A Step Forward in Solving Amyloidosis

Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review

PURPOSE OF REVIEW

Artificial intelligence (AI) is transforming electrocardiography (ECG) interpretation. AI diagnostics can reach beyond human capabilities, facilitate automated access to nuanced ECG interpretation, and expand the scope of cardiovascular screening in the population. AI can be applied to the standard 12-lead resting ECG and single-lead ECGs in external monitors, implantable devices, and direct-to-consumer smart devices. We summarize the current state of the literature on AI-ECG.

RECENT FINDINGS

Rhythm classification was the first application of AI-ECG. Subsequently, AI-ECG models have been developed for screening structural heart disease including hypertrophic cardiomyopathy, cardiac amyloidosis, aortic stenosis, pulmonary hypertension, and left ventricular systolic dysfunction. Further, AI models can predict future events like development of systolic heart failure and atrial fibrillation. AI-ECG exhibits potential in acute cardiac events and non-cardiac applications, including acute pulmonary embolism, electrolyte abnormalities, monitoring drugs therapy, sleep apnea, and predicting all-cause mortality. Many AI models in the domain of cardiac monitors and smart watches have received Food and Drug Administration (FDA) clearance for rhythm classification, while others for identification of cardiac amyloidosis, pulmonary hypertension and left ventricular dysfunction have received breakthrough device designation. As AI-ECG models continue to be developed, in addition to regulatory oversight and monetization challenges, thoughtful clinical implementation to streamline workflows, avoiding information overload and overwhelming of healthcare systems with false positive results is necessary. Research to demonstrate and validate improvement in healthcare efficiency and improved patient outcomes would be required before widespread adoption of any AI-ECG model.

Vutrisiran: a new drug in the treatment landscape of hereditary transthyretin amyloid polyneuropathy

INTRODUCTION

Hereditary transthyretin (ATTRv) amyloidosis is a progressive, fatal disorder caused by mutations in the transthyretin (TTR) gene leading to deposition of the misfolded protein in amyloid fibrils. The main phenotypes are peripheral neuropathy (PN) and cardiomyopathy (CM).

AREAS COVERED

Gene silencing therapy, by dramatically reducing liver production of TTR, has transformed ATTRv-PN patient care in the last decade. In this drug discovery case history, the authors discuss the treatment history of ATTRv-PN and focus on the latest siRNA therapy: vutrisiran. Vutrisiran is chemically enhanced and N-acetylgalactosamin-conjugated, allowing increased stability and specific liver delivery. HELIOS-A, a phase III, multicenter randomized study, tested vutrisiran in ATTRv-PN and showed significant improvement in neuropathy impairment, disability, quality of life (QoL), gait speed, and nutritional status. Tolerance was acceptable, no safety signals were raised.

EXPERT OPINION

Vutrisiran offers a new treatment option for patients with ATTRv-PN. Vutrisian's easier delivery and administration route, at a quarterly frequency, as well as the absence of premedication, are major improvements to reduce patients' disease burden and improve their QoL. Its place in the therapeutic strategy is to be determined, considering affordability.