Reliability of updated left ventricular diastolic function recommendations in predicting elevated left ventricular filling pressure and prognosis

Left Atrial Hemodynamics and Clinical Utility in Heart Failure

Comprehensive knowledge of the left atrium (LA) and its pathophysiology has emerged as an important clinical and research focus in the heart failure (HF) arena. Although studies on HF focusing on investigating left ventricular remodeling are numerous, those on atrial structural and functional changes have received comparatively less attention. Studies on LA remodeling have recently received increasing attention, and LA pressure (LAP) has become a novel target for advanced monitoring and is a potential therapeutic approach for treating HF. Various devices specifically designed for the direct measurement of LAP have been developed to optimize HF treatment by reducing LAP. This review focuses on LA hemodynamic monitoring and effective LAP decompression.

Novel combined echocardiographic score comprising prognostically validated measures of left ventricular size and function to predict long-term survival following myocardial infarction: A proposal to improve risk stratification

BACKGROUND

While left ventricular ejection fraction (LVEF) is the primary variable utilized for prognosis following myocardial infarction (MI), it is relatively indiscriminate for survival in patients with mildly reduced (> 40%) or preserved LVEF (> 50%). Improving risk stratification in patients with mildly reduced or preserved LVEF remains an unmet need, and could be achieved by using a combination approach using prognostically validated measures of left-ventricular (LV) size, geometry, and function.

AIMS

The aim of this study was to compare the prognostic utility of a Combined Echo-Score for predicting all-cause (ACM) and cardiac mortality (CM) following MI to LVEF alone, including the sub-groups with LVEF > 40% and LVEF > 50%.

METHODS

Retrospective data on 3094 consecutive patients with MI from 2013 to 2021 who had inpatient echocardiography were included, including both patients with ST-elevation MI (n = 869 [28.1%]) and non-ST-elevation MI (n = 2225 [71.9%]). Echo-Score consisted of LVEF < 40% (2 points) or LVEF < 50% (1 point), and 1 point each for left atrial volume index > 34 mL/m2, septal E/e' > 15, abnormal LV mass-index, tricuspid regurgitation velocity > 2.8 m/s, and abnormal LV end-systolic volume-index. Simple addition was used to derive a score out of 7.

RESULTS

At a median follow-up of 4.5 years there were 445 deaths (130 cardiac deaths). On Cox proportional-hazards multivariable analysis incorporating significant clinical and echocardiographic predictors, Echo-Score was an independent predictor of both ACM (HR 1.34, p < .001) and CM (HR 1.59, p < .001). Inter-model comparisons of model 𝛘2, Harrel's C and Somer's D, and Receiver operating curves confirmed the superior prognostic value of Echo-Score for both endpoints compared to LVEF. In the subgroups with LVEF > 40% and LVEF > 50%, Echo-Score was similarly superior to LVEF for predicting ACM and CM.

CONCLUSIONS

An Echo-Score composed of prognostically validated LV parameters is superior to LVEF alone for predicting survival in patients with MI, including the subgroups with mildly reduced and preserved LVEF. This could lead to improved patient risk stratification, better-targeted therapies, and potentially more efficient use of device therapies. Further studies should be considered to define the benefit of further investigation and treatment in high-risk subgroups.

The roles of exercise stress echocardiography for the evaluation of heart failure with preserved ejection fraction in the heart failure pandemic era

Heart failure with preserved ejection fraction (HFpEF) accounts for nearly 70% of all HF and has become the dominant form of HF. The increased prevalence of HFpEF has contributed to a rise in the number of HF patients, known as the "heart failure pandemic". In addition to the fact that HF is a progressive disease and a delayed diagnosis may worsen clinical outcomes, the emergence of disease-modifying treatments such as sodium-glucose transporter 2 inhibitors and glucagon-like peptide-1 receptor agonists has made appropriate and timely identification of HFpEF even more important. However, diagnosis of HFpEF remains challenging in patients with a lower degree of congestion. In addition to normal EF, this is related to the fact that left ventricular (LV) filling pressures are often normal at rest but become abnormal during exercise. Exercise stress echocardiography can identify such exercise-induced elevations in LV filling pressures and facilitate the diagnosis of HFpEF. Exercise stress echocardiography may also be useful for risk stratification and assessment of exercise tolerance as well as cardiovascular responses to exercise. Recent attention has focused on dedicated dyspnea clinics to identify early HFpEF among patients with unexplained dyspnea and to investigate the causes of dyspnea. This review discusses the role of exercise stress echocardiography in the diagnosis and evaluation of HFpEF.

MR 4D flow-derived left atrial acceleration factor for differentiating advanced left ventricular diastolic dysfunction

OBJECTIVES

The magnetic resonance (MR) 4D flow imaging-derived left atrial (LA) acceleration factor α was recently introduced as a means to non-invasively estimate LA pressure. We aimed to investigate the association of α with the severity of left ventricular (LV) diastolic dysfunction using echocardiography as the reference method.

METHODS

Echocardiographic assessment of LV diastolic function and 3-T cardiac MR 4D flow imaging were prospectively performed in 94 subjects (44 male/50 female; mean age, 62 ± 12 years). LA early diastolic peak outflow velocity (vE), systolic peak inflow velocity (vS), and early diastolic peak inflow velocity (vD) were evaluated from 4D flow data. α was calculated from α = vE / [(vS + vD) / 2]. Mean parameter values were compared by t-test; diagnostic performance of α in predicting diastolic (dys)function was investigated by receiver operating characteristic curve analysis.

RESULTS

Mean α values were 1.17 ± 0.14, 1.20 ± 0.08, 1.33 ± 0.15, 1.77 ± 0.18, and 2.79 ± 0.69 for grade 0 (n = 51), indeterminate (n = 9), grade I (n = 13), grade II (n = 13), and grade III (n = 8) LV diastolic (dys)function, respectively. α differed between subjects with non-advanced (grade < II) and advanced (grade ≥ II) diastolic dysfunction (1.20 ± 0.15 vs. 2.16 ± 0.66, p < 0.001). The area under the curve (AUC) for detection of advanced diastolic dysfunction was 0.998 (95% CI: 0.958-1.000), yielding sensitivity of 100% (95% CI: 84-100%) and specificity of 99% (95% CI: 93-100%) at cut-off α ≥ 1.58. The AUC for differentiating grade III diastolic dysfunction was also 0.998 (95% CI: 0.976-1.000) at cut-off α ≥ 2.14.

CONCLUSION

The 4D flow-derived LA acceleration factor α allows grade II and grade III diastolic dysfunction to be distinguished from non-advanced grades as well as from each other.

CLINICAL RELEVANCE STATEMENT

As a single continuous parameter, the 4D flow-derived LA acceleration factor α shows potential to simplify the multi-parametric imaging algorithm for diagnosis of advanced LV diastolic dysfunction, thereby identifying patients at increased risk for cardiovascular events.

KEY POINTS

• Detection of advanced diastolic dysfunction is typically performed using a complex, multi-parametric approach. • The 4D flow-derived left atrial acceleration factor α alone allows accurate detection of advanced left ventricular diastolic dysfunction. • As a single continuous parameter, the left atrial acceleration factor α could simplify the diagnosis of advanced diastolic dysfunction.

Association of Coronary Wall Thickening and Diminished Diastolic Function in Asymptomatic, Low Cardiovascular Disease-Risk Persons Living with HIV

Purpose To assess early subclinical coronary artery disease (CAD) burden and its relation to myocardial function in asymptomatic persons living with HIV (PLWH) who are at low risk for cardiovascular disease (CVD). Materials and Methods In this prospective, HIPAA-compliant study (ClinicalTrials.gov NCT01656564 and NCT01399385) conducted from April 2010 to May 2013, 74 adult PLWH without known CVD and 25 matched healthy controls underwent coronary MRI to measure coronary vessel wall thickness (VWT) and echocardiography to assess left ventricular function. Univariable and multivariable linear regression analyses were used to evaluate statistical associations. Results For PLWH, the mean age was 49 years ± 11 (SD), and the median Framingham risk score was 3.2 (IQR, 0.5-6.6); for matched healthy controls, the mean age was 46 years ± 8 and Framingham risk score was 2.3 (IQR, 0.6-6.1). PLWH demonstrated significantly greater coronary artery VWT than did controls (1.47 mm ± 0.22 vs 1.34 mm ± 0.18; P = .006) and a higher left ventricular mass index (LVMI) (77 ± 16 vs 70 ± 13; P = .04). Compared with controls, PLWH showed altered association between coronary artery VWT and both E/A (ratio of left ventricular-filling peak blood flow velocity in early diastole [E wave] to that in late diastole [A wave]) (P = .03) and LVMI (P = .04). In the PLWH subgroup analysis, coronary artery VWT increase was associated with lower E/A (P < .001) and higher LVMI (P = .03), indicating restricted diastolic function. In addition, didanosine exposure was associated with increased coronary artery VWT and decreased E/A ratio. Conclusion Asymptomatic low-CVD-risk PLWH demonstrated increased coronary artery VWT in association with impaired diastolic function, which may be amenable to follow-up studies of coronary pathogenesis to identify potential effects on the myocardium and risk modification strategies. Keywords: Coronary Vessel Wall Thickness, Diastolic Function, HIV, MRI, Echocardiography, Atherosclerosis Clinical trial registration nos. NCT01656564 and NCT01399385 Supplemental material is available for this article. © RSNA, 2024.

Echocardiographic artificial intelligence for pulmonary hypertension classification

OBJECTIVE

The classification of pulmonary hypertension (PH) is crucial for determining the appropriate therapeutic strategy. We investigated whether machine learning (ML) algorithms may assist in echocardiographic PH prediction, where current guidelines recommend integrating several different parameters.

METHODS

We obtained physical and echocardiographic data from 885 patients who underwent right heart catheterisation (RHC). Patients were classified into three groups: non-PH, precapillary PH and postcapillary PH, based on values obtained from RHC. Using 24 parameters, we created predictive models employing four different classifiers and selected the one with the highest area under the curve. We then calculated the macro-average classification accuracy for PH on the derivation cohort (n=720) and prospective validation data set (n=165), comparing the results with guideline-based echocardiographic assessment obtained from each cohort.

RESULTS

Logistic regression with elastic net regularisation had the highest classification accuracy, with areas under the curves of 0.789, 0.766 and 0.742 for normal, precapillary PH and postcapillary PH, respectively. The ML model demonstrated significantly better predictive accuracy than the guideline-based echocardiographic assessment in the derivation cohort (59.4% vs 51.6%, p<0.01). In the independent validation data set, the ML model's accuracy was comparable to the guideline-based PH classification (59.4% vs 57.8%, p=0.638).

CONCLUSIONS

This preliminary study suggests promising potential for our ML model in predicting echocardiographic PH. Further research and validation are needed to fully assess its clinical utility in PH diagnosis and treatment decision-making.

Left atrial strain as a predictor of left ventricular filling pressures in coronary artery disease with preserved ejection fraction: a comprehensive study with left ventricular end-diastolic and pre-atrial contraction pressures

Assessing left ventricular (LV) filling pressure (LVFP) is challenging in patients with coronary artery disease (CAD) and preserved LV ejection fraction (LVEF). We aimed to correlate left atrial strain (LAS) with two invasive complementary parameters of LVFP and compared its accuracy to other echocardiographic data to predict high LVFP. This cross-sectional, single-center study enrolled 81 outpatients with LVEF > 50% and significant CAD from a database. Near-simultaneous echocardiography and invasive measurements of both LV end-diastolic pressure (LVEDP) and LV pre-atrial contraction (pre-A) pressure were performed in each patient, based on the definition of LVEDP > 16 mmHg and LV pre-A > 12 mmHg as high LVFP. A moderate to strong correlation was observed between LAS reservoir (LASr), contractile strain, and LVEDP (r: 0.67 and 0.62, respectively; p < 0.001); the same was true for LV pre-A (r: 0.65 and 0.63, respectively; p < 0.001). LASr displayed good diagnostic performance to identify elevated LVFP, which was higher when compared to traditional parameters. Median value of LASr was higher for an isolated increase of LVEDP than for simultaneously high LV pre-A. The cutoff found to predict high LVFP was lower for LV pre-A than that one for LVEDP. In the current study, LASr did not provide an additional contribution to the 2016 diastolic function algorithm. LAS is a valuable tool for predicting LVFP in patients with CAD and preserved LVEF. The choice of LVEDP or LV pre-A as the representative marker of LVFP leads to different cutoffs to predict high pressures. The best strategy for adding this tool to a multiparametric algorithm requires further investigation.

Impact of Estimated Left Atrial Pressure on Cardiac Resynchronization Therapy Outcome

BACKGROUND

We investigated the impact of baseline left atrial (LA) strain data and estimated left atrial pressure (LAP) by applying the 2016 American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) guidelines on cardiac resynchronization therapy (CRT) outcomes.

METHODS

Datasets of 219 CRT patients were retrospectively analysed. All patients had full echocardiographic diastolic function assessment before CRT and were classified based on the guideline algorithm into normal LAP (nLAP = 40%), elevated LAP (eLAP = 49%) and indeterminate LAP (iLAP = 11%). All relevant baseline characteristics were analysed. CRT-induced left ventricular (LV) reverse remodeling was measured as the relative change of LV end-systolic volume (LVESV) at 12 ± 6 months after CRT compared to baseline. Patients were followed up for all-cause mortality for a mean of 4.8 years [interquartile range (IQR): 2.7-6.0 years].

RESULTS

At follow-up, CRT resulted in more pronounced reduction of LVESV in patients with nLAP than in patients with eLAP. In univariate analysis, nLAP was associated with LV reverse remodelling (p < 0.001), as well as long-term survival after CRT (p < 0.01). However, multivariable analysis showed that only the association between nLAP and LV reverse remodelling after CRT is independent (p < 0.01). Adding LA strain analysis to the guideline algorithm improved the feasibility of LAP estimation without affecting the association between estimated LAP and CRT outcome.

CONCLUSION

Normal LAP before CRT, estimated using the 2016 ASE/EACVI guideline algorithm, is associated with LV reverse remodelling and long-term survival after CRT. Albeit non-independent, it can serve as a non-invasive imaging-based predictor of effective therapy. Furthermore, the inclusion of LA reservoir strain in the guideline algorithm can enhance the feasibility of LAP estimation without affecting the association between LAP and CRT outcome.

Left Atrial Strain in the Assessment of Diastolic Function in Heart Failure: A Machine Learning Approach

BACKGROUND

Diastolic dysfunction (DD) assessment in heart failure is still challenging. Peak atrial longitudinal strain (PALS) is strongly related to end-diastolic pressure and prognosis, but it is still not part of standard DD assessment. We tested the hypothesis that a machine learning approach would be useful to include PALS in DD classification and refine prognostic stratification.

METHODS

In a derivation cohort of 864 heart failure patients in sinus rhythm (age, 66.6±12 years; heart failure with reduced ejection fraction, n=541; heart failure with mildly reduced ejection fraction, n=129; heart failure with preserved ejection fraction, n=194), machine learning techniques were retrospectively applied to PALS and guideline-recommended diastolic variables. Outcome (death/heart failure rehospitalization) of the identified DD-clusters was compared with that by guidelines-based classification. To identify the best combination of variables able to classify patients in one of the identified DD-clusters, classification and regression tree analysis was applied (with DD-clusters as dependent variable and PALS plus guidelines-recommended diastolic variables as explanatory variables). The algorithm was subsequently validated in a prospective cohort of 189 heart failure outpatients (age, 65±13 years).

RESULTS

Three distinct echocardiographic DD-clusters were identified (cluster-1, n=212; cluster-2, n=376; cluster-3 DD, n=276), with modest agreement with guidelines-recommended classification (kappa=0.40; P<0.001). DD-clusters were predicted by a simple algorithm including E/A ratio, left atrial volume index, E/e' ratio, and PALS. After 36.5±29.4 months follow-up, 318 events occurred. Compared to guideline-based classification, DD-clusters showed a better association with events in multivariable models (C-index 0.720 versus 0.733, P=0.033; net reclassification improvement 0.166 [95% CI, 0.035-0.276], P=0.013), without interaction with ejection fraction category. In the validation cohort (median follow-up: 18.5 months), cluster-based classification better predicted outcome than guideline-based classification (C-index 0.80 versus 0.78, P=0.093).

CONCLUSIONS

Integrating PALS by machine learning algorithm in DD classification improves risk stratification over recommended current criteria, regardless of ejection fraction status. This proof of concept study needs further validation of the proposed algorithm to assess generalizability to other populations.

Left atrial reservoir strain improves diagnostic accuracy of the 2016 ASE/EACVI diastolic algorithm in patients with preserved left ventricular ejection fraction: insights from the KARUM haemodynamic database

AIMS

This study aimed to investigate the incremental value offered by left atrial reservoir strain (LASr) to the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) diastolic algorithm to identify elevated left ventricular (LV) filling pressure in patients with preserved ejection fraction (EF).

METHODS AND RESULTS

Near-simultaneous echocardiography and right heart catheterization were performed in 210 patients with EF ≥50% in a large, dual-centre study. Elevated filling pressure was defined as invasive pulmonary capillary wedge pressure (PCWP) ≥15 mmHg. LASr was evaluated using speckle-tracking echocardiography. Diagnostic performance of the ASE/EACVI diastolic algorithm was validated against invasive reference and compared with modified algorithms incorporating LASr. Modest correlation was observed between E/e', E/A ratio, and LA volume index with PCWP (r = 0.46, 0.46, and 0.36, respectively; P < 0.001 for all). Mitral e' and TR peak velocity showed no association. The ASE/EACVI algorithm (89% feasibility, 71% sensitivity, 68% specificity) demonstrated reasonable ability (AUC = 0.69) and 68% accuracy to identify elevated LV filling pressure. LASr displayed strong ability to identify elevated PCWP (AUC = 0.76). Substituting TR peak velocity for LASr in the algorithm (69% sensitivity, 84% specificity) resulted in 91% feasibility, 81% accuracy, and stronger agreement with invasive measurements. Employing LASr as per expert consensus (71% sensitivity, 70% specificity) and adding LASr to conventional parameters (67% sensitivity, 84% specificity) also demonstrated greater feasibility (98% and 90%, respectively) and overall accuracy (70% and 80%, respectively) to estimate elevated PCWP.

CONCLUSIONS

LASr improves feasibility and overall accuracy of the ASE/EACVI algorithm to discern elevated filling pressures in patients with preserved EF.

Bedside assessment of left atrial pressure in critical care: a multifaceted gem

Evaluating left atrial pressure (LAP) solely from the left ventricular preload perspective is a restrained approach. Accurate assessment of LAP is particularly relevant when pulmonary congestion and/or right heart dysfunction are present since it is the pressure most closely related to pulmonary venous pressure and thus pulmonary haemodynamic load. Amalgamation of LAP measurement into assessment of the ‘transpulmonary circuit’ may have a particular role in differentiating cardiac failure phenotypes in critical care. Most of the literature in this area involves cardiology patients, and gaps of knowledge in application to the bedside of the critically ill patient remain significant. Explored in this review is an overview of left atrial physiology, invasive and non-invasive methods of LAP measurement and their potential clinical application.

Unsupervised Machine Learning for Assessment of Left Ventricular Diastolic Function and Risk Stratification

BACKGROUND

The 2016 American Society of Echocardiography (ASE) guidelines have been widely used to assess left ventricular diastolic function. However, limitations are present in the current classification system. We aimed to develop a data-driven, unsupervised machine learning approach for diastolic function classification and risk stratification using the left ventricular diastolic function parameters recommended by the 2016 ASE guidelines; the guideline grading was used as the reference standard.

METHODS

Baseline demographics, heart failure hospitalization and all-cause mortality data were obtained for all adult patients who underwent transthoracic echocardiography at Mayo Clinic Rochester in 2015. Patients with prior mitral valve intervention, congenital heart disease, cardiac transplant, or cardiac assist device were excluded. Nine left ventricular diastolic function variables (mitral E and A wave peak velocities, E/A, deceleration time, medial and lateral annulus e' and E/e', and tricuspid regurgitation peak velocity) were used for an unsupervised machine learning algorithm to identify different phenotype clusters. The cohort average of each variable was used for imputation. Patients were grouped according to the algorithm-determined clusters for Kaplan-Meier survival analysis.

RESULTS

Among 24,414 patients, age 63.6 ±16.2 years, all-cause mortality occurred in 4,612 (18.9%) patients during median follow-up 3.1 years. The algorithm determined 3 clusters with echocardiographic measurement characteristics corresponding to normal diastolic function (n= 8,312), impaired relaxation (n=11,779) and increased filling pressure (n =4,323), with 3-year cumulative mortality of 11.8%, 19.9% and 33.4%, respectively (p<0.0001). All 10,694 (43.8%) patients classified as indeterminate were reclassified into the 3 clusters (3,324, 5,353, and 2,017, respectively) with 3-year mortality of 16.6%, 22.9% and 34.4%, respectively. The clusters also outperformed guideline-based grade for prognostication (c-index: 0.607 vs. 0.582, p=0.013).

CONCLUSIONS

Unsupervised machine learning identified physiologically and prognostically distinct clusters based on 9 diastolic function Doppler variables. The clusters can be potentially applied in echocardiography laboratory practice and future clinical trials for simple, replicable diastolic function related risk stratification.

A Novel Continuous Left Ventricular Diastolic Function Score Using Machine Learning

BACKGROUND

Unlike left ventricular (LV) ejection fraction, which provides a precise, reliable, and prognostically valuable measure of systolic function, there is no single analogous measure of LV diastolic function.

OBJECTIVES

We aimed to develop a continuous score to grade LV diastolic function using machine learning modeling of echocardiographic data.

METHODS

Consecutive echo studies performed at a tertiary care centre between February 1, 2010 and March 31, 2016 were assessed, excluding studies containing features that would interfere with diastolic function assessment as well as studies in which one or more parameters within the contemporary diastolic function assessment algorithm were not reported. Diastolic function was graded based on 2016 American Society of Echocardiography (ASE) / European Association of Cardiovascular Imaging (EACVI) guidelines, excluding indeterminate studies. Machine learning models were trained (SVM [support vector machine], DT [decision tree], XGB [XGBoost], and DNN [dense neural network]) to classify studies within the training set by diastolic dysfunction severity, blinded to the ASE/EACVI classification. The DNN model was retrained to generate a regression model (R-DNN) to predict a continuous LV diastolic function score.

RESULTS

A total of 28,986 studies were included; 23,188 studies were used to train the models and 5798 studies were used for validation. The models were able to reclassify studies with high agreement to the ASE/EACVI algorithm (SVM 83%, DT 100%, XGB 100%, DNN 98%). The continuous diastolic function score corresponded well with ASE/EACVI guidelines, with scores of 1.00 ± 0.01 for studies with normal function; and 0.74 ± 0.05, 0.51 ± 0.06, and 0.27 ± 0.11 for mild, moderate, and severe diastolic dysfunction respectively (mean ± 1 standard deviation). A score of <0.91 predicted abnormal diastolic function (AUC 0.99) while a score of <0.65 predicted elevated filling pressure (AUC 0.99).

CONCLUSIONS

Machine learning can assimilate echocardiographic data and generate an automated continuous diastolic function score that corresponds well with current diastolic function grading recommendations.

Can echocardiographic assessment of diastolic function be automated?

Echocardiographic evaluation of left ventricular diastolic function relies on a multi-pronged algorithm, which incorporates Doppler-based and volumetric parameters. Integration of clinical data in diastolic assessment is recommended, though not clearly outlined. We sought to develop an automated tool for diastolic function, compare its performance to human-generated diagnoses and identify the common sources of error. Our software tool is based on the 2016 diastolic guidelines algorithm, which uses 8 parameters as input, with 10 conditions as the logic and 5 possible outputs as final diagnoses. Initially, we prospectively studied 563 patients whose diastolic function was independently evaluated by an expert echocardiographer and by the automated tool. Incongruent cases were further analyzed, after which features of myocardial disease were integrated into a refined version of the software that was tested in an independent cohort of 1106 patients. In the initial analysis, 202/563 grades (36%) were incongruent between the automated and human reads, with the highest rate of discordance for mild and indeterminate categories. In 17% of cases, human diagnoses differed from that dictated by the algorithm due to integration of clinical factors. Follow-up analysis using the refined automated tool did not improve the discordance rate (440/1106; 40%). There was more discordance in cases of: age > 40 years, impaired mitral inflow patterns (E/A < 0.8) and reduced mitral e' values. Further analysis revealed differences in how readers interpreted the interaction between these factors and diastolic function, which could not be incorporated into the automated tool. In conclusion, although assessment of diastolic function relies on an algorithm that can be automated, this algorithm does not include clear guidance on how to incorporate age, or age-related changes in Doppler-based parameters, often resulting in discordant diagnoses. Standardized interpretation of these factors is needed to improve the reproducibility of diastolic function grading by human readers and the accuracy of the automated classification.

Heart Failure and Atrial Fibrillation: Diastolic Function Differences Depending on Left Ventricle Ejection Fraction

Background: Heart failure (HF) and atrial fibrillation (AF) are prevalent cardiovascular diseases, and their association is common. Diastolic dysfunction may be present in patients with AF and all types of HF, leading to elevated intracardiac pressures. The objective of this study was to analyze diastolic dysfunction in patients with HF and AF depending on left ventricle ejection fraction (LVEF). Material and methods: This prospective study included 324 patients with chronic HF and AF (paroxysmal, persistent, or permanent) hospitalized between January 2018 and March 2021. The inclusion criteria were age older than 18 years, diagnosis of chronic HF and AF, and available echocardiographic data. The exclusion criteria were a suboptimal echocardiographic view, other cardiac rhythms than AF, congenital heart disease, or coronavirus 2 infection. Patients were divided into three subgroups according to LVEF: subgroup 1 included 203 patients with HF with reduced ejection fraction (HFrEF) and AF (62.65%), subgroup 2 included 42 patients with HF with mildly reduced ejection fraction (HFmrEF) and AF (12.96%), and subgroup 3 included 79 patients with HF with preserved ejection fraction (HFpEF) and AF (24.38%). We performed 2D transthoracic echocardiography in all patients. Statistical analysis was performed using R software. Results: The E/e' ratio (p = 0.0352, OR 1.9) and left atrial volume index (56.4 mL/m2 vs. 53.6 mL/m2) were higher in patients with HFrEF than in those with HFpEF. Conclusions: Patients with HFrEF and AF had more severe diastolic dysfunction and higher left ventricular filling pressures than those with HFpEF and AF.

Interrater reproducibility of the 2016 American society of echocardiography left ventricular diastolic function guidelines

BACKGROUND

Little data exist regarding interreader variability of diastolic measurements and their application by the 2016 American Society of Echocardiography left ventricular (LV) diastolic function guidelines.

METHODS

Volunteers (n = 49) were recruited from an outpatient cardiology practice. The presence and grade of diastology dysfunction (DD) was determined by the 2016 LV diastology guideline algorithm. We determined the mean, standard deviation, coefficient of variation, and intraclass correlation coefficient (ICC) for each measurement and Fleiss K-statistic to define differences in grading DD. We determined predictors associated with disagreement of DD grade using odds ratios.

RESULTS

The mean LVEF was 56%, LAVI 32 ml/m² , and peak TR velocity was 2.3 m/s. The ICC for mitral inflow and tissue Doppler velocities were >.90, for LV volumes were .80-.86, and for LA volume was .56. The Fleiss K-value for the agreement of the presence of DD was .68 and for DD grade was .59. Variables with increased odds of disagreement were (1) at least one reader considering a TR signal uninterpretable (OR 12.0; 95% CI 1.3-109.6), (2) at least one reader assessing both LVEF 50%-55% and LAVI 29-39 ml/m² (OR 9.3; 95% CI 1.0-87), and (3) at least one reader assessing LVEF 50-55% (OR 3.8; 95% CI 1.1-13.4).

CONCLUSIONS

Using the 2016 ASE/EACVI diastology guidelines, we found excellent interrater reliability of Doppler measurements, moderate-good interrater reliability of volumetric measurements, and moderate-good but not excellent agreement for diastology grade.

Prognostic Impact of Echocardiographic Diastolic Dysfunction on Outcomes in Patients With Heart Failure With Preserved Ejection Fraction - Insights From the PURSUIT-HFpEF Registry

BACKGROUND

Although diastolic dysfunction is important pathophysiology in heart failure with preserved ejection fraction (HFpEF), its prognostic impact in HFpEF patients, including those with atrial fibrillation (AF), remains to be elucidated.

METHODS AND RESULTS

We included the data for 863 patients (321 patients with AF) registered in a prospective multicenter observational study of patients with HFpEF. Patients were divided into 3 groups according to the 2016 ASE/EACVI recommendations. The primary endpoint was a composite of all-cause death or HF rehospitalization. Median age was 83 years, and 55.5% were female. 196 (22.7%) were classified with normal diastolic function (ND), 253 (29.3%) with indeterminate (ID) and 414 (48.0%) with diastolic dysfunction (DD). The primary endpoint occurred more frequently in patients with DD than in those with ND or ID (log-rank P<0.001 for DD vs. ND, and log-rank P=0.007 for DD vs. ID, respectively). Taking ND as the reference, multivariable Cox regression analysis revealed that DD (hazard ratio (HR): 1.57, 95% confidence interval (CI):1.06-2.32, P=0.024) was independently associated with the composite endpoint, whereas ID (HR: 1.28, 95% CI: 0.84-1.95, P=0.255) was not. DD was associated with the composite endpoint in both patients with and without AF.

CONCLUSIONS

HFpEF patients classified with DD using the 2016 ASE/EACVI recommendations had worse clinical outcomes than those with ND or ID. DD may be considered a prognostic marker in patients with HFpEF regardless of AF.

Assessment of diastolic function in aortic stenosis: A comparison between 2009 and 2016 guidelines

AIMS

New diastolic dysfunction (DD) guidelines were introduced in 2016 to replace the 2009 guidelines, but have not yet been evaluated in aortic stenosis (AS). We aimed to compare the 2009 and 2016 DD guidelines in severe AS patients in terms of association with left ventricular (LV) and left atrial (LA) remodeling, with pulmonary capillary wedge pressure (PCWP) at rest and exercise, and with prognosis.

METHODS AND RESULTS

We included 212 patients with severe AS (112 undergoing AVR, 100 asymptomatic). Echocardiography, magnetic resonance imaging, and brain natriuretic peptides (BNP) were performed/measured. Thirty-nine asymptomatic patients had PCWP measured during rest and maximal exertion. Asymptomatic patients were followed for 3.1 years for the combined endpoint of death, AVR or admission with heart failure. The 2009 and 2016 DD guidelines agreed poorly with each other (Cohens' κ = .15). 2009 guidelines showed many ambiguous DD findings. With the 2016 guidelines, 20% of patients had indeterminate DD. DD grade 2 according to 2016 guidelines showed stronger association with symptom status, BNP, global longitudinal strain (GLS) and peak exercise PCWP than 2009 guidelines. For indeterminate DD patients according to 2009 guidelines, GLS above the median was associated with event-free survival (HR .11 (95% CI .02-.53)). For neither guideline was DD associated with the combined endpoint in asymptomatic patients.

CONCLUSION

The 2016 guidelines show a stronger association with BNP, GLS, and exercise PCWP than the 2009 guidelines. The 2016 guidelines result in 20% of patients with indeterminate DD; however, these patients may possibly be stratified according to GLS.

Diamond-Forrester classification using echocardiography haemodynamic assessment in cardiac intensive care unit patients

AIMS

We sought to determine whether the Diamond-Forrester classification using non-invasive haemodynamic measurements by 2-D and Doppler echocardiography would predict hospital mortality in cardiac intensive care unit (CICU) patients.

METHODS AND RESULTS

We retrospectively analysed unique patients admitted to the CICU at Mayo Clinic Rochester from 2007 to 2018. Doppler-derived cardiac index (CI) and ratio of mitral valve E velocity to medial mitral annulus e' velocity (E/e' ratio) were used to classify patients into four profiles: Profile I (warm/dry), Profile II (warm/wet), Profile III (cold/dry), and Profile IV (cold/wet). Logistic regression was used to determine predictors of hospital mortality, and Cox proportional-hazards analysis was used to determine predictors of mortality during one year of follow-up. We included 4563 patients with a mean age of 68.3 ± 14.3 years, including 36.2% female patients. The distribution of each profile was as follows: I, 47.4%; II, 36.2%; III, 7.9%; IV, 8.5%. A total of 5.8% patients died during hospitalization, and 18.1% died by 1 year. Patients with either low CI or elevated E/e' ratio had higher in-hospital and 1 year mortality. Patients with elevated E/e' ratio (i.e. Profiles II and IV) had an increased risk of death during hospitalization and at 1 year after multivariate adjustment (adjusted hazard ratio 1.72 and 2.17 for 1 year mortality, respectively, compared with Profile I, P < 0.01).

CONCLUSIONS

Simple Doppler echocardiographic assessment can be used to identify haemodynamic profiles defined by the Diamond-Forester classification in patients admitted in CICU. These profiles predict outcomes and may be used to guide therapy in critically ill patients.

Echocardiography in the diagnostic evaluation and phenotyping of heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) represents one of the greatest unmet needs in modern cardiology given its diagnostic difficulty and limited therapeutic options. Echocardiography provides valuable information on cardiac structure, function, and hemodynamics and plays a central role in the evaluation of HFpEF. Echocardiography is crucial in identifying HFpEF among patients with dyspnea, especially when overt congestion is absent. The combination of echocardiographic indices of diastolic function, clinical characteristics, and natriuretic peptide tests has been proposed in the diagnostic evaluation of patients with suspected HFpEF. Echocardiography also provides valuable insight into the pathophysiology and underlying phenotypes of HFpEF. Exercise stress echocardiography can also detect abnormalities that develop only during exercise. This may enhance the diagnosis of HFpEF by demonstrating elevation in the left ventricular filling pressure and may have potential for better pathophysiological characterization. This review focuses on the role of echocardiography in the diagnostic evaluation and phenotyping of HFpEF. We also discuss the potential role of exercise stress echocardiography for the diagnosis and disease phenotyping of HFpEF.

Echocardiographic Advances in Dilated Cardiomyopathy

Although the overall survival of patients with dilated cardiomyopathy (DCM) has improved significantly in the last decades, a non-negligible proportion of DCM patients still shows an unfavorable prognosis. DCM patients not only need imaging techniques that are effective in diagnosis, but also suitable for long-term follow-up with frequent re-evaluations. The exponential growth of echocardiography’s technology and performance in recent years has resulted in improved diagnostic accuracy, stratification, management and follow-up of patients with DCM. This review summarizes some new developments in echocardiography and their promising applications in DCM. Although nowadays cardiac magnetic resonance (CMR) remains the gold standard technique in DCM, the echocardiographic advances and novelties proposed in the manuscript, if properly integrated into clinical practice, could bring echocardiography closer to CMR in terms of accuracy and may certify ultrasound as the technique of choice in the follow-up of DCM patients. The application in DCM patients of novel echocardiographic techniques represents an interesting emergent research area for scholars in the near future.

Prognostic implications of left heart diastolic dysfunction in adults with coarctation of aorta

AIMS

The prognostic implication of left atrial (LA) dysfunction and left ventricular diastolic dysfunction (LVDD) in patients with coarctation of aorta (COA) is unknown. The purpose of this study was to determine whether LA dysfunction and LVDD were associated with mortality in COA patients.

METHODS AND RESULTS

This is a retrospective review of adults (age ≥18 years) with repaired COA that underwent transthoracic echocardiogram (2000-18). LVDD was determined using the 2016 guidelines for LV diastolic function assessment, and LA dysfunction was assessed using LA reservoir strain. Of 721 patients, LV diastolic function could be determined in 635 (88%); and 414 (65%) had no LVDD, while 146 (23%), 53 (8%), and 22 (4%) had Grade I/II/III LVDD, respectively. The mean LA reservoir strain was 39 ± 11%, and patients were divided into quartiles: top quartile (reference group), mild LA dysfunction, moderate LA dysfunction, and severe LA dysfunction. Grade III LVDD (but not Grades I and II) was associated with death/transplant. On the other hand, there was an incremental risk of death/transplant across LA strain quartiles: mild LA dysfunction [hazard ratio (HR) 1.16, 1.04-2.06], moderate LA dysfunction (HR 1.75, 1.27-3.58), and severe LA dysfunction (HR 3.49, 1.88-7.16). Of 86 patients with indeterminate diastolic function, there was a trend towards a lower 5-year transplant-free survival in patients with LA dysfunction vs. normal LA function (83% vs. 91%, P = 0.06).

CONCLUSION

LA dysfunction (but not LVDD) was associated with incremental risk of mortality and thus can be used for prognostication in all patients including those with indeterminate diastolic function.

Validation of the 2016 ASE/EACVI Guideline for Diastolic Dysfunction in Patients With Unexplained Dyspnea and a Preserved Left Ventricular Ejection Fraction

Background

Echocardiography is considered the cornerstone of the diagnostic workup of heart failure with preserved ejection fraction. Thus far, validation of the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) echo‐algorithm for evaluation of diastolic (dys)function in a patient suspected of heart failure with preserved ejection fraction has been limited.

Methods and Results

The diagnostic performance of the 2016 ASE/EACVI algorithm was assessed in 204 patients evaluated for unexplained dyspnea or pulmonary hypertension with echocardiogram and right heart catheterization. Invasively measured pulmonary capillary wedge pressure (PCWP) was used as the gold standard. In addition, the diagnostic performance of H₂FPEF score and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) were evaluated. There was a poor correlation between indexed left atrial volume, E/e′ (septal and average) or early mitral inflow (E), and PCWP (r=0.25–0.30, P values all <0.01). No correlation was found in our cohort between e′ (septal or lateral) or tricuspid valve regurgitation and PCWP. The correlation between diastolic function grades of the ASE/EACVI algorithm and PCWP was poor (r=0.17, P<0.05). The ASE/EACVI algorithm had a sensitivity and specificity of 35% and 87%, respectively; an accuracy of 67% and an area under the curve of 0.56. Moreover, in 30% of cases the algorithm was not applicable or indeterminate. H₂FPEF score had a modest correlation with PCWP (r=0.44, P<0.0001), and accuracy was 73%; NT‐proBNP correlated weakly with PCWP (r=0.24, P<0.001), and accuracy was 57%.

Conclusions

The 2016 ASE/EACVI algorithm for the assessment of diastolic function has a limited diagnostic accuracy in patients evaluated for unexplained dyspnea and/or pulmonary hypertension, and especially sensitivity to detect diastolic dysfunction was low.

Machine Learning Augmented Echocardiography for Diastolic Function Assessment

Cardiac diastolic dysfunction is prevalent and is a diagnostic criterion for heart failure with preserved ejection fraction—a burgeoning global health issue. As gold-standard invasive haemodynamic assessment of diastolic function is not routinely performed, clinical guidelines advise using echocardiography measures to determine the grade of diastolic function. However, the current process has suboptimal accuracy, regular indeterminate classifications and is susceptible to confounding from comorbidities. Advances in artificial intelligence in recent years have created revolutionary ways to evaluate and integrate large quantities of cardiology data. Imaging is an area of particular strength for the sub-field of machine-learning, with evidence that trained algorithms can accurately discern cardiac structures, reliably estimate chamber volumes, and output systolic function metrics from echocardiographic images. In this review, we present the emerging field of machine-learning based echocardiographic diastolic function assessment. We summarise how machine-learning has made use of diastolic parameters to accurately differentiate pathology, to identify novel phenotypes within diastolic disease, and to grade diastolic function. Perspectives are given about how these innovations could be used to augment clinical practice, whilst areas for future investigation are identified.

Left ventricular diastolic pressure gradient and outcome in advanced chronic kidney disease patients with preserved ejection fraction

Assessment of left ventricular (LV) diastolic dysfunction is important in patients with chronic kidney disease (CKD). The early diastolic peak intraventricular pressure gradient (IVPG) has a vital role in diastolic function. Relative pressure imaging (RPI) is a new echocardiographic method to quantify IVPG. The purpose of this study was to analyze RPI-derived IVPG in advanced CKD patients with preserved LV ejection fraction. The study population consisted of 51 advanced CKD patients and 39 healthy controls. Patients were stratified by the evidence of heart failure with preserved ejection fraction (HFpEF) into HFpEF group (32 patients) and non-HFpEF group (19 patients). RPI analysis was used to determine the early diastolic LV relative pressure and pressure distribution. The total IVPG and segmental IVPGs corresponding to basal, mid, and apical part of the LV were calculated. Total IVPG, along with apical and mid IVPGs were all significantly reduced in HFpEF Group compared with non-HFpEF Group and controls (all P < 0.05). But no significant difference of total or segmental IVPGs was found between non-HFpEF Group and the controls. Additionally, apical IVPG < 0.02 mmHg/cm (Hazard ratio 9.82, 95 % confidence interval 2.01-48.01, P = 0.005) was the independent risk factor for the composite outcome (mortality and cardiovascular hospitalization) during a median follow-up of 24 months. Advanced CKD patients with HFpEF exhibited decreased apical and mid IVPG of the LV, and the severity of apical IVPG reduction correlated with poor outcome.

Intraoperative diastolic function assessed by TEE does not agree with preoperative diastolic function grade in CABG patients

OBJECTIVE

To compare the agreement of the 2016 ASE/EACVI guidelines for grading diastolic dysfunction (DD) with the most commonly used intraoperative transesophageal echocardiography (TEE)-based diastolic function grading algorithm in cardiac surgical patients, and to describe the contribution of the echocardiographic variables used in the algorithms to any observed differences.

DESIGN

Retrospective data analysis.

SETTING

University tertiary medical center.

PARTICIPANTS

Hundred and one patients undergoing coronary artery bypass grafting (CABG) at a single institution from June 2017 to February 2019.

INTERVENTIONS

Preoperative transthoracic echocardiography (TTE) diastolic function grade determined by the 2016 American Society of Echocardiography (ASE)/European Association of Cardiovascular Imaging (EACVI) guidelines was compared to intraoperative diastolic function grade obtained by TEE.

MEASUREMENTS AND MAIN RESULTS

Incidence of DD on preoperative TTE was only 19.8%, while 62.3% of patients were graded as having DD on the intraoperative TEE exam. There was grade agreement between TTE and TEE in only 47/101 patients (46.5%). The McNemar test showed poor agreement between the two algorithms (OR for disagreement = 15.33, CI = 4.77-49.30; p < 0.0001). Despite the low incidence of DD on preoperative TTE, mean lateral e' values were significantly lower on TTE compared to TEE (7.7 cm/s vs 9.5 cm/s; p = < 0.0001).

CONCLUSIONS

There is strong disagreement between TTE and TEE-based DD grading algorithms. Due to the different echocardiographic variables used in each and the unique clinical settings in which they are applied, they produce fundamentally different results.

Clinical Utility of Overlap Time for Incomplete Relaxation to Predict Cardiac Events in Heart Failure

BACKGROUND

The overlap time of transmitral flow can be a novel marker of subclinical left ventricular dysfunction for predicting adverse events in heart failure (HF). We aimed to (1) investigate the role of overlap time of the E-A wave in association with clinical parameters and (2) evaluate whether the overlap time could add prognostic information with respect to other conventional clinical prognosticators in HF.

METHODS

We prospectively evaluated 153 patients hospitalized with HF (mean age 68 ± 15 years; 63% male). The primary endpoint was readmission following HF or cardiac death.

RESULTS

During a median period of 25 months, 43 patients were readmitted or died. Overlap time appeared to be associated with worse outcomes. After adjustment for readmission scores and ratios of diastolic filling period and cardiac cycle length in a Cox proportional-hazards model, overlap time was associated with event-free survival, independent of elevated left atrial pressure based on guidelines. When overlap time was added to the model based on clinical variables and elevated left atrial pressure, the C-statistic significantly improved from 0.70 (95% CI: 0.63-0.77) to 0.77 (95% CI: 0.69-0.83, compared) (P = 0.035).

CONCLUSION

This preliminary study suggested that prolonged overlap time may have potential for predicting readmission and cardiac mortality risk assessment in patients with HF.

Alternative Echocardiographic Algorithm for Left Ventricular Filling Pressure in Patients With Heart Failure With Preserved Ejection Fraction

The American Society of Echocardiography and/or the European Association of Cardiovascular Imaging recommend a conventional algorithm for estimating left ventricular (LV) filling pressure in heart failure. However, several patients are classed as "indeterminate" due to their LV filling pressures being impossible to calculate. We investigated whether our new echocardiographic algorithm can predict clinical outcomes in patients with heart failure with preserved ejection fraction (HFpEF). We enrolled 754 consecutive patients from the PURSUIT-HFpEF registry. We used the new algorithm to divide them into 2 groups; a normal LV filling pressure group (N group) and a high LV filling pressure group (H group). The H group consisted of 342 patients. Over a mean follow-up of 342 days, 185 patients reached the primary composite end point (157 readmissions for worsening heart failure and 43 cardiovascular deaths). In a multivariable Cox analysis, being in the H group was significantly associated with an increased rate of cardiac events compared with the N group (hazard ratio: 1.71; 95% confidence interval: 1.17 to 2.50, p = 0.006). There were 56 patients (7%) who were assigned to "indeterminate" with the conventional algorithm. Using the new algorithm, we reclassified 16 patients (29%) into the H group and 40 patients (71%) into the N group. The Kaplan-Meier curves showed the reclassified H group had a significantly higher incidence of cardiac events than those assigned to the N group (p < 0.01). In conclusion, the present study demonstrated LV filling pressure assessed by our algorithm can predict clinical outcomes in patients with HFpEF.

Impact of Updated 2016 ASE/EACVI VIS-À-VIS 2009 ASE Recommendation on the Prevalence of Diastolic Dysfunction and LV Filling Pressures in Patients with Preserved Ejection Fraction

BACKGROUND

Assessment of diastolic dysfunction (DD) and left ventricular filling pressures (LVFP) by echocardiography is complex in patients with preserved ejection fraction (EF). The American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) jointly published recommendations in 2016 to simplify the diagnosis and classification of DD and the assessment of LVFP. We aimed to study the impact of the updated 2016 ASE/EACVI guidelines vis-à-vis the 2009 ASE recommendations on prevalence of DD and LVFP in patients with preserved EF.

METHODS

Five hundred patients referred to the echocardiography laboratory from March 2020 to May 2020 were analyzed. Patients with left ventricular ejection fraction (LVEF) < 50% were excluded. All patients underwent comprehensive transthoracic echocardiography. DD and LVFP were assessed by the 2016 ASE/EACVI and 2009 ASE recommendations. The concordance between the guidelines was analyzed by kappa coefficient and overall proportion of agreement.

RESULTS

Mean age was 53 ± 13 years and 63.4% were men. Prevalence of DD and abnormal LVFP were significantly lower with the 2016 recommendations than with the 2009 recommendations (9.4% vs. 16.8%, p < 0.001 and 8.4% vs. 12.8%, p < 0.05). Patients with Grade 1 DD (100%) and Grade 2 DD (46.4%) were reclassified by the 2016 recommendations. Indeterminate diastolic function (9.8%) was strikingly high according to the 2016 recommendations. The concordance between the two recommendations was moderate (kappa = 0.569). The overall proportion of agreement was 85.4%.

CONCLUSIONS

Prevalence of DD and abnormal LV filling pressures were lower with application of the 2016 ASE/EACVI recommendations in patients with preserved EF. There was moderate agreement between the 2009 and 2016 recommendations.

Feasibility, repeatability, and reproducibility of contemporary diastolic parameters and classification

PURPOSE

To evaluate feasibility, time of acquisition, retest repeatability and reproducibility of echocardiographic indexes and classification algorithms of diastolic function.

METHODS

A total of 356 patients were examined before coronary artery bypass-grafting and/or aortic valve surgery. A subgroup of 50 was examined with 3 successive echocardiograms in conditions reflecting daily clinical practice. Diastolic parameters were obtained and analysed according to previous (2009) and current (2016) guidelines. Acquisition and analysis time, plus intra- and inter-observer variability were assessed.

RESULTS

Feasibility of diastolic parameters was between 93 and 99%, except the maximal tricuspid regurgitation velocity (TR Vmax) (65%). Mean acquisition and analysis time were highest for left atrial volumes (141 ± 24 s) in contrast to other parameters which were obtained in approximately one minute. Mean 368 and 360 s were needed to classify diastolic function according to the 2009 and 2016 algorithms, respectively (non-significant). Reproducibility was overall moderate (Pearson r = 0.62 to 0.87), with TR Vmax having the highest (r = 0.62) and mitral valve E/A ratio the lowest (r = 0.87) variation. The 2009 algorithm resulted in more indeterminate cases than the 2016 algorithm. Inter-examiner analysis resulted in reclassification of 20 vs. 8 patients using the 2009 and 2016 algorithms, respectively.

CONCLUSION

Diastolic parameters are highly feasible and moderately reproducible, except TR Vmax. The 2016 algorithm is more restrictive than the 2009 algorithm in classifying patients with advanced stages of diastolic dysfunction. Time of acquisition according to the two guidelines is not significantly different.

Application of Guideline-Based Echocardiographic Assessment of Left Atrial Pressure to Heart Failure with Preserved Ejection Fraction

BACKGROUND

Early, noninvasive identification of patients with heart failure with preserved ejection fraction (HFpEF) with congestion may allow timely tailoring of decongestive therapies. The 2016 American Society of Echocardiography and European Association of Cardiovascular Imaging guidelines provide an algorithm to assess for elevated left atrial pressure (LAP); the associations of echocardiographic LAP with clinical status and disease progression in patients with HFpEF are unclear.

METHODS

Participants in the Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in HFpEF trial were categorized into one of four prespecified guideline-based echocardiographic LAP categories: (1) normal, (2) elevated, (3) atrial fibrillation (AF) at the time of echocardiography, or (4) indeterminate. Associations of echocardiographic LAP categories with baseline exercise capacity, change in exercise capacity, and change in N-terminal pro-B-type natriuretic peptide over 24 weeks were evaluated.

RESULTS

Of 216 participants, 199 underwent mitral inflow Doppler echocardiography for LAP categorization. Participants with elevated echocardiographic LAP (n = 81) or AF (n = 57) were older and had a higher prevalence of kidney dysfunction. Compared with the normal echocardiographic LAP group (n = 28), elevated echocardiographic LAP and AF were each independently associated with a greater reduction in peak oxygen consumption over 24 weeks after adjusting for baseline values and clinical covariates (β for elevated echocardiographic LAP = -1.55 [95% CI, -2.59 to -0.51], P = .004; β for AF = -1.33 [95% CI, -2.49 to -0.17], P = .03). Indeterminate echocardiographic LAP (n = 33) was also independently associated with a reduction in exercise capacity at 24 weeks compared with normal echocardiographic LAP (β = -1.35; 95% CI, -2.51 to -0.19; P = .02). Finally, elevated echocardiographic LAP and AF were significantly associated with increases in N-terminal pro-B-type natriuretic peptide over 24 weeks compared with normal echocardiographic LAP.

CONCLUSIONS

In patients with chronic HFpEF, elevated echocardiographic LAP and indeterminate echocardiographic LAP, as defined by contemporary guidelines, and AF were each independently associated with a reduction in exercise capacity compared with normal echocardiographic LAP. These findings suggest the potential utility of noninvasive LAP assessment in patients with HFpEF for tailoring treatments that decrease congestion.

Echocardiographic diagnosis of left ventricular diastolic dysfunction: Impact of coronary artery disease

BACKGROUND

In 2016, the American Society of Echocardiography (ASE) released guidelines for identifying left ventricular (LV) diastolic dysfunction (DD), but its ability to detect early hemodynamic abnormalities is not well established, especially in the setting of subclinical coronary artery disease (CAD). We hypothesize that the accuracy of ASE categorization of early LVDD is affected by knowledge of whether CAD history is present.

METHODS

We studied 34 patients (age 62 ± 7 years) with NYHA class I to II symptoms and with transthoracic echocardiography without findings suggesting myocardial disease (all with preserved LV ejection fraction), who underwent cardiac catheterization with high-fidelity LV pressure measurement. Echocardiographic images were evaluated for LVDD using ASE algorithm without and with knowledge of CAD history and angiography findings. CAD was considered as having DD for the algorithm.

RESULTS

CAD was identified in 22 patients at catheterization (65%). Using ASE guidelines without including history of CAD or angiographic results, 29 patients were DD-, 3 were DD+ (all grade II), and 2 were indeterminate. Inclusion of CAD history recategorized 59% (n = 20) patients to DD+ (all grade I) from DD- (P < .0001). Nineteen of the recategorized patients (95%) had increased isovolumetric relaxation time (IVRT). The addition of echocardiographic IVRT improved discrimination between DD- and DD+, when the presence of CAD is unknown.

CONCLUSIONS

2016-ASE algorithm reasonably accurately identifies early LVDD at rest as reflected by LV catheterization when CAD is disclosed, but without knowledge of the presence of CAD, it underdiagnoses DD+ grade I. The addition of IVRT may improve early LVDD diagnostics.

Biomechanics of diastolic dysfunction: a one-dimensional computational modeling approach

Diastolic dysfunction (DD) is a major component of heart failure with preserved ejection fraction (HFpEF). Accordingly, a profound understanding of the underlying biomechanical mechanisms involved in DD is needed to elucidate all aspects of HFpEF. In this study, we have developed a computational model of DD by leveraging the power of an advanced one-dimensional arterial network coupled to a four-chambered zero-dimensional cardiac model. The two main pathologies investigated were linked to the active relaxation of the myocardium and the passive stiffness of the left ventricular wall. These pathologies were quantified through two parameters for the biphasic delay of active relaxation, which simulate the early and late-phase relaxation delay, and one parameter for passive stiffness, which simulates the increased nonlinear stiffness of the ventricular wall. A parameter sensitivity analysis was conducted on each of the three parameters to investigate their effect in isolation. The three parameters were then concurrently adjusted to produce the three main phenotypes of DD. It was found that the impaired relaxation phenotype can be replicated by mainly manipulating the active relaxation, the pseudo-normal phenotype was replicated by manipulating both the active relaxation and passive stiffness, and, finally, the restricted phenotype was replicated by mainly changing the passive stiffness. This article presents a simple model producing a holistic and comprehensive replication of the main DD phenotypes and presents novel biomechanical insights on how key parameters defining the relaxation and stiffness properties of the myocardium affect the development and manifestation of DD.NEW & NOTEWORTHY This study uses a complete and validated computational model of the cardiovascular system to simulate the two main pathologies involved in diastolic dysfunction (DD), i.e., abnormal active relaxation and increased ventricular diastolic stiffness. The three phenotypes of DD were successfully replicated according to literature data. We elucidate the biomechanical effect of the relaxation pathologies involved and how these pathologies interact to create the various phenotypes of DD.

Novel Echocardiographic Approach to Hemodynamic Phenotypes Predicts Outcome of Patients Hospitalized With Heart Failure

BACKGROUND

Although in clinical practice heart failure (HF) patients are classified using left ventricular ejection fraction (LVEF), this categorization is insufficient for prognosis, especially when LVEF is preserved or there is a concomitant right ventricular (RV) dysfunction. We hypothesized that a combined noninvasive evaluation of LV forward flow, filling pressure, and RV function would be better than LVEF in predicting all-cause mortality of hospitalized patients with HF.

METHODS

Transthoracic echocardiographic examinations of 603 patients hospitalized with HF were analyzed. In a subsample of 200 patients with HF, LV stroke volume index, LV filling pressure estimation, tricuspid annular plane systolic excursion, and systolic pulmonary artery pressure were combined to determine 4 hemodynamic profiles: normal flow-normal pressure, normal flow-high pressure, low flow without RV dysfunction, and low flow with RV dysfunction profile. This model was then applied in a validation cohort (n=403).

RESULTS

Prognosis worsened from the normal flow-normal pressure profile to the low flow with right ventricular dysfunction profile. At the multivariate survival analysis, the model showed independent high risk-stratification capability (P<0.001), even in subgroups of patients with LVEF < or ≥50% (P=0.011 and P<0.001, respectively) and < or ≥40% (P=0.044 and P<0.001, respectively). LVEF and HF classification based on LVEF did not predict outcome.

CONCLUSIONS

Echocardiographic-derived profiling of LV forward flow, filling pressure, and RV function allowed categorization of patients hospitalized with HF and predicted all-cause mortality independently of LVEF. This model is based on conventional echocardiography, is easy to apply, and is, therefore, suggested for clinical practice.

Impact of the 2016 ASE/EACVI Guidelines on diastolic function reporting in routine clinical practice

OBJECTIVE

To evaluate the impact of 2016 ASE/EACVI guidelines on Diastolic Function (DF) reporting during routine clinical practice.

METHODS

Transthoracic echos performed 9 months before and 18 months after the 2016 guidelines (DF2016) were retrospectively analyzed.

RESULTS

Twenty thousand eight hundred forty three echos performed between July 1, 2015, and September 30, 2017, were analyzed. Quarterly trends showed a stable proportion of normal DF (nDF), diastolic dysfunction (DD), indeterminate DF (DF-I), and nonreported DF (DF-NR) for 3 quarters preceding DF2016. After DF2016 release, reporting of DD decreased by 57% (P < .001), nDF increased by 76% (P < .001), DF-NR increased by 266% (P < .001), and DF-I did not change significantly (P = .40). Grade 1 DD decreased by 64% (P < .001), grade 2 DD decreased by 51% (P < .001), and grade 3 DD did not change significantly (P = .18). Provider level analysis showed increased heterogeneity in grade 1 DD reporting and decreased heterogeneity in DD grades 2 or higher, after DF2016. Systolic dysfunction reporting remained relatively stable (22%→21%→20%) compared to a significant decrease in isolated DD (35%→21%→10%).

CONCLUSION

The 2016 guidelines update has impacted DF reporting patterns significantly. The likelihood of reporting DD decreased significantly, especially for grades 1 and 2. Inter-provider heterogeneity in DF reporting improved for grades 2 and 3 but worsened for grade 1. There was more than threefold increase in failure to report DF, suggesting a decrease in provider confidence.

Assessment of the Left Ventricular Diastolic Function and Its Association with the Left Atrial Pressure in Patients with Atrial Fibrillation

Background and Objectives

The evaluation of left ventricular (LV) diastolic function in patients with atrial fibrillation (AF) is challenging. This study aimed to investigate the efficacy of the diagnostic algorithm for LV diastolic dysfunction (LVDD) in the current guidelines and to evaluate the association between increased left atrial pressure (LAP) and LV diastolic parameters.

Methods

One hundred and twenty-four patients with non-valvular AF and a preserved LV ejection fraction who had the same rhythm status on echocardiography and LAP measurements during catheter ablation were included. LV diastolic function was classified as normal, indeterminate, or LVDD according to the recent guidelines. Increased LAP was defined as mean LAP (mLAP) ≥15 mmHg.

Results

The mLAP was not different among the normal, indeterminate, and LVDD groups. However, the prevalence of increased LAP was higher in the LVDD group. Among the LV diastolic parameters, only medial E/e′ was independently associated with mLAP in the whole study population. In patients with persistent AF (PeAF), E/e′ and e′ were significantly associated with mLAP, whereas in paroxysmal AF (PAF), mLAP was not associated with the LV diastolic parameters but with left atrial conduit function.

Conclusions

In general, increased LAP is known to be closely related with LVDD. However, the algorithm for LVDD from recent guidelines does not reflect well the increased LAP in AF patients. The diastolic parameters may aid in estimating the increased LAP in PeAF but may only have limited value for assessing increased LAP in PAF.

B-Type Natriuretic Peptides (BNP) and Tissue Doppler E/e´ Before and After 4 Weeks Standard Treatment of African Heart Failure Subjects: The ABU-BNP Longitudinal Survey

BACKGROUND

The study aimed at determining the response of BNP and tissue Doppler (TD) E/e´ to standard heart failure (HF) therapy in an African black population as data on these are lacking in Africa. BNP assessment in relation to HF severity and its association with its predictors were also determined.

METHODS

It was a longitudinal-analytical study with a one month follow-up among 100 HF patients seen at Ahmadu Bello University Teaching Hospital, Zaria-Nigeria. Two-way Repeated Measures ANOVA determined BNP levels before and after treatment according to the HF severity. Wilcoxon-Signed Ranks test determined the difference in BNP and TD E/e´ before and after treatment. Pearson's correlation assessed log-transformed BNP's association with its predictors.

RESULTS

BNP significantly (p<0.001) rose with increasing severity of HF from 386.6 ± 186.5 pg/mL to 581.7 ± 299.0 pg/mL to 805.0 ± 484.0 pg/mL in the NYHA II-IV HF, respectively, with consequent fall in a similar fashion following treatment. The Median (IQR) BNP levels reduced significantly (p<0.001) from 450 (362.5, 712.5) to 275.0 (225, 375.2) pg/mL with a 38.9% reduction over 4 weeks associated with significant improvement in TD E/e´, structural and functional parameters. Ln10BNP was significantly (p<0.001) positively correlated to TD E/e´ before (r=0.51) and after treatment (r=0.43). Likewise, Ln10BNP was significantly (p<0.05) negatively correlated to ejection fraction & fractional shortening before and after treatment.

CONCLUSION

BNP and tissue Doppler can serve as useful tools in the assessment of the effectiveness of African HF treatment and functional capacity over 4 weeks. TD E/e´ may be a reliable non-invasive estimate of left ventricular filling pressures and diastolic dysfunction.

Practical Impact of New Diastolic Recommendations on Noninvasive Estimation of Left Ventricular Diastolic Function and Filling Pressures

BACKGROUND

In 2016, an update of the 2009 recommendations for the evaluation of left ventricular (LV) diastolic function (DF) was released by the American Society of Echocardiography and the European Association of Cardiovascular Imaging. The aims of this study were to assess the concordance between the 2016 and 2009 recommendations and to test the impact of the consideration of "myocardial disease" recommended in the 2016 update on the evaluation of diastolic dysfunction (DD) and LV filling pressures in patients with normal and reduced LV ejection fractions referred to a general echocardiography laboratory.

METHODS

A total of 1,508 outpatients referred to an echocardiography laboratory during a predefined 5-month period were prospectively enrolled. All patients underwent targeted clinical history and Doppler echocardiographic examination. DD and LV filling pressures were assessed according to 2009 and 2016 recommendations. Concordance was calculated using the κ coefficient and overall proportion of agreement.

RESULTS

Overall proportion of agreement between the two recommendations was 64.7% (κ = 0.43). Comparing the 2009 and 2016 recommendations, 47.5% and 36.1% patients, respectively, had DD (P < .0001), and 22.7% and 12.6% had elevated LV filling pressures (P < .0001). This difference remained significant in the setting of patients with normal LV ejection fractions (21.6% vs 10.7%, P < .0001). In the application of the 2016 recommendations, whether or not the presence of "myocardial disease" was considered, the prevalence of indeterminate diastolic function was, respectively, 7.3% versus 13.7%, while patients in whom the DD grade could not be determined were 8.1% versus 14.4% (P < .0001 for all).

CONCLUSIONS

Considering the presence of myocardial disease when applying the 2016 recommendations resulted in a lower prevalence of inconclusive diagnosis.

Echocardiographic Detection of Occult Diastolic Dysfunction in Pulmonary Hypertension After Fluid Challenge

Background Identification of occult diastolic dysfunction often requires invasive right heart catheterization with provocative maneuvers such as fluid challenge. Non-invasive predictors of occult diastolic dysfunction have not been identified. We hypothesized that echocardiographic measures of diastolic function are associated with occult diastolic dysfunction identified at catheterization. Methods and Results We retrospectively examined hemodynamic and echocardiographic data from consecutive patients referred for right heart catheterization with fluid challenge from 2009 to 2017. A replication cohort of 52 patients who prospectively underwent simultaneous echocardiography and right heart catheterization before and after fluid challenge at Monaldi Hospital, Naples, Italy. In the retrospective cohort of 126 patients (83% female, 56+14 years), 27/126 (21%) had occult diastolic dysfunction. After adjusting for tricuspid regurgitant velocity and left atrial volume index, E velocity (odds ratio 1.8, 95% CI 1.1-2.9, P=0.01) and E/e' (odds ratio 1.9, 95% CI 1.1-3, P=0.005) were associated with occult diastolic dysfunction with an optimal threshold of E/e' >8.6 for occult diastolic dysfunction (sensitivity 70%, specificity 64%). In the prospective cohort, 5/52 (10%) patients had diastolic dysfunction after fluid challenge. Resting E/e' (odds ratio 8.75, 95% CI 2.3-33, P=0.001) and E velocity (odds ratio 7.7, 95% CI 2-29, P=0.003) remained associated with occult diastolic dysfunction with optimal threshold of E/e' >8 (sensitivity 73%, specificity 90%). Conclusions Among patients referred for right heart catheterization with fluid challenge, E velocity and E/e' are associated with occult diastolic dysfunction after fluid challenge. These findings suggest that routine echocardiographic measurements may help identify patients like to have occult diastolic dysfunction non-invasively.

Echocardiographic predictors of all-cause mortality in patients with left ventricular ejection fraction >35%: Value of guideline based assessment of diastolic dysfunction

Background

Recent data suggests that the majority of cardiac deaths in patients with heart failure occur in patients with a left ventricular ejection fraction (LVEF) >35%. This study sought to determine the value of guideline based assessment of diastolic dysfunction in predicting all-cause mortality in patients with a first-ever myocardial infarction (MI) with an LVEF >35%.

Methods

A retrospective single centre study involving 383 patients with a first-ever MI (STEMI or NSTEMI) with LVEF >35% was performed. Clinical, angiographic and echocardiographic data were obtained from prospectively maintained institutional databases. Outcomes data were obtained from national death registry. Echocardiography was performed early post-admission for all patients. Significant diastolic dysfunction (DD) was defined was grade 2/3 diastolic dysfunction according to current American Society of Echocardiography/European Association of Cardiovascular Imaging guidelines.

Results

At a median follow up of 2 years, there were 32 deaths. On Cox proportional hazards multivariate analysis incorporating significant clinical variables (age, chronic kidney disease and extent of coronary artery disease), significant DD (HR 2.57, 95%CI 1.16–5.68, p = 0.020) and left ventricular end-diastolic volume index (HR 1.03, 1.04–1.07, p = 0.021) were the only independent echocardiographic predictors of all-cause mortality. Intermodel comparisons using model χ² and Harrel's-C confirmed incremental value of DD. In the subgroup with LVEF 36–55% (n = 176), significant DD was the only independent echocardiographic predictor (HR 3.56, 95%CI 2.46–9.09, p = 0.006).

Conclusions

The presence of significant DD identifies patients with LVEF >35% following MI who are at a higher risk of all-cause mortality, and who may benefit from further risk stratification and treatment.

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The majority of deaths in heart failure patients occur in patients with LVEF>35%.

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Diastolic dysfunction identifies elevated risk of death in patients with LVEF>35%.

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Diastolic dysfunction thus identifies patients for further risk stratification.

Clinical utility of the 2016 ASE/EACVI recommendations for the evaluation of left ventricular diastolic function in the stratification of post-discharge prognosis in patients with acute heart failure

Aims

Left ventricular diastolic dysfunction (LVDD) has prognostic significance in heart failure (HF). We aimed to assess the impact of LVDD grade stratified by the updated 2016 echocardiographic algorithm (DD2016) on post-discharge outcomes in patients admitted for acute HF and compare with the previous 2009 algorithm (DD2009).

Methods and results

The study included 481 patients hospitalized for acute decompensated HF. Comprehensive echocardiography and LVDD evaluation were performed just before hospital discharge. The primary endpoint was a composite of cardiovascular death and readmission for HF. The concordance between DD2016 and DD2009 was moderate (κ = 0.44, P < 0.001); the reclassification rate was 39%. During the follow-up (median: 15 months), 127 (26%) patients experienced the primary endpoint. In the Kaplan–Meier analysis, Grade III in DD2016 showed a lower event-free survival rate than Grades I and II (log rank, P < 0.001 and P = 0.048, respectively) and was independently associated with a higher incidence of the primary endpoint than Grade I [hazard ratio 1.89; 95% confidence interval (CI) 1.17–3.04; P = 0.009]. Grade II or III in DD2016, reflecting elevation of left ventricular (LV) filling pressure, added an incremental predictive value of the primary endpoint to clinical variables irrespective of LV ejection fraction. DD2016 was comparable to DD2009 in predicting the endpoint (net reclassification improvement = 11%; 95% CI −7% to 30%, P = 0.23).

Conclusion

Despite simplification of the algorithm for LVDD evaluation, the prognostic value of DD2016 for post-discharge cardiovascular events in HF patients was maintained and not compromised in comparison with DD2009.