What will we ask to artificial intelligence for cardiovascular medicine in the next decade?

Transthyretin cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement: experience of a single center

BACKGROUND

Even if prevalent among patients with severe aortic stenosis (AS), the clinical suspicion for transthyretin cardiac amyloidosis (ATTR-CA) remains difficult in this subset. We report our single center experience on ATTR-CA detection among TAVR candidates to provide insights on the prevalence and clinical features of dual pathology as compared to lone AS.

METHODS

Consecutive severe AS patients undergoing transcatheter aortic valve replacement (TAVR) evaluation at a single center were prospectively included. Those with suspected ATTR-CA based on clinical assessment underwent 99m Tc-3,3-diphosphono-1,2-propanodicarboxylic acid (DPD) bone scintigraphy. The RAISE score, a novel screening tool with high sensitivity for ATTR-CA in AS, was retrospectively calculated to rule-out ATTR-CA in the remaining patients. Patients were categorized as follow: "ATTR-CA+": patients with confirmed ATTR-CA at DPD bone scintigraphy; "ATTR-CA-": patients with negative DPD bone scintigraphy or a negative RAISE score; "ATTR-CA indeterminate": patients not undergoing ATTR-CA assessment with a positive RAISE score. The characteristics of ATTR-CA+ and ATTR-CA- patients were compared.

RESULTS

Of 107 included patients, ATTR-CA suspicion was posed in 13 patients and confirmed in six. Patients were categorized as follow: 6 (5.6%) ATTR-CA+, 79 (73.8%) ATTR-CA-, 22 (20.6%) ATTR-CA indeterminate. Excluding ATTR-CA indeterminate patients, the prevalence of ATTR-CA was 7.1% (95% CI 2.6-14.7%). As compared to ATTR-CA - patients, ATTR-CA + patients were older, had higher procedural risk and more extensive myocardial and renal damage. They had higher left ventricle mass index and lower ECG voltages, translating into a lower voltage to mass ratio. Moreover, we describe for the first time bifascicular block as an ECG feature highly specific of patients with dual pathology (50.0% vs. 2.7%, P<0.001). Of note, pericardial effusion was rarely found in patients with lone AS (16.7% vs. 1.2%, P=0.027). No difference in procedural outcomes was observed between groups.

CONCLUSIONS

Among severe AS patients, ATTR-CA is prevalent and presents with phenotypic features that may aid to differentiate it from lone AS. A clinical approach based on routine search of amyloidosis features might lead to selective DPD bone scintigraphy with a satisfactory positive predictive value.

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review

Cardiac diseases form the lion's share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced "omics". These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the "omics", involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.

Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms

Stratifying prognosis following coronary bifurcation percutaneous coronary intervention (PCI) is an unmet clinical need that may be fulfilled through the adoption of machine learning (ML) algorithms to refine outcome predictions. We sought to develop an ML-based risk stratification model built on clinical, anatomical, and procedural features to predict all-cause mortality following contemporary bifurcation PCI. Multiple ML models to predict all-cause mortality were tested on a cohort of 2393 patients (training, n = 1795; internal validation, n = 598) undergoing bifurcation PCI with contemporary stents from the real-world RAIN registry. Twenty-five commonly available patient-/lesion-related features were selected to train ML models. The best model was validated in an external cohort of 1701 patients undergoing bifurcation PCI from the DUTCH PEERS and BIO-RESORT trial cohorts. At ROC curves, the AUC for the prediction of 2-year mortality was 0.79 (0.74–0.83) in the overall population, 0.74 (0.62–0.85) at internal validation and 0.71 (0.62–0.79) at external validation. Performance at risk ranking analysis, k-center cross-validation, and continual learning confirmed the generalizability of the models, also available as an online interface. The RAIN-ML prediction model represents the first tool combining clinical, anatomical, and procedural features to predict all-cause mortality among patients undergoing contemporary bifurcation PCI with reliable performance.