Daily Cardiology Research Analysis
AI-enabled cardiology made major strides: an AI model using single-view point-of-care ultrasound accurately screened for hypertrophic and amyloid cardiomyopathies years before diagnosis, while a machine-learning model predicted 1-year stroke/death after TCAR with excellent discrimination. Translationally, inhibiting ACLY with bempedoic acid prevented abdominal aortic aneurysm formation in mice, suggesting a repurposable pathway for a disease lacking medical therapy.
Summary
AI-enabled cardiology made major strides: an AI model using single-view point-of-care ultrasound accurately screened for hypertrophic and amyloid cardiomyopathies years before diagnosis, while a machine-learning model predicted 1-year stroke/death after TCAR with excellent discrimination. Translationally, inhibiting ACLY with bempedoic acid prevented abdominal aortic aneurysm formation in mice, suggesting a repurposable pathway for a disease lacking medical therapy.
Research Themes
- AI-enabled cardiac screening and prognostication
- Peri-procedural risk stratification using machine learning
- Drug repurposing targeting inflammatory-metabolic pathways in vascular disease
Selected Articles
1. Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study.
A video-based, single-view-capable AI model applied to cardiac POCUS discriminated hypertrophic cardiomyopathy and transthyretin amyloid cardiomyopathy with AUCs ~0.90–0.97 across two health systems and flagged cases a median of ~2 years before clinical diagnosis. In patients without known cardiomyopathy, higher AI scores independently predicted mortality over a median 2.8 years, supporting opportunistic screening with simple POCUS acquisitions.
Impact: This work operationalizes scalable AI screening for underdiagnosed cardiomyopathies using real-world POCUS, potentially enabling earlier detection and risk stratification without comprehensive echocardiography.
Clinical Implications: Emergency and community settings could deploy AI-assisted POCUS to triage patients for confirmatory imaging, genetics or biopsy, initiate earlier disease-modifying therapy (e.g., ATTR therapies), and identify high-risk individuals for closer follow-up.
Key Findings
- Single-view AI on POCUS discriminated HCM and ATTR cardiomyopathy with AUCs ~0.90–0.97 across independent health systems.
- AI-positive screens preceded clinical diagnosis by a median 2.1 years (HCM) and 1.9 years (ATTR).
- Among 25,261 individuals without known cardiomyopathy, top-quintile AI scores for HCM and ATTR associated with higher adjusted mortality (HR 1.17 and 1.39, respectively).
- Model used a multi-label video CNN with view-quality–weighted loss to adapt to POCUS variability.
Methodological Strengths
- Very large development corpus (290,245 echo videos) with external validation across systems
- Customized loss and single-view protocol validated for real-world POCUS variability
Limitations
- Retrospective design with potential selection bias and lack of prospective clinical impact trial
- Generalizability beyond two US health systems and to handheld devices requires testing
Future Directions: Prospective implementation trials to test clinical pathways, confirm diagnostic yield, outcomes impact, equity/fairness, and cost-effectiveness across diverse care settings.
2. Using machine learning to predict outcomes following transcarotid artery revascularization.
Across 38,325 TCAR procedures, an XGBoost model using 115 perioperative features predicted 1-year stroke/death with AUROC 0.91 pre-operatively and up to 0.94 post-operatively, outperforming logistic regression by a wide margin. The tool supports perioperative risk mitigation and individualized decision-making for a high-risk vascular population.
Impact: Delivers a validated, high-discrimination ML risk model at scale in a real-world registry for a technically demanding procedure where outcome prediction tools are scarce.
Clinical Implications: Preoperative and intra/postoperative ML scores could guide selection, optimization, resource allocation (ICU monitoring, neuroprotection), and counseling; integration into vascular workflow may reduce adverse events.
Key Findings
- In 38,325 TCAR cases, 7.0% had 1-year stroke or death; XGBoost predicted this with AUROC 0.91 using preoperative data.
- Performance improved with intra- and postoperative features (AUROCs 0.92 and 0.94), substantially outperforming logistic regression (AUROC 0.68).
- Model trained with tenfold cross-validation using 115 features spanning pre-, intra-, and postoperative phases.
Methodological Strengths
- Very large national registry with comprehensive perioperative features
- Systematic comparison to conventional modeling and staged (pre/intra/post) evaluation
Limitations
- Retrospective registry design without external validation beyond VQI; risk of dataset shift
- Model interpretability and clinical impact not prospectively tested
Future Directions: Prospective external validation, integration into clinical workflows with impact evaluation, calibration drift monitoring, and explainability to support clinician adoption.
3. Inhibition of ATP-citrate lyase by bempedoic acid protects against abdominal aortic aneurysm formation in mice.
Active ACLY was upregulated in human AAA inflammatory infiltrates and in AngII-induced aneurysms in ApoE−/− mice. Pharmacologic inhibition of ACLY with the clinically available agent bempedoic acid protected against AAA formation in mice, implicating immunometabolic ACLY signaling as a therapeutic target for a disease currently lacking medical therapy.
Impact: Suggests a repurposable, clinically available ACLY inhibitor to prevent or slow AAA, a high-burden condition without proven medical therapy.
Clinical Implications: If translated, bempedoic acid or ACLY pathway modulation could offer a pharmacologic option to reduce AAA growth or incidence, complementing surveillance and surgical/endovascular repair.
Key Findings
- Active (phosphorylated) ACLY is increased in human AAA inflammatory infiltrates and in aneurysmal lesions of AngII-infused ApoE−/− mice.
- Bempedoic acid, an ACLY inhibitor, protected mice against AAA formation, reducing inflammatory-destructive vascular remodeling.
- Findings link immunometabolic ACLY signaling in myeloid/lymphoid cells to aneurysm biology, supporting drug repurposing.
Methodological Strengths
- Human tissue corroboration alongside an established murine aneurysm model
- Target engagement of a clinically used metabolic enzyme (ACLY)
Limitations
- Preclinical mouse data; clinical dosing, safety, and efficacy for AAA remain unknown
- Potential confounding lipid effects of bempedoic acid not fully disentangled from anti-inflammatory actions
Future Directions: Dose-finding, biomarker-guided early-phase clinical trials in small AAA; mechanistic studies dissecting myeloid vs lymphoid ACLY contributions and lipid-independent effects.