Using Machine Learning to Generate a Core Set of Echocardiographic Indices for Pediatric Research: A Sub-study in the PCS2 Cohort

With a multitude of echocardiographic (echo) parameters at a clinician’s disposal and clinical efficiency paramount, determining the most reliable and relevant pediatric echo parameters remains challenging. Using machine learning (ML), clinical relevance, and inter/intra-rater reliability, we aimed to identify a core set of echo parameters from the PCS2 cohort of childhood cancer survivors and healthy controls to guide pediatric research and clinical care. A standard set of 94 echocardiographic parameters were chosen and screened for missing variation, linear combinations, and high correlations. A hierarchical cluster analysis using Ward’s method was performed on the remaining variables to produce a clustering dendrogram. Thereafter, inter- and intra-rater reliability analyses were conducted using intraclass correlation coefficients (ICC) and Bland-Altman (B-A) plots. Using highly reliable (\u3e0.65 ICC) and available (\u3e80% scored) parameters, five pediatric cardiologists ranked each parameter within cluster for clinical relevance. Of the 61 echo parameters selected for the dendrogram, only 54 were scored due to feasibility of sonographer acquisition. ≥73% of all scored parameters had good (0.60-0.74) or excellent (≥0.75) ICC in the inter- and intra-rater analyses. Mean within cluster ranks were assigned per parameter to identify a core set of 10, and minimal set of 5 parameters: ejection fraction (EF), mitral valve E/E’, tissue doppler interventricular septum valve S-velocity, average global longitudinal strain, and LV end diastolic diameter. Using clustering analysis, clinical relevance rankings, and reliability we have identified 10 core and 5 minimal echo indices to guide further pediatric echocardiographic research and clinical care

Response to Letter Regarding Article, "Comparison of Transplacental Treatment of Fetal Supraventricular Tachyarrhythmias With Digoxin, Flecainide, and Sotalol: Results of a Nonrandomized Multicenter Study"

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Medicine-Based Evidence in Congenital Heart Disease: How Artificial Intelligence Can Guide Treatment Decisions for Individual Patients

Built on the foundation of the randomized controlled trial (RCT), Evidence Based Medicine (EBM) is at its best when optimizing outcomes for homogeneous cohorts of patients like those participating in an RCT. Its weakness is a failure to resolve a clinical quandary: patients appear for care individually, each may differ in important ways from an RCT cohort, and the physician will wonder each time if following EBM will provide best guidance for this unique patient. In an effort to overcome this weakness, and promote higher quality care through a more personalized approach, a new framework has been proposed: Medicine-Based Evidence (MBE). In this approach, big data and deep learning techniques are embraced to interrogate treatment responses among patients in real-world clinical practice. Such statistical models are then integrated with mechanistic disease models to construct a “digital twin,” which serves as the real-time digital counterpart of a patient. MBE is thereby capable of dynamically modeling the effects of various treatment decisions in the context of an individual's specific characteristics. In this article, we discuss how MBE could benefit patients with congenital heart disease, a field where RCTs are difficult to conduct and often fail to provide definitive solutions because of a small number of subjects, their clinical complexity, and heterogeneity. We will also highlight the challenges that must be addressed before MBE can be embraced in clinical practice and its full potential can be realized

Comparison of Transplacental Treatment of Fetal Supraventricular Tachyarrhythmias With Digoxin, Flecainide, and Sotalol Results of a Nonrandomized Multicenter Study

Fetal tachyarrhythmia may result in low cardiac output and death. Consequently, antiarrhythmic treatment is offered in most affected pregnancies. We compared 3 drugs commonly used to control supraventricular tachycardia (SVT) and atrial flutter (AF). We reviewed 159 consecutive referrals with fetal SVT (n=114) and AF (n=45). Of these, 75 fetuses with SVT and 36 with AF were treated nonrandomly with transplacental flecainide (n=35), sotalol (n=52), or digoxin (n=24) as a first-line agent. Prenatal treatment failure was associated with an incessant versus intermittent arrhythmia pattern (n=85; hazard ratio [HR]=3.1; P <0.001) and, for SVT, with fetal hydrops (n=28; HR=1.8; P=0.04). Atrial flutter had a lower rate of conversion to sinus rhythm before delivery than SVT (HR=2.0; P=0.005). Cardioversion at 5 and 10 days occurred in 50% and 63% of treated SVT cases, respectively, but in only 25% and 41% of treated AF cases. Sotalol was associated with higher rates of prenatal AF termination than digoxin (HR=5.4; P=0.05) or flecainide (HR=7.4; P=0.03). If incessant AF/SVT persisted to day 5 (n=45), median ventricular rates declined more with flecainide (-22%) and digoxin (-13%) than with sotalol (-5%; P <0.001). Flecainide (HR=2.1; P=0.02) and digoxin (HR=2.9; P=0.01) were also associated with a higher rate of conversion of fetal SVT to a normal rhythm over time. No serious drug-related adverse events were observed, but arrhythmia-related mortality was 5%. Flecainide and digoxin were superior to sotalol in converting SVT to a normal rhythm and in slowing both AF and SVT to better-tolerated ventricular rates and therefore might be considered first to treat significant fetal tachyarrhythmi

Machine Learning Identifies Clinical and Genetic Factors Associated With Anthracycline Cardiotoxicity in Pediatric Cancer Survivors

BACKGROUND Despite known clinical risk factors, predicting anthracycline cardiotoxicity remains challenging. OBJECTIVES This study sought to develop a clinical and genetic risk prediction model for anthracycline cardiotoxicity in childhood cancer survivors. METHODS We performed exome sequencing in 289 childhood cancer survivors at least 3 years from anthracycline exposure. In a nested case-control design, 183 case patients with reduced left ventricular ejection fraction despite low-dose doxorubicin (\u3c= 250 mg/m(2)), and 106 control patients with preserved left ventricular ejection fraction despite doxorubicin \u3e250 mg/m(2) were selected as extreme phenotypes. Rare/low-frequency variants were collapsed to identify genes differentially enriched for variants between case patients and control patients. The expression levels of 5 top-ranked genes were evaluated in human induced pluripotent stem cell-derived cardiomyocytes, and variant enrichment was confirmed in a replication cohort. Using random forest, a risk prediction model that included genetic and clinical predictors was developed. RESULTS Thirty-one genes were differentially enriched for variants between case patients and control patients (p \u3c 0.001). Only 42.6% case patients harbored a variant in these genes compared to 89.6% control patients (odds ratio: 0.09; 95% confidence interval: 0.04 to 0.17; p = 3.98 x 10(-15)). A risk prediction model for cardiotoxicity that included clinical and genetic factors had a higher prediction accuracy and lower misclassification rate compared to the clinical-only model. In vitro inhibition of gene-associated pathways (PI3KR2, ZNF827) provided protection from cardiotoxicity in cardiomyocytes. CONCLUSIONS Our study identified variants in cardiac injury pathway genes that protect against cardiotoxicity and informed the development of a prediction model for delayed anthracycline cardiotoxicity, and it also provided new targets in autophagy genes for the development of cardio-protective drugs

Three Linked Vasculopathic Processes Characterize Kawasaki Disease: A Light and Transmission Electron Microscopic Study

Kawasaki disease is recognized as the most common cause of acquired heart disease in children in the developed world. Clinical, epidemiologic, and pathologic evidence supports an infectious agent, likely entering through the lung. Pathologic studies proposing an acute coronary arteritis followed by healing fail to account for the complex vasculopathy and clinical course.Specimens from 32 autopsies, 8 cardiac transplants, and an excised coronary aneurysm were studied by light (n=41) and transmission electron microscopy (n=7). Three characteristic vasculopathic processes were identified in coronary (CA) and non-coronary arteries: acute self-limited necrotizing arteritis (NA), subacute/chronic (SA/C) vasculitis, and luminal myofibroblastic proliferation (LMP). NA is a synchronous neutrophilic process of the endothelium, beginning and ending within the first two weeks of fever onset, and progressively destroying the wall into the adventitia causing saccular aneurysms, which can thrombose or rupture. SA/C vasculitis is an asynchronous process that can commence within the first two weeks onward, starting in the adventitia/perivascular tissue and variably inflaming/damaging the wall during progression to the lumen. Besides fusiform and saccular aneurysms that can thrombose, SA/C vasculitis likely causes the transition of medial and adventitial smooth muscle cells (SMC) into classic myofibroblasts, which combined with their matrix products and inflammation create progressive stenosing luminal lesions (SA/C-LMP). Remote LMP apparently results from circulating factors. Veins, pulmonary arteries, and aorta can develop subclinical SA/C vasculitis and SA/C-LMP, but not NA. The earliest death (day 10) had both CA SA/C vasculitis and SA/C-LMP, and an "eosinophilic-type" myocarditis.NA is the only self-limiting process of the three, is responsible for the earliest morbidity/mortality, and is consistent with acute viral infection. SA/C vasculitis can begin as early as NA, but can occur/persist for months to years; LMP causes progressive arterial stenosis and thrombosis and is composed of unique SMC-derived pathologic myofibroblasts

Kawasaki syndrome: an intriguing disease with numerous unsolved dilemmas

More than 40 years have passed since Kawasaki syndrome (KS) was first described. Yet KS still remains an enigmatic illness which damages the coronary arteries in a quarter of untreated patients and is the most common cause of childhood-acquired heart disease in developed countries. Many gaps exist in our knowledge of the etiology and pathogenesis of KS, making improvements in therapy difficult. In addition, many KS features and issues still demand further efforts to achieve a much better understanding of the disease. Some of these problem areas include coronary artery injuries in children not fulfilling the classic diagnostic criteria, genetic predisposition to KS, unpredictable ineffectiveness of current therapy in some cases, vascular dysfunction in patients not showing echocardiographic evidence of coronary artery abnormalities in the acute phase of KS, and risk of potential premature atherosclerosis. Also, the lack of specific laboratory tests for early identification of the atypical and incomplete cases, especially in infants, is one of the main obstacles to beginning treatment early and thereby decreasing the incidence of cardiovascular involvement. Transthoracic echocardiography remains the gold-standard for evaluation of coronary arteries in the acute phase and follow-up. In KS patients with severe vascular complications, more costly and potentially invasive investigations such as coronary CT angiography and MRI may be necessary. As children with KS with or without heart involvement become adolescents and adults, the recognition and treatment of the potential long term sequelae become crucial, requiring that rheumatologists, infectious disease specialists, and cardiologists cooperate to develop specific guidelines for a proper evaluation and management of these patients. More education is needed for physicians and other professionals about how to recognize the long-term impact of systemic problems related to KS

Patient-reported quality of life outcomes for children with serious congenital heart defects

Objective To compare patient-reported, health-related quality of life (QoL) for children with serious congenital heart defects (CHDs) and unaffected classmates and to investigate the demographic and clinical factors influencing QoL. Design Retrospective cohort study. Setting UK National Health Service. Patients UK-wide cohort of children with serious CHDs aged 10–14 years requiring cardiac intervention in the first year of life in one of 17 UK paediatric cardiac surgical centres operating during 1992–1995. A comparison group of classmates of similar age and sex was recruited. Main outcome measures Child self-report of healthrelated QoL scores (Pediatric Quality of Life Inventory, PedsQL) and parental report of schooling and social activities. Results Questionnaires were completed by 477 children with CHDs (56% boys; mean age 12.1 (SD 1.0) years) and 464 classmates (55%; 12.0 (SD 1.1) years). Children with CHDs rated QoL significantly lower than classmates (CHDs: median 78.3 (IQR 65.0–88.6); classmates: 88.0 (80.2–94.6)) and scored lower on physical (CHDs: 84.4; classmates: 93.8; difference 9.4 (7.8 to 10.9)) and psychosocial functioning subscales (CHDs: 76.7, classmates: 85.0; difference 8.3 (6.0 to 10.6)). Cardiac interventions, school absence, regular medications and non-cardiac comorbidities were independently associated with reduced QoL. Participation in sport positively influenced QoL and was associated with higher psychosocial functioning scores. Conclusions Children with serious CHDs experience lower QoL than unaffected classmates. This appears related to the burden of clinical intervention rather than underlying cardiac diagnosis. Participation in sports activities is positively associated with increased emotional well-being. Child self-report measures of QoL would be a valuable addition to clinical outcome audit in this age group.RLK was awarded an MRC Special Training Fellowship in Health of the Public and Health Services Research (reference G106/1083). TD was supported by an NIHR Academic Clinical Fellowship. This work was supported by a British Heart Foundation project grant (reference PG/02/065/13934). The Centre for Paediatric Epidemiology and Biostatistics benefits from funding support from the Medical Research Council in its capacity as the MRC Centre of Epidemiology for Child Health (reference G04005546). Great Ormond St Hospital for Children NHS Trust and the UCL Institute of Child Health receives a proportion of funding from the Department of Health’s NIHR Biomedical Research Centres schem