In the present study, we aimed to characterize gut microbiome and develop a gut microbiome-based diagnostic model in patients with coronary artery disease (CAD). Prospectively, we collected 309 fecal samples from Central China and Northwest China and carried out the sequencing of the V3−V4 regions of the 16S rRNA gene. The gut microbiome was characterized, and microbial biomarkers were identified in 152 CAD patients and 105 healthy controls (Xinjiang cohort, n = 257). Using the biomarkers, we constructed a diagnostic model and validated it externally in 34 CAD patients and 18 healthy controls (Zhengzhou cohort, n = 52). Fecal microbial diversity was increased in CAD patients compared to that in healthy controls (P = 0.021). Phylum Bacteroidetes was increased in CAD patients versus healthy controls (P = 0.001). Correspondingly, 48 microbial markers were identified through a 10-fold cross-validation on a random forest model, and an area under the curve (AUC) of 87.7% (95% CI: 0.832 to 0.916, P < 0.001) was achieved in the Xinjiang cohort (development cohort, n = 257). Notably, an AUC of 90.4% (95% CI: 0.848 to 0.928, P < 0.001) was achieved using combined analysis of gut microbial markers and clinical variables. This model provided a robust tool for the prediction of CAD. It could be widely employed to complement the clinical assessment and prevention of CAD.

Monocyte to lymphocyte ratio (MLR) has been confirmed as a novel marker of poor prognosis in patients with coronary heart disease (CAD). However, the prognosis value of MLR for patients with CAD after percutaneous coronary intervention (PCI) needs further studies. In present study, we aimed to investigate the correlation between MLR and long-term prognosis in patients with CAD after PCI. A total of 3,461 patients with CAD after PCI at the First Affiliated Hospital of Zhengzhou University were included in the analysis. According to the cutoff value of MLR, all of the patients were divided into 2 groups: the low-MLR group (<0.34, n = 2338) and the high-MLR group (≥0.34, n = 1123). Kaplan–Meier curve was performed to compare the long-term outcome. Multivariate COX regression analysis was used to assess the independent predictors for all-cause mortality, cardiac mortality and MACCEs. Multivariate COX regression analysis showed that the high MLR group had significantly increased all-cause mortality (ACM) [hazard ratio (HR) = 1.366, 95% confidence interval (CI): 1.366-3.650, p = 0.001] and cardiac mortality (CM) (HR = 2.379, 95%CI: 1.611-3,511, p < 0.001) compared to the low MLR group. And high MLR was also found to be highly associated with major adverse cardiovascular and cerebrovascular events (MACCEs) (HR = 1.227, 95%CI: 1.003-1.500, p = 0.047) in patients with CAD undergoing PCI. MLR was an independent predictor of ACM, CM and MACCEs in CAD patients who underwent PCI.

BackgroundIt has been confirmed that the triglyceride to high-density lipoprotein cholesterol ratio (THR) is associated with insulin resistance and metabolic syndrome. However, to the best of our knowledge, only a few studies with small sample sizes have investigated the relationship between THR and coronary artery disease (CAD). Therefore, we aimed to assess the correlation between the THR and long-term mortality in patients with CAD after undergoing percutaneous coronary intervention (PCI) in our study that enrolled a large number of patients.MethodsA total of 3269 post-PCI patients with CAD were enrolled in the CORFCHD-ZZ study from January 2013 to December 2017. The mean follow-up time was 37.59 ± 22.24 months. Patients were divided into two groups according to their THR value: the lower group (THR < 2.84, n = 1232) and the higher group (THR ≥ 2.84, n = 2037). The primary endpoint was long-term mortality, including all-cause mortality (ACM) and cardiac mortality (CM). The secondary endpoints were major adverse cardiac events (MACEs) and major adverse cardiac and cerebrovascular events (MACCEs).ResultsIn our study, ACM occurred in 124 patients: 30 (2.4%) in the lower group and 94 (4.6%) in the higher group (P = 0.002). MACEs occurred in 362 patients: 111 (9.0%) in the lower group and 251 (12.3%) in the higher group (P = 0.003). The number of MACCEs was 482: 152 (12.3%) in the lower group and 320 (15.7%) in the higher group (P = 0.008). Heart failure occurred in 514 patients: 89 (7.2%) in the lower group and 425 (20.9%) in the higher group (P < 0.001). Kaplan–Meier analyses showed that elevated THR was significantly related to long-term ACM (log-rank, P = 0.044) and the occurrence of heart failure (log-rank, P < 0.001). Multivariate Cox regression analyses showed that the THR was an independent predictor of long-term ACM (adjusted HR = 2.042 [1.264–3.300], P = 0.004) and heart failure (adjusted HR = 1.700 [1.347–2.147], P < 0.001).ConclusionsAn increased THR is an independent predictor of long-term ACM and heart failure in post-PCI patients with CAD.

Background: This study was to assess the prognostic value of Fasting Blood Glucose to HDL-C Ratio (GHR) in non-diabetic patients with CAD undergoing PCI. Methods and Results: 6645 non-diabetic patients from two independent cohort the CORFCHD-PCI study (n=4282) and the CORFCHD-ZZ (n=2363) study were enrolled in Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI, Patients were divided into two groups according to the GHR value. The primary outcome included all-cause mortality (ACM) and cardiac mortality (CM). The average follow-up time was 36.51±22.50 months. We found that there were significant differences between the two groups in the incidences of ACM (P =0.013) and CM (P=0.038). Multivariate Cox regression analysis revealed GHR as an independent prognostic factor for ACM. The incidence of ACM increased 1.284 times in patients in the higher GHR group (hazard ratio [HR]:1.284 [95% confidence interval [CI]:1.010-1.631], P &lt;0.05). Kaplan-Meier survival analysis suggested that patients with high GHR value tended to have an increased accumulated risk of ACM. However, we did not found significant differences in the incidence of major adverse cardiac events, main adverse cardiovascular and cerebrovascular events (MACCE), stroke, recurrent MI, bleeding events. Conclusions: This study indicates that GHR index is an independent and novel predictor of ACM in non-diabetic CAD patients who underwent PCI.

Objective In the present study, we aimed to establish a novel score to predict long-term mortality of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients who underwent percutaneous coronary intervention (PCI). Methods A total of 2,174 NSTE-ACS patients from the CORFCHD-ZZ study were enrolled as the derivation cohort. The validation cohort including 1,808 NSTE-ACS patients were from the CORFCHD-PCI study. Receiver operating characteristic analysis and area under the curve (AUC) evaluation were used to select the candidate variables. The model performance was validated internally and externally. The primary outcome was cardiac mortality (CM). We also explored the model performance for all-cause mortality (ACM). Results Initially, 28 risk factors were selected and ranked according to their AUC values. Finally, we selected age, N-terminal pro-B-type natriuretic peptide, and creatinine to develop a novel prediction model named “ABC” model. The ABC model had a high discriminatory ability for both CM (C-index: 0.774, p < 0.001) and ACM (C-index: 0.758, p < 0.001) in the derivation cohort. In the validation cohort, the C-index of CM was 0.802 (p < 0.001) and that of ACM was 0.797 (p < 0.001), which suggested good discrimination. In addition, this model had adequate calibration in both the derivation and validation cohorts. Furthermore, the ABC score outperformed the GRACE score to predict mortality in NSTE-ACS patients who underwent PCI. Conclusion In the present study, we developed and validated a novel model to predict mortality in patients with NSTE-ACS who underwent PCI. This model can be used as a credible tool for risk assessment and management of NSTE-ACS after PCI.

Background C-reactive protein (CRP) has been proposed as a contributor to the pathogenesis of coronary artery disease (CAD) and inflammatory reactions, which are associated with a decrease in serum albumin, and it has been reported that the CRP-to-serum albumin ratio (CAR) can predict CAD severity in inpatient ischemic cardiomyopathy (ICM) patients. However, the relationship between the CAR and long-term adverse outcomes in CAD patients after percutaneous coronary intervention (PCI) is still unknown. Methods A total of 3561 CAD patients enrolled in the Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI: an investigation based on case records and follow-up (CORFCHD-ZZ), a retrospective cohort study conducted from January 2013 to December 2017, and 1630 patients meeting the study inclusion criteria were divided into two groups based on the CAR (CAR < 0.186; n = 1301 and CAR ≥ 0.186; n = 329). The primary outcome was long-term mortality, including all-cause mortality (ACM) and cardiac mortality. The average follow-up time was 37.59 months. Results We found that there were significant differences between the two groups in the incidences of ACM (P < 0.001) and cardiac mortality (P  = 0.003). Cox multivariate regression analyses demonstrated that CAR was an independent predictor of ACM [hazard ratio, 2.678; (95% confidence interval (CI), 1.568–4.576); P < 0.001] and cardiac mortality (hazard ratio, 2.055; 95% CI, 1.056–3.998; P = 0.034) in CAD patients after PCI. Conclusion This study revealed that the CAR is an independent and novel predictor of long-term adverse outcomes in CAD patients who have undergone PCI.

Background: Monocyte count and serum albumin (Alb) have been proven to be involved in the process of systemic inflammation. Therefore, we investigated the prognostic value of monocyte-to-albumin ratio (MAR) in patients who underwent percutaneous coronary intervention (PCI). Methods：We enrolled a total of 3561 patients in this study from January 2013 to December 2017. They were divided into two groups according to MAR cutoff value (MAR &lt; 0.014, n = 2220; and MAR ≥ 0.014, n = 1119) as evaluated by receiver operating characteristic (ROC) curve. The average follow-up time was 37.59 ± 22.24 months. Results: The two groups differed significantly in the incidences of all-cause mortality (ACM; P &lt; 0.001), cardiac mortality (CM; P &lt; 0.001), major adverse cardiovascular events (MACEs; P = 0.038), and major adverse cardiovascular and cerebrovascular events (MACCEs; P = 0.037). Multivariate Cox regression analyses revealed MAR as an independent prognostic factor for ACM and CM. The incidence of ACM increased 56.5% (hazard ratio [HR] = 1.565; 95% confidence interval [CI], 1.086–2.256; P = 0.016) and that of CM increased 76.3% (HR = 1.763; 95% CI, 1.106–2.810; P = 0.017) in patients in the higher-MAR group. Kaplan–Meier survival analysis suggested that patients with higher MAR tended to have an increased accumulated risk of ACM ( Log rank P &lt; 0.001) and CM (Log rank P &lt; 0.001). Conclusion: The findings of the present study suggested that MAR was a novel independent predictor of long-term mortality in patients who underwent PCI.

The role of activation of the coagulation and fibrinolysis system in the pathogenesis and prognosis of cardiovascular diseases (CVDs) has drawn wide attention. Recently, the D-dimer to fibrinogen ratio (DFR) is considered as a useful biomarker for the diagnosis and prognosis of ischemic stroke and pulmonary embolism. However, few studies have explored the relationship between DFR and cardiovascular disease. In our study, patients were divided into 2 groups according to DFR value: the lower group (DFR < 0.52, n = 2123) and the higher group (DFR ≥ 0.52, n = 1073). The primary outcome was all-cause mortality (ACM) and cardiac mortality (CM). The average follow-up time was 37.59 ± 22.24 months. We found that there were significant differences between the 2 groups in term of ACM (2.4% vs 6.6%, P < 0.001) and CM (1.5% vs 4.0%, P < 0.001). Kaplan–Meier analyses showed that elevated DFR had higher incidences of ACM (log rank P < 0.001) and CM (log rank P < 0.001). Multivariate Cox regression analyses showed that DFR was an independent predictor of ACM (HR = 1.743, 95%CI: 1.187-2.559 P = 0.005) and CM (HR = 1.695, 95%CI: 1.033-2.781 P = 0.037). This study indicates that DFR is an independent and novel predictor of long-term ACM and CM in post-PCI patients with CAD.