Citations

Abstract Background Sarcoidosis, amyloidosis, hemochromatosis and scleroderma are the most common systemic disorders leading to infiltrative cardiomyopathy (InCM). Each of them has been associated with conduction abnormalities and sudden cardiac death. In patients who undergo in-hospital cardiac arrest, a high index of suspicion is required to rule out InCM as an underlying contributor. Purpose We aimed to analyse the temporal trend in the prevalence of InCM among patients with in-hospital cardiac arrest and identify factors associated with increased mortality in this population. Methods We analysed data from the National Inpatient Sample (NIS), which is the largest publicly available database of in-hospital patients in the Unites States. Using ICD-10 coding, we identified patients who were hospitalized across 10 years from 2010–2019. Patients with diagnosis codes for both cardiac arrest and a subtype of InCM were included. Demographic characteristics and co-morbidity data were collected. Statistical analysis was performed using STATA. Results The total number of patients with a diagnosis of in-hospital cardiac arrest was 19,34,260. Of these, the total number with InCM was 14,803 (0.77%), which comprised our study population. Mean age was 63 years. The overall prevalence of InCM across the years ranged between 0.75 to 0.9%, with a significant temporal increase (p<0.01). Prevalence of females ranged between 51% to 62% and significantly outnumbered males across the time period. (p=0.011). Incidence of in-hospital mortality ranged between 61% to 76% for females and 30 to 38% for males. Race based analysis showed that prevalence of Caucasians ranged from 51% to 62% while that of African Americans (AA) ranged from 57% to 73%. The incidence of mortality was similar in both populations. Sarcoidosis was the most prevalent form of InCM, accounting for nearly two-fifths of all cases while amyloidosis and scleroderma both accounted for nearly 20% each. Haemochromatosis was present in 10% of the population. Overall mortality rate in our study population was 60.6%. The following co-morbidities were more prevalent in patients with InCM than those without: history of heart failure, chronic obstructive pulmonary disease (COPD), chronic kidney disease, anaemia, malignancy, coagulopathy, ventricular tachycardia, acute kidney injury and stroke. The following factors were independent predictors of in-hospital mortality-age (p=0.001), female gender (p=0.016), Hispanic race (p=0.039), history of COPD (p<0.001) and presence of malignancy (p=0.042). Conclusion The prevalence of infiltrative cardiomyopathy in patients with in-hospital cardiac arrest is increasing. Females, older patients and Hispanic population are at an increased risk of mortality. Sex and race based disparities in the prevalence of InCM in patients with in-hospital cardiac arrest is an area of further research. Funding Acknowledgement Type of funding sources: None.

Abstract Introduction Transthyretin amyloid cardiomyopathy (ATTR-CM) is a chronic condition associated with progressive heart failure, resulting from extracellular deposition of misfolded transthyretin (TTR) protein as amyloid fibrils in the myocardium. Currently, there are few disease-modifying treatments. NNC6019–0001 is a humanized monoclonal antibody designed to deplete amyloid via antibody-mediated phagocytosis by targeting a unique epitope that is exposed only on misfolded monomeric and aggregated forms of TTR. In a phase 1, open-label, 3-month dose escalation trial, NNC6019–0001 was well tolerated at all doses tested (up to and including 30 mg/kg).1 The maximum tolerated dose was not reached. Exploratory cardiac endpoints were stable or indicated a possible benefit. Purpose To evaluate the effect of NNC6019–0001 30 mg/kg and 100 mg/kg on cardiac functional endpoints and predictive biomarkers in patients with ATTR-CM, and to assess pharmacokinetics, safety and tolerability, to establish the optimal dose for a phase 3 trial. Methods This is a randomized, double-blind, placebo-controlled trial recruiting 99 patients with hereditary or wild-type ATTR-CM (Figure). Inclusion criteria are New York Heart Association (NYHA) class II or III heart failure, left ventricle wall thickening (LVWT) ≥12 mm, N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels ≥650 pg/mL in sinus rhythm and >1000 pg/mL in atrial fibrillation, and a 6-minute walk test (6MWT) distance of 150–450 m. Patients will be randomly assigned to receive intravenous NNC6019–0001 30 mg/kg or 100 mg/kg or placebo, each in addition to standard of care, every 4 weeks for 52 weeks, followed by a 12-week follow-up. In a sentinel dosing phase, three patients per arm will receive the study drug or placebo, in combination with 24-hour inpatient cardiac monitoring and 7 days of continuous cardiac (tele-) monitoring. The primary endpoints are change from baseline to week 52 in 6MWT and in NT-proBNP levels. Secondary endpoints include cardiac measures: extracellular volume on cardiac magnetic resonance imaging, global longitudinal strain, troponin T levels, hospitalization due to cardiovascular events, and urgent visits due to heart failure. Quality of life will be assessed using the Kansas City Cardiomyopathy Questionnaire (KCCQ). All-cause mortality, pharmacokinetics and treatment-emergent adverse events will also be assessed. Results The trial will start mid-2022 with global recruitment. Conclusion Disease-modifying treatments are needed for patients with ATTR-CM, where treatment is often limited to managing symptoms and best supportive care; the first disease-modifying therapies recently became available. This phase 2 trial will be used to determine the appropriate dose for the phase 3 trial of NNC6019–0001, a novel antibody therapy designed to deplete amyloid in patients with ATTR-CM. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This trial was funded by Novo Nordisk A/S. Medical writing support was provided by Johanna Scheinost PhD, PharmaGenesis Oxford Central, Oxford, UK, with funding from Novo Nordisk A/S.

ImportanceTransthyretin amyloid cardiomyopathy (ATTR-CM) is a form of heart failure (HF) with preserved ejection fraction (HFpEF). Technetium Tc 99m pyrophosphate scintigraphy (PYP) enables ATTR-CM diagnosis. It is unclear which patients with HFpEF have sufficient risk of ATTR-CM to warrant PYP.ObjectiveTo derive and validate a simple ATTR-CM score to predict increased risk of ATTR-CM in patients with HFpEF.Design, Setting, and ParticipantsRetrospective cohort study of 666 patients with HF (ejection fraction ≥ 40%) and suspected ATTR-CM referred for PYP at Mayo Clinic, Rochester, Minnesota, from May 10, 2013, through August 31, 2020. These data were analyzed September 2020 through December 2020. A logistic regression model predictive of ATTR-CM was derived and converted to a point-based ATTR-CM risk score. The score was further validated in a community ATTR-CM epidemiology study of older patients with HFpEF with increased left ventricular wall thickness ([WT] ≥ 12 mm) and in an external (Northwestern University, Chicago, Illinois) HFpEF cohort referred for PYP. Race was self-reported by the participants. In all cohorts, both case patients and control patients were definitively ascertained by PYP scanning and specialist evaluation.Main Outcomes and MeasuresPerformance of the derived ATTR-CM score in all cohorts (referral validation, community validation, and external validation) and prevalence of a high-risk ATTR-CM score in 4 multinational HFpEF clinical trials.ResultsParticipant cohorts included were referral derivation (n = 416; 13 participants [3%] were Black and 380 participants [94%] were White; ATTR-CM prevalence = 45%), referral validation (n = 250; 12 participants [5%]were Black and 228 participants [93%] were White; ATTR-CM prevalence = 48% ), community validation (n = 286; 5 participants [2%] were Black and 275 participants [96%] were White; ATTR-CM prevalence = 6% ), and external validation (n = 66; 23 participants [37%] were Black and 36 participants [58%] were White; ATTR-CM prevalence = 39%). Score variables included age, male sex, hypertension diagnosis, relative WT more than 0.57, posterior WT of 12 mm or more, and ejection fraction less than 60% (score range −1 to 10). Discrimination (area under the receiver operating characteristic curve [AUC] 0.89; 95% CI, 0.86-0.92; P < .001) and calibration (Hosmer-Lemeshow; χ2 = 4.6; P = .46) were strong. Discrimination (AUC ≥ 0.84; P < .001 for all) and calibration (Hosmer-Lemeshow χ2 = 2.8; P = .84; Hosmer-Lemeshow χ2 = 4.4; P = .35; Hosmer-Lemeshow χ2 = 2.5; P = .78 in referral, community, and external validation cohorts, respectively) were maintained in all validation cohorts. Precision-recall curves and predictive value vs prevalence plots indicated clinically useful classification performance for a score of 6 or more (positive predictive value ≥25%) in clinically relevant ATTR-CM prevalence (≥10% of patients with HFpEF) scenarios. In the HFpEF clinical trials, 11% to 35% of male and 0% to 6% of female patients had a high-risk (≥6) ATTR-CM score.Conclusions and RelevanceA simple 6 variable clinical score may be used to guide use of PYP and increase recognition of ATTR-CM among patients with HFpEF in the community. Further validation in larger and more diverse populations is needed.

Aims Increased LV wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. Methods and Results Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 to 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4 chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: CA: 0.90, HCM: 0.93, and HTN/other: 0.92). Conclusion The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

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.

Background: Cardiac amyloidosis (CA) results from extracellular deposition of insoluble amyloid fibrils in the myocardium, leading to myocardial stiffening, restrictive cardiomyopathy and poor prognosis. Thus, measurements of myocardial stiffness might help with identification of patients with cardiac amyloid deposition. The speed of wave transmission of myocardial stretch (Vm) is a novel measure of myocardial elasticity. Our aim was to investigate the behavior of Vm in the left ventricular (LV) myocardium of patients with CA. We hypothesized this wave speed will be increased in these patients and will partly explain the reduction in systolic myocardial function. Methods: We prospectively studied 23 consecutive patients with systemic amyloidosis, of whom 17 (age 59±13 years) had confirmed cardiac involvement (15 AL, 2 TTR), and compared to 18 control subjects (age 47±13 years) with normal LV function. Comprehensive transthoracic echocardiography was performed. Tissue Doppler cineloops (350-450 frames/s) were acquired from 6 LV walls from 3 standard apical views. Regional and global Vm were measured as the wave speed of the onset of myocardial stretch from LV base to apex (late diastole). Results: Subjects with CA (n=17) had higher Vm compared to normal subjects (2.5±0.8 vs 1.5±0.2 m/s; P<0.001, respectively). They also had lower LV ejection fraction (56±11 vs 65±4%; P=0.02), global longitudinal strain (GLS -14±5 vs -20±2%, P<0.001), and myocardial relaxation (mitral annulus septal e’ velocity 4.7±1.9 vs 9.2±2.4 cm/s; P<0.001) and higher LV mass (150±54 vs 87±18 g/m2; P<0.001), left atrial volume (44±7 vs 27±6 mL/m2; P<0.001), and estimated LV filling pressure (E/e’ 20±9 vs 8±3; P<0.001). There was a strong positive association between Vm and LV wall thickness (R=0.62; P<0.001), GLS (R=0.45; P=0.01) and septal E/e’ (R=0.42; P=0.02) and an inverse correlation between Vm and septal e’ (R=-0.39; P=0.03), but not with ejection fraction (P=0.37). Conclusion: This pilot study indicates that Vm is elevated in patients with CA compared to normal subjects, commensurate with the effects of amyloid deposition on LV structure and function. This novel measurement shows promise for noninvasive assessment of diastolic myocardial stiffness in patients with CA.