Cardiology journal最新文献

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.

Background: To investigate whether the antiPCSK9 vaccine can affect the CRP and oxidative stress (OS) during acute systemic inflammation.

Methods: Male albino mice were randomly divided into three groups: non-treated mice (the sham group), treated with a nonspecific stimulator of the immune response - Freund's complete adjuvant (CFA; the CFA group), and vaccinated mice treated with CFA (the vaccine group). The vaccine group was subcutaneously immunized with the antiPCSK9 formulation, 4 × in bi-weekly intervals. To induce inflammation, all mice were subjected to the CFA challenge after the vaccination plan. The hsCRP level and OS status were evaluated by a mouse CRP ELISA kit and the pro-oxidant antioxidant balance (PAB) assay, respectively.

Results: The vaccine induced a high-titter IgG antiPCSK9 antibody, which was accompanied with a significant PCSK9 reduction (-24.7% and -28.5% compared with the sham and CFA group, respectively), and the inhibition of PCSK9/LDLR interaction (-27.8% and -29.4%, respectively). hsCRP was significantly increased in the vaccine and CFA groups by 225% and 274% respectively, when compared with the sham group; however, it was non-significantly decreased (-18%; p = 0.520) in the vaccine group in comparison with the CFA group. The PAB values indicated that OS was significantly increased in the CFA group (by 72.7%) and the vaccine group (by 76%) when compared to the sham group; however, there was no significant difference in the PAB values between the vaccine and CFA groups.

Conclusion: The antiPCSK9 vaccine failed to significantly reduce the serum hs-CRP and OS induced in the CFA-challenged albino mice.

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.