Myocardial Recovery With HeartMate 3 Left Ventricular Assist Device: An Attainable Goal That Needs Better Precision.

Despite advances in our understanding of myocardial recovery among left ventricular assist device (LVAD) patients, with 10-30% of patients achieving substantial myocardial improvement, the rates of LVAD support cessation remain extremely low (1-2%). These numbers are in stark contrast to clinical trial data where successful LVAD cessation is reported in up to 47% of patients. The majority of LVAD programs lack structured recovery programs and targeted protocols, likely underscoring the heterogeneity that exists among LVAD patients with myocardial recovery. This perspective summarizes the current medical and surgical challenges with respect to 1) identifying the appropriate candidates for LVAD cessation; 2) methods to wean LVAD support; 3) reviewing surgical techniques for cessation of current generation HeartMate 3 LVAD; and 4) approaching shared decision making for LVAD cessation between patients and providers given the uncertainties that remain in the field.

Remote Cardiac Monitoring in Patients With Heart Failure: A Review.

Importance: Heart failure (HF) is often characterized by an insidious disease course leading to frequent rehospitalizations and a high use of ambulatory care. Remote cardiac monitoring is a promising approach to detect worsening HF early and intervene prior to an overt decompensation. Observations: Recently, a multitude of novel technologies for remote cardiac monitoring (RCM) in patients with HF have been developed and are undergoing clinical trials. This development has been accelerated by the COVID-19 pandemic. Conclusions and Relevance: This review summarizes the major clinical trials on RCM in patients with HF and present the most recent developments in noninvasive and invasive RCM technologies.

Deep significance clustering: a novel approach for identifying risk-stratified and predictive patient subgroups.

OBJECTIVE: Deep significance clustering (DICE) is a self-supervised learning framework. DICE identifies clinically similar and risk-stratified subgroups that neither unsupervised clustering algorithms nor supervised risk prediction algorithms alone are guaranteed to generate. MATERIALS AND METHODS: Enabled by an optimization process that enforces statistical significance between the outcome and subgroup membership, DICE jointly trains 3 components, representation learning, clustering, and outcome prediction while providing interpretability to the deep representations. DICE also allows unseen patients to be predicted into trained subgroups for population-level risk stratification. We evaluated DICE using electronic health record datasets derived from 2 urban hospitals. Outcomes and patient cohorts used include discharge disposition to home among heart failure (HF) patients and acute kidney injury among COVID-19 (Cov-AKI) patients, respectively. RESULTS: Compared to baseline approaches including principal component analysis, DICE demonstrated superior performance in the cluster purity metrics: Silhouette score (0.48 for HF, 0.51 for Cov-AKI), Calinski-Harabasz index (212 for HF, 254 for Cov-AKI), and Davies-Bouldin index (0.86 for HF, 0.66 for Cov-AKI), and prediction metric: area under the Receiver operating characteristic (ROC) curve (0.83 for HF, 0.78 for Cov-AKI). Clinical evaluation of DICE-generated subgroups revealed more meaningful distributions of member characteristics across subgroups, and higher risk ratios between subgroups. Furthermore, DICE-generated subgroup membership alone was moderately predictive of outcomes. DISCUSSION: DICE addresses a gap in current machine learning approaches where predicted risk may not lead directly to actionable clinical steps. CONCLUSION: DICE demonstrated the potential to apply in heterogeneous populations, where having the same quantitative risk does not equate with having a similar clinical profile.

Remote Hemodynamic Monitoring Equally Reduces Heart Failure Hospitalizations in Women and Men in Clinical Practice: A Sex-Specific Analysis of the CardioMEMS Post-Approval Study.

BACKGROUND: Response to pharmacological and device-based therapy for heart failure (HF) may vary by sex. We examined sex differences in response to ambulatory hemodynamic monitoring in clinical practice using the CardioMEMS PAS (Post-Approval Study). METHODS: The CardioMEMS PAS was a prospective, single-arm, multicenter, open-label study of 1200 adults with New York Heart Association class III HF and at least 1 HF hospitalization (HFH) within 12 months who underwent pulmonary artery pressure sensor implantation between 2014 and 2017. Changes in pulmonary artery pressure over time were stratified by ejection fraction <40% and sex. Clinical outcomes including HFH rate at 12 months, 1-year mortality, and quality of life were examined in women and men. RESULTS: Four hundred fifty-two women (38% of total) enrolled in the PAS were less likely to be White (78% versus 86%) and more likely to have nonischemic cardiomyopathy (44% versus 34%) and had significantly higher SBP (132 versus 124 mm Hg), mean ejection fraction (44% versus 36%), and pulmonary vascular resistance (3.2 versus 2.6 WU) than men (P<0.001 for all). There were similar reductions in pulmonary artery pressure from baseline to 12 months in both men and women for the whole cohort and for subgroups with HF with reduced ejection fraction and HF with preserved ejection fraction. Both sexes experienced significant decreases in HFH over 12 months (men: HR, 0.46 [95% CI, 0.40-0.52]; women: HR, 0.39 [95% CI, 0.33-0.46]). In adjusted models, there were no significant differences in change in HFH between men and women (interaction P=0.13) or all-cause mortality at 1 year (adjusted HR, 1.25 [95% CI, 0.88-1.77]). CONCLUSIONS: Women and men enrolled in the CardioMEMS PAS had similar reductions from baseline in pulmonary artery pressure over 1 year and experienced similar reductions in HFH. Hemodynamic monitoring provides similar benefit with regard to HF events in both women and men. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02279888.

Using electronic health records for population health sciences: a case study to evaluate the associations between changes in left ventricular ejection fraction and the built environment.

OBJECTIVE: Electronic health record (EHR) data linked with address-based metrics using geographic information systems (GIS) are emerging data sources in population health studies. This study examined this approach through a case study on the associations between changes in ejection fraction (EF) and the built environment among heart failure (HF) patients. MATERIALS AND METHODS: We identified 1287 HF patients with at least 2 left ventricular EF measurements that are minimally 1 year apart. EHR data were obtained at an academic medical center in New York for patients who visited between 2012 and 2017. Longitudinal clinical information was linked with address-based built environment metrics related to transportation, air quality, land use, and accessibility by GIS. The primary outcome is the increase in the severity of EF categories. Statistical analyses were performed using mixed-effects models, including a subgroup analysis of patients who initially had normal EF measurements. RESULTS: Previously reported effects from the built environment among HF patients were identified. Increased daily nitrogen dioxide concentration was associated with the outcome while controlling for known HF risk factors including sex, comorbidities, and medication usage. In the subgroup analysis, the outcome was significantly associated with decreased distance to subway stops and increased distance to parks. CONCLUSIONS: Population health studies using EHR data may drive efficient hypothesis generation and enable novel information technology-based interventions. The availability of more precise outcome measurements and home locations, and frequent collection of individual-level social determinants of health may further drive the use of EHR data in population health studies.

United network for organ sharing outcomes after heart transplantation for al compared to ATTR cardiac amyloidosis.

Light-chain (AL) cardiac amyloidosis (CA) has a worse prognosis than transthyretin (ATTR) CA. In this single-center study, we compared post-heart transplant (OHT, orthotopic heart transplantation) survival for AL and ATTR amyloidosis, hypothesizing that these differences would persist post-OHT. Thirty-nine patients with CA (AL, n = 18; ATTR, n = 21) and 1023 non-amyloidosis subjects undergoing OHT were included. Cox proportional hazards modeling was used to evaluate the impact of amyloid subtype and era (early era: from 2001 to 2007; late era: from 2008 to 2018) on survival post-OHT. Survival for non-amyloid patients was greater than ATTR (P = .034) and AL (P < .001) patients in the early era. One, 3-, and 5-year survival rates were higher for ATTR patients than AL patients in the early era (100% vs 75%, 67% vs 50%, and 67% vs 33%, respectively, for ATTR and AL patients). Survival in the non-amyloid cohort was 87% at 1 year, 81% at 3 years, and 76% at 5 years post-OHT. In the late era, AL and ATTR patients had unadjusted 1-year, 3-year, and 5-year survival rates of 100%, which was comparable to non-amyloid patients (90% vs 84% vs 81%). Overall, these findings demonstrate that in the current era, differences in post-OHT survival for AL compared to ATTR are diminishing; OHT outcomes for selected patients with CA do not differ from non-amyloidosis patients.

Foreign body-induced abscess resembling pancreatic neoplasia.

We report the case of a 44-year-old man presenting with abdominal pain and leukocytosis. His initial computed tomography demonstrated a pancreatic head mass concerning for pancreatic adenocarcinoma. However, on further review of the patient's imaging, the mass was determined to be an abscess caused by foreign body ingestion and gastric perforation rather than cancer. This report describes the clinical and radiographic distinctions between pancreatic neoplasia and abscess. It also reviews the pertinent medical literature on how such viscus perforations affect subsequent prognostication and clinical management.

Unmasking Evans syndrome: T-cell phenotype and apoptotic response reveal autoimmune lymphoproliferative syndrome (ALPS).

Autoimmune lymphoproliferative syndrome (ALPS) is a rare disorder of disrupted lymphocyte homeostasis. Clinical manifestations of ALPS vary but typically include autoimmune cytopenias, organomegaly, lymphadenopathy, and increased risk of malignancies. A similar spectrum of symptoms may be seen in some patients with Evans syndrome (ES), a hematologic disorder defined by autoimmune destruction of at least 2 hematologic cell types. We hypothesized that a subset of patients diagnosed with ES may have ALPS. We screened 12 children with ES by flow cytometric analysis for CD4-/CD8- (double negative) T cells (DNTs) and with the definitive test for ALPS, defective in vitro Fas-mediated apoptosis. Six of the patients had elevated DNTs, suggestive of ALPS and also had defective Fas-mediated apoptosis. The other 6 patients displayed normal T-cell apoptosis; 5 of whom had normal DNTs, and 1 had a borderline result. Thus, 7 (58%) of 12 patients with ES had elevated DNTs suggestive of ALPS, with functional confirmation in 6 of 7. This suggests that analysis of DNTs may be a sensitive first-line screening test, serving as a marker of patients who should undergo definitive testing for ALPS. Our data further suggest that a number of patients with ES may have ALPS, a novel finding with important therapeutic implications.