Background: Mechanical unloading via left ventricular assist devices (LVADs) is an established therapy for end-stage heart failure (ESHF). Although LVAD support improves hemodynamics and can promote structural reverse remodeling, the accompanying metabolic changes within the myocardium and systemic circulation remain insufficiently defined. The objective of this study was to describe metabolic signatures associated with LVAD support in ESHF using an unbiased, untargeted profiling approach. Methods: Paired serum (N = 8) and myocardial tissue (N = 12) samples were collected from ESHF patients at two timepoints: at LVAD implantation and at heart transplantation. Global metabolic profiling was conducted using untargeted liquid chromatography-mass spectrometry (LC-MS). Differential abundance analysis was carried out to identify metabolites with significant changes between time points, with filtering applied to exclude pharmaceutical metabolites and metabolites lacking annotations. Results: In myocardial tissue, LVAD support was associated with lower levels of adenosine-5-diphosphate (logFC -0.58, FDR q < 0.05) and octanoic acid (logFC -0.32, FDR q < 0.05), metabolites related to cellular energetics and fatty acid oxidation pathways. In contrast, androsterone glucuronide (logFC 1.44, FDR q < 0.05) and estrone (logFC 0.9, FDR q < 0.05) increased following LVAD support, indicating shifts in steroid-related metabolic pathways. Serum profiles differed from tissue findings and were characterized primarily by reduced pyruvic acid levels (logFC -0.65, FDR q < 0.05) post-LVAD support, consistent with a reduction in systemic anaerobic glycolysis and improved peripheral perfusion. Conclusion: We show that LVAD support is accompanied by measurable tissue-specific metabolic differences. While systemic changes appear to reflect the clearance of glycolytic byproducts due to improved perfusion, the myocardium is characterized by changes in energetic substrates and steroid metabolites. These findings suggest that mechanical unloading may facilitate a re-regulation of cardiomyocyte metabolism, offering further insight into the physiology of reverse remodeling. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Background: Changes in metabolic pathways have been described in patients with heart failure (HF) and reduced ejection fraction. Selected patients with end-stage HF are candidates for left ventricular assist devices (LVAD) implantation to improve survival and quality of life. Myocardial tissue obtained at the time of LVAD implantation offers the possibility to study the metabolic pathways at end-stage HF. The effects of HF etiology and sex on the metabolomic profile of end-stage HF have not been described. Our objective was to compare the sex-specific metabolomic signatures in end-stage HF of ischemic (ICMP) and non-ischemic (NICMP) cardiomyopathy patients. Methods: Blood and myocardial tissue were collected at the time of left ventricular assist device (LVAD) implantation in end-stage HF patients. A total of 119 patients were included in the study. Of these 35 (29.4%) were female. Fifty-four (45.4%) patients had ICMP. The mean age of our cohort was 57.8 ± 12.9 years, and 105 (88.2%) were white. A total of 96 blood samples and 119 myocardial tissue samples were analyzed. Metabolomic profiles for blood and myocardial tissue were obtained utilizing proton nuclear magnetic resonance ( 1 H-NMR) and liquid chromatography coupled with mass spectrometry (LC-MS). Patients were classified according to sex and etiology of HF (NICMP and ICMP). Concentrations of metabolites were compared between groups. Those metabolites with a p-value <0.05 were considered significantly different. Results: Substantial differences were observed in the metabolome when samples were analyzed according to sex and etiology of HF (graphic representation in Figure 1). In serum, a total of 673 metabolites were accurately quantified. In males, 4 metabolites were increased in ischemic cardiomyopathy (1A), whereas 50 metabolites were different in female patients (1B). In myocardial tissue, a total of 576 metabolites were quantified. In males, 200 metabolites differed between ischemic and non-ischemic cardiomyopathy (1C), whereas female patients had differential concentration of 100 different metabolites (1D). Conclusion: The metabolome of blood and myocardial tissue in patients with end-stage HF differs between ischemic and non-ischemic cardiomyopathy, the differences are accentuated in a sex specific manner. Further studies are required to determine the implications of these differences in the progression and recovery of HF.

BACKGROUND:Gene mutations are responsible for a sizeable proportion of cases of heart failure. However, the number of patients with any specific mutation is small. Repositioning of existing US Food and Drug Administration-approved compounds to target specific mutations is a promising approach to efficient identification of new therapies for these patients. METHODS:The National Institutes of Health Library of Integrated Network-Based Cellular Signatures database was interrogated to identify US Food and Drug Administration-approved compounds that demonstrated the ability to reverse the transcriptional effects of LMNA knockdown. Top hits from this screening were validated in vitro with patient-specific induced pluripotent stem cell-derived cardiomyocytes combined with force measurement, gene expression profiling, electrophysiology, and protein expression analysis. RESULTS:Several angiotensin receptor blockers were identified from our in silico screen. Of these, olmesartan significantly elevated the expression of sarcomeric genes and rate and force of contraction and ameliorated arrhythmogenic potential. In addition, olmesartan exhibited the ability to reduce phosphorylation of extracellular signal-regulated kinase 1 in LMNA-mutant induced pluripotent stem cell-derived cardiomyocytes. CONCLUSIONS:In silico screening followed by in vitro validation with induced pluripotent stem cell-derived models can be an efficient approach to identifying repositionable therapies for monogenic cardiomyopathies.

Cardiomyocytes in the adult human heart show a regenerative capacity, with an annual renewal rate around 0.5%. Whether this regenerative capacity of human cardiomyocytes is employed in heart failure has been controversial. Using retrospective 14C birth dating we analyzed cardiomyocyte renewal in patients with end-stage heart failure. We show that cardiomyocyte generation is minimal in end-stage heart failure patients at rates 18-50 times lower compared to the healthy heart. However, patients receiving left ventricle support device therapy, who showed significant functional and structural cardiac improvement, had a >6-fold increase in cardiomyocyte renewal relative to the healthy heart. Our findings reveal a substantial cardiomyocyte regeneration potential in human heart disease, which could be exploited therapeutically.

Purpose There is limited research on the use and outcomes of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) treatment for massive pulmonary embolism (PE). This study compared VA-ECMO treatment for massive PE versus patients treated medically. Materials and methods Patients diagnosed with massive PE at one hospital system were reviewed. VA-ECMO and non-ECMO groups were compared by t test and Chi-square. Mortality risk factors were identified by logistic regression. Survival was assessed by Kaplan Meier and propensity matching of groups. Results Ninety-two patients were included (22 VA-ECMO and 70 non-ECMO). Age (OR 1.08, 95% CI 1.03-1.13), arterial SBP (OR 0.97, 95% CI 0.94-0.99), albumin (OR 0.3, 95% CI 0.1-0.8), and phosphorus (OR 2.0, 95% CI 1.4-3.17) were independently associated with 30-day mortality. Alkaline phosphate (OR 1.03, 95% CI 1.01-1.05) and SOFA score (OR 1.3, 95% CI 1.06-1.51) were associated with 1-year mortality. Propensity matching showed no difference in 30-day (59% VA-ECMO versus 72% non-ECMO, p = 0.363) or 1-year survival (50% VA-ECMO versus 64% non-ECMO, p = 0.355). Conclusions Patients treated with VA-ECMO for massive PE and medically treated patients have similar short- and long-term survival. Further research is needed to define clinical recommendations and benefits of intensive therapy such as VA-ECMO in this critically ill population.

HeartMate 3 is the only durable left ventricular assist devices (LVAD) currently implanted in the United States. The purpose of this study was to develop a predictive model for 1 year mortality of HeartMate 3 implanted patients, comparing standard statistical techniques and machine learning algorithms. Adult patients registered in the Society of Thoracic Surgeons, Interagency Registry for Mechanically Assisted Circulatory Support (STS-INTERMACS) database, who received primary implant with a HeartMate 3 between January 1, 2017, and December 31, 2019, were included. Epidemiological, clinical, hemodynamic, and echocardiographic characteristics were analyzed. Standard logistic regression and machine learning (elastic net and neural network) were used to predict 1 year survival. A total of 3,853 patients were included. Of these, 493 (12.8%) died within 1 year after implantation. Standard logistic regression identified age, Model End Stage Liver Disease (MELD)-XI score, right arterial (RA) pressure, INTERMACS profile, heart rate, and etiology of heart failure (HF), as important predictor factors for 1 year mortality with an area under the curve (AUC): 0.72 (0.66-0.77). This predictive model was noninferior to the ones developed using the elastic net or neural network. Standard statistical techniques were noninferior to neural networks and elastic net in predicting 1 year survival after HeartMate 3 implantation. The benefit of using machine-learning algorithms in the prediction of outcomes may depend on the type of dataset used for analysis.

Endothelial dysfunction and impaired vasodilation are linked with adverse cardiovascular events. T lymphocytes expressing choline acetyltransferase (ChAT), the enzyme catalyzing biosynthesis of the vasorelaxant acetylcholine (ACh), regulate vasodilation and are integral to the cholinergic antiinflammatory pathway in an inflammatory reflex in mice. Here, we found that human T cell ChAT mRNA expression was induced by T cell activation involving the PI3K signaling cascade. Mechanistically, we identified that ChAT mRNA expression was induced following the attenuation of RE-1 Silencing Transcription factor REST-mediated methylation of the ChAT promoter, and that ChAT mRNA expression levels were up-regulated by GATA3 in human T cells. In functional experiments, T cell-derived ACh increased endothelial nitric oxide-synthase activity, promoted vasorelaxation, and reduced vascular endothelial activation and promoted barrier integrity by a cholinergic mechanism. Further, we observed that survival in a cohort of patients with severe circulatory failure correlated with their relative frequency of ChAT + CD4 + T cells in blood. These findings on ChAT + human T cells provide a mechanism for cholinergic immune regulation of vascular endothelial function in human inflammation.

BACKGROUND: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a key support modality for cardiogenic shock. The 2018 United Network for Organ Sharing (UNOS) heart transplant allocation algorithm prioritizes VA-ECMO patients.OBJECTIVE: To evaluate the role of VA-ECMO in bridging to advanced heart failure therapies.METHODS: We analyzed adult patients from the multicenter Extracorporeal Life Support Organization registry receiving VA-ECMO for cardiac support or resuscitation between 2016 and 2021 in the United States, comparing bridge-to-transplant (BTT) and non-BTT intent patients, as well as pre-vs post-2018 patients, on a wide range of demographic and clinical outcome predictors.RESULTS: Of 17,087 patients, 797 received left ventricular assist device (LVAD)/heart transplant, 7,931 died or had poor prognosis, and 8,359 had expected recovery at ECMO discontinuation. Patients sup-ported with BTT intent had lower clinical acuity than non-BTT candidates and were more likely to receive LVAD/transplant. The proportion of patients who received VA-ECMO as BTT and received LVAD/transplant increased after 2018. Post-2018 BTT patients had significantly lower clinical acuity and higher likelihood of transplant than both post-2018 non-BTT patients and pre-2018 BTT patients. ECMO complications were associated with lower likelihood of transplant but were significantly less common post-2018 than pre-2018.CONCLUSIONS: After implementation of the 2018 UNOS allocation system, ECMO utilization as BTT or LVAD has increased, and the acuity of BTT intent patients cannulated for ECMO has decreased. There has not yet been an increase in more acute ECMO patients getting transplanted. This may par-tially explain the post-transplant outcomes of ECMO patients in the current era reported in UNOS. J Heart Lung Transplant 2023;42:1059-1071 & COPY; 2023 International Society for Heart and Lung Transplantation. All rights reserved.

Introduction: Acute kidney injury (AKI) in patients treated with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is associated with high mortality. The objective of this study was to investigate whether cytokine levels before the initiation of ECMO treatment could predict AKI. We also aimed to investigate the impact of AKI on 30-day and 1-year mortality. Methods: Serum cytokine levels were analyzed in 100 consecutive VA-ECMO-treated patients at pre-cannulation, at 48 h post-cannulation, and at 8 days. Clinical data to establish the incidence and outcome of AKI after the start of ECMO was retrieved from the local ECMO registry. Setting: The study was conducted at tertiary care, university hospital. Participants included 100 patients treated with VA-ECMO. Interventions: The blood samples for cytokine analysis were collected before VA-ECMO treatment, at 48 h after VA-ECMO treatment was started, and at 8 days. Results: Pre-cannulation serum IL-10 levels were significantly higher in patients who developed AKI (212 [38.9, 620.7]) versus those who did not (49.0 [11.9, 102.2]; p = 0.007), and the development of AKI can be predicted by pre-cannulation IL-10 levels (p = 0.025, OR = 1.2 [1.02–1.32]). The development of AKI during ECMO treatment is associated with increased 30-day mortality (p = 0.049) compared to patients who did not develop AKI and had a pre-cannulation estimated glomerular filtration rate ≥ 45 mL/min. The 1-year survival rate for patients with AKI who survived the first 30 days of ECMO treatment is comparable to that of patients without AKI. Conclusion: Increased pre-cannulation IL-10 levels are associated with the development of AKI during VA-ECMO support. AKI is associated with increased 30-day mortality compared to patients with no AKI and better renal function. However, patients with AKI who survive the first 30 days have a 1-year survival rate similar to those without AKI.

Purpose To evaluate the effect of the new heart transplant (HT) allocation system in left ventricular assist device (LVAD) supported patients listed as bridge to transplantation (BTT). Methods Adult patients who were listed for HT between October 18, 2016 and October 17, 2019, and were supported with an LVAD, enrolled in the UNOS database were included in this study. Patients were classified in the old or new system if they were listed or transplanted before or after October 18, 2018, respectively. Results A total of 3261 LVAD patients were listed for transplant. Of these, 2257 were classified in the old and 1004 in the new system. The cumulative incidence of death or removal from the transplant list due to worsening clinical status at 360-days after listing was lower in the new system (4% vs. 7%, P = .011). LVAD Patients listed in the new system had a lower frequency of transplantation within 360-days of listing (52% vs. 61%, P < .001). A total of 1843 LVAD patients were transplanted, 1004 patients in the old system and 839 patients in the new system. The post-transplant survival at 360 days was similar between old and new systems (92.3% vs. 90%, P = .08). However, LVAD patients transplanted in the new system had lower frequency of the combined endpoint, freedom of death or re-transplantation at 360 days (92.2% vs. 89.6%, P = .046). Conclusion The new HT allocation system has affected the LVAD-BTT population significantly. On the waitlist, LVAD patients have a decreased cumulative frequency of transplantation and a concomitant decrease in death or delisting due to worsening status. In the new system, LVAD patients have a decreased survival free of re-transplantation at 360 days post-transplant.

Introduction Highly sensitized heart transplant candidates have a longer waitlist time, worse waitlist outcomes and often require higher levels of immunosuppression post-transplantation. Expanding the heart transplant donor pool with Hepatitis C NAAT positive (Hep C NAAT (+)) donors could increase the chances of transplantation in highly sensitized patients. The effects of sensitization on post-transplant outcomes in patients who received Hep C NAAT (+) donor allografts is unknown. Methods Adult patients who received HT from a Hep C NAAT (+) donor, between May 2015 and Dec 2020, were identified from the United Network for Organ Sharing (UNOS) database. These patients were classified according to the percentage of panel reactive antibody (PRA): Non-sensitized (0%), mildly sensitized (0%-20%), Moderately sensitized (21%-50%), and highly sensitized (>50%). Clinical characteristics and post-transplant survival were compared between groups. Results A total of 831 patients received HT from a hep C NAAT (+) donor during the study period. Of these 605 (72.8%), 88 (10.6%), 70 (8.4%) and 68 (8.2%) patients were non-sensitized, mildly sensitized, moderately sensitized, and highly sensitized, respectively. Highly sensitized patients were more likely to be women and African American. The 360-day post-transplant survival was 90.8%, 92.1%, 92.7%, 93% for the non-sensitized, mildly, moderately, and highly sensitized groups, respectively (p =ns). The frequency of graft failure (p= 0.97), acute rejection (p=0.193) and coronary vasculopathy (p=0.51) were similar among groups. Conclusions Highly sensitized patients who received Hepatitis C NAAT positive allografts have similar post-transplant survival than non-sensitized patients. Thus, highly sensitized patients should not be excluded from the donor pool expansion offered by hepatitis C NAAT positive donors.

Purpose In the United States the Heartmate3 (HM3) has become the only durable LVAD for implantation in end stage heart failure (HF) patients. Prior predictive scores included older generation devices and thus may not applicable. The purpose of this study was to develop a one-year survival predictive score for HM3 candidates. Methods Adult patients registered in the STS-INTERMACS database, who received primary implant with a HM3 device between 1/1/2014 and 6/1/2020 were included in this study. Epidemiological, clinical, hemodynamic, and echocardiographic characteristics were analyzed. Machine learning, elastic-net method, was used to build a one-year mortality predictive model on the derivation cohort; and its performance was tested on the validation cohort. Results A total of 3642 patients met inclusion criteria. Of these, 429 died within 1 year after HM3 implantation. Non-survivors were older (61.7 vs. 56.8 years, p<0.001), less frequently male (15.2% vs. 20.6%, p=0.01), had higher frequency of chronic HF (82.8% vs. 79% p=0.004), had a higher frequency of ECMO (10.3 %vs. 4.26%, p<0.001), higher rates of dialysis (6.29% vs. 1.93%, p<0.001), higher frequency of previous cardiac surgery (35% vs. 24.2%, p<0.001), and higher frequency of concomitant cardiac surgery (50.4% vs. 44.3%, p=0.02). Machine learning identified 9 variables associated with one-year mortality in the training data set (Age, right atrial pressure, MELD-XI score, INTERMACS profile 1, Chronic HF, White blood cell count, hemoglobin, heart rate < 90, and ECMO prior to implant), with an AUC 0.68 (figure 1A). The importance of each variable in the predicting model is shown in figure 1B. Our score predicted one year survival in the testing cohort with a good accuracy (AUC:0.72, Figure 1C). Conclusion Using the machine learning algorithm, we developed a model for predicting one-year survival for patients receiving HM3 LVAD. Age, right atrial pressure and MELD-XI score were the most important predictive factors.

Purpose We previously reported using UNOS data that patients bridged with ECMO to heart transplantation (HT) in the new allocation system have improved survival in the waitlist and after transplantation. Whether this improvement was due to the improved access to HT in this population or due to differences in patient characteristics was unclear. The purpose of our study was to compare the clinical characteristics of patients who received ECMO as a bridge to transplant before and after the allocation system using the Extracorporeal Life Support Organization (ELSO) database. Methods Adult patients listed for HT who received ECMO as a bridge to HT in the United States and were registered in the ELSO database were included in this study. Patients were classified in old allocation system (2016-2017) and new allocation system (2019-2021). Clinical characteristics were compared between groups. Results A total of 623 patients were listed for HT and received VA-ECMO as a bridge to transplant during the study period. Of these, 214 and 409 were classified in the old and new systems respectively. The proportion of patients who received HT was higher (34% vs. 3.74%, p<0.001) and mortality was lower (23.47% vs. 36.45%, p<0.001) in the new system. At the time of ECMO cannulation, patients in the new system had a better tissue perfusion profile as demonstrated by higher pH and bicarbonate, improved oxygenation as demonstrated by decreased frequency of mechanical ventilation and higher PaO2 at similar FIO2, and less hemodynamic instability as demonstrated by higher pre-cannulation systolic blood pressure and lower pump flow (Table 1). Conclusion Patients bridged on ECMO to HT in the United States after 2018 (new allocation system) are less sick than those in the old allocation system and are more likely to get transplanted on ECMO. This difference could, in part, explain the previously described improved outcomes in the waitlist and post-transplantation in this population.

OBJECTIVES:To evaluate the use of temporary-permanent pacemaker (TPP) in patients with right bundle branch block (RBBB) undergoing transcatheter aortic valve replacement (TAVR). We also sought to identify key predictors of permanent pacemaker (PPM) within 30 days of TAVR in this population. BACKGROUND:RBBB is a well-recognized risk factor for PPM post TAVR. TPP provides stable transient pacing and reduces the need for critical care beds. METHODS:This is a retrospective chart review of 371 patients who underwent TAVR at our institution. All patients with pre-existing RBBB had TPP placed prior to TAVR (n = 37). The primary outcome was the need for critical care beds. Multivariate logistic regression analysis was performed to identify predictors of PPM within 30 days of TAVR. RESULTS:67 patients required PPM within 30 days of TAVR, and 56 implanted before discharge. 51% (19 out of 37) of TPP group required PPM before discharge compared to 11% (37 out of 334) of No TPP (p < 0.001), yet TPP group spent significantly fewer hours in a critical care bed (19 vs 28 h, p = 0.01). Length of membranous septum (LMS) <8.49 mm was the strongest independent predictor of PPM within 30 days of TAVR (RAUC of 0.80, Sensitivity 0.7 and Specificity 0.8) and 98% of patients with LMS < 7 mm required PPM within 30 days. CONCLUSION:TPP-TAVR is a well-defined multidisciplinary protocol that reduces the need for critical care beds in patients with pre-existing RBBB referred for TAVR. Additionally, LMS is the strongest predictor of PPM implantation in this population. CONDENSED ABSTRACT (100 WORDS): This study evaluated the use of temporary-permanent pacemakers (TPP) in patients with right bundle branch block (RBBB) undergoing transcatheter aortic valve replacement (TAVR). TPP-TAVR provided stable pacing allowing for early mobilization and reduced the need for critical care beds. Multivariate logistic regression analysis identified length of membranous septum (LMS) <8.49 mm in patients with RBBB as the strongest independent predictor of PPM need within 30 days of TAVR. 98% of patients with RBBB and LMS < 7 mm required PPM at 30 days regardless of other characteristics including valve type and size.

Purpose Patients with refractory cardiogenic shock (Stage E) face imminent death and often require extra-corporeal membrane oxygenation (ECMO) to achieve stabilization and survival. ECMO is a resource intense therapy and with high morbidity and mortality. The purpose of our study was to develop a prediction model, using machine learning, of short-term mortality in patients with decompensated heart failure (DHF) and acute myocardial infarction (AMI) who required ECMO. Methods Patients supported by VA-ECMO due to DHF or AMI registered in the Spectrum Health ECMO registry were included in this study. Clinical, echocardiographic, laboratory and hemodynamic characteristics were obtained in all patients. Thirty-day survival from ECMO cannulation was calculated using Kaplan-Meier methodology. Using machine learning (elastic-net method) a predictive model for 30-day mortality was developed in the derivation cohort, the model was then tested on the validation cohort. Results A total of 283 patients met the inclusion criteria (228 DHF and 55 AMI). Of these, 151 died within the first 30 days post ECMO insertion. Survivors had similar characteristics to non-survivors except for lower troponin and creatinine levels. Machine learning identified 8 variables associated with 30-day mortality in the derivation cohort (Troponin, eGFR, total bilirubin, BMI, lactate, ethnicity, age and pH) with AUC of 0.68 (figure 1 A). The importance of each variable in the predicting model is shown in Figure 1B. Our score predicted 30 days mortality in the validation cohort with a good accuracy (AUC: 0.72, Figure 1C). Conclusion Using the machine learning algorithm, we developed a model for predicting 30-day survival for cardiogenic shock patients supported by ECMO due to DHF and AMI. Patients with refractory cardiogenic shock (Stage E) face imminent death and often require extra-corporeal membrane oxygenation (ECMO) to achieve stabilization and survival. ECMO is a resource intense therapy and with high morbidity and mortality. The purpose of our study was to develop a prediction model, using machine learning, of short-term mortality in patients with decompensated heart failure (DHF) and acute myocardial infarction (AMI) who required ECMO. Patients supported by VA-ECMO due to DHF or AMI registered in the Spectrum Health ECMO registry were included in this study. Clinical, echocardiographic, laboratory and hemodynamic characteristics were obtained in all patients. Thirty-day survival from ECMO cannulation was calculated using Kaplan-Meier methodology. Using machine learning (elastic-net method) a predictive model for 30-day mortality was developed in the derivation cohort, the model was then tested on the validation cohort. A total of 283 patients met the inclusion criteria (228 DHF and 55 AMI). Of these, 151 died within the first 30 days post ECMO insertion. Survivors had similar characteristics to non-survivors except for lower troponin and creatinine levels. Machine learning identified 8 variables associated with 30-day mortality in the derivation cohort (Troponin, eGFR, total bilirubin, BMI, lactate, ethnicity, age and pH) with AUC of 0.68 (figure 1 A). The importance of each variable in the predicting model is shown in Figure 1B. Our score predicted 30 days mortality in the validation cohort with a good accuracy (AUC: 0.72, Figure 1C). Using the machine learning algorithm, we developed a model for predicting 30-day survival for cardiogenic shock patients supported by ECMO due to DHF and AMI.