Daily Cardiology Research Analysis

BACKGROUND: The HOST-IDEA trial demonstrated non-inferiority of 3-to-6-month dual antiplatelet therapy (DAPT) to 12-month DAPT for net adverse clinical event (NACE) at 1 year in patients undergoing percutaneous coronary intervention (PCI) with third-generation drug-eluting stents (DES). We evaluated the long-term outcomes of abbreviated antiplatelet therapy following PCI with third-generation DES. METHODS: In the open-label, adjudicator-blinded, multicentre, randomised HOST-IDEA trial, 2013 patients from 37 hospitals in South Korea were randomly allocated to 3-to-6-month (n = 1002) or 12-month (n = 1011) DAPT between January 2016 and May 2021. The primary outcome was NACE at 3 years, comprising cardiac death, target vessel myocardial infarction (TVMI), clinically driven target lesion revascularisation (CD-TLR), stent thrombosis, and major bleeding (Bleeding Academic Research Consortium type 3 or 5). Major secondary outcomes were target lesion failure (TLF)-comprising cardiac death, TVMI, and CD-TLR-and major bleeding at 3 years. To evaluate the efficacy and safety of >1-year DAPT, patients event-free at 1 year were classified into >1-year and ≤1-year DAPT groups and matched using a propensity score. These 3-year clinical outcomes were prespecified in the published protocol as mandatory clinical follow-up. HOST-IDEA is registered with ClinicalTrials.gov, NCT02601157. FINDINGS: At 3 years, clinical follow-up was completed in 955 patients (95.3%) and 966 patients (95.5%) in the 3-to-6-month and 12-month DAPT groups, respectively. The median follow-up duration was 1095 days (IQR 1095-1095). The primary outcome occurred in 7.7% and 8.2% of patients in the 3-to-6-month and 12-month DAPT groups, respectively (HR 0.94; 95% CI 0.69-1.29;

Heart failure (HF) patients have complex health profiles that existing risk models fail to capture. We developed TRisk, a Transformer-based artificial intelligence survival model for predicting mortality using routine electronic health records (EHR) in HF patients. Using UK data from 403,534 HF patients across 1418 English general practices, we trained and validated TRisk and compared it against MAGGIC-EHR, the MAGGIC model adapted for use on routine EHR by substituting variables (e.g. left-ventricular ejection fraction) that are not routinely available. External validation was conducted on 21,767 patients from USA hospitals. In the UK cohort, TRisk achieved a concordance index (C-index): 0.845 (95% CI: 0.841, 0.849), outperforming MAGGIC-EHR (C-index: 0.728 [0.723, 0.733]) for 36-month mortality prediction. In subgroup analyses, TRisk demonstrated less variability in predictive performance by sex, age, and baseline characteristics compared to MAGGIC-EHR, suggesting less biased modelling. Evaluating TRisk in USA data via transfer learning yielded a C-index of 0.802 (0.789, 0.816). Explainability analysis revealed TRisk captured established risk factors while identifying underappreciated ones, particularly cancers and hepatic failure, with cancers maintaining prognostic utility even a decade before baseline. TRisk provides more accurate, well-calibrated mortality prediction using routine data across international healthcare settings, demonstrating potential for improved risk stratification in patients with HF.

BACKGROUND: Atherosclerosis commences with endothelial dysfunction and the retention of cholesterol within the vessel wall, followed by a chronic inflammatory response. Lowering LDL-C (low-density lipoprotein-cholesterol; such as statins and PCSK9 [proprotein convertase subtilisin/kexin type 9] inhibitors) is the mainstay of current treatment for patients with atherosclerotic cardiovascular diseases, but residual inflammatory risk remains high. METHODS: To address this pressing challenge, we used connectivity map screening of Food and Drug Administration-approved drugs, using perturbational data sets obtained from TNF-α (tumor necrosis factor-α) and IL (interleukin)-1β-stimulated human endothelial cells. Male and female RESULTS: This screening endeavor allows us to identify neratinib, a clinical drug against breast cancer, as the hit compound with broad anti-inflammatory actions in endothelial cells. Further studies reveal that neratinib inhibited endothelial cell inflammation elicited by 3 different proinflammatory stimuli (TNF-α, IL-1β, and lipopolysaccharide). Intriguingly, the anti-inflammatory effect of neratinib was independent of its classical target HER2 (human epidermal growth factor receptor 2)/ERBB2 inhibition. Further mechanistic investigation revealed that neratinib directly binds to ASK1 (apoptosis signal-regulating kinase 1) and suppresses ASK1 activation. Importantly, in both male and female CONCLUSIONS: Taken together, these findings support the concept that neratinib could be tested as a repurposed drug for vascular inflammation and atherosclerosis, thereby streamlining efforts to translate preclinical discoveries to clinical testing in humans.