Daily Cardiology Research Analysis
Analyzed 50 papers and selected 3 impactful papers.
Summary
Analyzed 50 papers and selected 3 impactful articles.
Selected Articles
1. Efficacy and safety of inclisiran in adolescents with heterozygous familial hypercholesterolaemia (ORION-16): a two-part, randomised, multicentre clinical trial.
In this phase 3, two-part randomized trial across 51 sites, inclisiran reduced LDL cholesterol by 28.5% versus placebo at day 330 in adolescents with HeFH on maximally tolerated background therapy. LDL lowering was sustained to day 720 (~33.7%), with only mild injection site reactions and no treatment-related serious adverse events.
Impact: This is the first randomized evidence of PCSK9-targeting siRNA therapy in adolescents with HeFH, demonstrating clinically meaningful and durable LDL-C reduction with infrequent dosing.
Clinical Implications: Inclisiran may serve as an add-on option for adolescents with HeFH whose LDL-C remains above target despite statins and ezetimibe, offering twice-yearly dosing that could improve adherence.
Key Findings
- Primary endpoint: LS mean LDL-C change at day 330 was −27.1% with inclisiran vs +1.4% with placebo; between-group difference −28.5% (95% CI −35.8 to −21.3; p<0.0001).
- Sustained efficacy in Part 2: mean LDL-C change at day 720 was −33.7% (SD 24.0).
- Safety: injection site reactions were more frequent with inclisiran (16%) than placebo (6%) but were mild; no treatment-related serious adverse events and no deaths.
Methodological Strengths
- Randomized, double-blind, multicenter phase 3 design with global enrollment
- Pre-specified extension assessing durability and safety over 2 years
Limitations
- Surrogate endpoint (LDL-C) without hard cardiovascular outcomes in adolescents
- Modest sample size and predominantly White population may limit generalizability
Future Directions: Prospective pediatric outcomes studies, head-to-head comparisons with monoclonal PCSK9 inhibitors, and adherence/implementation research in real-world adolescent populations.
BACKGROUND: Inclisiran, a small interfering RNA targeting hepatic PCSK9, was previously studied in various adult patient populations, but it has not yet been assessed in paediatric patients with heterozygous familial hypercholesterolaemia (HeFH), a genetic disorder characterised by elevated LDL cholesterol. The ORION-16 study aimed to evaluate the efficacy and safety of inclisiran treatment in adolescents with HeFH. METHODS: ORION-16 was a two-part (1-year double-blind, 1-year open-label), randomised, pha
2. Proton pump inhibitors accelerate vascular calcification via COX-2-mediated mitophagy inhibition in chronic kidney disease.
Integrating clinical, animal, and cellular data, this study identifies a COX-2–mitophagy axis by which PPIs accelerate vascular calcification in CKD. PPIs increased coronary calcium in CKD patients, induced aortic calcification and VSMC osteogenic switching in rats via inhibition of PINK1/Parkin-mediated mitophagy, and these effects were mitigated by rapamycin or COX-2 silencing, suggesting a class effect and a targetable pathway.
Impact: Reveals a novel, targetable COX-2–mitophagy pathway linking a ubiquitous drug class (PPIs) to accelerated vascular calcification in high-risk CKD patients.
Clinical Implications: Clinicians should reassess chronic PPI use in CKD, preferentially use lowest effective doses or alternatives when appropriate, and recognize a potential class effect on vascular calcification. The COX-2–mitophagy axis suggests therapeutic avenues (e.g., mitophagy enhancers) for high-risk patients.
Key Findings
- In CKD patients, PPI use was associated with higher odds of elevated coronary artery calcium scores (adjusted OR 5.365; 95% CI 2.539–11.338; P<0.001).
- In CKD rats, omeprazole dose-dependently induced aortic calcification and VSMC osteogenic phenotype switching with mitochondrial dysfunction.
- PPIs inhibited PINK1/Parkin-mediated mitophagy (reduced TOMM20, LC3B-II, PINK1, Parkin; impaired mitochondrial-lysosomal colocalization; swollen mitochondria on TEM).
- Rapamycin restored mitophagy and mitigated calcification; COX-2 was upregulated by PPIs, and COX-2 silencing reversed mitophagy inhibition and calcification; esomeprazole and lansoprazole reproduced pro-calcific effects.
Methodological Strengths
- Multimodal evidence spanning human clinical association, in vivo CKD models, and mechanistic in vitro assays
- Rescue experiments (rapamycin) and target validation (COX-2 silencing) demonstrating causality and a class effect across PPIs
Limitations
- Human data are observational with potential residual confounding, including indication bias for PPI use
- Translational gaps remain regarding dose, duration, and clinical outcome modulation in humans
Future Directions: Prospective CKD cohorts stratified by PPI exposure with calcification progression endpoints; interventional trials testing mitophagy enhancers or COX-2 modulation; mechanistic dissection in human VSMCs and organoids.
Prolonged use of proton pump inhibitors (PPIs) is associated with increased cardiovascular risks, including vascular calcification (VC). Patients with chronic kidney disease (CKD) are particularly vulnerable to the adverse vascular effects of PPIs. However, the underlying mechanism remains poorly understood. Clinical data from CKD patients treated with PPIs showed a higher incidence of elevated coronary artery calcium scores (adjusted odds ratio=5.365, 95% CI: 2.539-11.338, P<0.001), indicating a
3. Use of Electrocardiograms to Identify Coronary Artery Disease: Cross-Validation of an Artificial Intelligence Model.
Using 16,476 ECG–angiography pairs with 10-fold cross-validation and external validation, a deep-learning model predicted angiographic significant CAD with AUC ~0.92. Performance was robust across datasets with PPV up to 91.7% and NPV up to 88.1%, suggesting utility for noninvasive triage.
Impact: Demonstrates high diagnostic performance of an ECG-based AI model against the angiographic gold standard with external validation, enabling scalable, noninvasive CAD detection.
Clinical Implications: If prospectively validated, AI-ECG could prioritize patients for imaging or angiography, reduce unnecessary testing, and improve access in settings without advanced imaging.
Key Findings
- Cross-validation cohort (n=16,476): AUC 91.4% (95% CI 89.4%-94.4%), PPV 91.7%, NPV 72.8% for predicting significant CAD.
- External validation: AUC 92.4% (95% CI 89.7%-95.1%), PPV 82.5%, NPV 88.1%, despite lower disease prevalence (36%).
- Clinically significant CAD defined as ≥70% stenosis in major epicardials or ≥50% in left main by angiography.
Methodological Strengths
- Large sample with angiographic reference standard and 10-fold cross-validation
- Independent external validation demonstrating generalizability
Limitations
- Retrospective design with potential selection bias and prevalence shift across cohorts
- Lack of prospective utility assessment and unclear performance in primary care or asymptomatic populations
Future Directions: Prospective impact trials comparing AI-ECG–guided pathways vs standard care; calibration across prevalence settings; fairness and subgroup analyses; integration with clinical risk models.
BACKGROUND: The current gold standard for the diagnosis of coronary artery disease (CAD) is invasive angiography; however, it is an invasive procedure. Therefore, we developed an artificial intelligence model designed to predict significant CAD from a resting digital 12-lead electrocardiogram (ECG). OBJECTIVES: This retrospective study assessed the model's ability to predict clinically significant CAD in a patient population presenting for coronary angiography. METHODS: From 2019 to 2021, 16,476 pa