocardiography; TR-mPG: tricuspid regurgitation mean pressure gradient.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors Affecting The Accuracy Of Spap Estimation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were 79 patients (36.2%) in overestimated group, 81 patients (37.2%) in accurate group and 58 patients (26.6%) in underestimated group. sPAP\u003csub\u003eRHC\u003c/sub\u003e was divided into three levels according to its tertile (63mmHg, 85mmHg). Univariable ordinal analysis demonstrated that RV WT, FAC, TR signal quality, sPAP\u003csub\u003eRHC\u003c/sub\u003e level, RAP, PVR, PAWP and mPAP were associated with inaccuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e estimation (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). After multivariate ordinal regression analysis, it was found that TR signal quality, PAWP and sPAP\u003csub\u003eRHC\u003c/sub\u003e level affected the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e significantly (P \u0026lt; 0.05). The OR value of PAWP was 0.94 (95%CI: 0.89, 0.99). Compared with high sPAP\u003csub\u003eRHC\u003c/sub\u003e level, the OR value of low and medium sPAP\u003csub\u003eRHC\u003c/sub\u003e level were 21.56 (95%CI: 9.57, 48.55) and 5.13 (95%CI: 2.55, 10.32), respectively. Relative to the signal quality of type A, the OR value of type B and C signal quality were 0.26 (95%CI: 0.14, 0.48) and 0.23 (95%CI: 0.07, 0.73), respectively. While TR severity, RV systolic function parameters such as TAPSE, S\u0026rsquo; and FAC didn\u0026rsquo;t remain in the final equation.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eKey findings of our study: (1) Compared with TR Vmax and its derived parameters, sPAP\u003csub\u003eECHO\u003c/sub\u003e showed better sensitivity for predicting PH while maintaining similar specificity. (2) Patients with lower PAWP tends to overestimate sPAP\u003csub\u003eECHO\u003c/sub\u003e at lower sPAP\u003csub\u003eRHC\u003c/sub\u003e level, even with\u0026nbsp;good TR signal quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerformance of sPAP\u003csub\u003eECHO\u003c/sub\u003e in PH screening\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our study, sPAP\u003csub\u003eECHO\u003c/sub\u003e exhibited best correlation with sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003eand was superior to TR Vmax and its derived methods in PH screening. Compared with mPAP\u003csub\u003eECHO\u003c/sub\u003e, sPAP\u003csub\u003eECHO\u003c/sub\u003e is more convenient to measure. As a derived variables of TR Vmax, sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003edidn\u0026rsquo;t amplify measurement errors in assessing pulmonary artery pressure as indicated by the currents guideline, on the contrary, it showed better sensitivity while maintaining similar specificity. Relative to TR-PG and TR-mPG, sPAP\u003csub\u003eECHO\u003c/sub\u003e contains more information from RAP which may accounts for its better accuracy and lower bias.\u0026nbsp;RAP would elevate with the increase of RV overload\u003csup\u003e[8]\u003c/sup\u003e, it is an important measurement that provides heart failure and prognostic information\u003csup\u003e[9]\u003c/sup\u003e.\u0026nbsp;Hellenkamp\u0026rsquo;s study on mPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003ealso supported RAP is of additional diagnostic value in predicting PH\u003csup\u003e[2]\u003c/sup\u003e.\u0026nbsp;In a word,\u0026nbsp;sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003eas a simple and reliable parameter is more suitable than other TR related methods for clinical practice in PH screening.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReasons for inaccuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e estimation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, our data suggested patients with lower PAWP tended to overestimate sPAP\u003csub\u003eECHO\u003c/sub\u003e. Finkelhor et al also found PAWP had a strong inverse correlation with the difference between sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003eand sPAP\u003csub\u003eECHO\u003c/sub\u003e too\u003csup\u003e[2]\u003c/sup\u003e. They speculated that elevated left atrial pressure can be transmitted to the right atrium via the shared inter-atrial septum as well as through pericardial constraint and limit TR velocities, thus the accuracy of sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003ewill be affected. Even though the mechanism of how PAWP affects pulmonary artery pressure is still unclear, interestingly, more and more studies are beginning to notice this phenomenon. Amsallem et al found patients with higher PAWP is associated with lower\u0026nbsp;sPAP\u003csub\u003eECHO\u003c/sub\u003e thresholds for PH diagnosis\u003csup\u003e[11]\u003c/sup\u003e.\u0026nbsp;Our result supported this view in the opposite way. Pre-capillary PH patients with lower PAWP accounted for 85.8% of our population, and the optimal cut-off value of our cohort was 55.5 mmHg which is higher than previous studies focusing on post-capillary\u0026nbsp;PH patients with higher PAWP\u003csup\u003e[12, 13]\u003c/sup\u003e. We speculated the underestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e due to high PAWP leads to lower\u0026nbsp;sPAP\u003csub\u003eECHO\u003c/sub\u003e threshold for post-capillary PH. In contrast, the higher sPAP\u003csub\u003eECHO\u003c/sub\u003e threshold of pre-capillary PH might be associated with overestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e because of\u003csub\u003e\u0026nbsp;\u003c/sub\u003elower PAWP. Therefore, a higher sPAP\u003csub\u003eECHO\u003c/sub\u003e threshold for determining pre-capillary PH is more appropriate. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecond, for the effect of sPAP\u003csub\u003eRHC\u003c/sub\u003e level on the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e, Groh et al found DE inaccurately estimated right ventricular pressure in children with elevated right heart pressure\u003csup\u003e[14]\u003c/sup\u003e. Our results provided further evidence that DE tended to overestimate\u0026nbsp;sPAP\u003csub\u003eRHC\u003c/sub\u003e at low sPAP\u003csub\u003eRHC\u003c/sub\u003e level and increasingly underestimated the sPAP\u003csub\u003eRHC\u003c/sub\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003ewith the advance of sPAP\u003csub\u003eRHC\u003c/sub\u003e level.\u0026nbsp;We assumed that the coupling mechanism between RV contractility and its load may account for this phenomenon. sPAP\u003csub\u003eRHC\u003c/sub\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003eis mildly elevated during the initial phase of PH, RV coupling is maintained by a 4- to 5-fold increase in contractility through muscle hypertrophy as well as changes in muscle properties\u003csup\u003e[15]\u003c/sup\u003e. The compensatory\u0026nbsp;enhancement of RV contractility\u003csup\u003e[16]\u003c/sup\u003e would\u0026nbsp;make TR\u0026nbsp;Vmax become higher, sPAP\u003csub\u003eRHC\u003c/sub\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003ewill be overestimated by DE, while the pulmonary artery pressure is still in the normal range due to the natural vascular elasticity. As sPAP\u003csub\u003eRHC\u003c/sub\u003e increased moderately, the compensatory contractility of RV would halt and the stroke volume would decrease, but CO is maintained by increasing heart rate. At this stage of PH, the estimation of sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003eby DE is relatively reliable. However, sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003ewould become higher with the development of PH, when RV uncoupling occurs, CO would reduce which will result in increasing of RV preload. The elevated RV preload and RAP would lead to a decreased right atrial-ventricular pressure gradient, thus DE would underestimate the sPAP\u003csub\u003eRHC\u003c/sub\u003e. sPAP\u003csub\u003eRHC\u003c/sub\u003e level may affect the accuracy of sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003ethrough coupling mechanism between RV contractility and its load, but studies with larger sample sizes are needed test this hypothesis.\u003c/p\u003e\n\u003cp\u003eThird, our finding confirmed previous reports that the TR signal quality would affect the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e\u003csup\u003e[17]\u003c/sup\u003e. Except poor signal quality of TR leads to underestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e, we also found good signal quality also brings overestimation of sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003efor some cases. As in our cohort, 41% of patients who obtained type A signal quality of TR still overestimated sPAP\u003csub\u003eECHO\u003c/sub\u003e. After further analysis, we found lower sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003elevel and PAWP were significantly associated with overestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e for patients with type A signal quality. This phenomenon suggests we cannot simply rely on good signal quality, attention should also be given to patients with pre-capillary PH, especially during the initial stage of disease, cause TR signal quality, sPAP\u003csub\u003eRHC\u0026nbsp;\u003c/sub\u003elevel and PAWP work together to affect the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, there is no consensus on how TR severity would interfere the accuracy of the sPAP\u003csub\u003eECHO\u003c/sub\u003e. Hioka et al reported that echocardiography increasingly overestimated the TR PG with the advance of TR severity, as was theoretically predicted by the pressure recovery phenomenon associated with the laminar regurgitant flow\u003csup\u003e[18]\u003c/sup\u003e. But Parasuraman et al reported that severe TR could cause equalisation of right atrial and ventricular pressures which may cause the TR Doppler envelope to be cut short, leading to underestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e\u003csup\u003e[19]\u003c/sup\u003e. Our study differed from other studies in that the TR severity did not significantly affect the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e. On the one hand, only 9.6% of patients in our cohort had severe TR which is in line with the actual clinical situation that severe TR only appears in the minority of the total patients. On the other hand, patients with mild or moderate TR could also obtained type A signal quality and estimate sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003eappropriately (\u003cstrong\u003eFig 5\u003c/strong\u003e)\u003cstrong\u003e.\u003c/strong\u003e TR severity was also affected by RV contractility and dimension. So the overall impact of TR severity to the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e is not as significant as TR signal quality.\u003c/p\u003e\n\u003cp\u003eAt last, we didn\u0026rsquo;t find RV systolic parameters have significant impact on the accuracy of sPAP\u003csub\u003eECHO\u0026nbsp;\u003c/sub\u003eneither.\u003csub\u003e\u0026nbsp;\u003c/sub\u003eTheoretically, RV systolic function will gradually decrease\u003csup\u003e[20]\u003c/sup\u003e, but the RV can remain coupled for the large increase in load by increasing contractility until heart failure\u003csup\u003e[15]\u003c/sup\u003e. Therefore, RV systolic parameters are relatively stable before the end stage of PH. In addition, the heart movement and measurement angle dependence also affect the accuracy of the relevant parameters. Although RV systolic parameters had clinical significance for the assessment of PH, they didn\u0026rsquo;t have significant effect on the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations that merits emphasis. First, this is a retrospective research with a small sample size. 90.5% had PH and 47.7% of them were due to chronic pulmonary thromboembolism, the sample size of other type PH was relatively small. Thus we couldn\u0026rsquo;t give specific suggestion for each type of PH. Furthermore, we included patients who underwent RHC and echocardiography within 7 days due to the restriction of clinical actual conditions. But the average interval time was 3 days in this study, and the majority of our patients have pre-capillary PH which indicates the patient\u0026apos;s hemodynamics are relatively stable and wouldn\u0026rsquo;t change dramatically during this short time. At last, the single-center nature of the present study limited generalization.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003esPAP\u003csub\u003eECHO\u003c/sub\u003e was superior to other TR-related methods in PH screening, and was often overestimated in patients with pre-capillary PH at low sPAP\u003csub\u003eRHC\u003c/sub\u003e level, even with good TR signal quality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eFull Title\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePulmonary Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRight Heart\u0026nbsp;Catheterization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eDoppler Echocardiography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTricuspid Regurgitation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003esPAP\u003csub\u003eRHC\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePulmonary Artery Systolic Pressure measured by RHC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003esPAP\u003csub\u003eECHO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePulmonary Artery Systolic Pressure estimated by DE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003emPAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eMean Pulmonary Artery Pressure\u0026nbsp;measured by RHC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003emPAP\u003csub\u003eECHO\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eMean Pulmonary Artery Pressure\u0026nbsp;estimated\u0026nbsp;by\u0026nbsp;DE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePAWP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePulmonary Artery Wedge Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRight Atrial Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCardiac output\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTR PG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTR Pressure Gradient\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTR-mPG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTR Mean Pressure Gradient\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePVR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePulmonary Vascular Resistance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRight Ventricle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRV WT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRV Wall Thickness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTAPSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTricuspid Annular Plane Systolic Excursion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;S\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eSystolic Annular Tissue Velocity of the Lateral Tricuspid Annulus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eFAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eRV Fractional Area Change\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eIVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eInferior Vena Cava\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;: This study was supported by grants from the National Natural Key Clinical Specialty Construction Project (2020-QTL-009) and the Capital Health Development Research Project (2020-2-4063).\u003c/p\u003e\n\u003cp id=\"isPasted\"\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study complied with the Declaration of Helsinki. Ethical approval number was 2020-95-K59. The protocol was approved by the Ethic Committee of China-Japan Friendship Hospital. The institutional review board of the China-Japan Friendship Hospital waived the need for written patient informed consent as this study involved the retrospective analysis of clinically acquired data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Aili Li searched relevant literature and conceived the study. Zhenguo Zhai, Xincao Tao and Wanmu Xie were involved in research Implementation. Material preparation and data collection were performed by Qian Gao, Yu Zhan and Yanan Zhai. Jieping Lei was involved interpreted the results. Guangjie Lv analyzed the data and drafted the paper. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Cardiology, China-Japan Friendship Hospital, Beijing 100029, China; \u003csup\u003e2\u003c/sup\u003eDepartment of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing 100029, China; \u003csup\u003e3\u003c/sup\u003eNational Clinical Research Center for Respiratory Diseases, Beijing 100029, China; \u003csup\u003e4\u003c/sup\u003eInstitute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing 100029, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGalie N, Humbert M, Vachiery J L, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT)[J]. Eur Respir J, 2015,46(4):903\u0026ndash;975.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHellenkamp K, Unsold B, Mushemi-Blake S, et al. Echocardiographic Estimation of Mean Pulmonary Artery Pressure: A Comparison of Different Approaches to Assign the Likelihood of Pulmonary Hypertension[J]. J Am Soc Echocardiogr, 2018,31(1):89\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreiner S, Jud A, Aurich M, et al. Reliability of noninvasive assessment of systolic pulmonary artery pressure by Doppler echocardiography compared to right heart catheterization: analysis in a large patient population[J]. J Am Heart Assoc, 2014,3(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantiago-Vacas E, Lupon J, Gavidia-Bovadilla G, et al. Pulmonary hypertension and right ventricular dysfunction in heart failure: prognosis and 15-year prospective longitudinal trajectories in survivors[J]. Eur J Heart Fail, 2020,22(7):1214\u0026ndash;1225.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJalalian R, Moghadamnia A A, Tamaddoni A, et al. Comparing the Efficacy of Tadalafil Versus Placebo on Pulmonary Artery Systolic Pressure and Right Ventricular Function in Patients with Beta-Thalassaemia Intermedia[J]. Heart Lung Circ, 2017,26(7):677\u0026ndash;683.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Wang Y, Li H, et al. Evaluation of the hemodynamics and right ventricular function in pulmonary hypertension by echocardiography compared with right-sided heart catheterization[J]. Exp Ther Med, 2017,14(4):3616\u0026ndash;3622.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishnan A, Markham R, Savage M, et al. Right Heart Catheterisation: How To Do It[J]. Heart Lung Circ, 2019,28(4):e71-e78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuerejeta R G, Campbell P, Claggett B, et al. Right Atrial Function in Pulmonary Arterial Hypertension[J]. Circ Cardiovasc Imaging, 2015,8(11):e3521, e3521.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustin C, Alassas K, Burger C, et al. Echocardiographic assessment of estimated right atrial pressure and size predicts mortality in pulmonary arterial hypertension[J]. Chest, 2015,147(1):198\u0026ndash;208.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinkelhor R S, Scrocco J D, Madmani M, et al. Discordant Doppler right heart catheterization pulmonary artery systolic pressures: importance of pulmonary capillary wedge pressure[J]. Echocardiography, 2014,31(3):279\u0026ndash;284.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmsallem M, Tedford R J, Denault A, et al. Quantifying the Influence of Wedge Pressure, Age, and Heart Rate on the Systolic Thresholds for Detection of Pulmonary Hypertension[J]. J Am Heart Assoc, 2020,9(11):e16265.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSawada N, Kawata T, Daimon M, et al. Detection of Pulmonary Hypertension with Systolic Pressure Estimated by Doppler Echocardiography[J]. Int Heart J, 2019,60(4):836\u0026ndash;844.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreiner S, Jud A, Aurich M, et al. Reliability of noninvasive assessment of systolic pulmonary artery pressure by Doppler echocardiography compared to right heart catheterization: analysis in a large patient population[J]. J Am Heart Assoc, 2014,3(4):e1103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroh G K, Levy P T, Holland M R, et al. Doppler echocardiography inaccurately estimates right ventricular pressure in children with elevated right heart pressure[J]. J Am Soc Echocardiogr, 2014,27(2):163\u0026ndash;171.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVonk N A, Westerhof B E, Westerhof N. The Relationship Between the Right Ventricle and its Load in Pulmonary Hypertension[J]. J Am Coll Cardiol, 2017,69(2):236\u0026ndash;243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMargonato D, Ancona F, Ingallina G, et al. Tricuspid Regurgitation in Left Ventricular Systolic Dysfunction: Marker or Target?[J]. Front Cardiovasc Med, 2021,8:702589.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmsallem M, Sternbach J M, Adigopula S, et al. Addressing the Controversy of Estimating Pulmonary Arterial Pressure by Echocardiography[J]. J Am Soc Echocardiogr, 2016,29(2):93\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHioka T, Kaga S, Mikami T, et al. Overestimation by echocardiography of the peak systolic pressure gradient between the right ventricle and right atrium due to tricuspid regurgitation and the usefulness of the early diastolic transpulmonary valve pressure gradient for estimating pulmonary artery pressure[J]. Heart Vessels, 2017,32(7):833\u0026ndash;842.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParasuraman S, Walker S, Loudon B L, et al. Assessment of pulmonary artery pressure by echocardiography-A comprehensive review[J]. Int J Cardiol Heart Vasc, 2016,12:45\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong D, Shu X, Pan C, et al. Evaluation of right ventricular regional volume and systolic function in patients with pulmonary arterial hypertension using three-dimensional echocardiography[J]. Echocardiography, 2012,29(6):706\u0026ndash;712.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Doppler echocardiography, Pulmonary hypertension, Right heart catheterization, Tricuspid regurgitation","lastPublishedDoi":"10.21203/rs.3.rs-1087290/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1087290/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u0026nbsp;Noninvasive assessment of pulmonary artery systolic pressure by Doppler echocardiography (sPAP\u003csub\u003eECHO\u003c/sub\u003e) has been widely adopted to screen for pulmonary hypertension (PH). But high proportion of overestimation or underestimation of sPAP\u003csub\u003eECHO\u003c/sub\u003e still remained. So we aimed to explore the accuracy and influencing factors of sPAP\u003csub\u003eECHO\u003c/sub\u003e with right heart catheterization (RHC) as reference. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA total of 218 highly suspected pulmonary hypertension (PH) patients who underwent RHC and echocardiography within 7 days were included. The correlation and consistency between tricuspid regurgitation (TR) derived parameters and RHC results were tested by Pearson and Bland-Altaman methods. With mPAP ≥25mmHg measured by RHC as the standard diagnostic criteria of PH, ROC curve was used to compared the diagnostic efficacy of sPAP\u003csub\u003eECHO \u003c/sub\u003ewith other TR related methods. The ratio of (sPAP\u003csub\u003eECHO\u003c/sub\u003e-sPAP\u003csub\u003eRHC\u003c/sub\u003e)/sPAP\u003csub\u003eRHC\u003c/sub\u003e was calculated and divided into three groups, namely, the underestimation group, accurate group and overestimation group by ±10% as the boundary. The influencing factors of sPAP\u003csub\u003eECHO\u003c/sub\u003e were analyzed by ordinal regression analysis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e sPAP\u003csub\u003eECHO\u003c/sub\u003e had the greatest correlation coefficient (r=0.781, P\u0026lt;0.001), best diagnostic efficiency (AUC=0.98) and lowest bias\u003csub\u003e \u003c/sub\u003e(mean bias= 0.07mmHg, 95% limits of agreement: -32.08 to +32.22mmHg) compared with other TR related methods. Ordinal regression analysis showed that TR signal quality, PAWP and sPAP\u003csub\u003eRHC\u003c/sub\u003e level affected the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e (P \u0026lt; 0.05). The OR value of PAWP was 0.94 (95%CI: 0.89, 0.99). Compared with high sPAP\u003csub\u003eRHC\u003c/sub\u003e level, the OR value of low and medium sPAP\u003csub\u003eRHC \u003c/sub\u003elevel were 21.56 (95%CI: 9.57, 48.55) and 5.13 (95%CI: 2.55, 10.32) , respectively. Relative to the signal quality of type A, the OR value of type B and C signal quality were 0.26 (95%CI: 0.14, 0.48) and 0.23 (95%CI: 0.07, 0.73), respectively. While TR severity and right ventricular systolic function had no significant effect on the accuracy of sPAP\u003csub\u003eECHO\u003c/sub\u003e. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003esPAP\u003csub\u003eECHO\u003c/sub\u003e was superior to other TR-related methods in PH screening, and was often overestimated in patients with pre-capillary PH at low sPAP\u003csub\u003eRHC\u003c/sub\u003e level, even with good TR signal quality.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration: \u003c/strong\u003eThis is a retrospectively registered study.\u003c/p\u003e","manuscriptTitle":"The Accuracy and Influencing Factors of Doppler Echocardiography in Estimating Pulmonary Artery Systolic Pressure: Comparison With Right Heart Catheterization : A Retrospective Cross-sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-30 15:54:29","doi":"10.21203/rs.3.rs-1087290/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-01-27T06:22:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-12-31T09:27:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1fbe72e6-566f-4be4-a7de-a6a8eb92866a","date":"2021-12-29T18:31:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9afff6fb-8adc-432a-8cca-cb6379338c08","date":"2021-12-22T12:35:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"ecce8866-df40-4d44-b9f2-cf601d0fe180","date":"2021-12-07T07:06:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170c0df0-8049-4ef8-b854-3d04cb149cee","date":"2021-12-03T18:06:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"fa7d14a9-1ec8-49b1-9aad-85b468e7d0e1","date":"2021-12-01T20:00:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-11-24T07:00:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-11-24T06:47:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-11-19T02:38:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-11-19T02:36:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2021-11-17T00:35:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aacea772-8fe8-4ede-a53b-e5fef4617dcf","owner":[],"postedDate":"November 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":8727712,"name":"Medical Genetics"}],"tags":[],"updatedAt":"2022-04-22T09:44:23+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-30 15:54:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1087290","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1087290","identity":"rs-1087290","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}