Redfield, Margaret M.

Introduction: Through degradation of the cardio- and renal-protective second messenger cyclic GMP, phosphodiesterase-9 (PDE9) excess may contribute to cardiomyocyte hypertrophy, fibrosis, and renal dysfunction, common features in heart failure with preserved ejection fraction (HFpEF) development and progression. Hypothesis: Selective PDE9 inhibition with IMR-687 mitigates an adverse cardiac and renal phenotype in mouse models of HFpEF. Methods: Cardiac and renal responses to IMR-687 (60 mg/kg, 100 mg/kg) compared with vehicle were examined over 6-8 weeks in 3 adult male mouse models of HFpEF (1.5 mg/kg/d angiotensin-II infusion [ang-II]; uninephrectomy + 0.30 ug/h d-aldosterone infusion + 1% NaCl drinking water [neph-aldo]; and db/db [db]). Phenotyping included wheat germ agglutinin staining for cardiomyocyte cross-sectional area (CSA); RT-PCR for myocardial PDE9, natriuretic peptide, inflammatory and fibrosis marker transcript abundances; ELISA for plasma natriuretic peptides; and urinary albumin to creatinine ratio (UACR). Results: IMR-687 reduced median cardiomyocyte size (CSA) by 54, 58, and 35% compared with vehicle in the ang-II, neph-aldo, and db models, respectively; p < 0.003 for all. Myocardial PDE9, NPPA, NPPB, COL3A1, and IL-1β expression were decreased by IMR-687 in all models (Table). Median plasma BNP levels (pg/mL) were lower in IMR-687 vs. vehicle treated mice in all models (ang-II: 2376 vs. 5757; neph-aldo: 1216 vs. 1860; db: 830 vs. 1216); p < 0.007 for all, with similar findings for ANP (Table). UACR was lower in IMR-687 compared with vehicle treated mice in all models (Table). Heart rate and blood pressure did not differ between IMR-687 and vehicle treated mice. Conclusion: Selective PDE9 inhibition with IMR-687 was effective for prevention and treatment of cardiac hypertrophy and renal dysfunction in 3 different preclinical models of HFpEF. IMR-687 may be a promising candidate therapy for testing in clinical trials of human HFpEF.

Introduction: Transthyretin cardiac amyloidosis (TTR-CA) can cause heart failure with preserved EF (HFpEF). We previously reported a clinical/echo-based score (TCAS) and defined a cut-off that predicted risk of TTR-CA in HFpEF. Herein, we assess the comparative performance of an artificial-intelligence ECG-based screening tool (AI-ECG). Hypothesis: AI-ECG successfully identifies TTR-CA in HFpEF cohorts across a range of TTR-CA prevalence Methods: Referral HFpEF cohort was constructed from a referral population of HFpEF patients (EF ≥ 40%) undergoing 99m Tc-pyrophosphate scintigraphy (PYP) at Mayo Clinic (2013-2020, n=484, 38% with TTR-CA). Community HFpEF cohort was prospectively screened with PYP (n=275; age ≥ 60, LV wall thickness (WT) ≥ 12 mm, 4% with TTR-CA). TCAS was built using a multivariable logistic regression model and converted to a simple point score comprised of age (60-69, 70-79, ≥ 80: +2, +3, +4 points respectively), male sex (+2), relative WT > 0.57 (+2), posterior WT ≥ 12 mm (+1), EF < 60% (+1), and hypertension diagnosis (-1). TCAS was validated in the community cohort. A deep neural network trained to predict cardiac amyloidosis from a single 12-lead ECG, was applied to both referral and community cohorts. Patients were excluded if ECG was not available ≤ 12 months before PYP or if used in development of the AI-ECG. Standard ROC methods were applied. Youden’s index was used to define optimal cut-off. Results: Predictive characteristics of AI-ECG were strong and compared favorably with TCAS across a range of true TTR-CA prevalence (Table). Conclusions: Using a single ECG, AI-ECG effectively predicts TTR-CA with an excellent negative predictive value to rule out TTR-CA and a positive predictive value sufficient to warrant specific TTR-CA testing. This was particularly evident in the community. AI-ECG holds promise for simple, cost-effective global screening of at-risk populations, especially those with limited access to advanced cardiac imaging.

Abstract Aims Pulmonary hypertension (PH) and pulmonary vascular disease (PVD) are common and associated with adverse outcomes in left heart disease (LHD). This study sought to characterize the pathophysiology of PVD across the spectrum of PH in LHD. Methods and results Patients with PH-LHD [mean pulmonary artery (PA) pressure &gt;20 mmHg and PA wedge pressure (PAWP) ≥15 mmHg] and controls free of PH or LHD underwent invasive haemodynamic exercise testing with simultaneous echocardiography, expired air and blood gas analysis, and lung ultrasound in a prospective study. Patients with PH-LHD were divided into isolated post-capillary PH (IpcPH) and PVD [combined post- and pre-capillary PH (CpcPH)] based upon pulmonary vascular resistance (PVR &lt;3.0 or ≥3.0 WU). As compared with controls (n = 69) and IpcPH-LHD (n = 55), participants with CpcPH-LHD (n = 40) displayed poorer left atrial function and more severe right ventricular (RV) dysfunction at rest. With exercise, patients with CpcPH-LHD displayed similar PAWP to IpcPH-LHD, but more severe RV–PA uncoupling, greater ventricular interaction, and more severe impairments in cardiac output, O2 delivery, and peak O2 consumption. Despite higher PVR, participants with CpcPH developed more severe lung congestion compared with both IpcPH-LHD and controls, which was associated lower arterial O2 tension, reduced alveolar ventilation, decreased pulmonary O2 diffusion, and greater ventilation-perfusion mismatch. Conclusions Pulmonary vascular disease in LHD is associated with a distinct pathophysiologic signature marked by greater exercise-induced lung congestion, arterial hypoxaemia, RV–PA uncoupling, ventricular interdependence, and impairment in O2 delivery, impairing aerobic capacity. Further study is required to identify novel treatments targeting the pulmonary vasculature in PH-LHD.

Background: Recent studies have suggested that patient activation, or having the knowledge, skills and confidence to manage one’s own health, has a substantial impact on patient behaviors and health outcomes. However, the role of activation in patients with heart failure is unknown. Methods: We prospectively recruited Southeastern Minnesota residents hospitalized with acute decompensated heart failure (ADHF) from January 2014 through July 2015. Activation was measured by face-to-face questionnaire using the Patient Activation Measure (PAM) and patients were categorized into four activation levels (lowest to highest activation) per PAM guidelines. Logistic regression was used to examine the association between activation level and discharge location and early post-discharge outcomes. Results: Among the 302 patients enrolled, the mean age was 77.3 years, 57.3% were men, and 46.8% had preserved ejection fraction. Median (25th-75th percentile) length of stay was 4 (3-7) days and 7 (2.3%) patients died prior to discharge. Among survivors, 73.3% discharged to home, while the remainder went to skilled nursing facilities (23.0%), assisted living facilities (2.0%) or other arrangements (1.4%). The 30-day mortality rate was 7.0% and the 30-day readmission rate was 21.2%. The number (%) of patients in each activation category from highest to lowest was 9 (3.0%), 121 (40.1%), 122 (40.4%), and 50 (16.6%). Patients with lower activation were older, less educated, had worse overall and financial satisfaction, and worse health literacy. They more often discharged to skilled nursing facilities and had higher 30-day mortality, though 30-day readmission did not differ by activation (Figure). Adjusting for age, patients in the lowest activation level were at 3.1-fold increased odds of discharging to a skilled nursing facility and 6.0-fold increased odds of dying within 30 days of hospital discharge compared with patients in the highest two activation levels. Conclusions: Patients hospitalized with ADHF with lower activation are less satisfied, have worse health literacy, more often require skilled care and are at increased risk for early post-discharge mortality. Activation is easy to measure, identifies a high-risk subgroup, and is potentially modifiable.

Background: Left ventricular assist device (LVAD) implantation is a new therapy for advanced heart failure (HF). The number of HF patients eligible for LVAD and the cardiology providers’ comfort level with referral for LVAD remains unclear. Objective: To assess provider perception of LVAD candidacy and LVAD referral patterns in consecutive HF patients. Methods: Providers completed a survey for each HF patient seen between March 1, 2013 and April 26, 2013. The survey listed standard LVAD candidacy criteria and asked 1) if a patient was an LVAD candidate (yes, no, unsure); 2) reasons patients were not LVAD candidates (check list, table); and 3) whether the patient had been referred for LVAD evaluation (yes, no, unsure). Results: Patients (n=522) were seen in a tertiary HF outpatient clinic (n=357; 68%), a tertiary HF inpatient service (n=36; 7%), a tertiary general cardiology service (n=45; 9%) or a community based outpatient cardiac clinic (n=84; 16%) Median age of patients was 73 years and 65% were male. Provider assessment of LVAD candidacy was “no” in 443 (85%), “yes” in 35 (7%) and “unsure” in 43 (8%) with ineligibility for LVAD attributed to multiple concerns (Table). Ninety percent of patients considered “too old” for LVAD were over 78 years of age. Provider designation of LVAD candidacy as yes or unsure varied across practice setting: tertiary HF outpatient clinic, 12%; tertiary HF inpatient service, 42%; tertiary general cardiology service, 22%; and community based outpatient cardiac clinic, 13%. In patients with a provider designation of LVAD candidacy as yes or unsure (n=78), only 21 (27%) patients had been referred for LVAD evaluation. Conclusion: When provided with LVAD candidacy criteria, providers indicated 15% of HF patients were (7%) or were possibly (8%) LVAD candidates but indicated that few patients had undergone a formal LVAD evaluation. These data suggest that measures to improve evaluation of HF patients for LVAD are needed.

Background: Heart failure (HF) is a clinical syndrome with an overall poor prognosis, but the clinical trajectory is often unpredictable in individuals. There has been an impetus to promote iterative patient-provider discussions regarding preferences for end of life (EOL) care and advanced care planning. However, very little is known regarding provider preferences or their personal confidence addressing EOL care with their patients with HF. To address these gaps in knowledge, we surveyed clinicians at three practice sites in a large integrated health system. Methods: Physicians, nurse practitioners (NP), and physician assistants (PA) at Mayo Clinic (Rochester, Minnesota) and its surrounding health system were asked to participate in an electronic survey in October 2013. Clinicians surveyed included tertiary care HF specialists (Tertiary Care Cardiology), cardiologists and NP/PAs practicing in a community setting (Community Cardiology), and primary care clinicians (Primary Care). Results: A total of 95 clinicians completed the survey (52.5% response rate), including 50 physicians and 45 NP/PAs. Clinicians reported discussing prognosis and EOL wishes when their patient’s health status was worsening, but only 12% reported annual discussions as advocated by the American Heart Association. In total 52% of providers reported one or more reasons that they hesitate to discuss EOL care with their patients, including provider discomfort (11%), perception of patient (21%) or family (12%) unreadiness to have the discussion, fear of destroying hope (9%), or a lack of time (8%). Tertiary Care (63%) and Community Cardiology (58%) clinicians were more likely to attribute responsibility for having EOL discussions to the HF cardiologist, while 66% of Primary Care providers felt it was their responsibility. Tertiary and Community Cardiology clinicians were more likely to have referred patients to Palliative Medicine within the last year than Primary Care (89% vs. 21%, p<0.001). Overall, 30% of those surveyed reported low or very low confidence levels in initiating prognosis or EOL discussions, enrolling patients in hospice, or providing EOL care, with lower confidence among those with fewer years of clinical experience. The majority of clinicians expressed a high level of interest in further skills acquisition on these topics. Conclusion: There is tremendous variability in the way that clinicians view and approach advanced care discussions with their patients with HF; varying provider perception and lack of provider confidence may contribute. Despite this variability, most clinicians are interested in further development and skills acquisition. Addressing the learning needs of providers is an important next step toward enhancing the EOL care of patients with HF.

Background: Echocardiography is an important component of the assessment of patients with heart failure (HF). However, its longitudinal use after initial HF diagnosis has not been evaluated. Methods: We studied patterns of echocardiogram use after HF diagnosis among a random sample of validated incident HF cases in Olmsted County, Minnesota, from 1987 to 2006. Results: Among 1472 HF patients (mean age 76.0 years, 45% male), 4817 echocardiograms were obtained over a mean follow-up of 5.1 years. The majority were transthoracic (n=3952, 82%), with fewer transesophageal (n=604, 13%) and stress (n=250, 5%) studies obtained. Most patients died during follow-up (n=1126, 76%), and thus had their entire lifetime after HF diagnosis captured. The number of echocardiograms per person ranged from 0-38 (Figure) with a median (25 th , 75 th percentile) of 2 (1, 4). The mean rate of echocardiograms obtained per 10 years of follow-up was 6.4, and increased over time with mean echocardiograms per 10 years follow-up of 4.9, 5.9, 7.2, and 7.8 for persons diagnosed from 1987-1991, 1992-96, 1997-2001, and 2002-06, respectively (p for trend <0.001). Men had echocardiograms more frequently than women (7.2 vs. 5.7 per 10 person years follow-up, p<0.001). Patients who were younger at diagnosis had more frequent echocardiography with rates of 7.1, 6.8, and 5.2 per 10 years follow-up for those who were <70 years, 70-79 years, and 80 years or older at diagnosis (p for trend <0.001). Conclusions: Most patients have multiple echocardiograms performed after HF diagnosis, and echocardiography use in patients with HF has increased over time. Men and younger patients have higher rates of use after HF diagnosis.

Introduction: Some patients with heart failure (HF) will go on to develop advanced HF, characterized by severe HF symptoms despite attempts to optimize medical therapy. Our understanding of advanced HF at a population level remains limited. The goals of this study were to determine the risk of developing advanced HF in patients with newly diagnosed HF, identify risk factors for developing advanced HF, and evaluate the impact of advanced HF on outcomes. Methods: This was a population-based, retrospective cohort study of Olmsted County, Minnesota residents with a new clinical diagnosis of HF between 2007-2017. The primary outcome was development of advanced HF, defined using the 2018 European Society of Cardiology Criteria. Risk factors for development of advanced HF from the time of incident HF diagnosis were examined using cause-specific Cox proportional hazard regression models. The associations of development of advanced HF with risks of hospitalization and mortality were examined using Andersen-Gill and Cox models, respectively, with advanced HF treated as a time dependent covariate. Results: There were 4597 residents with incident HF from 2007 to 2017. The cumulative incidence of advanced HF was 6.0%, 9.1%, and 11.5% at 2, 4, and 6 years after incident HF diagnosis. Characteristics independently associated with development of advanced HF included older age, male sex, diabetes, chronic obstructive pulmonary disease, peripheral vascular disease, lower serum sodium, worse right ventricular function, left atrial enlargement, higher estimated filling pressures, and higher right ventricular systolic pressure (p<0.05 for each). Development of advanced HF was associated with increased risks of all-cause hospitalization (adjusted HR 3.00; 95% CI 2.65-3.41, p<0.001), HF hospitalization (HR 10.24, 95% CI 8.67-12.10), all-cause mortality (HR 5.00, 95% CI 4.46-5.59, p<0.001), and cardiovascular mortality (HR 7.84, 95% CI 6.74-9.12). Conclusions: In this population-based study, clinical, laboratory and echocardiographic characteristics at the time of incident HF diagnosis were associated with future risk of advanced HF. Development of advanced HF was associated with markedly increased morbidity and mortality.

Introduction: Guideline-directed medical therapy (GDMT) dramatically improves outcomes in heart failure with reduced ejection fraction (HFrEF). Our goal was to examine GDMT use in community patients with newly diagnosed HFrEF. Methods: We performed a population-based, retrospective cohort study of all Olmsted County, Minnesota residents with newly diagnosed HFrEF (EF≤40%) 2007-2017. We excluded patients with contraindications to medication initiation (allergy, intolerance, heart rate<50 for beta blockers, SBP <80mm Hg for beta blockers, ACEi/ARB/ARNI; high creatinine (>3 mg/dL ACEi/ARB/ARNI, >2.5 men or >2.0 mg/dL women for mineralocorticoid receptor antagonists, MRAs) or hyperkalemia (potassium >5 meQ/L for ACEi/ARB/ARNI, MRA). We examined use and peak dose achieved for beta blockers, HF beta blockers (metoprolol succinate, carvedilol, bisoprolol), ACEi/ARB/ARNI, and MRA in the first year after HFrEF diagnosis. We used logistic regression to evaluate predictors of GDMT use. Results: From 2007-2017, 1160 patients were diagnosed with HFrEF (mean age 69.7 years, 65.6% men). Most eligible patients received beta blockers (92.1%) and ACEi/ARB/ARNI (86.5%) in the first year after HFrEF. However, only 63.6% of patients were treated with a HF beta blocker, and most did not receive MRAs (82.6%). The percentage of treated patients reaching medication target doses was 20.5% for HF beta blockers, 25.3% for ACEi/ARB/ARNI, and 11.2% for MRA. Compared to patients not seen in an HF clinic, patients seen in an HF clinic (n=380, 32.8%) were at greater odds of receiving beta blockers (OR 3.85, 95% CI 1.79-8.33); HF beta blockers (OR 3.85, 95% CI 2.63-5.26); ACEi/ARB/ARNIs (OR 3.85, 95% CI 2.17-6.67); and MRAs (OR 3.03, 95% CI 2.08-4.35). Other independent predictors of GDMT use included younger age (beta blockers, ACEi/ARB/ARNI), male gender (MRAs), higher SBP (beta blockers, ACEi/ARB/ARNI), lower EF (HF beta blockers), higher BMI (MRAs), and diabetes (ACEi/ARB/ARNI, p<0.05 for each). Conclusions: In this population-based study, most patients with newly diagnosed HFrEF received beta blockers and ACEi/ARB/ARNIs, but goal doses were usually not achieved. GDMT use was much higher in patients referred to an HF clinic.

Introduction: Advanced or “Stage D” heart failure (Adv HF) patients are at high risk of poor outcomes. However, recognition of Adv HF is limited as diagnostic criteria are complex. Administrative algorithms to identify Adv HF could enable better understanding of who has advanced HF and lead to enhanced therapeutics development, dissemination, and outcomes. Methods: In a population-based cohort of all Olmsted County, Minnesota residents with ≥1 HF billing code 2007-2017 (n=9881), we identified all patients with Adv HF (n=753) by applying the gold standard European Society of Cardiology Adv HF criteria via manual medical review by a HF cardiologist. The Adv HF index date was the date the patient first met all ESC criteria. We then developed candidate algorithms to identify Adv HF using only administrative data (billing codes and HF prescriptions or comorbidities known to affect HF outcomes), applied them to the entire HF cohort and assessed their ability to identify patients with Adv HF on or after their Adv HF index date. Results: A single hospitalization (Hsp) for HF or ventricular arrhythmias (VA, 2007-2017) identified all patients with Adv HF (sensitivity 100%), but the PPV was low (36.4%). Requiring more Hsp, other signs of Adv HF such as hyponatremia, acute kidney injury, hypotension or high-dose diuretic use decreased the sensitivity but improved specificity and PPV. As Adv HF was relatively uncommon, negative predictive values (NPV) were high regardless of algorithm characteristics. Conclusions: Algorithms using administrative data can identify patients with Adv HF with clinically useful accuracy.