Journal of Geriatric Cardiology最新文献

Background: As the global population ages, the number of elderly patients with acute coronary syndrome (ACS) rises. However, prognostic assessment tools for elderly patients with ACS remain lacking, particularly in the Chinese population. This study aimed to develop and validate a nomogram to predict 2-year major adverse cardiovascular and cerebrovascular events (MACCE) in elderly Chinese patients with ACS.

Methods: A retrospective analysis was conducted using two independent cohorts of ACS patients aged ≥ 65 years who underwent percutaneous coronary intervention: the derivation cohort (n = 1674) and the validation cohort (n = 2333). Candidate predictors were selected using multivariable Cox proportional hazards regression and the Akaike information criterion. A final nomogram incorporating ten variables was constructed. Model performance was evaluated in terms of discrimination [concordance index (C-index) and area under the receiver operating characteristic curve (AUC)] and calibration (calibration plots).

Results: The 2-year incidence of MACCE was 12.5% (n = 210) in the derivation cohort and 15.6% (n = 364) in the validation cohort. The nomogram demonstrated good discrimination, with C-index values of 0.727 and 0.661 and AUCs of 0.723 and 0.699 in the derivation cohort and the validation cohort, respectively; significantly outperforming the GRACE risk score (P < 0.001). Calibration plots showed good agreement between the predicted and observed outcomes. Patients classified as the high-risk group by the nomogram had a significantly higher MACCE incidence compared to that of the low-risk group (log-rank P < 0.001).

Conclusions: This newly developed nomogram provides a reliable tool for individualized prediction of the 2-year MACCE risk in elderly Chinese patients with ACS who underwent percutaneous coronary intervention. It outperformed the GRACE score in both discrimmination and calibration and may help improve clinical decision-making and personalized risk stratification in this vulnerable population.

Background: Heart failure with preserved ejection fraction (HFpEF) following acute myocardial infarction (AMI) carries substantial morbidity and mortality, yet reliable prognostic markers beyond conventional cardiovascular factors remain limited. Frailty, reflecting diminished physiological reserve, has emerged as a potential determinant of adverse outcomes in this high-risk population. Therefore, the aim of this study was to address a critical knowledge gap and to provide evidence that may guide frailty-adapted management strategies to improve prognosis and quality of life in this high-risk population.

Methods: We conducted a multicenter retrospective cohort study including 4507 patients with HFpEF discharged after AMI across 82 hospitals in China (from January 2010 to March 2024). Frailty was assessed using the Hospital Frailty Risk Score (HFRS), with HFRS < 5 defined as non-frail and HFRS ≥ 5 as frail. Multivariable Cox proportional hazards models, adjusted for demographics, comorbidities, left ventricular ejection fraction, and therapies, were applied to evaluate associations between frailty and clinical outcomes. The primary endpoints were all-cause death and major adverse cardiovascular events (MACE), which defined as the composite of cardiovascular death and heart failure rehospitalization. Secondary endpoints included net adverse clinical events (NACE), which defined as the composite of all-cause death, stroke, recurrent myocardial infarction, revascularization, and major bleeding, as well as the individual components of MACE.

Results: Frailty was independently associated with a higher risk of all-cause death [adjusted hazard ratio (aHR) = 1.52, 95% CI: 1.31-2.03, P = 0.005] and NACE (aHR = 1.20, 95% CI: 1.02-1.41, P = 0.026). At one year, frail patients had higher unadjusted rates of all-cause death (9.0% vs. 2.9%) and NACE (19.8% vs. 13.7%) compared with non-frail patients. For cardiovascular death, the association did not reach statistical significance (aHR = 1.42, 95% CI: 0.99-2.03, P = 0.053). No significant associations were found for MACE (aHR = 1.05, 95% CI: 0.86-1.28, P = 0.636) or heart failure rehospitalization (aHR = 0.94, 95% CI: 0.75-1.19, P = 0.616).

Conclusions: Frailty, as measured by the HFRS, is an independent predictor of one-year mortality and composite adverse events in post-AMI HFpEF patients. These findings support the use of HFRS at discharge to identify high-risk population who may benefit from closer follow-up, optimization of medical therapy, and targeted frailty-focused interventions.

Background: Understanding the type and extent of coronary artery involvement in patients with acute type A aortic dissection (ATAAD) is vital for surgical planning. The Neri classification has been proposed as a guide for surgical strategies, however, its prognostic impact on postoperative mortality rates remains understudied in large-scale cohorts.

Methods: We reviewed 600 ATAAD patients who underwent surgery and coronary computed tomography angiography from 2016 to 2020 at Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Patients were classified based on the Neri classification system: no coronary artery involvement, type A (ostial involvement), type B (dissection in coronary body), and type C (circumferential detachment or complete avulsion). The primary endpoint was 30-day mortality.

Results: Overall, 28.3% of the patients had coronary artery involvement, with Neri type A, Neri type B, and Neri type C accounting for 13.3%, 11.2%, and 3.8%, respectively. The right coronary artery was more frequently involved (25.3%) than the left coronary artery (8.0%). In the unadjusted analysis, patients with coronary artery involvement exhibited a numerically higher 30-day mortality compared to those without (5.3% vs. 2.3%) (OR = 2.35, 95% CI: 0.94-5.88, P = 0.07), though this difference did not reach statistical significance. However, multivariable adjustment revealed significant association (adjusted OR = 3.71, 95% CI: 1.05-13.13, P = 0.04). Interestingly, after additional adjustment for coronary artery bypass grafting, the impact of coronary artery involvement on 30-day mortality no longer remained statistically significant (adjusted OR = 3.13, 95% CI: 0.85-11.58, P = 0.09). The 1-year mortality was higher in those with coronary artery involvement, but this significant association disappeared after adjusting for potential confounding variables. Furthermore, no significant difference in 30-day and 1-year mortality were observed among patients with different Neri classifications.

Conclusions: In patients with ATAAD who undergo surgery, the presence of coronary artery involvement is significantly associated with an increased risk of 30-day mortality. Proactive coronary artery bypass grafting may potentially mitigate the adverse impact of coronary artery involvement on 30-day mortality.

Background: Acute myocardial infarction (AMI) is a major cause of mortality worldwide. The stress hyperglycemia ratio (SHR), which integrates glucose and glycated hemoglobin A1c levels, better reflects acute metabolic stress. This study assessed the SHR and long-term prognosis of patients with AMI.

Methods: This study was a post-hoc analysis based on the prospective, multicenter OPTIMAL registry (http://www.clinicaltrials.gov, NCT number: NCT03084991). A total of 3384 consecutive patients who underwent percutaneous coronary intervention (PCI) at Department of Cardiology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, China were included in the present analysis after exclusions. Patients were stratified into quartiles according to the SHR. The primary endpoint was cardiovascular death, with all-cause death and major adverse cardiovascular events as secondary endpoints. The median follow-up duration was 24.1 months, with a completion rate of 99.5%.

Results: Kaplan-Meier survival curves showed progressively worse survival across SHR quartiles (log-rank P < 0.001), with patients in Q4 (SHR ≥ 1.34) experiencing the highest risk. Multivariate Cox regression analysis confirmed that the SHR was an independent predictor of cardiovascular death [hazard ratio (HR) = 1.56], all-cause death (HR = 1.48), and major adverse cardiovascular events (HR = 1.34) for Q4 (SHR ≥ 1.34) versus Q2 (SHR: 0.93-1.11). Restricted cubic spline analysis revealed a J-shaped association between SHR and outcomes, with the lowest risk observed at an SHR of approximately 1.0.

Conclusions: The SHR is an independent predictor of long-term adverse outcomes in patients with AMI undergoing PCI, supporting its use for early risk stratification and glycemic management.

Background: Cardiovascular disease (CVD) remains a major health challenge globally, particularly in aging populations. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study examines the Triglyceride-glucose (TyG) index dynamics, a marker for insulin resistance, and its relationship with CVD in Chinese adults aged 45 and older.

Methods: This reanalysis utilized five waves of CHARLS data with multistage sampling. From 17,705 participants, 5,625 with TyG index and subsequent CVD data were included, excluding those lacking 2011 and 2015 TyG data. TyG derived from glucose and triglyceride levels, CVD outcomes via self-reports and records. Participants divided into four groups based on TyG changes (2011-2015): low-low, low-high, high-low, high-high TyG groups.

Results: Adjusting for covariates, stable high group showed a significantly higher risk of incident CVD compared to stable low group, with an HR of 1.18 (95% CI: 1.03-1.36). Similarly, for stroke risk, stable high group had a HR of 1.45 (95% CI: 1.11-1.89). Survival curves indicated that individuals with stable high TyG levels had a significantly increased CVD risk compared to controls. The dynamic TyG change showed a greater risk for CVD than abnormal glucose metabolism, notably for stroke. However, there was no statistical difference in single incidence risk of heart disease between stable low and stable high group. Subgroup analyses underscored demographic disparities, with stable high group consistently showing elevated risks, particularly among < 65 years individuals, females, and those with higher education, lower BMI, or higher depression scores. Machine learning models, including random forest, XGBoost, CoxBoost, Deepsurv and GBM, underscored the predictive superiority of dynamic TyG over abnormal glucose metabolism for CVD.

Conclusions: Dynamic TyG change correlate with CVD risks. Monitoring these changes could predict and manage cardiovascular health in middle-aged and older adults. Targeted interventions based on TyG index trends are crucial for reducing CVD risks in this population.