Elevated Pulmonary Artery Wedge Pressure Research Articles

Improved Interpretation of Pulmonary Artery Wedge Pressures through Left Atrial Volumetry-A Cardiac Magnetic Resonance Imaging Study.

The pulmonary artery wedge pressure (PAWP) is regarded as a reliable indicator of left ventricular end-diastolic pressure (LVEDP), but this association is weaker in patients with left-sided heart disease (LHD). We compared morphological differences in cardiac magnetic resonance imaging (CMR) in patients with heart failure (HF) and a reduced left ventricular ejection fraction (LVEF), with or without elevation of PAWP or LVEDP. We retrospectively identified 121 patients with LVEF < 50% who had undergone right heart catheterization (RHC) and CMR. LVEDP data were available for 75 patients. The mean age of the study sample was 63 ± 14 years, the mean LVEF was 32 ± 10%, and 72% were men. About 53% of the patients had an elevated PAWP (>15 mmHg). In multivariable logistic regression analysis, NT-proBNP, left atrial ejection fraction (LAEF), and LV end-systolic volume index independently predicted an elevated PAWP. Of the 75 patients with available LVEDP data, 79% had an elevated LVEDP, and 70% had concomitant PAWP elevation. By contrast, all but one patient with elevated PAWP and half of the patients with normal PAWP had concomitant LVEDP elevation. The Bland-Altman plot revealed a systematic bias of +5.0 mmHg between LVEDP and PAWP. Notably, LAEF was the only CMR variable that differed significantly between patients with elevated LVEDP and a PAWP ≤ or >15 mmHg. In patients with LVEF < 50%, a normal PAWP did not reliably exclude LHD, and an elevated LVEDP was more frequent than an elevated PAWP. LAEF was the most relevant determinant of an increased PAWP, suggesting that a preserved LAEF in LHD may protect against backward failure into the lungs and the subsequent increase in pulmonary pressure.

Non-invasive assessment of left ventricular filling pressure in aortic stenosis.

The assessment of left ventricular (LV) filling pressure (FP) is important for the management of aortic stenosis (AS) patients. Although, it is often restricted for predict LV FP in AS because of mitral annular calcification and a certain left ventricular hypertrophy. Thus, we tested the predictive ability of the algorithm for elevated LV FP in AS patients and also applied a recently-proposed echocardiographic scoring system of LV FP, visually assessed time difference between the mitral valve and tricuspid valve opening (VMT) score. We enrolled consecutive 116 patients with at least moderate AS in sinus rhythm who underwent right heart catheterization and echocardiography within 7 days. Mean pulmonary artery wedge pressure (PAWP) was measured as invasive parameter of LV FP. LV diastolic dysfunction (DD) was graded according to the ASE/EACVI guidelines. The VMT score was defined as follows: time sequence of opening of mitral and tricuspid valves was scored to 0-2 (0: tricuspid valve first, 1: simultaneous, 2: mitral valve first). When the inferior vena cava was dilated, one point was added and VMT score was finally calculated as 0-3. Of the 116 patients, 29 patients showed elevated PAWP. Ninety patients (93%) and 67 patients (63%) showed increased values for left atrium volume index (LAVI) and E/e', respectively when the cut-off values recommended by the guidelines were applied and thus the algorism predicted elevated PAWP with a low specificity and positive predictive value (PPV). VMT≥2 predicted elevated PAWP with a sensitivity of 59%, specificity of 90%, PPV of 59%, and negative predictive value of 89%. An alternative algorithm that applied tricuspid regurgitation velocity and VMT scores was tested, and its predictive ability was markedly improved. VMT score was applicable for AS patients. Alternative use of VMT score improved diagnostic accuracy of guideline-recommended algorism.

Exercise catheterization in adults post-Fontan with normal and abnormal haemodynamic criteria: Insights into normal Fontan physiology.

The normal (i.e. expected) haemodynamics in adults post-Fontan remain poorly delineated. Moreover, the definitions of elevated exercise pulmonary artery (PA) and PA wedge pressure (PAWP) for this population have not been described. Seventy-two adults post-Fontan undergoing exercise catheterization were categorized into abnormal (Group I, n = 59; defined as resting mean PA ≥14 mmHg and/or PAWP ≥12 mmHg, ΔPAWP/Δsystemic flow [Qs] >2 mmHg/L/min, and/or ΔPA/Δpulmonary flow >3 mmHg/L/min) and normal (Group II, n = 13) haemodynamics. Thirty-nine patients with non-cardiac dyspnoea (NCD) were included as controls. There was no difference in exercise arterial oxygen saturation (87% [81-92] vs. 89% [85-93], p = 0.29), while exercise PA pressure (27 [23-31] vs. 16 [14.5-19.5] mmHg, p < 0.001) and PAWP were higher (21 [18-28] vs. 12 [8-14] mmHg, p < 0.001) in Group I. At peak exercise, Group I had lower heart rate (97 [81-120] vs. 133 [112.5-147.5] bpm, p < 0.001) and Qs response (67.3 [43.8-93.1] vs. 105.9 (82-118.5) % predicted, p < 0.001) than Group II. Exercise superior vena cava pressures were higher (16 [14-22.5] vs. 5.5 [3-7.3] mmHg, p < 0.001) and arterial oxygen saturation lower (89% [85-93] vs. 97% [96-98], p < 0.001) in Group II compared to NCD, while no differences in PAWP, stroke volume index, heart rate, or Qs response were seen. If defined as two standard deviations above mean values for Group II, elevated PAWP and mean PA pressure post-Fontan would correspond to 20.6 mmHg and 25.8 mmHg, respectively. PAWP >20 mmHg and mean PA pressure >25 mmHg could be used to define elevated values during exercise in adults post-Fontan. The major discrepancy in exercise haemodynamics among Group II compared to controls appears to be the degree of systemic venous hypertension and arterial desaturation.

Application of a novel echocardiographic scoring system to estimate left ventricular filling pressure in aortic stenosis

Abstract Background Despite the increased number of aortic stenosis (AS) patients, non-invasive estimation of the left ventricular (LV) filling pressure (FP) is often challenging partly because of unavailability of E/e' due to the presence of mitral annular calcification (MAC). Recently, an echocardiographic scoring system to estimate LVFP, visually assessed time difference between the mitral valve and tricuspid valve opening (VMT) score was proposed. Because VMT score can be applied for patients with significant MAC, we hypothesized that VMT score could be an alternative parameter of E/e' in AS. Purpose To test whether VMT score could be used as an alternative marker of LVFP to E/e' in AS patients. Methods We enrolled consecutive 116 patients with at least moderate AS in sinus rhythm who underwent right heart catheterization and echocardiography within 7 days. Mean pulmonary artery wedge pressure (PAWP) was measured as invasive parameter of LVFP. LV diastolic dysfunction (DD) was graded according to the ASE / EACVI guidelines. Using two-dimensional echocardiographic images, time sequence of opening of mitral and tricuspid valves was assessed and scored to 0 to 2 (0: tricuspid valve first, 1: simultaneous, 2: mitral valve first). This was based on the phenomenon in which early-diastolic opening of the mitral valve becomes earlier than tricuspid valve with an increase in LV FP and pulmonary artery pressure. When the inferior vena cava was dilated, 1 point was added and VMT score was finally calculated as 0 to 3. Results Overall, PAWP was 12±7 mmHg and elevated (≥15 mmHg) in 29 patients. MAC was observed in 82 patients. Although E/e' was higher in patients with elevated PAWP than in those without (23±11 vs 18±8, P=0.007), its predictive ability to elevated PAWP was non-significant (c-index: 0.59, P=0.13), resulting in low specificity of DD grading to predict elevated LVFP (sensitivity: 79%, specificity: 36%). In contrast, VMT score predicted elevated LVFP with c-index of 0.74 (P&amp;lt;0.001). When VMT score was used instead of E/e', diagnostic accuracy of DD grading was improved (c-index: 0.57 vs 0.82, P&amp;lt;0.001). Conclusion VMT score could be an alternative marker of LVFP to E/e' in AS patients.

Lung ultrasonography derived B-line scores as predictors of left ventricular end-diastolic pressure and pulmonary artery wedge pressure

BackgroundNon-invasive assessment of elevated left ventricular end-diastolic pressure (LVEDP) and pulmonary artery wedge pressure (PAWP) in patients with heart diseases is challenging. Lung ultrasonography (LUS) is a promising modality for predicting LVEDP and PAWP. MethodsFifty-seven stable ambulatory patients who underwent right and left heart catheterization were included. Following the procedures, LUS was performed in twenty-eight ultrasonographic zones, and the correlation between five different LUS derived B-line scores with LVEDP and PAWP was examined. ResultsThe B-line index correlated with LVEDP and PAWP, with coefficients of 0.45 (p = 0.006) and 0.30 (p = 0.03), respectively. B-line index showed an AUC of 0.76 for identifying LVEDP > 15 mmHg (p = 0.01) and an AUC of 0.73 for identifying PAWP > 15 mmHg (p = 0.008). Overall, scores performances were similar in predicting LVEDP or PAWP > 15 mmHg. A B-line index ≥ 28 was significantly associated with LVEDP > 15 mmHg (OR: 9.97) and PAWP > 15 mmHg (OR: 6.61), adjusted for age and indication for heart catheterization. ConclusionsLUS derived B-line scores are moderately correlated with PAWP and LVEDP in patients with heart diseases. A B-line index ≥ 28 can be used to predict elevated LVEDP and PAWP with high specificity.

Deep learning approach for analyzing chest x-rays to predict cardiac events in heart failure.

A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF). The aim of this study was to (1) investigate the role of probability of elevated PAWP for the prediction of clinical outcomes in association with other parameters, and (2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP. Readmission following HF and cardiac mortality were the primary endpoints. Probability of elevated PAWP was associated with diastolic function by echocardiography. During a median follow-up period of 58 months, 57 individuals either died or were readmitted. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge was associated with event free survival, independent of elevated left atrial pressure (LAP) based on echocardiographic guidelines (p < 0.001). In sequential Cox models, a model based on clinical data was improved by elevated LAP (p = 0.005), and increased further by probability of elevated PAWP (p < 0.001). In contrast, the addition of pulmonary congestion interpreted by a doctor did not statistically improve the ability of a model containing clinical variables (compared p = 0.086). This study showed the potential of using a DL model on a chest x-ray to predict PAWP and its ability to add prognostic information to other conventional clinical prognostic factors in HF. The results may help to enhance the accuracy of prediction models used to evaluate the risk of clinical outcomes in HF, potentially resulting in more informed clinical decision-making and better care for patients.

Pathogenesis of pulmonary hypertension caused by left heart disease.

Pulmonary hypertension has high disability and mortality rates. Among them, pulmonary hypertension caused by left heart disease (PH-LHD) is the most common type. According to the 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension, PH-LHD is classified as group 2 pulmonary hypertension. PH-LHD belongs to postcapillary pulmonary hypertension, which is distinguished from other types of pulmonary hypertension because of its elevated pulmonary artery wedge pressure. PH-LHD includes PH due to systolic or diastolic left ventricular dysfunction, mitral or aortic valve disease and congenital left heart disease. The primary strategy in managing PH-LHD is optimizing treatment of the underlying cardiac disease. Recent clinical studies have found that mechanical unloading of left ventricle by an implantable non-pulsatile left ventricular assist device with continuous flow properties can reverse pulmonary hypertension in patients with heart failure. However, the specific therapies for PH in LHD have not yet been identified. Treatments that specifically target PH in LHD could slow its progression and potentially improve disease severity, leading to far better clinical outcomes. Therefore, exploring the current research on the pathogenesis of PH-LHD is important. This paper summarizes and classifies the research articles on the pathogenesis of PH-LHD to provide references for the mechanism research and clinical treatment of PH-LHD, particularly molecular targeted therapy.

Abstract 14409: Deep Learning Approach for Analyzing Chest X-rays to Predict Cardiac Events in Heart Failure

Introduction: A deep learning (DL) model based on a chest X-ray (CXR) was reported to predict elevated pulmonary artery wedge pressure (PAWP) as congestive heart failure (HF). Hypothesis: We hypothesize that a previously developed application of a CXR-based DL algorithm could also be used to predict re-hospitalized HF in patients with HF. This study aimed to 1) investigate the role of probability of elevated PAWP to predict clinical outcomes in association with other parameters, and 2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. Methods: We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP in the study cohort. The primary endpoint was readmission following HF and cardiac death. Results: Probability of elevated PAWP was associated with echocardiographic parameters including left atrial size, filling pressure, and pulmonary artery pressure. During a median follow-up period of 58 months, 57 patients were either readmitted or died. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge (per 1SD) was associated with event free survival, independent of elevated left atrial pressure (LAP) by echocardiography (hazard ratio:1.39, 95%CI:1.17-1.65, p&lt;0.001). In sequential Cox models, a model based on clinical data (χ2, 16.8) was improved by elevated LAP (χ2,24.4; p =0.005), and increased further by probability of elevated PAWP (χ2,41.1; p &lt;0.001). Conclusions: This study suggests that probability of elevated PAWP provides important incremental prognostic value for predicting readmission and cardiac mortality risk assessment in patients with HF.

Quantitative estimation of pulmonary artery wedge pressure from chest radiographs by a regression convolutional neural network

Abstract Introduction Recent studies reported that a convolutional neural network (CNN; a deep learning model) can detect elevated pulmonary artery wedge pressure (PAWP) from chest radiographs, the diagnostic images most commonly used for assessing pulmonary congestion in heart failure. However, no method has been published for quantitatively estimating PAWP from such radiographs. We hypothesized that a regression CNN, an alternative type of deep learning, could be a useful tool for quantitatively estimating PAWP from chest radiographs in cardiovascular diseases. Methods We retrospectively enrolled 936 patients with cardiovascular diseases who had undergone right heart catheterization (RHC) and chest radiography and estimated PAWP by constructing a regression CNN based on the VGG16 model. We randomly categorized 80% of the data as training data (training group, n=748) and 20% as test data (test group, n=188). Moreover, we tuned the learning rate–one of the model parameters–by 5-hold cross-validation of the training group. Correlations between PAWP measured by RHC (ground truth [GT] PAWP) and PAWP derived from the regression CNN (estimated PAWP) were tested. To visualize how the regression CNN assessed the images, we created a regression activation map (RAM), a visualization technique for regression CNN. Results Estimated PAWP correlated significantly with GT PAWP in both the training (r=0.76, P&amp;lt;0.001) and test group (r=0.62, P&amp;lt;0.001). Bland-Altman plots found a mean (SEM) difference between GT and estimated PAWP of −0.23 (0.16) mm Hg in the training and −0.05 (0.41) mm Hg in the test group. The RAM showed that our regression CNN model estimated high PAWP by focusing on the cardiomegaly and pulmonary congestion. In the test group, the area under the curve (AUC) for detecting elevated PAWP (≥18 mm Hg) produced by the regression CNN model was similar to the AUC of an experienced cardiologist (0.86 vs 0.83, respectively; P=0.24). Conclusion This proof-of-concept study shows that regression CNN can quantitatively estimate PAWP from standard chest radiographs in cardiovascular diseases. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The Bayer Academic Support

Left atrial acceleration factor as a magnetic resonance 4D flow measure of mean pulmonary artery wedge pressure in pulmonary hypertension.

BackgroundMean pulmonary artery wedge pressure (PAWP) represents a right heart catheter (RHC) surrogate measure for mean left atrial (LA) pressure and is crucial for the clinical classification of pulmonary hypertension (PH). Hypothesizing that PAWP is related to acceleration of blood throughout the LA, we investigated whether an adequately introduced LA acceleration factor derived from magnetic resonance (MR) four-dimensional (4D) flow imaging could provide an estimate of PAWP in patients with known or suspected PH.MethodsLA 4D flow data of 62 patients with known or suspected PH who underwent RHC and near-term 1.5 T cardiac MR (ClinicalTrials.gov identifier: NCT00575692) were retrospectively analyzed. Early diastolic LA peak outflow velocity (vE) as well as systolic (vS) and early diastolic (vD) LA peak inflow velocities were determined with prototype software to calculate the LA acceleration factor (α) defined as α = vE/[(vS + vD)/2]. Correlation, regression and Bland-Altman analysis were employed to investigate the relationship between α and PAWP, α-based diagnosis of elevated PAWP (>15 mmHg) was analyzed by receiver operating characteristic curve analysis.Resultsα correlated very strongly with PAWP (r = 0.94). Standard deviation of differences between RHC-derived PAWP and PAWP estimated from linear regression model (α = 0.61 + 0.10·PAWP) was 2.0 mmHg. Employing the linear-regression-derived cut-off α = 2.10, the α-based diagnosis of elevated PAWP revealed the area under the curve 0.97 with sensitivity/specificity 93%/92%.ConclusionsThe very close relationship between the LA acceleration factor α and RHC-derived PAWP suggests α as potential non-invasive parameter for the estimation of PAWP and the distinction between pre- and post-capillary PH.

Bioactive adrenomedullin for assessment of venous congestion in heart failure.

Bioactive adrenomedullin (bio-ADM) is a vascular-derived peptide hormone that has emerged as a promising biomarker for assessment of congestion in decompensated heart failure (HF). We aimed to evaluate diagnostic and prognostic performance of bio-ADM for HF in comparison to amino-terminal pro-B-type natriuretic peptide (NT-proBNP), with decision thresholds derived from invasive haemodynamic and population-based studies. Normal reference ranges for bio-ADM were derived from a community-based cohort (n=5060). Correlations with haemodynamic data were explored in a cohort of HF patients undergoing right heart catheterization (n=346). Mortality and decision cutoffs for bio-ADM was explored in a cohort of patients presenting in the ER with acute dyspnoea (n=1534), including patients with decompensated HF (n=570). The normal reference range was 8-39pg/mL. The area under the receiver operating characteristic curve (AUROC) for discrimination of elevated mean right atrial pressure (mRAP) and pulmonary arterial wedge pressure (PAWP) was 0.74 (95% CI=0.67-0.79) and 0.70 (95% CI=0.64-0.75), respectively, with optimal bio-ADM decision cutoff of 39pg/mL, concordant with cubic spline analyses. NT-proBNP discriminated PAWP slightly better than mRAP (AUROC 0.73 [95% CI=0.68-0.79] and 0.68 [95% CI=0.61-0.75]). Bio-ADM correlated with (mRAP, r=0.55) while NT-proBNP correlated with PAWP. Finally, a bio-ADM decision cutoff of 39pg/mL associated with 30 and 90day mortality and conferred a two-fold increased odds of HF diagnosis, independently from NT-proBNP. Bio-ADM tracks with mRAP and associates with measures of systemic congestion and with mortality in decompensated HF independently from NT-proBNP. Our findings support utility of bio-ADM as a biomarker of systemic venous congestion in HF and nominate a decision threshold.

Histopathological Findings of Pulmonary Hypertension With Elevated Pulmonary Arterial Wedge Pressure in Hereditary Hemorrhagic Telangiectasia.

Histopathological Findings of Pulmonary Hypertension With Elevated Pulmonary Arterial Wedge Pressure in Hereditary Hemorrhagic Telangiectasia.

Impact of Esophageal Pressure Measurement on Pulmonary Hypertension Diagnosis in Patients With Obesity

Elevated intrathoracic pressure could affect pulmonary vascular pressure measurements and influence pulmonary hypertension (PH) diagnosis and classification. Esophageal pressure (Pes) measurement adjusts for the increase in intrathoracic pressure, better reflecting the pulmonary hemodynamics in patients with obesity. In individuals with obesity, what is the impact of adjusting pulmonary hemodynamic determinations for Pes on PH diagnosis and classification? Can Pes be estimated by positional or respiratory hemodynamic changes? In this prospective cohort study, we included patients with obesity who underwent right heart catheterization and demonstrated elevated pulmonary artery wedge pressure (PAWP;≥ 12mmHg). After placement of an esophageal balloon, we performed pressure determination using an air-filled transducer connected to a regular hemodynamic monitor. We measured pulmonary pressures changes when sitting and the variations during the respiratory cycle. We included 53 patients (mean ± SD age, 59 ± 12 years; mean ± SD BMI, 44.4 ± 10.2kg/m2). Supine end-expiratory pressures revealed a mean pulmonary artery pressure of > 20mmHg in all patients and a PAWP of >15mmHg in most patients (n= 50). The Pes adjustment led to a significant decrease in percentage of patients with postcapillary PH (from 60%to 8%) and combined precapillary and postcapillary PH (from 34%to 11%), at the expense of an increase in percentage of patients with no PH (0%to 23%), isolated precapillary PH (2%to 25%), and undifferentiated PH (4%to 34%). Adjusting pulmonary hemodynamics for Pes in patients with obesity leads to a pronounced reduction in the number of patients who receive a diagnosis of postcapillary PH. Measuring Pes should be considered in patients with obesity, particularly those with elevated PAWP.

Quantitative estimation of pulmonary artery wedge pressure from chest radiographs by a regression convolutional neural network

Recent studies reported that a convolutional neural network (CNN; a deep learning model) can detect elevated pulmonary artery wedge pressure (PAWP) from chest radiographs, the diagnostic images most commonly used for assessing pulmonary congestion in heart failure. However, no method has been published for quantitatively estimating PAWP from such radiographs. We hypothesized that a regression CNN, an alternative type of deep learning, could be a useful tool for quantitatively estimating PAWP in cardiovascular diseases. We retrospectively enrolled 936 patients with cardiovascular diseases who had undergone right heart catheterization (RHC) and chest radiography and estimated PAWP by constructing a regression CNN based on the VGG16 model. We randomly categorized 80% of the data as training data (training group, n = 748) and 20% as test data (test group, n = 188). Moreover, we tuned the learning rate—one of the model parameters—by 5-hold cross-validation of the training group. Correlations between PAWP measured by RHC [ground truth (GT) PAWP] and PAWP derived from the regression CNN (estimated PAWP) were tested. To visualize how the regression CNN assessed the images, we created a regression activation map (RAM), a visualization technique for regression CNN. Estimated PAWP correlated significantly with GT PAWP in both the training (r = 0.76, P < 0.001) and test group (r = 0.62, P < 0.001). Bland–Altman plots found a mean (SEM) difference between GT and estimated PAWP of − 0.23 (0.16) mm Hg in the training and − 0.05 (0.41) mm Hg in the test group. The RAM showed that our regression CNN model estimated high PAWP by focusing on the cardiomegaly and pulmonary congestion. In the test group, the area under the curve (AUC) for detecting elevated PAWP (≥ 18 mm Hg) produced by the regression CNN model was similar to the AUC of an experienced cardiologist (0.86 vs 0.83, respectively; P = 0.24). This proof-of-concept study shows that regression CNN can quantitatively estimate PAWP from standard chest radiographs in cardiovascular diseases.

Exercise Systolic Reserve and Exercise Pulmonary Hypertension Improve Diagnosis of Heart Failure With Preserved Ejection Fraction.

AimsDiastolic stress testing (DST) is recommended to confirm heart failure with preserved ejection fraction (HFpEF) in patients with exertional dyspnea, but current algorithms do not detect all patients. We aimed to identify additional echocardiographic markers of elevated pulmonary arterial wedge pressure during exercise (exPAWP) in patients referred for DST.Methods and ResultsWe identified candidate parameters in 22 patients referred for exercise right heart catheterization with simultaneous echocardiography. Elevated exPAWP (≥25 mmHg) was present in 14 patients, and was best identified by peak septal systolic annular velocity <9.5 cm/s [exS', area under the receiver operating characteristic curve (AUC) 0.97, 95% confidence interval 0.92–1.0] and mean pulmonary artery pressure/cardiac output slope ≥3.2 mmHg/L [mPAP/CO, AUC 0.88 (0.72–1.0)]. We propose a decision tree to identify patients with elevated exPAWP. Applying this decision tree to 326 patients in an independent non-invasive DST cohort showed that patients labeled as “high probability of HFpEF” (n = 85) had reduced peak oxygen uptake [13.0 (10.7–15.1) mL/kg/min, p < 0.001 vs. intermediate/low probability], high H2FPEF score [53 (40–72) %, p < 0.001 vs. intermediate/low probability], and typical clinical characteristics. The diagnostic yield of DST increased from 11% using exercise E/e', to 62% using the decision tree.ConclusionIn DST for suspected HFpEF, exS' was the most accurate echocardiographic parameter to identify elevated PAWP. We propose a decision tree including exS' and mPAP/CO for interpretation of DST. Application of this decision tree revealed typical HFpEF characteristics in patients labeled as high probability of HFpEF, and substantially reduced the number of inconclusive results.

Abstract 10226: Bioactive Adrenomedullin for Assessment of Venous Congestion in Heart Failure

Introduction: Bioactive adrenomedullin (bio-ADM) is a vascular-derived peptide hormone that has emerged as a promising biomarker for assessment of congestion in decompensated heart failure (HF). Hypothesis: We aimed to evaluate diagnostic and prognostic performance of bio-ADM for HF in comparison to amino-terminal pro-B-type natriuretic peptide (NT-proBNP), with decision thresholds derived from invasive hemodynamic and population-based studies. Methods and Results: Normal reference ranges (95% prediction interval) for bio-ADM were derived from a community-based cohort (n=5060): 8-39 pg/mL. In a cohort of HF patients undergoing right heart catheterization (n=346), bio-ADM was correlated with mean right atrial pressure (mRAP, r=0.55) and followed a concordant trajectory to mRAP after heart transplantation. In contrast, NT-proBNP was correlated with pulmonary arterial wedge pressure (PAWP). The area under the receiver operating characteristic curve (AUROC) for discrimination of elevated mRAP and PAWP was 0.74 (95%CI=0.67-0.79) and 0.70 (95%CI=0.64-0.75), respectively, with optimal bio-ADM decision cutoff of 39 pg/mL, concordant with cubic spline analyses. NT-proBNP discriminated PAWP slightly better than mRAP (AUROC 0.73 [95%CI=0.68-0.79] and 0.68 [95%CI=0.61-0.75]). In a cohort of patients presenting with acute dyspnea (n=1534), including patients with decompensated HF (n=570), a bio-ADM decision cutoff of 39 pg/mL was associated with 30- and 90-day mortality and conferred a 2-fold increased odds of HF diagnosis, independently from NT-proBNP. Conclusions: Bio-ADM tracks with mRAP and associates with measures of systemic congestion and with mortality in decompensated HF independently from NT-proBNP. Our findings support utility of bio-ADM as a biomarker of systemic venous congestion in HF and nominate a decision threshold.

Simple Two-Dimensional Echocardiographic Scoring System for the Estimation of Left Ventricular Filling Pressure

When left ventricular filling pressure (LVFP) increases, the mitral valve opens early and precedes tricuspid valve opening in early diastole. The authors hypothesized that a visually assessed time sequence of atrioventricular valve opening could become a new marker of elevated LVFP. The aim of this study was to test the diagnostic ability of a novel echocardiographic scoring system, the visually assessed time difference between mitral valve and tricuspid valve opening (VMT) score, in patients with heart failure. One hundred nineteen consecutive patients who underwent cardiac catheterization within 24hours of echocardiographic examination were retrospectively analyzed as a derivation cohort. In addition, a prospective study was conducted to validate the diagnostic ability of the VMT score in 50 patients. Elevated LVFP was defined as mean pulmonary artery wedge pressure (PAWP)≥15mm Hg. The time sequence of atrioventricular valve opening was visually assessed and scored (0=tricuspid valve first, 1=simultaneous, 2=mitral valve first). When the inferior vena cava was dilated, 1 point was added, and VMT score was ultimately graded as 0 to 3. Cardiac events were recorded for 1year after echocardiography. In the derivation cohort, PAWP was elevated with higher VMT scores (score 0, 10±5; score 1, 12±4; score 2, 22±8; score 3, 28±4mm Hg; P<.001, analysis of variance). VMT score ≥ 2 predicted elevated PAWP with accuracy of 86% and showed incremental predictive value over clinical variables and guideline-recommended diastolic function grading. These observations were confirmed in the prospective validation cohort. Importantly, VMT score ≥ 2 discriminated elevated PAWP with accuracy of 82% in 33 patients with monophasic left ventricular inflow in the derivation cohort. Kaplan-Meier analysis demonstrated that patients with VMT scores ≥ 2 were at higher risk for cardiac events than those with VMT scores ≤ 1 (P<.001). VMT scoring could be a novel additive marker of elevated LVFP and might also be associated with adverse outcomes in patients with heart failure.

Deep Learning for Detection of Elevated Pulmonary Artery Wedge Pressure Using Standard Chest X-Ray

BackgroundTo accurately diagnose and control heart failure (HF), it is important to carry out a simple assessment of elevated pulmonary arterial wedge pressure (PAWP). The aim of this study was to develop and validate an objective method for detecting elevated PAWP by applying deep learning (DL) to a chest x-ray (CXR). MethodsWe enrolled 1013 consecutive patients with a right-heart catheter between October 2009 and February 2020. We developed a convolutional neural network to identify patients with elevated PAWP (> 18 mm Hg) as the actual value of PAWP to be used in the dataset for training. In the prospective validation dataset used to detect elevated PAWP, the area under the receiver operating characteristic curve (AUC) was calculated using the DL model that evaluated the CXR. ResultsIn the prospective validation dataset, the AUC of the DL model with CXR was not significantly different from the AUC produced by brain natriuretic peptide (BNP) and the echocardiographic left-ventricular diastolic dysfunction (DD) algorithm (DL model: 0.77 vs BNP: 0.77 vs DD algorithm: 0.70; respectively; P = NS for all comparisons); it was, however, significantly higher than the AUC of the cardiothoracic ratio (DL model vs cardiothoracic ratio [CTR]: 0.66, P = 0.044). The model based on 3 parameters (BNP, DD algorithm, and CTR) was improved by adding the DL model (AUC: from 0.80 to 0.86; P = 0.041). ConclusionsApplying the DL model based on a CXR (a classical, universal, and low-cost test) is useful for screening for elevated PAWP.

A novel echocardiographic method for estimation of pulmonary artery wedge pressure and pulmonary vascular resistance.

AimsThis study aimed to evaluate a novel echocardiographic algorithm for quantitative estimation of pulmonary artery wedge pressure (PAWP) and pulmonary vascular resistance (PVR) in patients with heart failure and pulmonary hypertension (PH) scheduled to right heart catheterization (RHC).Methods and resultsIn this monocentric study, 795 consecutive patients (427 men; age 68.4 ± 12.1 years) undergoing echocardiography and RHC were evaluated. Multiple regression analysis was performed to identify echocardiographic predictors of PAWP and PVR measured by RHC in the derivation group (the first 200 patients). The diagnostic accuracy of the model was then tested in the validation group (the remaining 595 patients). PH was confirmed by RHC in 507 (63.8%) patients, with 192 (24.2%) cases of precapillary PH, 248 (31.2%) of postcapillary PH, and 67 (8.4%) of combined PH. At regression analysis, tricuspid regurgitation maximal velocity, mitral E/e′ ratio, left ventricular ejection fraction, right ventricular fractional area change, inferior vena cava diameter, and left atrial volume index were included in the model (R = 0.8, P < 0.001). The model showed a high diagnostic accuracy in estimating elevated PAWP (area under the receiver operating characteristic curve = 0.97, 92% sensitivity, and 93% specificity, P < 0.001) and PVR (area under the receiver operating characteristic curve = 0.96, 89% sensitivity, and 92% specificity, P < 0.001), outperforming 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging recommendations (P < 0.001) and Abbas' equation (P < 0.001). Bland–Altman analysis showed satisfactory limits of agreement between echocardiography and RHC for PAWP (bias 0.7, 95% confidence interval −7.3 to 8.7) and PVR (bias −0.1, 95% confidence interval −2.2 to 1.9 Wood units), without indeterminate cases.ConclusionsA novel quantitative echocardiographic approach for the estimation of PAWP and PVR has high diagnostic accuracy in patients with heart failure and PH.

Abstract 13157: Deep Learning for Detection of Elevated Pulmonary Artery Wedge Pressure Using Standard Chest X-ray

Introduction: Chest X-ray (CXR) is a useful and economical modality for the detection of congestive heart failure. However, the accuracy is limited by the subjective nature of its interpretation. Deep learning (DL) can be used to recognize diseases or findings objectively in various imaging modalities, and may outperform previous diagnostic techniques. Hypothesis: We hypothesized that DL-based analysis of CXR detect the presence of elevated pulmonary arterial wedge pressure (PAWP) in patients with suspected heart failure. Methods: We enrolled 1,013 patients with paired right heart catheterization and CXR performed from October 2009 to February 2020 in our hospital. DL algorithm for the detection of elevated PAWP was developed using the training dataset, based on a single CXR image. Independent evaluation cohort of 115 patients was performed using CXR-based DL model and echocardiographic data to detect the presence of high PAWP. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the DL-based models compared with echocardiographic data. Results: The study included 1,013 patients (mean age, 67±13 years; 569 males [56%]). The mean PAWP was 12.5±6.4 mmHg and 218 patients (22%) had more than 18mmHg. To detect high PAWP, the AUC produced by DL algorithms was effective, and the DL algorithm with the largest AUC was ResNet50. In an evaluation cohort, to detect high PAWP, the AUC using the DL model with CXR was similar to the AUC produced by the echocardiographic left ventricular diastolic dysfunction algorithm (0.77 vs. 0.70; respectively; p=0.27), and significantly higher than the AUC by measurements of echocardiographic parameters (ResNet50 vs. other parameters; all compared p &lt;0.05) (Figure) . Conclusions: The present results demonstrated that DL based on analysis of CXR can detect the presence of high PAWP. This finding suggests that the DL based approach may support an objective evaluation of CXR in the clinical setting.