Comparative prognostic importance of measures of left atrial structure and function in non-ischaemic dilated cardiomyopathy.

AIMS: To compare the association between measures of left atrial (LA) structure and function, derived from cardiovascular magnetic resonance (CMR), with cardiovascular (CV) death or non-fatal heart failure (HF) events in patients with non-ischaemic dilated cardiomyopathy (DCM). METHODS AND RESULTS: CMR studies of 580 prospectively recruited patients with DCM in sinus rhythm (median age 54 [interquartile range 44-64] years, 61% men, median LVEF 42% [30-51%]) were analysed for measures of LA structure (left atrial maximum volume index [LAVImax], left atrial minimum volume index [LAVImin]) and function (left atrial emptying fraction [LAEF], left atrial reservoir strain [LARS], left atrial conduit strain [LACS] and left atrial booster strain [LABS]). Over median follow-up of 7.4 years, 103 patients (18%) met the primary endpoint. Apart from LACS, each measure of LA structure and function was associated with the primary endpoint after adjusting for other important prognostic variables. The addition of each LA metric to a baseline model containing the same important prognostic covariates improved model discrimination, with LAVImin providing the greatest improvement (C-statistic improvement: 0.702 to 0.738; χ2 test comparing likelihood ratio p < 0.0001; categorical net reclassification index: 0.210 (95% CI 0.023-0.392)). Patients in the highest tercile of LAVImin had similar event rates to those with persistent atrial fibrillation. Measures of LA strain did not enhance model discrimination above LA volumetric measures. CONCLUSION: Measure of left atrial structure and function offer important prognostic information in patients with DCM and enhance prediction of adverse outcomes. LA strain was not incremental to volumetric analysis for risk prediction.

Assessing the association between genetic and phenotypic features of dilated cardiomyopathy and outcome in patients with coronary artery disease.

AIMS: To examine the relevance of genetic and cardiovascular magnetic resonance (CMR) features of dilated cardiomyopathy (DCM) in individuals with coronary artery disease (CAD). METHODS AND RESULTS: This study includes two cohorts. First, individuals with CAD recruited into the UK Biobank (UKB) were evaluated. Second, patients with CAD referred to a tertiary centre for evaluation with late gadolinium enhancement (LGE)-CMR were recruited (London cohort); patients underwent genetic sequencing as part of the research protocol and long-term follow-up. From 31 154 individuals with CAD recruited to UKB, rare pathogenic variants in DCM genes were associated with increased risk of death or major adverse cardiac events (hazard ratio 1.57, 95% confidence interval [CI] 1.22-2.01, p < 0.001). Of 1619 individuals with CAD included from the UKB CMR substudy, participants with a rare variant in a DCM-associated gene had lower left ventricular ejection fraction (LVEF) compared to genotype negative individuals (mean 47 ± 10% vs. 57 ± 8%, p < 0.001). Of 453 patients in the London cohort, 63 (14%) had non-infarct pattern LGE (NI-LGE) on CMR. Patients with NI-LGE had lower LVEF (mean 38 ± 18% vs. 48 ± 16%, p < 0.001) compared to patients without NI-LGE, with no significant difference in the burden of rare protein altering variants in DCM-associated genes between groups (9.5% vs. 6.7%, odds ratio 1.5, 95% CI 0.4-4.3, p = 0.4). NI-LGE was not independently associated with adverse clinical outcomes. CONCLUSION: Rare pathogenic variants in DCM-associated genes impact left ventricular remodelling and outcomes in stable CAD. NI-LGE is associated with adverse remodelling but is not an independent predictor of outcome and had no rare genetic basis in our study.

Precision prediction of heart failure events in patients with dilated cardiomyopathy and mildly reduced ejection fraction using multi-parametric cardiovascular magnetic resonance.

AIMS: To assess whether left ventricular (LV) global longitudinal strain (GLS), derived from cardiovascular magnetic resonance (CMR), is associated with (i) progressive heart failure (HF), and (ii) sudden cardiac death (SCD) in patients with dilated cardiomyopathy with mildly reduced ejection fraction (DCMmrEF). METHODS AND RESULTS: We conducted a prospective observational cohort study of patients with DCM and LV ejection fraction (LVEF) ≥40% assessed by CMR, including feature-tracking to assess LV GLS and late gadolinium enhancement (LGE). Long-term adjudicated follow-up included (i) HF hospitalization, LV assist device implantation or HF death, and (ii) SCD or aborted SCD (aSCD). Of 355 patients with DCMmrEF (median age 54 years [interquartile range 43-64], 216 men [60.8%], median LVEF 49% [46-54]) followed up for a median 7.8 years (5.2-9.4), 32 patients (9%) experienced HF events and 19 (5%) died suddenly or experienced aSCD. LV GLS was associated with HF events in a multivariable model when considered as either a continuous (per % hazard ratio [HR] 1.10, 95% confidence interval [CI] 1.00-1.21, p = 0.045) or dichotomized variable (LV GLS > -15.4%: HR 2.70, 95% CI 1.30-5.94, p = 0.008). LGE presence was not associated with HF events (HR 1.49, 95% CI 0.73-3.01, p = 0.270). Conversely, LV GLS was not associated with SCD/aSCD (per % HR 1.07, 95% CI 0.95-1.22, p = 0.257), whereas LGE presence was (HR 3.58, 95% CI 1.39-9.23, p = 0.008). LVEF was neither associated with HF events nor SCD/aSCD. CONCLUSION: Multi-parametric CMR has utility for precision prognostic stratification of patients with DCMmrEF. LV GLS stratifies risk of progressive HF, while LGE stratifies SCD risk.

Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes, but there is no systematic framework for classifying morphology or assessing associated risks. Here, we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression. METHODS: We enrolled 436 patients with HCM (median age, 60 years; 28.8% women) with clinical, genetic, and imaging data. An independent cohort of 60 patients with HCM from Singapore (median age, 59 years; 11% women) and a reference population from the UK Biobank (n=16 691; mean age, 55 years; 52.5% women) were also recruited. We used machine learning to analyze the 3-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree. RESULTS: Carriers of pathogenic or likely pathogenic variants for HCM had lower left ventricular mass, but greater basal septal hypertrophy, with reduced life span (mean follow-up, 9.9 years) compared with genotype negative individuals (hazard ratio, 2.66 [95% CI, 1.42-4.96]; P<0.002). Four main phenotypic branches were identified using unsupervised learning of 3-dimensional shape: (1) nonsarcomeric hypertrophy with coexisting hypertension; (2) diffuse and basal asymmetrical hypertrophy associated with outflow tract obstruction; (3) isolated basal hypertrophy; and (4) milder nonobstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for pathogenic or likely pathogenic variants, 2.18 [95% CI, 1.93-2.28]; P=0.0001). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalizable to an independent cohort (trustworthiness, M1: 0.86-0.88). CONCLUSIONS: We report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk, and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.

Clinical Correlates and Outcomes of Methamphetamine-Associated Cardiovascular Diseases in Hospitalized Patients in California.

Background Methamphetamine misuse affects 27 million people worldwide and is associated with cardiovascular disease (CVD); however, risk factors for CVD among users have not been well studied. Methods and Results We studied hospitalized patients in California, captured by the Healthcare Cost and Utilization Project database, between 2005 and 2011. We studied the association between methamphetamine use and CVD (pulmonary hypertension, heart failure, stroke, and myocardial infarction). Among 20 249 026 persons in the Healthcare Cost and Utilization Project, 66 199 used methamphetamines (median follow-up 4.58 years). Those who used were more likely younger (33 years versus 45 years), male (63.3% versus 44.4%), smoked, misused alcohol, and had depression and anxiety compared with nonusers. Methamphetamine use was associated with the development of heart failure (hazard ratio [HR], 1.53 [95% CI, 1.45-1.62]) and pulmonary hypertension (HR, 1.42 [95% CI, 1.26-1.60]). Among users, male sex (HR, 1.73 [95% CI, 1.37-2.18]) was associated with myocardial infarction. Chronic kidney disease (HR, 2.38 [95% CI, 1.74-3.25]) and hypertension (HR, 2.26 [95% CI, 2.03-2.51]) were strong risk factors for CVD among users. When compared with nonuse, methamphetamine use was associated with a 32% significant increase in CVD, alcohol abuse with a 28% increase, and cocaine use with a 47% increase in CVD. Conclusions Methamphetamine use has a similar magnitude of risk of CVD compared with alcohol and cocaine. Prevention and treatment could be focused on those with chronic kidney disease, hypertension, and mental health disorders.

An ensemble of neural networks provides expert-level prenatal detection of complex congenital heart disease.

Congenital heart disease (CHD) is the most common birth defect. Fetal screening ultrasound provides five views of the heart that together can detect 90% of complex CHD, but in practice, sensitivity is as low as 30%. Here, using 107,823 images from 1,326 retrospective echocardiograms and screening ultrasounds from 18- to 24-week fetuses, we trained an ensemble of neural networks to identify recommended cardiac views and distinguish between normal hearts and complex CHD. We also used segmentation models to calculate standard fetal cardiothoracic measurements. In an internal test set of 4,108 fetal surveys (0.9% CHD, >4.4 million images), the model achieved an area under the curve (AUC) of 0.99, 95% sensitivity (95% confidence interval (CI), 84-99%), 96% specificity (95% CI, 95-97%) and 100% negative predictive value in distinguishing normal from abnormal hearts. Model sensitivity was comparable to that of clinicians and remained robust on outside-hospital and lower-quality images. The model's decisions were based on clinically relevant features. Cardiac measurements correlated with reported measures for normal and abnormal hearts. Applied to guideline-recommended imaging, ensemble learning models could significantly improve detection of fetal CHD, a critical and global diagnostic challenge.

Computed tomography guided sizing for transcatheter pulmonary valve replacement.

OBJECTIVE: To evaluate the predictive value of Computed Tomography Angiography (CTA) measurements of the RVOT for transcatheter valve sizing. BACKGROUND: Transcatheter pulmonary valve replacement (TPVR) provides an alternative to surgery in patients with right ventricular outflow tract (RVOT) dysfunction. We studied 18 patients who underwent catheterization for potential TPVR to determine whether CT imaging can be used to accurately predict implant size. METHODS: Cases were grouped by RVOT characteristics: native or transannular patch (n = 8), conduit (n = 5) or bioprosthetic valve (n = 5). TPVR was undertaken in 14/18 cases, after balloon-sizing was used to confirm suitability and select implant size. Retrospective CT measurements of the RVOT (circumference-derived (Dcirc) and area-derived (Darea) diameters) were obtained at the level of the annulus, bioprosthesis or conduit. Using manufacturer sizing guidance, a valve size was generated and a predicted valve category assigned: (1) <18 mm, (2) 18-20 mm, (3) 22-23 mm, (4) 26-29 mm and (5) >29 mm. Predicted and implanted valves were compared for inter-rater agreement using Cohen's kappa coefficient. RESULTS: The median age of patients was 37 years old (IQR: 30-49); 55% were male. Diagnoses included: Tetralogy of Fallot (12/18), d-Transposition repair (3/18), congenital pulmonary stenosis (2/18) and carcinoid heart disease (1/18). Measurements of Darea (κ = 0.697, p < 0.01) and Dcirc (κ = 0.540, p < 0.01) were good predictors of implanted valve size. When patients with RVOT conduits were excluded, the predictive accuracy improved for Darea (κ = 0.882, p < 0.01) and Dcirc (κ = 0.882, p < 0.01). CONCLUSIONS: CT measurement of the RVOT, using Darea or Dcirc, can predict prosthetic valve sizing in TPVR. These measurements are less predictive in patients with conduits, compared to those with a native RVOT or pulmonic bioprosthesis. CONDENSED ABSTRACT: We studied 18 patients who underwent catheterization for TPVR to determine whether CT imaging could be used to accurately predict implant size. Retrospective RVOT measurements were used to generate a predicted valve size, which was compared with implanted valve size for inter-rater agreement. Measurements of Darea (κ = 0.697, p < 0.01) and Dcirc (κ = 0.540, p < 0.01) were good predictors of implanted valve size. When cases with RVOT conduits were excluded, the predictive accuracy improved for Darea (κ = 0.882, p < 0.01) and Dcirc (κ = 0.882, p < 0.01). CT measurement of the RVOT can accurately predict prosthetic valve sizing in TPVR. These measurements are less predictive in patients with conduits.

Visual Loss Post Ross Procedure in an Adolescent With Newly Diagnosed Mucopolysaccharidosis Type II.

Perioperative visual loss is a rare but serious complication after cardiac surgery. The etiology is not fully understood, and there is no consensus on the optimal management of this condition. A 15-year-old male patient developed severe visual impairment attributed to nonarteritic anterior ischemic optic neuropathy after a Ross aortic root replacement procedure. A new diagnosis of the lysosomal storage disorder, mucopolysaccharidosis type II (Hunter syndrome), was subsequently made, raising questions about the pathogenesis of this devastating postoperative complication.