Desai, Viral

Abstract Background and Aims Accurate differentiation of cardiac amyloidosis (CA) from phenotypic mimics remains challenging using current clinical and echocardiographic techniques. The accuracy of a novel artificial intelligence (AI) screening algorithm for echocardiography-based CA detection was assessed. Methods Utilizing a multisite, multiethnic dataset (n = 2612, 52% CA), a convolutional neural network was trained to differentiate CA from phenotypic controls using transthoracic apical four-chamber video clips. External validation was conducted globally across 18 sites including 597 CA cases and 2122 controls. Classification accuracy was assessed on the entire external validation dataset, and subgroup analyses were performed both on technetium pyrophosphate scintigraphy referrals, and individuals matched for age, sex, and wall thickness. Model accuracy was also compared with the transthyretin CA score and the increased wall thickness score within a subset of older heart failure with preserved ejection fraction patients with increased wall thickness. Results Cardiac amyloidosis patients and controls displayed similar age, sex, race, and comorbidities. After the removal of uncertain AI predictions (13%), model discrimination and classification were excellent for the entire external validation dataset [area under the receiver operating characteristic curve (AUROC) 0.93, sensitivity 85%, specificity 93%], irrespective of CA subtype (sensitivity: light-chain = 84%, wild-type transthyretin = 85%, and hereditary transthyretin = 86%). Performance was maintained in subgroup analysis in patients clinically referred for technetium pyrophosphate scintigraphy imaging (AUROC 0.86, sensitivity 77%, specificity 86%) and matched patients (AUROC 0.92, sensitivity 84%, specificity 91%). The AI model (AUROC 0.93) also outperformed transthyretin CA score (AUROC 0.73) and increased wall thickness (AUROC 0.80) scores. Conclusions This AI screening model—using only an apical four-chamber view—effectively differentiated CA from other causes of increased left ventricular wall thickness.

AbstractDespite significant progress in the care of patients suffering from cardiovascular disease, there remains a persistent sex disparity in the diagnosis, management, and outcomes of these patients. These sex disparities are seen across the spectrum of cardiovascular care, but, are especially pronounced in acute cardiovascular care. The spectrum of acute cardiovascular care encompasses critically ill or tenuous patients with cardiovascular conditions that require urgent or emergent decision-making and interventions. In this narrative review, the disparities in the clinical course, management, and outcomes of six commonly encountered acute cardiovascular conditions, some with a known sex-predilection will be discussed within the basis of underlying sex differences in physiology, anatomy, and pharmacology with the goal of identifying areas where improvement in clinical approaches are needed.

Background: There are limited data on acute myocardial infarction with cardiogenic shock (AMI-CS) stratified by chronic kidney disease (CKD) stages. Objective: To assess clinical outcomes in AMI-CS stratified by CKD stages. Methods: A retrospective cohort of AMI-CS during 2005–2016 from the National Inpatient Sample was categorized as no CKD, CKD stage-III (CKD-III), CKD stage-IV (CKD-IV) and end-stage renal disease (ESRD). CKD-I/II were excluded. Outcomes included in-hospital mortality, use of coronary angiography, percutaneous coronary intervention (PCI) and mechanical circulatory support (MCS). We also evaluated acute kidney injury (AKI) and acute hemodialysis in non-ESRD admissions. Results: Of 372,412 AMI-CS admissions, CKD-III, CKD-IV and ESRD comprised 20,380 (5.5%), 7367 (2.0%) and 18,109 (4.9%), respectively. Admissions with CKD were, on average, older, of the White race, bearing Medicare insurance, of a lower socioeconomic stratum, with higher comorbidities, and higher rates of acute organ failure. Compared to the cohort without CKD, CKD-III, CKD-IV and ESRD had lower use of coronary angiography (72.7%, 67.1%, 56.9%, 61.1%), PCI (53.7%, 43.8%, 38.4%, 37.6%) and MCS (47.9%, 38.3%, 33.3%, 34.2%), respectively (all p < 0.001). AKI and acute hemodialysis use increased with increase in CKD stage (no CKD–38.5%, 2.6%; CKD-III–79.1%, 6.5%; CKD-IV–84.3%, 12.3%; p < 0.001). ESRD (adjusted odds ratio [OR] 1.25 [95% confidence interval {CI} 1.21–1.31]; p < 0.001), but not CKD-III (OR 0.72 [95% CI 0.69–0.75); p < 0.001) or CKD-IV (OR 0.82 [95 CI 0.77–0.87] was predictive of in-hospital mortality. Conclusions: CKD/ESRD is associated with lower use of evidence-based therapies. ESRD was an independent predictor of higher in-hospital mortality in AMI-CS.