The prognostic role of advanced hemodynamic variables in patients with left ventricular assist devices.

BACKGROUND: Invasive hemodynamic variables obtained from right heart catheterization have been used for risk-stratifying patients with advanced heart failure (HF). However, there is a paucity of data on the prognostic value of invasive hemodynamic variables in patients with left ventricular assist devices (LVAD). We hypothesized that cardiac power output (CPO), cardiac power efficiency (CPE), and left ventricular stroke work index (LVSWI) can serve as prognostic markers in patients with LVADs. METHODS: Baseline hemodynamic data from patients who had LVAD ramp studies at our institution from 4/2014 to 7/2018 were prospectively collected, from which advanced hemodynamic variables (CPO, CPE, and LVSWI) were retrospectively analyzed. Univariate and multivariable analyses were performed for hemocompatibility-related adverse events (HRAE), HF admissions, and mortality. RESULTS: Ninety-one participants (age 61 ± 11 years, 34% women, 40% Black or African American, and 38% ischemic cardiomyopathy) were analyzed. Low CPE was significantly associated with mortality (HR 2.42, 95% CI 1.02-5.74, p = 0.045) in univariate analysis and Kaplan-Meier analysis (p = 0.04). Low LVSWI was significantly associated with mortality (HR 2.13, 95% CI 1.09-4.17, p = 0.03) in univariate analysis and Kaplan-Meier analysis (p = 0.02). CPO was not associated with mortality. CPO, CPE, and LVSWI were not associated with HRAE or HF admissions. CONCLUSIONS: Advanced hemodynamic variables can serve as prognostic indicators for patients with LVADs. Low CPE and LVSWI are prognostic for higher mortality, but no variables were associated with HF admissions or HRAEs.

Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence.

BACKGROUND: Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development. METHODS: We identified 100 patients from our prior study who had the largest differences between manually measured and automated RVEF values. Automated RVEF measurements were performed using the original version of the algorithm (DL1), an updated version (DL2) developed from a dataset that included a wider range of RV pathology and validated using multiple domain-specific quantitative performance evaluation metrics, and conventional methodology performed by a core laboratory (CORE). Each of the DL-RVEF approaches was compared against CORE-RVEF reference values using linear regression and Bland-Altman analyses. Additionally, RVEF values were classified into 3 categories: ≤ 35%, 35-50%, and ≥ 50%. Agreement between RVEF classifications made by the DL approaches and the CORE measurements was tested. RESULTS: CORE-RVEF and DL-RVEFs were obtained in all patients (feasibility of 100%). DL2-RVEF correlated with CORE-RVEF better than DL1-RVEF (r = 0.87 vs. r = 0.42), with narrower limits of agreement. As a result, DL2 algorithm also showed increasing accuracy from 0.53 to 0.80 for categorizing RV function. CONCLUSIONS: The use of a new DL algorithm cross-validated on a dataset with a wide range of RV pathology using multiple domain-specific metrics resulted in a considerable improvement in the accuracy of automated RVEF measurements. This improvement was demonstrated in patients whose images were the most challenging and resulted in the largest RVEF errors. These findings underscore the critical importance of this strategy in the development of DL approaches for automated CMR measurements.

Aortic Pulsatility Index: A Novel Hemodynamic Variable for Evaluation of Decompensated Heart Failure.

BACKGROUND: Right heart catheterization for invasive hemodynamics has shown only modest correlation with clinical outcomes. We designed a novel hemodynamic variable that incorporates ventricular output and filling pressure. We anticipated that the aortic pulsatility index (API) would correlate with clinical outcomes in patients with heart failure. METHODS AND RESULTS: We retrospectively analyzed consecutive patients undergoing right heart catheterization with milrinone drug study at our institution (February 2013 to November 2019). The API was calculated as (systolic blood pressure - diastolic blood pressure)/pulmonary capillary wedge pressure. The primary outcome was freedom from advanced therapies, defined as the need for inotropes, temporary mechanical circulatory support, a left ventricular assist device, or orthotopic heart transplantation, or death at 30 days. A total of 224 patient encounters, age 57 years (48-66 years; 34% women; 31% ischemic cardiomyopathy) were included. In univariable analysis, lower baseline API was significantly associated with progression to advanced therapies or death at 30-days (odds ratio 0.43, 95% confidence interval 0.30-0.61; P < .001) compared with those on continued medical management. Receiver operator characteristic analysis specified an optimal cutpoint of 1.45 for API. A Kaplan-Meier analysis indicated an association of API with the primary outcome (79% for API ≥ 1.45 vs 48% for API < 1.45). In multivariable analysis, higher API was strongly associated with freedom from advanced therapies or death (odds ratio 0.38, 95% confidence interval 0.22-0.65, P ≤ .001), even when adjusted for baseline characteristics and routine right heart catheterization measurements. CONCLUSIONS: The API is a novel invasive hemodynamic measurement that is associated independently with freedom from advanced therapies or death at 30-day follow-up.

Disparities in acute decompensated heart failure.

PURPOSE OF REVIEW: The aim of this review is to discuss racial and sex disparities in the management and outcomes of patients with acute decompensated heart failure (ADHF). RECENT FINDINGS: Race and sex have a significant impact on in-hospital admissions and overall outcomes in patients with decompensated heart failure and cardiogenic shock. Black patients not only have a higher incidence of heart failure than other racial groups, but also higher admissions for ADHF and worse overall survival, while women receive less interventions for cardiogenic shock complicating acute myocardial infarction. Moreover, White patients are more likely than Black patients to be cared for by a cardiologist than a noncardiologist in the ICU, which has been linked to overall improved survival. In addition, recent data outline inherent racial and sex bias in the evaluation process for advanced heart failure therapies indicating that Black race negatively impacts referral for transplant, women are judged more harshly on their appearance, and that Black women are perceived to have less social support than others. This implicit bias in the evaluation process may impact appropriate timing of referral for advanced heart failure therapies. SUMMARY: Though significant racial and sex disparities exist in the management and treatment of patients with decompensated heart failure, these disparities are minimized when therapies are properly utilized and patients are treated according to guidelines.

Overexpression of Latent TGFß Binding Protein 4 in Muscle Ameliorates Muscular Dystrophy through Myostatin and TGFß.

Latent TGFß binding proteins (LTBPs) regulate the extracellular availability of latent TGFß. LTBP4 was identified as a genetic modifier of muscular dystrophy in mice and humans. An in-frame insertion polymorphism in the murine Ltbp4 gene associates with partial protection against muscular dystrophy. In humans, nonsynonymous single nucleotide polymorphisms in LTBP4 associate with prolonged ambulation in Duchenne muscular dystrophy. To better understand LTBP4 and its role in modifying muscular dystrophy, we created transgenic mice overexpressing the protective murine allele of LTBP4 specifically in mature myofibers using the human skeletal actin promoter. Overexpression of LTBP4 protein was associated with increased muscle mass and proportionally increased strength compared to age-matched controls. In order to assess the effects of LTBP4 in muscular dystrophy, LTBP4 overexpressing mice were bred to mdx mice, a model of Duchenne muscular dystrophy. In this model, increased LTBP4 led to greater muscle mass with proportionally increased strength, and decreased fibrosis. The increase in muscle mass and reduction in fibrosis were similar to what occurs when myostatin, a related TGFß family member and negative regulator of muscle mass, was deleted in mdx mice. Supporting this, we found that myostatin forms a complex with LTBP4 and that overexpression of LTBP4 led to a decrease in myostatin levels. LTBP4 also interacted with TGFß and GDF11, a protein highly related to myostatin. These data identify LTBP4 as a multi-TGFß family ligand binding protein with the capacity to modify muscle disease through overexpression.

Right heart failure after durable left ventricular assist device implantation.

INTRODUCTION: Right heart failure (RHF) is a well-known complication after left ventricular assist device (LVAD) implantation and portends increased morbidity and mortality. Understanding the mechanisms and predictors of RHF in this clinical setting may offer ideas for early identification and aggressive management to minimize poor outcomes. A variety of medical therapies and mechanical circulatory support options are currently available for the management of post-LVAD RHF. AREAS COVERED: We reviewed the existing definitions of RHF including its potential mechanisms in the context of durable LVAD implantation and currently available medical and device therapies. We performed a literature search using PubMed (from 2010 to 2023). EXPERT OPINION: RHF remains a common complication after LVAD implantation. However, existing knowledge gaps limit clinicians' ability to adequately address its consequences. Early identification and management are crucial to reducing the risk of poor outcomes, but existing risk stratification tools perform poorly and have limited clinical applicability. This is an area ripe for investigation with the potential for major improvements in identification and targeted therapy in an effort to improve outcomes.

Mechanical circulatory support device selection for bridging to cardiac transplantation: a clinical guide.

INTRODUCTION: Many patients listed for transplant require temporary or durable mechanical circulatory support (MCS) devices for bridging to cardiac transplantation. The choice of device for bridging to heart depends on a number of factors including level of support desired and patient-device hemocompatibility. AREAS COVERED: The authors summarize the current heart transplant landscape including the new UNOS listing criteria as well as indications for bridging to transplant with MCS devices. The authors also review the characteristics of commonly used MCS devices and discuss the limited evidence supporting their use in cardiogenic shock and specifically as a bridge to heart transplant. EXPERT OPINION: The new UNOS heart organ allocation policy has resulted in a growth in the use of temporary MCS devices as bridge to transplantation for patients with cardiogenic shock, while bridging with durable MCS devices has become more challenging. Patients supported on temporary MCS devices should be routinely assessed for potential of myocardial recovery prior to urgent transplantation. Emerging machine learning algorithms may help better identify individuals who are likely to recover on temporary or durable MCS therapy. Modifications to the current heart allocation policy may facilitate bridging of patients with durable left ventricular assist devices.

Relation of Myocardial Perfusion Reserve and Left Ventricular Ejection Fraction in Ischemic and Nonischemic Cardiomyopathy.

Quantification of myocardial perfusion reserve (MPR) using vasodilator stress cardiac magnetic resonance is increasingly used to detect coronary artery disease. However, MPR can also be altered because of changes in microvascular function. We aimed to determine whether MPR can distinguish between ischemic cardiomyopathy (IC) secondary to coronary artery disease and non-IC (NIC) with microvascular dysfunction and no underlying epicardial coronary disease. A total of 60 patients (mean age 65 ± 14 years, 30% women), including 31 with IC and 29 with NIC, were identified from a pre-existing vasodilator stress cardiac magnetic resonance registry. Short-axis cine slices were used to measure left ventricular ejection fraction (LVEF) using the Simpson method of disks. MPR index (MPRi) was determined from first-pass myocardial perfusion images during stress and rest using the upslope ratio, normalized for the arterial input and corrected for rate pressure product. Patients in both groups were divided into subgroups of LVEF ≤35% and LVEF >35%. Differences in MPRi between the subgroups were examined. MPRi was moderately correlated with LVEF in patients with NIC (r = 0.53, p = 0.03), whereas the correlation in patients with IC was lower (r = 0.32, p = 0.22). Average LVEF in NIC and IC was 34% ± 8% and 35% ± 8%, respectively (p = 0.63). MPRi was not significantly different in IC compared with NIC (1.17 [0.88 to 1.61] vs 1.23 [1.07 to 1.66], p = 0.41), including the subgroups of LVEF (IC: 1.20 ± 0.56 vs NIC: 1.15 ± 0.24, p = 0.75 for LVEF ≤35% and IC: 1.35 ± 0.44 vs NIC: 1.58 ± 0.50, p = 0.19 for LVEF >35%). However, MPRi was significantly lower in patients with LVEF ≤35% compared with those with LVEF>35% (1.17 ± 0.40 vs 1.47 ± 0.47, p = 0.01). Similar difference between LVEF groups was noted in the patients with NIC (1.15 ± 0.24 vs 1.58 ± 0.50, p = 0.006) but not in the patients with IC (1.20 ± 0.56 vs 1.35 ± 0.44, p = 0.42). MPRi can be abnormal in the presence of left ventricular dysfunction with nonischemic etiology. This is a potential pitfall to consider when using this approach to detect ischemia because of epicardial coronary disease using myocardial perfusion imaging.

AI Based CMR Assessment of Biventricular Function: Clinical Significance of Intervendor Variability and Measurement Errors.

OBJECTIVES: The aim of this study was to determine whether left ventricular ejection fraction (LVEF) and right ventricular ejection fraction (RVEF) and left ventricular mass (LVM) measurements made using 3 fully automated deep learning (DL) algorithms are accurate and interchangeable and can be used to classify ventricular function and risk-stratify patients as accurately as an expert. BACKGROUND: Artificial intelligence is increasingly used to assess cardiac function and LVM from cardiac magnetic resonance images. METHODS: Two hundred patients were identified from a registry of individuals who underwent vasodilator stress cardiac magnetic resonance. LVEF, LVM, and RVEF were determined using 3 fully automated commercial DL algorithms and by a clinical expert (CLIN) using conventional methodology. Additionally, LVEF values were classified according to clinically important ranges: <35%, 35% to 50%, and ≥50%. Both ejection fraction values and classifications made by the DL ejection fraction approaches were compared against CLIN ejection fraction reference. Receiver-operating characteristic curve analysis was performed to evaluate the ability of CLIN and each of the DL classifications to predict major adverse cardiovascular events. RESULTS: Excellent correlations were seen for each DL-LVEF compared with CLIN-LVEF (r = 0.83-0.93). Good correlations were present between DL-LVM and CLIN-LVM (r = 0.75-0.85). Modest correlations were observed between DL-RVEF and CLIN-RVEF (r = 0.59-0.68). A >10% error between CLIN and DL ejection fraction was present in 5% to 18% of cases for the left ventricle and 23% to 43% for the right ventricle. LVEF classification agreed with CLIN-LVEF classification in 86%, 80%, and 85% cases for the 3 DL-LVEF approaches. There were no differences among the 4 approaches in associations with major adverse cardiovascular events for LVEF, LVM, and RVEF. CONCLUSIONS: This study revealed good agreement between automated and expert-derived LVEF and similarly strong associations with outcomes, compared with an expert. However, the ability of these automated measurements to accurately classify left ventricular function for treatment decision remains limited. DL-LVM showed good agreement with CLIN-LVM. DL-RVEF approaches need further refinements.

The Clinical Importance of Hyponatremia in Patients with Left Ventricular Assist Devices.

Hyponatremia is associated with increased morbidity and mortality in heart failure (HF) patients. The implication of hyponatremia during left ventricular assist device (LVAD) therapy remains unknown. In this retrospective study, consecutive LVAD patients implanted between April 2014 and March 2018 were stratified by the presence of hyponatremia (serum sodium <135 mEq/L) at 30 days post-LVAD. Incidence of HF readmissions and survival during 1-year follow-up were compared between the groups. Of 204 patients identified, 170 were included. Serum sodium levels improved significantly from pre-LVAD to 1-year post-LVAD (136 [133, 139] mEq/L to 137 [135, 140] mEq/L, p < 0.001). At 30 days, 35 patients (21%) were in the hyponatremia group. No difference was observed for 1-year survival between groups (77% vs. 81%, p = 0.66). However, the incidence of HF readmissions was significantly higher in the hyponatremia group (44% vs. 15%, p = 0.001). Among the patients with pre-LVAD hyponatremia (N = 60), those with normalized serum sodium levels (N = 42) had a lower incidence of HF readmissions compared with those with persistent hyponatremia (12% vs. 44%, p = 0.008). Hyponatremia in LVAD patients is associated with a higher incidence of HF readmissions. Further studies are needed to elucidate whether therapies directed at hyponatremia (e.g., vasopressin antagonists) would improve outcomes in LVAD patients.

Prognostic value of pre-treatment CT texture analysis in combination with change in size of the primary tumor in response to induction chemotherapy for HPV-positive oropharyngeal squamous cell carcinoma.

BACKGROUND: To determine the additive value of quantitative radiomic texture features in predicting progression in human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) based on pre-treatment CT. METHODS: Retrospective analysis of a single-center cohort of adult patients enrolled in a response-adapted radiation volume de-escalation trial treated with induction chemotherapy. Texture analysis of HPV-positive OPSCC was performed via primary tumor site contouring on pre-treatment contrast-enhanced CT scans. Percent change in size of the tumor in response to induction chemotherapy based on RECIST 1.1 criteria and progression free survival were clinically determined for this cohort. Receiver operating characteristic (ROC) analysis was performed to compare the accuracy of percent change in tumor size after induction chemotherapy with a combination of change in tumor size and radiomic texture features for predicting tumor progression. RESULTS: Radiomic texture analysis of the primary tumors in 38 patients with OPSCC depicted on pre-treatment neck CT scans using skewness and entropy in combination with percent change in tumor size after induction chemotherapy yielded a statistically significant increase in accuracy for predicting tumor progression over change in tumor size alone, with an area under the curve of 0.80 versus 0.56 (one-tailed P=0.0087). CONCLUSIONS: This pilot study suggests that disease progression in patients with HPV-positive OPSCC is more accurately predicted using a combination of texture features on pre-treatment CT scans, along with change in tumor size compared to change in tumor size alone and could therefore serve as a radiomic texture signature.

Genotype-Specific Interaction of Latent TGFß Binding Protein 4 with TGFß.

Latent TGFß binding proteins are extracellular matrix proteins that bind latent TGFß to form the large latent complex. Nonsynonymous polymorphisms in LTBP4, a member of the latent TGFß binding protein gene family, have been linked to several human diseases, underscoring the importance of TGFß regulation for a range of phenotypes. Because of strong linkage disequilibrium across the LTBP4 gene, humans have two main LTBP4 alleles that differ at four amino acid positions, referred to as IAAM and VTTT for the encoded residues. VTTT is considered the "risk" allele and associates with increased intracellular TGFß signaling and more deleterious phenotypes in muscular dystrophy and other diseases. We now evaluated LTBP4 nsSNPs in dilated cardiomyopathy, a distinct disorder associated with TGFß signaling. We stratified based on self-identified ethnicity and found that the LTBP4 VTTT allele is associated with increased risk of dilated cardiomyopathy in European Americans extending the diseases that associate with LTBP4 genotype. However, the association of LTBP4 SNPs with dilated cardiomyopathy was not observed in African Americans. To elucidate the mechanism by which LTBP4 genotype exerts this differential effect, TGFß's association with LTBP4 protein was examined. LTBP4 protein with the IAAM residues bound more latent TGFß compared to the LTBP4 VTTT protein. Together these data provide support that LTBP4 genotype exerts its effect through differential avidity for TGFß accounting for the differences in TGFß signaling attributed to these two alleles.

Targeting latent TGFß release in muscular dystrophy.

Latent transforming growth factor-ß (TGFß) binding proteins (LTBPs) bind to inactive TGFß in the extracellular matrix. In mice, muscular dystrophy symptoms are intensified by a genetic polymorphism that changes the hinge region of LTBP, leading to increased proteolytic susceptibility and TGFß release. We have found that the hinge region of human LTBP4 was also readily proteolysed and that proteolysis could be blocked by an antibody to the hinge region. Transgenic mice were generated to carry a bacterial artificial chromosome encoding the human LTBP4 gene. These transgenic mice displayed larger myofibers, increased damage after muscle injury, and enhanced TGFß signaling. In the mdx mouse model of Duchenne muscular dystrophy, the human LTBP4 transgene exacerbated muscular dystrophy symptoms and resulted in weaker muscles with an increased inflammatory infiltrate and greater LTBP4 cleavage in vivo. Blocking LTBP4 cleavage may be a therapeutic strategy to reduce TGFß release and activity and decrease inflammation and muscle damage in muscular dystrophy.