Cardiology journal最新文献

Background: Cumulative data has highlighted the efficacy of intra-vascular lithotripsy (IVL) in patients with stent failure (SF). However, it remains unclear whether the effectiveness of IVL, and subsequent clinical outcomes, are influenced by the timing of SF. We aimed to evaluate the outcomes of patients with SF undergoing IVL according to the age of index stent implantation.

Methods: This is a pre-specified subgroup analysis of the COIL registry (coronary intravascular lithotripsy in patients with stent failure), which included patients who underwent IVL treatment for SF, divided according to the timing of SF, i.e., early (≤12 months), mid-term (12-36 months), and late SF (>36 months). Procedural and clinical outcomes up to 12 months following IVL treatment were recorded. The primary endpoint was defined as the composite of cardiovascular death, spontaneous myocardial infarction, or target vessel revascularization (TVR).

Results: There were 88 patients included in this sub-study, of whom 40 (45%), 17 (19%), and 31 (35%) had early, mid-term, and late SF, respectively. Final procedural results were better in those with early compared to mid-term or late SF. At one-year follow-up, the incidence of the primary endpoint was associated with the timing of SF (8% vs. 12% vs. 29%, p = 0.042). The difference among the subgroups was driven by TVR (3% vs. 12% vs. 29%, p = 0.005).

Conclusions: Procedural and clinical outcomes following IVL treatment for patients with SF were influenced by the timing of index stent implantation. Further studies are needed to better understand the mechanisms behind recurrent SF.

Background: This study aimed to employ Mendelian randomization (MR) analysis to investigate the causal relationship between sodium-glucose cotransporter 2 (SGLT2) inhibition and atrial fibrillation (AF), as well as assess the potential mediating role of inflammatory proteins in this association.

Methods: A two-sample MR analysis was conducted using summary-level data from the genome-wide association study (GWAS) were used to evaluate the genetic prediction of SGLT2 inhibition and AF. Additionally, a two-step MR approach was applied to explore the causal mediation effects of inflammatory proteins in the SGLT2-AF pathway.

Results: Genetically predicted SGLT2 inhibition was associated with a significantly lower risk of AF (odds ratio [OR] 0.51; 95% confidence interval [CI]: 0.27-0.97; p = 0.039). Mendelian randomization analysis further identified FGF-23 (OR 0.88; 95% CI: 0.79, 0.98; p = 0.024) and PD-L1 (OR 0.90; 95% CI: 0.82, 0.96; p = 0.023) as significant mediators, accounting for 21.28% and 17.69% of the total effect, respectively.

Conclusions: These findings provide potential protective role of SGLT2 inhibition against AF, mediated by inflammatory proteins. Further mechanistic and clinical investigations are warranted to elucidate the underlying pathways and therapeutic implications.

Background: Studies of animal and human aortic tissue samples showed that sirtuins may protect against aortic aneurysm (AA). However, to date, no studies have assessed plasma or serum sirtuin levels in humans. Therefore, the aim of this study was to evaluate associations between plasma sirtuin 1 (SIRT1) and sirtuin 2 (SIRT2) levels and the presence of ascending AA.

Methods: Plasma SIRT1 and SIRT2 levels were assessed in patients with and without ascending AA using an enzyme-linked immunosorbent assay.

Results: The study included 32 patients with ascending AA (median age: 67 years) and 37 controls without AA (median age: 68 years). Plasma SIRT1 and SIRT2 levels did not differ between groups (p > 0.05). However, slightly higher sirtuin levels were observed in patients with ascending AA than in controls, particularly for SIRT1 in the subgroups of patients without coronary artery disease, atrial fibrillation, and chronic obstructive pulmonary disease (COPD). Among patients with ascending AA, higher SIRT2 levels were noted for those without COPD vs. those with COPD (p = 0.04).

Conclusions: The study showed no significant differences in SIRT1 and SIRT2 levels between patients with and without ascending AA. However, there was a trend towards higher SIRT1 levels in patients with AA, especially in those without comorbidities.

Background: Sacubitril/valsartan (S/V) improve left ventricular ejection fraction (LVEF) in heart failure patients, but the magnitude of improvement may depend on baseline values.

Methods: We analyzed whether baseline LVEF can predict its improvement in patients with LVEF ≤ 45% receiving S/V. Patients were divided into 4 groups (G) according to baseline LVEF (G1: ≤ 20%; G2: 21-30%; G3: 31-40%; G4: 41-45%).

Results: We included 256 patients (age 73 ± 12 years; 73% male; 174 ischemic cardiomyopathy [CM], 82 nonischemic CM) and assessed LVEF at S/V initiation and at 6 and 12 months of therapy. Baseline LVEF (%) values (overall 30.9 ± 8.6) were: G1: 17.3 ± 3.3; G2: 27.5 ± 2.4; G3: 35.5 ± 2; G4: 44.4 ± 1. LVEF increased in 62% of patients, reaching 34.3 ± 10.4% and 35.5 ± 11.2% at 6 and 12 months, respectively (p < 0.001). A significantly higher absolute LVEF increase was found in Groups 3 (7.2 ± 4.3) and 4 (4.2 ± 3.05) than in Groups 1 (0.6 ± 1.5) and 2 (3.5 ± 1.5), in women (5.9 ± 4.4 vs. 4.1 ± 4.5; p < 0.001), with high S/V doses (7.4 ± 4.7 vs. 4.3 ± 4.4; p < 0.001), and in nonischemic CM (6.3 ± 4.9 vs. 3.8 ± 4.2; p < 0.001). On multivariate analysis, female sex (OR 2.18; 95% CI [1.06-4.48]; p = 0.034), high dose (OR 3.38; 95% CI [1.10-10.34]; p = 0.033), and baseline LVEF > 30% (OR 8.62; 95% CI [4.69-15.82]; p = 0.001) were significant predictors of LVEF improvement.

Conclusions: LVEF improvement with S/V depends on baseline values, sex, and dose.

Background: To ascertain the diagnostic value of radiomic features of pericoronary adipose tissue (PCAT) and other coronary computed tomography angiography (CCTA) parameters for differentiating non-ST-segment-elevation myocardial infarction (NSTEMI) from unstable angina (UA).

Methods: This study included NSTEMI and UA patients (n = 102 each). The radiomic features of PCAT were selected according to the intraclass correlation coefficient, Pearson's coefficient, the t test, and least absolute shrinkage and selection operator. Six classifiers-random forest, support vector machine, naive Bayes, K-nearest neighbors, extreme gradient boosting, and light gradient boosting machine (LightGBM)-were used to build radiomics models, and the best were selected. Four CCTA parameter models, encapsulating plaque parameters (model 1), plaque parameters + fatty attenuation index (FAI) (model 2), plaque parameters + CT fractional flow reserve (CT-FFR) (model 3), and plaque parameters + CT-FFR + FAI (model 4), were constructed. Finally, we established a fusion model (nomogram) with all CCTA parameters and radiomics model scores. All models were compared regarding their performance.

Results: The LightGBM radiomics model achieved the highest AUC. Among CCTA parameter models, only model 4 achieved a predictive performance similar to that of the radiomics model in the training and test cohorts (AUC = 0.904 vs. 0.898 and 0.860 vs. 0.877). The combined model (nomogram) showed greater predictive efficacy (AUC = 0.963, 0.910) than model 4 or the radiomics model.

Conclusion: The PCAT-based radiomics model accurately distinguishes between NSTEMI and UA, with similar diagnostic performance as the model that combined all the significant CCTA parameters. The nomogram integrating CCTA parameters and the radiomic score has good clinical application prospects.