The Public Health Burden of Cardiomyopathies: Insights from a Nationwide Inpatient Study

Regulated cell death pathways in cardiomyopathy

Heart disease is a worldwide health menace. Both intractable primary and secondary cardiomyopathies contribute to malignant cardiac dysfunction and mortality. One of the key cellular processes associated with cardiomyopathy is cardiomyocyte death. Cardiomyocytes are terminally differentiated cells with very limited regenerative capacity. Various insults can lead to irreversible damage of cardiomyocytes, contributing to progression of cardiac dysfunction. Accumulating evidence indicates that majority of cardiomyocyte death is executed by regulating molecular pathways, including apoptosis, ferroptosis, autophagy, pyroptosis, and necroptosis. Importantly, these forms of regulated cell death (RCD) are cardinal features in the pathogenesis of various cardiomyopathies, including dilated cardiomyopathy, diabetic cardiomyopathy, sepsis-induced cardiomyopathy, and drug-induced cardiomyopathy. The relevance between abnormity of RCD with adverse outcome of cardiomyopathy has been unequivocally evident. Therefore, there is an urgent need to uncover the molecular and cellular mechanisms for RCD in order to better understand the pathogenesis of cardiomyopathies. In this review, we summarize the latest progress from studies on RCD pathways in cardiomyocytes in context of the pathogenesis of cardiomyopathies, with particular emphasis on apoptosis, necroptosis, ferroptosis, autophagy, and pyroptosis. We also elaborate the crosstalk among various forms of RCD in pathologically stressed myocardium and the prospects of therapeutic applications targeted to various cell death pathways.

Role of 3 Tesla Magnetic Resonance Imaging in the Assessment of Infiltrative Cardiomyopathies

BACKGROUND

The aim of the present study was to assess the role of 3 Tesla (3T) magnetic resonance imaging (MRI) in the assessment of infiltrative cardiomyopathy (ICM).

METHODS

Cardiac MRI was performed on a 3T MRI machine for 15 patients who had clinical or echocardiographic signs of infiltrative cardiomyopathy. Each scan was assessed on a set of anatomical and functional parameters. The patterns of left ventricular (LV) late gadolinium enhancement (LGE) were also analyzed.

RESULTS

Bi-atrial dilatation was noted in 14 patients, consistent with a restrictive phenotype. All 15 patients had diastolic dysfunction with reduced LV diastolic ventricular filling and prolonged peak filling times. Eleven patients had a decreased peak filling rate. Twelve patients had systolic dysfunction with reduced ejection fraction (EF). Ten patients had contractile dysfunction in the form of global LV hypokinesia. On delayed contrast imaging, four patients showed no abnormal LGE. Two patients showed diffuse subendocardial enhancement. Two patients showed patchy subendocardial enhancement. Six patients showed patchy mid-myocardial enhancement. One patient showed diffuse mid-myocardial enhancement. Three patients showed patchy subepicardial enhancement. Two patients showed patchy transmural enhancement. Three patients showed reversed myocardial nulling. All 15 patients received a provisional diagnosis of infiltrative cardiomyopathy on the basis of cardiac MRI findings. Sarcoidosis was given as a probable cause in four patients, amyloidosis in three patients, an infectious cause in two patients, and drug-induced cardiomyopathy in one patient. In five patients, no obvious cause could be identified.

CONCLUSION

Infiltrative cardiomyopathies, although relatively uncommon, pose significant challenges in diagnosis and treatment. Cardiac MRI has become the gold standard for non-invasive diagnosis of all infiltrative cardiomyopathies.

Cardiomyopathy and Sudden Cardiac Death Among the Athletes in Developing Countries: Incidence and Their Prevention Strategies

The incidence of cardiomyopathy in athletes contributes significantly to the public health burden in developing countries. Most effective management strategies primarily rely on the modification of risk factors, and it is less expensive compared to other advanced investigations. Moreover, limited data is available concerning the incidence of adverse events including cardiac arrest and the strategies to prevent them, especially in this population subset. Therefore, devising preventative strategies that can easily be implemented in athletes and provide a cost-effective approach is warranted. We aim to discuss the incidence of major adverse cardiac events in athletes with cardiomyopathies and their associated risk factors and to evaluate the various strategies proposed to prevent the progression of cardiomyopathy in this population, with the initial hypothesis that the treatment of these pathologies poses a substantial challenge in this population. With regard to methodology, this is a narrative review. Search terms were described using the Population, Exposure, and Outcome (PEO) framework. A comprehensive search strategy was used to screen and identify any relevant literature in the PubMed and Google Scholar databases. This was done in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Four studies were identified in the final analysis. The incidence of sudden cardiac arrest varied between 0.3% and 0.33% among the athletes affected with cardiomyopathies. Routine and pre-participation screening has shown success in reducing the incidence of sudden cardiac death in athletes as a result of undiagnosed cardiomyopathies. Supervised exercise regimes have been proposed to reduce the incidence of cardiomyopathy in athletes. Beyond identification strategies, the prevention of cardiomyopathies revolves around the modification of risk factors. To conclude, the challenges athletes face, suffering from cardiomyopathy, have been an ongoing issue with unexpected cardiac arrest as the end result. Despite the decreased incidence of cardiomyopathies observed in athletes, the challenge in diagnosis can result in catastrophic outcomes, especially in developing countries. Therefore, adopting prevention strategies can have a profound impact on the identification and management of these pathologies.

Artificial Intelligence Applied to Cardiomyopathies: Is It Time for Clinical Application?

PURPOSE OF REVIEW

Artificial intelligence (AI) techniques have the potential to remarkably change the practice of cardiology in order to improve and optimize outcomes in heart failure and specifically cardiomyopathies, offering us novel tools to interpret data and make clinical decisions. The aim of this review is to describe the contemporary state of AI and digital health applied to cardiomyopathies as well as to define a potential pivotal role of its application by physicians in clinical practice.

RECENT FINDINGS

Many studies have been undertaken in recent years on cardiomyopathy screening especially using AI-enhanced electrocardiography (ECG). Even with mild left ventricular (LV) dysfunction, AI-ECG screening for amyloidosis, hypertrophic cardiomyopathy, or dilated cardiomyopathy is now feasible. Introduction of AI-ECG in routine clinical care has resulted in higher detection of LV systolic dysfunction; however, clinical research on a broader scale with diverse populations is necessary and ongoing. In the area of cardiac-imaging, AI automatically assesses the thickness and characteristics of myocardium to differentiate cardiomyopathies, but research on its prognostic capability has yet to be conducted. AI is also being applied to cardiomyopathy genomics, especially to predict pathogenicity of variants and identify whether these variants are clinically actionable. While the implementation of AI in the diagnosis and treatment of cardiomyopathies is still in its infancy, an ever-growing clinical research strategy will ascertain the clinical utility of these AI tools to help improve diagnosis of and outcomes in cardiomyopathies. We also need to standardize the tools used to monitor the performance of AI-based systems which can then be used to expedite decision-making and rectify any hidden biases. Given its potential important role in clinical practice, healthcare providers need to familiarize themselves with the promise and limitations of this technology.

Usefulness of Longitudinal Strain Adjusted to Regional Thickness in Hypertrophic Cardiomyopathy

Background. We assessed the usefulness of a longitudinal strain adjusted to regional thickness in hypertrophic cardiomyopathy (HCM). Indeed, with conventional software, the width of the region of interest (ROI) is the same over the entire myocardial wall, wherein the software analyzes only partially the left ventricular (LV) hypertrophic segments. Methods. We included 110 patients: 55 patients with HCM (HCM group) and 55 healthy subjects (age- and sex-matched control group). The global longitudinal strain (GLS) and regional strain for each of the 17 segments was calculated with standard software (for two groups) and with software adjusted to the myocardial wall thickness (for the HCM group). Results. GLS was significantly decreased in the HCM group compared to the control group (−15.1 ± 4.8% versus −20.5 ± 4.3%, p < 0.0001). In the HCM group, GLS (standard method versus adjusted to thickness) measurements were not significantly different (p = 0.34). Interestingly, the regional strain adjusted to thickness was significantly lower than the standard strain in the hypertrophic segments, especially in the basal inferoseptal segment (p = 0.0002), median inferoseptal segment (p < 0.001) and median anteroseptal segment (p = 0.02). The strain adjusted to thickness was still significantly lower in the most hypertrophic segments (≥20 mm) (−3.7 ± 3%, versus −5.9 ± 4.4%, p = 0.049 in the basal inferoseptal segment and −5.7 ± 3.5% versus −8.3 ± 4.5%, p = 0.0007 in the median inferoseptal segment). In the segments with significant myocardial fibrosis, the longitudinal strain adjusted to thickness was significantly lower than the conventional strain (−8.3 ± 3.3% versus −11.4 ± 4.5%, p = 0.002). The analysis of the strain adjusted to thickness had a better feasibility (97.5% versus 99%, p = 0.01). Conclusions. The analysis of a longitudinal strain adjusted to regional thickness is feasible in HCM and allows a better evaluation of myocardial deformation, especially in the most LV hypertrophic segments.

A bibliometric review of peripartum cardiomyopathy compared to other cardiomyopathies using artificial intelligence and machine learning

As developments in artificial intelligence and machine learning become more widespread in healthcare, their potential to transform clinical outcomes also increases. Peripartum cardiomyopathy is a rare and poorly-characterised condition that presents as heart failure in the last trimester prior to delivery or within 5-6 months postpartum. The lack of a definitive understanding of the molecular causes and clinical progress of this condition suggests that bibliometrics will be well-suited to creating new insights into this serious clinical problem. We examine similarities and differences between peripartum and its closely related familial dilated cardiomyopathy and idiopathic dilated cardiomyopathy. Using PubMed as the source of bibliometric data, we apply artificial intelligence-supported natural language processing to compare extracted data and genes association with these cardiomyopathies. Gene data were enhanced with additional metadata from third-party datasets and then analysed for their impact and specificity for peripartum cardiomyopathy. Artificial intelligence identified 14 genes that distinguished peripartum from both dilated and familial dilated cardiomyopathy. They are as follows: CTSD, RLN2, MMP23B*, SLC17A5, ST2*, PTHLH, CFH*, CFI, GPT, MR1, Rln1, SRI, STAT5A* and THBD. We then used the Human Protein Atlas website that uses affinity-purified rabbit polyclonal antibodies to identify genes that are expressed at the protein level (bold), or as RNA transcripts (*) in healthy human left ventricles. Additional analysis focussed on the full set of peripartum genes on linkage and specificity to cardiomyopathy yielded a different set of thirteen genes (bold font indicates those expressed in cardiomyocytes: PRL, RLN2, PLN, ST2, CTSD, F2, ACE, STAT3, TTN, SPP1, LGALS3, miR-146a, GNB3, SRI). This type of analysis can highlight new avenues for research, aimed at improving genomics-driven peripartum cardiomyopathy diagnosis as well as potential pathological and clinical sub-classification. We expect that this will allow for future improvements in identification, treatment and management of this condition. The first step in the application of these bibliometric-based artificial intelligence methods is to understand the current knowledge, and it is the aim of this paper to show how this might be achieved.

Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer

PURPOSE

Cardiovascular disease is a significant cause of late morbidity and mortality in survivors of childhood cancer. Clinical informatics tools could enhance provider adherence to echocardiogram guidelines for early detection of late-onset cardiomyopathy.

METHODS

Cancer registry data were linked to electronic health record data. Structured query language facilitated the construction of anthracycline-exposed cohorts at a single institution. Primary outcomes included the data quality from automatic anthracycline extraction, sensitivity of International Classification of Disease coding for heart failure, and adherence to echocardiogram guideline recommendations.

RESULTS

The final analytic cohort included 385 pediatric oncology patients diagnosed between July 1, 2013, and December 31, 2018, among whom 194 were classified as no anthracycline exposure, 143 had low anthracycline exposure (< 250 mg/m²), and 48 had high anthracycline exposure (≥ 250 mg/m²). Manual review of anthracycline exposure was highly concordant (95%) with the automatic extraction. Among the unexposed group, 15% had an anthracycline administered at an outside institution not captured by standard query language coding. Manual review of echocardiogram parameters and clinic notes yielded a sensitivity of 75%, specificity of 98%, and positive predictive value of 68% for International Classification of Disease coding of heart failure. For patients with anthracycline exposure, 78.5% (n = 62) were adherent to guideline recommendations for echocardiogram surveillance. There were significant association with provider adherence and race and ethnicity (P = .047), and 50% of patients with Spanish as their primary language were adherent compared with 90% of patients with English as their primary language (P = .003).

CONCLUSION

Extraction of treatment exposures from the electronic health record through clinical informatics and integration with cancer registry data represents a feasible approach to assess cardiovascular disease outcomes and adherence to guideline recommendations for survivors.

Prospective follow-up in various subtypes of cardiomyopathies: insights from the ESC EORP Cardiomyopathy Registry

AIMS

The European Society of Cardiology (ESC) European Observational Research Programme (EORP) Cardiomyopathy Registry is a prospective multinational registry of consecutive patients with cardiomyopathies. The objective of this report is to describe the short-term outcomes of adult patients (≥18 years old).

METHODS AND RESULTS

Out of 3208 patients recruited, follow-up data at 1 year were obtained in 2713 patients (84.6%) [1420 with hypertrophic (HCM); 1105 dilated (DCM); 128 arrhythmogenic right ventricular (ARVC); and 60 restrictive (RCM) cardiomyopathies]. Improvement of symptoms (dyspnoea, chest pain, and palpitations) was globally observed over time (P < 0.05 for each). Additional invasive procedures were performed: prophylactic implantation of implantable cardioverter-defibrillator (ICD) (5.2%), pacemaker (1.2%), heart transplant (1.1%), ablation for atrial or ventricular arrhythmia (0.5% and 0.1%). Patients with atrial fibrillation increased from 28.7% to 32.2% of the cohort. Ventricular arrhythmias (VF/ventricular tachycardias) in ICD carriers (primary prevention) at 1 year were more frequent in ARVC, then in DCM, HCM, and RCM (10.3%, 8.2%, 7.5%, and 0%, respectively). Major cardiovascular events (MACE) occurred in 29.3% of RCM, 10.5% of DCM, 5.3% of HCM, and 3.9% of ARVC (P < 0.001). MACE were more frequent in index patients compared to relatives (10.8% vs. 4.4%, P < 0.001), more frequent in East Europe centres (13.1%) and least common in South Europe (5.3%) (P < 0.001). Subtype of cardiomyopathy, geographical region, and proband were predictors of MACE on multivariable analysis.

CONCLUSIONS

Despite symptomatic improvement, patients with cardiomyopathies remain prone to major clinical events in the short term. Outcomes were different not only according to cardiomyopathy subtypes but also in relatives vs. index patients, and according to European regions.