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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.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.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.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.

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.

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: 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.

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.

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.

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.

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

Background: It is unclear whether artificial intelligence (AI) can provide automatic solutions to measure right ventricular ejection fraction (RVEF), due to the complex RV geometry. Although several deep learning (DL) algorithms are available to quantify RVEF from cardiac magnetic resonance (CMR) images, there has been no systematic comparison of these algorithms, and the prognostic value of these automated measurements is unknown. We aimed to determine whether RVEF measurements made using DL algorithms could be used to risk stratify patients similarly to measurements made by an expert. Methods: We identified from a pre-existing registry 200 patients who underwent CMR. RVEF was determined using 3 fully automated commercial DL algorithms (DL-RVEF) and also by a clinical expert (CLIN-RVEF) using conventional methodology. Each of the DL-RVEF approaches was compared against CLIN-RVEF using linear regression and Bland-Altman analyses. In addition, RVEF values were classified according to clinically important cutoffs: Results: The CLIN-RVEF and the three DL-RVEFs were obtained in all patients. We found only modest correlations between DL-RVEF and CLIN-RVEF (figure). The DL-RVEF algorithms had accuracy ranging from 0.59 to 0.78 for categorizing RV function. Nevertheless, ROC analysis showed no significant differences between the 4 approaches in predicting MACE, as reflected by respective AUC values of 0.68, 0.69, 0.64 and 0.63. Conclusions: Although the automated algorithms predicted patient outcomes as well as the CLIN-RVEF, the agreement between DL-RVEF and the clinical expert’s measurements was not optimal. DL approaches need further refinements to improve automated assessment of RV function.

Purpose Hemocompatibility-related clinical adverse events (HRAE) are thought to be driven by the pump-patient interaction. We hypothesized that the hemodynamic variables cardiac power output (CPO) and cardiac power efficiency (CPE), which reflect underlying ventricular contribution, have prognostic value in patients with left ventricular assist devices (LVADs). Methods Prospectively collected hemodynamic data from patients with LVADs who had undergone invasive hemodynamic ramp study at our institution between 4/2014-7/2018 were analyzed. CPO [(mean arterial pressure x cardiac output)/451], cardiac power index (CPI) (CPO/body surface area), and CPE (CPI/ pulmonary capillary wedge pressure) were calculated. Patients were divided into groups of high and low CPO and CPE using ROC-derived cutoff values of 0.847W and 0.0552 WmmHg/m2 respectively. Hemocompatibility scores (HCS) were also calculated for each patient based on their HRAE. Univariate and multivariate logistic regression analyses were performed to determine the association between CPO and CPE with primary endpoints of HRAE, HCS, heart failure readmissions, and mortality. Results 91 patients (average age 61 ± 11 years, 34% women, 40% Black, 38% ischemic cardiomyopathy) were included in the analysis. Low CPO was significantly associated with higher rates of HRAE, HR 2.02 (95% CI 1.12-3.66, p=0.02, Figure 1A). CPO was not significantly associated with mortality or heart failure readmission, HR 1.84 (95% CI 0.68-3.32, p=0.31) and HR 1.84 (95% CI 0.92-3.68, p=0.083), respectively. Low CPE was significantly associated with higher rates of HRAE, heart failure readmission (Figure 1B), and mortality (Figure 1C) when adjusted for LVAD type: HR 1.97 (95% CI 1.02-3.81, p=0.043), HR 3.11 (95% CI 1.28-7.58, p=0.012), and HR 3.41 (95% CI 1.18-9.88, p=0.024), respectively. Conclusion CPO and CPE demonstrate prognostic value in patients with LVADs, showing significant associations with HRAE, heart failure readmissions, and mortality.

Purpose We hypothesized that the change in hemodynamic values after milrinone infusion would predict clinical outcomes. Methods We reviewed 177 patients undergoing right heart catheterization and milrinone loading at our center between January 2013 and December 2018. Percent increase in aortic pulsatility index (piAPI) was calculated as 100 * (aortic pulsatility index after milrinone infusion - aortic pulsatility index prior to milrinone infusion)/aortic pulsatility index prior to milrinone infusion, and percent increase in pulmonary artery pulsatility index (piPAPI) was calculated as 100 * (pulmonary artery pulsatility index after milrinone infusion - pulmonary artery pulsatility index prior to milrinone infusion)/pulmonary artery pulsatility index prior to milrinone infusion. Cutpoints were determined by ROC analysis, and patients were stratified as follows: (1) High piAPI, High piPAPI; (2) High piAPI, Low piPAPI; (3) Low piAPI, High piPAPI; and (4) Low piAPI, Low piPAPI. Univariate and multivariate logistic and cox regression analyses were performed to determine association with escalation of therapy, defined as left ventricular assist device implantation, heart transplantation, or death. Results Cutpoints of 70% and 103% were determined for piAPI and piPAPI, respectively. Low piAPI, Low piPAPI was associated with escalation of therapy or death at 30-days (OR 2.42, 95% CI 1.16 - 5.3, p = 0.022; OR). In multivariate analysis, Low piAPI, Low piPAPI and High piAPI, Low piPAPI were predictors of the one-year endpoint (OR 8.95, 95% CI 2.43 - 43.1, p = 0.002; OR 6.87, 95% CI 1.79 - 34.16, p = 0.008; respectively). Grouping patients according to whether they possessed Low piAPI, Low piPAPI showed a greater hazard for the endpoint at 30-days and one-year (HR 2.27, 95% CI 1.24 - 4.15, p = 0.0076; HR 1.58, 95% CI 1.01 - 2.28, p = 0.014; respectively). Conclusion Low piAPI, Low piAPI status may indicate lower myocardial reserve and predict poorer outcomes.

Purpose To assess the prognostic role of simultaneous biventricular function using hemodynamic parameters in advanced heart failure patients. Methods We retrospectively analyzed 184 patients undergoing a milrinone drug study at time of right heart catheterization (RHC) at our institution from January 2013 to January 2019. Aortic pulsatility index (API) was calculated as (systolic blood pressure - diastolic blood pressure)/pulmonary capillary wedge pressure, and pulmonary artery pulsatility index (PAPI) was calculated as (systolic pulmonary artery pressure - diastolic pulmonary artery pressure)/central venous pressure. Using our team's previous identification of cutpoint values for API and PAPI, 1.45 and 2.3, respectively, we stratified patients into the following groups: (1) High API, High PAPI; (2) High API, Low PAPI; (3) Low API, High PAPI; and (4) Low API, Low PAPI. Univariate and multivariate logistic regression analyses were performed to determine association with escalation of therapy, defined as left ventricular assist device implantation, heart transplantation, or death. Results Low API, Low PAPI was associated with escalation of therapy or death at 30-days (OR 3.2, 95% CI 1.23 - 9.49, p = 0.024). Low API, Low PAPI and Low API, High PAPI were also associated with the one-year endpoint of freedom from escalation of therapy or death (OR 3.63, 95% CI 1.55 - 8.75, p = 0.003; OR 4.13, 95% CI 1.5 - 12.45, p = 0.008; respectively). In multivariate analysis, both of these risk statuses remained significant predictors of the one-year endpoint when adjusting for Fick cardiac index (OR 3.72, 95% CI 1.5 - 9.48, p = 0.005; OR 4.18, 95% CI 1.49 - 12.82, p = 0.009; respectively). Conclusion The combined use of API and PAPI possesses utility for risk stratification regarding both short- and long-term freedom from escalation of therapy or death.

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.

The skin, by virtue of being the largest organ in the human body and being exposed to the surroundings, is the generally first point of impact with trauma. Injury to the skin commonly is an indicator of trauma to underlying organs. Diagnostic imaging plays an important role in evaluating the extent of injury beyond the skin. This chapter reviews the clinical and imaging findings related to penetrating trauma, blunt trauma, thermal injury, and birth injury, non-accidental trauma, and associated complications involving the head and neck, such as fractures, intracranial hemorrhage, brain injuries, retained foreign bodies, orbital injuries, infection, and vascular compromise.

Purpose We hypothesized that simultaneous assessment of biventricular function could predict clinical outcomes. Methods We reviewed 180 patients undergoing a milrinone drug study and right heart catheterization at our center from January 2013 to January 2019. Left ventricular stroke work index (LVSWI) was calculated as 0.0136 * ((cardiac index/heart rate) * 1000) * (mean arterial pressure - pulmonary capillary wedge pressure), and right ventricular stroke work index (RVSWI) was calculated as 0.0136 * ((cardiac index/heart rate) * 1000) * (mean pulmonary arterial pressure - right atrial pressure). Cutpoints were determined by ROC analysis. Patients were stratified as: (1) High LVSWI, High RVSWI; (2) High LVSWI, Low RVSWI; (3) Low LVSWI, High RVSWI; and (4) Low LVSWI, Low RVSWI. Univariate and multivariate logistic regression analyses were performed to determine association with escalation of therapy, defined as left ventricular assist device implantation, heart transplantation, or death. Results Cutpoints of 18.3 and 10 were determined for LVSWI and RVSWI, respectively. Low LVSWI, High RVSWI was associated with escalation of therapy or death at 30 days (OR 4, 95% CI 1.05 - 15.59, p = 0.041). All of the following statuses were associated with a negative outcome at one year: Low LVSWI, High RVSWI (OR 14, 95% CI 2.44 - 265.8, p = 0.015), Low LVSWI, Low RVSWI (OR 4.85, 95% CI 2.25 - 10.85, p Conclusion Simultaneous assessment of biventricular function using LVSWI and RVSWI is associated with clinical outcomes and may be useful for risk stratification.

Purpose We hypothesized that changes in biventricular function would approximate myocardial reserve and predict outcomes. Methods We reviewed 178 patients undergoing right heart catheterization and milrinone loading at our center between January 2013 and January 2019. Percent increase in left ventricular stroke work index (piLVSWI) was calculated as 100 * (left ventricular stroke work index after infusion - left ventricular stroke work index before infusion)/left ventricular stroke work index before infusion, and percent increase in right ventricular stroke work index (piRVSWI) was calculated as 100 * (right ventricular stroke work index after infusion - right ventricular stroke work index before infusion)/right ventricular stroke work index before infusion. Cutpoints were determined by ROC analysis, and patients were stratified as follows: (1) High piLVSWI, High piRVSWI; (2) High piLVSWI, Low piRVSWI; (3) Low piLVSWI, High piRVSWI; and (4) Low piLVSWI, Low piRVSWI. Cox regression analyses were performed to determine association with escalation of therapy, defined as left ventricular assist device implantation, heart transplantation, or death. Results Cutpoints of 18.9% and 17.5% were determined for piLVSWI and piRVSWI, respectively. Low piLVSWI, High piRVSWI was associated with escalation of therapy or death at 30-days (HR 3.78, 95% CI 1.41 - 10.17, p = 0.0084). Multivariate analysis identified Low piLVSWI, High piRVSWI as a predictor of escalation of therapy or death at one-year (HR 1.96, 95% CI 1.02 - 3.78, p = 0.043). Grouping patients according to whether they possessed Low piLVSWI, High piRVSWI revealed a greater hazard for the endpoint at 30-days and one-year (HR 2.98, 95% CI 1.41 - 6.28, p = 0.004; HR 1.79, 95% CI 1.0002 - 3.2, p Conclusion Change in biventricular function after milrinone infusion, particularly Low piLVSWI, High piRVSWI, may prognosticate worse clinical outcomes at 30-days and one-year.

Purpose Hemocompatibility-related adverse events (HRAE) are thought to be largely driven by the pump-patient interaction. We hypothesized that patients with left ventricular assist devices (LVADs) with low left ventricular stroke work index (LVSWI), and thus less native contribution to total flow, would have more adverse clinical outcomes. Methods Hemodynamic data was prospectively collected from LVAD patients who had undergone a right heart catheterization with ramp study at our institution between April 2014 and July 2018. LVSWI was calculated as 0.0136 * ((cardiac index/heart rate) * 1000) * (mean arterial pressure - pulmonary capillary wedge pressure). We used a previously identified cutoff point of 31.73 for LVSWI to separate patients into low and high LVSWI groups. Univariate and multivariate logistic regression analyses were performed to determine the association between LVSWI and HRAE, heart failure (HF) readmission, and mortality. Results A total of 93 patients were included in this analysis - average age 61 +/- 11 years, 34% women, 40% Black, and 38% ischemic cardiomyopathy. Low LVSWI was not significantly associated with HRAE (HR 1.65, 95% CI 0.93-2.91, p = 0.081) in univariate analysis, but was statistically significant (HR 1.81, 95% CI 1.02-3.22, p = 0.042) when adjusted for LVAD type (HeartWare HVAD, Heartmate II, and Heartmate 3). Low LVSWI was significantly associated with HF readmission (HR 3.02, 95% CI 1.46-6.24, p = 0.0029) and mortality (HR 2.97, 95% CI 1.29-6.85, p = 0.011), even when adjusted for LVAD type (HR 3.15, 95% CI 1.52-6.54, p = 0.0021 and HR 3.13, 95% CI 1.36-7.21, p = 0.0074, respectively). Conclusion Low LVSWI in LVAD patients is associated with poor prognosis and worse clinical outcomes such as increased HF readmission and mortality.

Purpose Elevated mean arterial pressure (MAP) is associated with stroke in patients with HeartMate II and Heartware HVAD left ventricular assist devices (LVADs). We assessed the relationship between mean arterial pressure (MAP) and hemocompatibility-related clinical adverse events (HRAE) in patients with LVADs. Methods Prospectively collected hemodynamic data from LVAD patients who had undergone invasive hemodynamic ramp study at our institution between 4/2014-7/2018 were analyzed. ROC analysis was performed to determine optimal cutoff value for MAP, and patients were divided into two groups: high MAP (≥90mmHg) and low MAP ( Results 91 patients (average age 61 ± 11 years, 34% women, 40% Black, 38% ischemic cardiomyopathy) were included in the analysis. Of all patients, 29% had HeartWare HVADs, 57% HeartMate II, and 14% HeartMate 3 LVADs. MAP was not significantly associated with HRAE, HR 1.53 (95% CI 0.88-2.64, p=0.13), even when adjusted for LVAD type, HR 1.65 (95% CI 0.95-2.87, p=0.076). Similarly, MAP was not significantly associated with HCS. Low MAP was, however, significantly associated with higher mortality, HR 2.47 (95% CI 1.13-5.39, p=0.024, Figure 1A), and higher rates of heart failure readmission, HR 2.05 (95% CI 1.06-3.99, p=0.034) (figure 1B). Conclusion MAP was not significantly associated with HRAE in this population of LVAD patients. However, low MAP was significantly associated with mortality and heart failure readmission.

Introduction HLA matching is not current practice in heart transplant (HT) donor allocation due to scarcity of donor organs and ischemic time. However HLA mismatch might adversely affect transplant outcomes. Even if HLA matching is not possible the degree of HLA mismatch might help inform clinicians on a patients risk for long term transplant complications. Hypothesis We hypothesize that the degree of HLA mismatch affects long-term complications in a stable HT cohort. Methods 65 clinically stable HT recipients (no cellular (ACR) or antibody mediated rejection (AMR) in the preceding 6 months) ≥ 2 years post transplant were enrolled. Serologic HLA typing was obtained for donor and recipients (D/R) pairs and the number of matches was analyzed combined for HLA class I and HLA II. Study endpoints were donor specific antibody (DSA) formation and significant cardiac allograft vasculopathy (CAV). Results HLA-A,-B,-C, -DR and-DQ (ABCDRQ) typing were available for 37 D/R pairs and were analyzed for matches. Additionally, 53 D/R pairs had HLA-A,-B, -DR (ABDR) typing. Meantime post HT was 8.5±5.4 years. A total of 28 patients had CAV and 9 patients had DSA. Among the ABCDRDQ cohort the number of matches was 1.54 ± 1.17 and 1.00 (0.00-1.00) in the ABDR cohort. There were no differences in the number of HLA matches for both cohorts among those with and without DSA and those with and without CAV (Table).However among the ABCDRDQ cohort there was a trend towards higher number of HLA matches in those without DSA 1.63 ± 1.19 versus 1.14 ± 1.07 in the DSA group (p 0.32), this was likely limited by the small sample size.There was no significant relationship between total HLA matches and number of ACR episodes (p 0.89). The incidence of AMR was too low for analysis. Conclusion In this highly selected cohort of clinically stable long time transplant survivors the degree of serological HLA matching was not associated with the development of CAV or ACR. However, there was a trend towards less DSA formation in those with more D/R HLA matches. Future longitudinal studies should evaluate the development of long-term complications as a function of HLA matching and potentially incorporate HLA mismatch as an indicator for the need of enhanced clinical surveillance.

Background The novel SARS-CoV-2 virus causing COVID-19 has been associated with diverse cardiovascular pathology. We present a case of cardiomyopathy due to possible COVID-19 resulting in cardiogenic shock. Case A 54 year-old male presented to the hospital with 4 weeks of progressive dyspnea, leg swelling, and weight gain. His symptoms began 4 weeks after experiencing influenza-like symptoms after a trip to China during the height of their COVID-19 outbreak. He was admitted to the COVID unit in cardiogenic shock and was later intubated for acute hypoxic respiratory failure. Laboratory data demonstrated acute kidney injury, elevated transaminases, lactic acidosis, elevated pro-BNP N-Terminal to 3932pg/mL, and high sensitivity troponin to 72ng/L. Transthoracic echocardiogram showed severe biventricular failure with a LVEF of 10% and a LVIDd 5.2cm. SARS-CoV-2 RNA was negative twice, but SARS-CoV-2 IgG AB and SARS-CoV-2 IgA AB were positive. Urgent right and left heart catheterization was performed demonstrating non-obstructive coronary artery disease and hemodynamics consistent with cardiogenic shock. While supported with an intra-aortic balloon pump (IABP) and norepinephrine, he had a fick cardiac output 3.1 L/min, fick cardiac index 1.6 L/min/m2, pulmonary capillary wedge pressure 37mmHg, right atrial pressure 25mmHg, and pulmonary arterial pressures 65/40mmHg. Given persistent cardiogenic shock on IABP and inotropes, he was later transitioned to Veno-Arterial Extracorporeal Membrane Oxygenation (VA ECMO) and an Impella CP for left ventricular unloading. He continued to have persistent INTERMACS I shock and underwent successful implantation of a HeartMate 3 LVAD with percutaneous temporary right ventricular assist device (RVAD). Pathology of the left ventricular apical core demonstrates polyclonal endocardial infiltration of B-Cells, CD4 and CD8 positive T-Cells, eosinophils, macrophages, and plump reactive endothelial cells (Figure 1). He is currently recovering in the ICU off of vasoactive support with subsequent removal of percutaneous RVAD. Conclusion This is a suspected case of COVID-19 associated cardiomyopathy presenting as new on-set heart failure with reduced ejection fraction complicated by cardiogenic shock. There is still much to learn about the cardiac manifestations of COVID-19 and further studies are needed to determine appropriate diagnostics and management of such cases.

Latent TGFβ binding proteins (LTBPs) regulate the extracellular availability of latent TGFβ. 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 TGFβ 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 TGFβ and GDF11, a protein highly related to myostatin. These data identify LTBP4 as a multi-TGFβ family ligand binding protein with the capacity to modify muscle disease through overexpression., Author Summary Muscular dystrophy is a genetic disease with muscle weakness, replacement of muscle tissue with fibrosis, and premature death. The gene for latent TGFβ binding protein 4 (LTBP4) was previously found to modify muscular dystrophy in both mice and humans with variants that confer protection from disease. In order to better understand this modifier gene, the protective version of LTBP4 was overexpressed specifically in the skeletal muscles of mice. Increased levels of LTBP4 protein resulted in increased muscle mass. Overexpression of LTBP4 in a mouse model of Duchenne muscular dystrophy alleviated many disease-associated features producing larger muscles, increased strength, and reduced fibrosis in muscle. LTBP4 formed a complex with myostatin, a protein that when inhibited leads to muscle growth. In LTBP4-overexpressing mice, active myostatin protein was decreased. This study shows that LTBP4 modifies muscular dystrophy based on its ability to scaffold and regulate multiple TGFβ family members including myostatin.

Latent transforming growth factor-β (TGFβ) binding proteins (LTBPs) bind to inactive TGFβ 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 TGFβ 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 TGFβ 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 TGFβ release and activity and decrease inflammation and muscle damage in muscular dystrophy.