永井 良三

BACKGROUND: Coronary artery disease (CAD) and aortic valve stenosis (AS) often coexist, with AS exacerbating myocardial ischemia and affecting prognosis. AIMS: To investigate the prognostic impact of AS stratified by peak aortic jet velocity (AV-Vel) in patients undergoing PCI. METHODS AND RESULTS: We conducted retrospective multicenter observational study involving patients who underwent percutaneous coronary intervention (PCI) between April 2013 and March 2019. The patients were divided into non-AS group and AS group. The AS group was further categorized: 2.6 ≤ AV-Vel < 3.0 m/s, mild AS; 3.0 ≤ AV-Vel < 4.0 m/s, moderate AS; and AV-Vel ≥ 4.0 m/s, severe AS. The primary outcome was all-cause mortality, and the secondary outcome was major adverse cardiovascular events (MACE), defined as a composite of all-cause mortality, myocardial infarction, or stroke. Multivariable Cox proportional hazards analysis was performed over 5-year observation period, with landmark analyses conducted at 30 days after PCI and from day 31 after PCI to 5 years. In total, 9,690 patients were analyzed (AS group, n = 361). Over a median follow-up of 2.57 (IQR: 0.89-4.24) years, AS group exhibited higher rates of mortality (HR: 3.06; 95% CI: 2.41-3.90; p < 0.001) and MACE (HR: 2.45; 95%CI: 1.97-3.04; p < 0.001) compared with non-AS group. Subgroup analysis revealed that patients with moderate and severe AS had worse short-term mortality and MACE within 30 days after PCI than the non-AS group, while patients with mild to severe AS showed significantly worse long-term outcomes than the non-AS group. CONCLUSIONS: AV-Vel is independently associated with both short- and long-term outcomes in patients undergoing PCI.

UNLABELLED: Krüppel-like factor 5 (KLF5) is an intrinsically disordered transcription factor involved in cardiac remodeling, cancer, and metabolic diseases. Targeting KLF5 has been a persistent challenge in drug development due to its structural inaccessibility. We investigated cardioprotective effects of NC114, a rationally designed small molecule that mimics a short, hydrophobic α-helical motif in KLF5, thereby disrupting its protein–protein interactions. Adult C57BL/6J male mice underwent transverse aortic constriction (TAC) or sham surgery, followed by administration of NC114 or vehicle. NC114-treated TAC mice exhibited preserved cardiac function, reduced heart weight-to-body weight ratio, and markedly attenuated interstitial fibrosis. Gene expression analysis demonstrated decreased cardiac expression of Klf5, Nppb, Tgfb1, PAI-1, Col1a1, and Fn1. NC114 also suppressed oxidative stress and reduced phosphorylation of PKCδ and expression of HIF-1α during the early phase post-TAC. Metabolomic profiling revealed that NC114 treatment reversed TAC-induced accumulation of organic and amino acids. NC114, a novel peptidomimetic molecule, targets the undruggable transcription factor KLF5 to attenuate cardiac hypertrophy, fibrosis, and metabolic dysregulation in pressure overload-induced heart failure. This study highlights the potential of KLF5 inhibition as a therapeutic strategy in cardiovascular disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1038/s41598-025-32155-y.

Background Accurately predicting left ventricular ejection fraction (LVEF) recovery after percutaneous coronary intervention (PCI) in patients with chronic coronary syndrome (CCS) is crucial for clinical decision-making. Objective This study aimed to develop and compare multiple machine learning (ML) models to predict LVEF recovery and identify key contributing features. Methods We retrospectively analyzed 520 patients with CCS from the Clinical Deep Data Accumulation System database. Patients were categorized into 4 binary classification tasks based on baseline LVEF (≥50% or &lt;50%) and degree of recovery: (1) good recovery, defined as an LVEF increase of &gt;10% compared with ≤0%; and (2) normal recovery, defined as an LVEF increase of 0% to 10% compared with ≤0%. For each task, 3 feature selection strategies (all features, least absolute shrinkage and selection operator [LASSO] regression, and recursive feature elimination [RFE]) were combined with 4 ML algorithms (extreme gradient boosting [XGBoost], categorical boosting, light gradient boosting machine, and random forest), resulting in 48 models. Models were evaluated using 10-fold cross-validation and assessed by the area under the curve (AUC), decision curve analysis, and calibration plots. Results The highest AUCs were achieved by RFE combined with XGBoost (AUC=0.93) for preserved LVEF with good recovery, LASSO combined with XGBoost (AUC=0.79) for preserved LVEF with normal recovery, LASSO combined with XGBoost (AUC=0.88) for reduced LVEF with good recovery, and RFE combined with XGBoost (AUC=0.84) for reduced LVEF with normal recovery. Shapley Additive Explanation analysis identified uric acid, platelets, hematocrit, brain natriuretic peptide, glycated hemoglobin, glucose, creatinine, baseline LVEF, left ventricular end-diastolic internal diameter, heart rate, R wave amplitude in V5, and R wave amplitude in V6 as important predictive factors of LVEF recovery. Conclusions ML models incorporating feature selection strategies demonstrated strong predictive performance for LVEF recovery after PCI. These interpretable models may support clinical decision-making and can improve the management of patients with CCS after PCI.

OBJECTIVES: The association between blood pressure (BP) and the mortality risk may vary depending on the comorbidities. This study was conducted to investigate the subgroup-specific correlation between systolic BP (SBP) and mortality in patients with coronary artery disease undergoing percutaneous coronary intervention (PCI). METHODS: The Clinical Deep Data Accumulation System for PCI (CLIDAS-PCI), a nation-wide multicenter database with seven tertiary medical hospitals in Japan, retrospectively collected data on patients undergoing PCI for acute coronary syndrome or stable coronary artery disease. Cubic spline curves modeled the relationship between SBP and all-cause death in the entire cohort and subgroups stratified by age, sex, diabetes, left ventricular (LV) hypertrophy, renal function and LV systolic function. We assessed the SBP, which minimizes mortality risk. RESULTS: A total of 8384 patients [71 [IQR 64, 78] years, 6494 (77%) male] with SBP at hospital discharge were analyzed. During 2.7 years of median follow-up, 695 deaths occurred. In the overall population, spline analysis demonstrated a nadir range of mortality risk around an SBP of 110-130 mmHg. Subgroup analyses revealed that elderly (age ≥ 80 years), those with renal dysfunction, and those with preserved LV systolic function had higher SBP levels associated with lowest risk. Conversely, patients <80 years, those with better renal function, and those with LV systolic dysfunction exhibited lower SBP levels at lowest risk. CONCLUSION: This study demonstrated differential association between SBP and mortality risk in various subgroups, highlighting the need for personalized BP management in multimorbid patients with coronary artery disease.