High Prevalence of Cardiac Amyloidosis in Clinically Significant Aortic Stenosis: A Meta-Analysis

Using electronic medical records to identify patients at risk for underlying cardiac amyloidosis

BACKGROUND

Identification of transthyretin cardiac amyloidosis (ATTR-CA) patients is largely based on pattern recognition by providers, and this can be automated through electronic medical systems (EMR).

METHODS

All patients in a large academic hospital with age > 60, ICD-10 code for chronic diastolic heart failure and no previous diagnosis of any amyloidosis were included. An Epic EMR scoring logic assigned risk scores to patients for ICD-10 and CPT codes associated with ATTR-CA, as follows: carpal tunnel syndrome (score 5), aortic stenosis/TAVR (5), neuropathy (4), bundle branch block (4), etc. The individual patients' scores were added, and patients were arranged in descending order of total scores- ranging from 50 to 0. Data is reported as median (interquartile range) and analyzed with non-parametric tests.

RESULTS

Of the total 11,648 patients identified, 132 consecutive patients with highest risk scores (score ≥ 30) were enrolled as cases, while 132 patients with scores between 10 and 19 with available echocardiography data served as age-matched controls. Strain echocardiography is not routinely performed. Patients with high scores were more likely to have CA associated findings- African-American race, higher left ventricular (LV) mass index and left atrial volume and lower LV ejection fraction. High score patients had higher troponin and a trend towards high NT-proBNP.

CONCLUSION

The modern EMR can be used to flag patients with high risk for ATTR-CA (score ≥ 30 using the proposed logic) through best practice advisory. This could encourage screening during echocardiography using strain or during unsuspected clinic visits.

The prognostic value of artificial intelligence to predict cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

Aims

Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients.

Methods and results

In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01-1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01-1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13-2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction.

Conclusion

Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Cardiac Amyloidosis and Valvular Heart Disease

Growing interest has accrued in the co-existence of cardiac amyloidosis and valvular heart disease. Amyloid infiltration from either transthyretin (ATTR) or of light chain (AL) origin may affect any structure of the heart, including the valves. The recent literature has mainly focused on aortic stenosis and cardiac amyloidosis, improving our understanding of the epidemiology, diagnosis, treatment and prognosis of this dual pathology. Despite being of high clinical relevance, data on mitral/tricuspid regurgitation and cardiac amyloidosis are rather scarce and mostly limited to case reports and small cases series. It is the aim of this review article to summarize the current evidence of concomitant valvular heart disease and cardiac amyloidosis by including studies on epidemiology, diagnostic approaches, screening possibilities, therapeutic management, and prognostic implications.

Cardiac amyloidosis and aortic stenosis: a state-of-the-art review

Cardiac amyloidosis is caused by the extracellular deposition of amyloid fibrils in the heart, involving not only the myocardium but also any cardiovascular structure. Indeed, this progressive infiltrative disease also involves the cardiac valves and, specifically, shows a high prevalence with aortic stenosis. Misfolded protein infiltration in the aortic valve leads to tissue damage resulting in the onset or worsening of valve stenosis. Transthyretin cardiac amyloidosis and aortic stenosis coexist in patients > 65 years in about 4-16% of cases, especially in those undergoing transcatheter aortic valve replacement. Diagnostic workup for cardiac amyloidosis in patients with aortic stenosis is based on a multi-parametric approach considering clinical assessment, electrocardiogram, haematologic tests, basic and advanced echocardiography, cardiac magnetic resonance, and technetium labelled cardiac scintigraphy like technetium-99 m (99mTc)-pyrophosphate, 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, and 99mTc-hydroxymethylene diphosphonate. However, a biopsy is the traditional gold standard for diagnosis. The prognosis of patients with coexisting cardiac amyloidosis and aortic stenosis is still under evaluation. The combination of these two pathologies worsens the prognosis. Regarding treatment, mortality is reduced in patients with cardiac amyloidosis and severe aortic stenosis after undergoing transcatheter aortic valve replacement. Further studies are needed to confirm these findings and to understand whether the diagnosis of cardiac amyloidosis could affect therapeutic strategies. The aim of this review is to critically expose the current state-of-art regarding the association of cardiac amyloidosis with aortic stenosis, from pathophysiology to treatment.