Growth differentiation factor-15 predicts all-cause death and major adverse cardiovascular events in patients with coronary heart disease: a prospective cohort study.

The prognostic value of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in coronary heart disease (CHD) patients remains limited. Our study examines the association between GDF-15 and adverse outcomes over an extended period in CHD patients and firstly assesses the incremental prognostic effect of incorporating GDF-15 into the Framingham risk score (FRS)-based model. This single-center prospective cohort study included 3,321 patients with CHD categorized into 2,479 acute coronary syndrome (ACS) (74.6%) and 842 non-ACS (25.4%) groups. The median age was 61.0 years (range: 53.0-70.0), and 917 (27.6%) were females. Mortality and major adverse cardiovascular events (MACEs) included cardiovascular mortality, myocardial infarction (MI), stroke, and heart failure (HF) (inclusive of HF episodes requiring outpatient treatment and/or hospital admission). Cox regression models assessed the associations between GDF-15 and the incidence of all-cause mortality and MACEs. Patients were stratified into three groups based on GDF-15 levels: the first tertile group (< 1,370 ng/L), the second tertile group (1,370-2,556 ng/L), and the third tertile group (> 2,556 ng/L). The C-index, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA) were used to assess incremental value. Over a median 9.4-year follow-up, 759 patients (22.9%) died, and 1,291 (38.9%) experienced MACEs. The multivariate Cox model indicated that GDF-15 was significantly associated with all-cause mortality (per ln unit increase, HR = 1.49, 95% CI: 1.36-1.64) and MACEs (per ln unit increase, HR = 1.29, 95% CI: 1.20-1.38). These associations persisted when GDF-15 was analyzed as an ordinal variable (p for trend < 0.05). Subgroup analysis of ACS and non-ACS for the components of MACEs separately showed a significant association between GDF-15 and both cardiovascular mortality and HF, but no association was observed between GDF-15 and MI /stroke in both ACS and non-ACS patients. The addition of GDF-15 to the FRS-based model enhanced the discrimination for both all-cause mortality (∆ C-index = 0.009, 95% CI: 0.005-0.014; IDI = 0.030, 95% CI: 0.015-0.047; continuous NRI = 0.631, 95% CI: 0.569-0.652) and MACEs (∆ C-index = 0.009, 95% CI: 0.006-0.012; IDI = 0.026, 95% CI: 0.009-0.042; continuous NRI = 0.593, 95% CI: 0.478-0.682). DCA suggested that incorporating GDF-15 into the FRS-based model demonstrated higher net benefits compared to FRS-based models alone (All-cause mortality: FRS-based model: area under the curve of DCA (AUDC) = 0.0903, FRS-based model + GDF-15: AUDC = 0.0908; MACEs: FRS-based model: AUDC = 0.1806, FRS-based model + GDF-15: AUDC = 0.1833). GDF-15 significantly associates with the long-term prognosis of all-cause mortality and MACEs in CHD patients and significantly improves the prognostic accuracy of the FRS-based model for both outcomes.

Serum albumin and cardiovascular disease: a Mendelian randomization study.

BACKGROUND: An increasing body of evidence suggests that serum albumin levels play a role in cardiovascular diseases. However, the specific causal relationship between serum albumin levels and cardiovascular disease remains partially unknown. METHODS: Mendelian randomization (MR) was employed in this study to examine potential causal relationships between instrumental variables and cardiovascular diseases. Specifically, we utilized genetic variants of serum albumin levels within the reference range as our instrumental variables. To acquire data on genetic associations with cardiovascular diseases, we sourced information from renowned genome-wide association studies such as UK BioBank, EMBL-EBI, and FinnGen. Notably, our study leveraged summary statistics from large cohorts that have been previously described. RESULTS: We explored the association between serum albumin levels and various conditions, including heart failure (HF), venous thromboembolism (VTE), stroke, atrial fibrillation (AF), coronary artery disease (CAD), type 2 diabetes (T2DM), and pulmonary heart disease (PHD). Genetically predicted serum albumin levels were associated with PHD (odds ratio = 0.737, 95% CI = 0.622 - 0.874, P < 0.001), AF (odds ratio = 0.922, 95% CI = 0.870 - 0.977, P = 0.006), VTE (odds ratio = 0.993, 95% CI = 0.991 - 0.995, P < 0.001), and Stroke (odds ratio = 0.997, 95% CI = 0.995 - 0.999, P = 0.002). However, genetically predicted serum albumin level traits were not associated with HF, CAD and T2DM. CONCLUSION: Our study demonstrates a significant association between serum albumin levels and cardiovascular disease, underscoring the crucial role of low serum albumin as a predictive factor in patients with cardiovascular disease.

The relationship between triglyceride-glucose index and prospective key clinical outcomes in patients hospitalised for coronary artery disease.

BACKGROUND: The triglyceride-glucose (TyG) index is regarded as a dependable alternative for assessing insulin resistance (IR), given its simplicity, cost-effectiveness, and strong correlation with IR. The relationship between the TyG index and adverse outcomes in patients with coronary heart disease (CHD) is not well established. This study examines the association of the TyG index with long-term adverse outcomes in hospitalized CHD patients. METHODS: In this single-center prospective cohort study, 3321 patients hospitalized with CHD were included. Multivariate Cox regression models were employed to assess the associations between the TyG index and the incidence of all-cause mortality and major adverse cardiovascular events (MACEs). To examine potential nonlinear associations, restricted cubic splines and threshold analysis were utilized. RESULTS: During a follow-up period of 9.4 years, 759 patients (22.9%) succumbed to mortality, while 1291 (38.9%) experienced MACEs. Threshold analysis demonstrated a significant "U"-shaped nonlinear relationship with MACEs, with different hazard ratios observed below and above a TyG index of 8.62 (below: HR 0.71, 95% CI 0.50-0.99; above: HR 1.28, 95% CI 1.10-1.48). Notably, an increased risk of all-cause mortality was observed only when the TyG index exceeded 8.77 (HR 1.53, 95% CI 1.19-1.96). CONCLUSIONS: This study reveals a nonlinear association between the TyG index and both all-cause mortality and MACEs in hospitalized CHD patients with CHD. Assessing the TyG index, particularly focusing on individuals with extremely low or high TyG index values, may enhance risk stratification for adverse outcomes in this patient population.

Association of Frailty with Adverse Outcomes in Patients with Critical Acute Myocardial Infarction: A Retrospective Cohort Study.

Background: Frailty is a risk factor for acute myocardial infarction (AMI). This study examined the association between the modified frailty index (MFI) and adverse outcomes in patients with critical AMI. Methods: Data were obtained from the Medical Information Mart for Intensive Care IV database. Logistic and Cox regression models and a competing risk model were applied. Results: Of 5003 patients, 1496 were non-frail and 3507 were frail. Frailty was significantly associated with in-hospital mortality (per point, OR 1.13, 95% CI: 1.05-1.21; frail vs non-frail, OR 1.31, 95% CI: 1.04-1.65) and 1-year mortality (per point, HR 1.15, 95% CI: 1.11-1.20; frail vs non-frail, HR 1.37, 95% CI: 1.20-1.58). Frailty was significantly associated with post-discharge care needs (per point, OR 1.23, 95% CI: 1.14-1.33; frail vs non-frail, OR 1.47, 95% CI: 1.22-1.78). In the competing risk models, frailty was significantly associated with a lower probability of being discharged from the ICU (per point, HR 0.87, 95% CI: 0.85-0.90; frail vs non-frail, HR 0.73, 95% CI: 0.68-0.79) and hospital (per point, HR 0.82, 95% CI: 0.80-0.85; frail vs non-frail, HR 0.62, 95% CI: 0.57-0.68). Subgroup analyses showed the association of frailty with in-hospital and 1-year mortality was stronger in patients with a SOFA score ≤2 than in those with a SOFA score >2 (both p<0.05 for interaction). Conclusion: Frailty assessed by the MFI was an independent predictor of adverse outcomes in patients with critical AMI and may be helpful for prognostic risk stratification.