Aim: The aim of the study was to evaluate the potential predictive value of permanent RBBB and LBBB for longer-term prognosis in patients with new-onset STEMI who underwent percutaneous coronary intervention (PCI).Methods: Patients with new-onset STEMI that underwent emergency PCI at our department from June 2012 to September 2020 were included in the study. Gensini score (GS) was employed to evaluate the severity of coronary lesions. The primary endpoint of the study was the occurrence of major adverse cardiac and cerebrovascular events (MACCEs), the composite of cardiac mortality, recurrence of myocardial infarction, cardiac shock, stroke, stent thrombosis, or revascularization. We also set all-cause mortality as a secondary endpoint.Results: Out of the 547 patients, 29 patients had new-onset permanent LBBB, 51 patients had new-onset permanent RBBB, and 467 patients had no bundle-branch block (BBB). The occurrence of no BBB, new permanent LBBB, or RBBB was not associated with the severity of coronary artery lesions as evaluated by the GS. After follow-up at an average of 43.93 months, MACCEs occurred in 52 patients. Kaplan-Meier analysis showed that patients with new-onset RBBB were at greater risk for MACCEs compared to those with new onset LBBB (χ2 = 5.107, p = 0.021). Also, an independent correlation was found between new permanent RBBB and LBBB and MACCEs risk. The adjusted hazard ratios (HRs) were 6.862 [95% confidence interval (CI) of 3.764–12.510] for the new-onset permanent RBBB and 3.395 (95% CI of 1.280–9.005) for LBBB, compared to those with no BBB, respectively (both p < 0.05).Conclusion: New onset permanent RBBB in patients with new onset STEMI who underwent PCI may be correlated independently with increased risk of poor long-term prognosis.
Background Blood pressure (BP) exhibits seasonal variations, with peaks reported in winter. However, the association between seasonal variations and blood pressure variability in patients with new-onset essential hypertension is not fully understood. This study evaluated the potential association of seasonal variations with new-onset essential hypertension. Methods This retrospective observational study recruited a total of 440 consecutive patients with new-onset essential hypertension who underwent 24-h ambulatory electrocardiograph (ECG) and BP measurement at our department between January 2019 and December 2019. Demographic and baseline clinical data including BP variability, heart rate variability, and blood tests were retrieved. Multivariate linear regression analysis was performed to identify factors independently associated with mean BP and BP variability. Results Among the 440 patients recruited, 93 cases were admitted in spring, 72 in summer, 151 in autumn, and 124 in winter. Univariate analysis revealed that systolic BP (SBP), diastolic BP (DBP), high-sensitivity C-reactive protein, SBP drop rate, DBP drop rate, 24-h standard deviation of SBP, 24-h standard deviation of DBP, 24-h SBP coefficient of variation, and 24-h DBP coefficient of variation were associated with patients admitted in winter (P < 0.05 for all). Multivariate linear regression analysis showed that winter was the influencing factor of 24-h standard deviation of SBP (B = 1.851, t = 3.719, P < 0.001), 24-h standard deviation of DBP (B = 1.176, t = 2.917, P = 0.004), 24-h SBP coefficient of variation (B = 0.015, t = 3.670, P < 0.001), and 24-h DBP coefficient of variation (B = 0.016, t = 2.849, P = 0.005) in hypertensive patients. Conclusions Seasonal variations are closely associated with BP variability in patients with new-onset essential hypertension. Our study provides insight into the underlying pathogenesis of new-onset essential hypertension.
Background The triglyceride glucose (TyG) index is a well-established biomarker for insulin resistance (IR) that shows correlation with poor outcomes in patients with coronary artery disease. We aimed to integrate the TyG index with clinical data in a prediction nomogram for the long-term prognosis of new onset ST-elevation myocardial infarction (STEMI) following primary percutaneous coronary intervention (PCI) . Methods This retrospective study included new-onset STEMI patients admitted at two heart centers for emergency PCI from December 2015 to March 2018 in development and independent validation cohorts. Potential risk factors were screened applying least absolute shrinkage and selection operator (LASSO) regression. Multiple Cox regression was employed to identify independent risk factors for prediction nomogram construction. Nomogram performance was assessed based on receiver operating characteristic curve analysis, calibration curves, Harrell’s C-index and decision curve analysis (DCA). Results In total, 404 patients were assigned to the development cohort and 169 to the independent validation cohort. The constructed nomogram included four clinical variables: age, diabetes mellitus, current smoking, and TyG index. The Harrell’s C-index values for the nomogram were 0.772 (95% confidence interval [CI]: 0.721–0.823) in the development cohort and 0.736 (95%CI: 0.656–0.816) in the independent validation cohort. Significant correlation was found between the predicted and actual outcomes in both cohorts, indicating that the nomogram is well calibrated. DCA confirmed the clinical value of the development prediction nomogram. Conclusions Our validated prediction nomogram based on the TyG index and electronic health records data was shown to provide accurate and reliable discrimination of new-onset STEMI patients at high- and low-risk for major adverse cardiac events at 2, 3 and 5 years following emergency PCI.
Background. Obstructive sleep apnea syndrome (OSAS) is common in patients with chronic coronary syndrome (CCS); however, a predictive model of OSAS in patients with CCS remains rarely reported. The study aimed to construct a novel nomogram scoring system to predict OSAS comorbidity in patients with CCS. Methods. Consecutive CCS patients scheduled for sleep monitoring at our hospital from January 2019 to September 2020 were enrolled in the current study. Coronary CT angiography or coronary angiography was used for the diagnosis of CCS, and clinical characteristics of the patients were collected. Significant predictors for OSAS in patients with moderate/severe CCS were estimated via logistic regression analysis, and a clinical nomogram was constructed. A calibration plot, examining discrimination (Harrell’s concordance index) and decision curve analysis (DCA), was applied to validate the nomogram’s predictive performance. Internal validity of the predictive model was assessed using bootstrapping (1000 replications). Results. The nomograms were constructed based on available clinical variables from 527 patients which were significantly associated with moderate/severe OSAS in patients with CCS, including body mass index, impaired glucose tolerance, hypertension, diabetes mellitus, nonalcoholic fatty liver disease, and routine laboratory indices such as neutrophil to lymphocyte ratio, platelet-to-lymphocyte ratio, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. The C-index (0.793) and AUC (0.771, 95% CI: 0.731–0.811) demonstrated a favorable discriminative ability of the nomogram. Moreover, calibration plots revealed consistency between moderate/severe OSAS predicted by the nomogram and validated by the results of sleep monitoring. Clinically, DCA showed that the nomogram had good discriminative ability to predict moderate/severe OSAS in patients with CCS. Conclusions. The risk nomogram constructed via the routinely available clinical variables in patients with CCS showed satisfying discriminative ability to predict comorbid moderate/severe OSAS, which may be useful for identification of high-risk patients with OSAS in patients with CCS.
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