Neural cell adhesion molecule-1 may be a new biomarker of coronary artery disease

NCAM1 modulates the proliferation and migration of pulmonary arterial smooth muscle cells in pulmonary hypertension

BACKGROUND

Pulmonary hypertension (PH) is a malignant vascular disease characterized by pulmonary arterial remodeling. Neural cell adhesion molecule 1 (NCAM1) is a cell surface glycoprotein that is involved in a variety of diseases, including cardiovascular disease. However, the role of NCAM1 in PH remains underexplored.

METHODS

Pulmonary hypertension models were established using monocrotaline in rats and hypoxia in mice. NCAM1 protein levels in plasma from patients and rats were measured by ELISA. Expression of NCAM1 in rat lung tissues were evaluated using qRT-PCR, Western blotting, and immunofluorescence. The effects of NCAM1 on rat pulmonary artery smooth muscle cells were studied by stimulating these cells with PDGF-BB.

RESULTS

Elevated levels of NCAM1 protein and mRNA were observed in both PH patients and monocrotaline-induced PH rats. NCAM1 knockdown ameliorated hypoxia-induced PH, highlighting its role in pulmonary artery remodeling. In PASMCs, NCAM1 expression was upregulated by PDGF-BB stimulation, enhancing cell proliferation and migration. This effect was attenuated by NCAM1 knockdown but partially restored by an ERK1/2 pathway activator (tert-butylhydroquinone, TBHQ), suggesting NCAM1's involvement in PASMC dynamics through the ERK1/2 signaling pathway.

CONCLUSION

Our findings confirm the role of NCAM1 in pulmonary arterial hypertension and demonstrate its promotion of PASMC proliferation and migration through the ERK1/2 signaling pathway.

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

Background

Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

Cardiometabolic biomarker patterns associated with cardiac MRI defined fibrosis and microvascular dysfunction in patients with heart failure with preserved ejection fraction

Introduction

Heart failure with preserved ejection fraction (HFpEF) is a complex disease process influenced by metabolic disorders, systemic inflammation, myocardial fibrosis, and microvascular dysfunction. The goal of our study is to identify potential relationships between plasma biomarkers and cardiac magnetic resonance (CMR) imaging markers in patients with HFpEF.

Methods

Nineteen subjects with HFpEF and 15 age-matched healthy controls were enrolled and underwent multiparametric CMR and plasma biomarker analysis using the Olink® Cardiometabolic Panel (Olink Proteomics, Uppsala, Sweden). Partial least squares discriminant analysis (PLS-DA) was used to characterize CMR and biomarker variables that differentiate the subject groups into two principal components. Orthogonal projection to latent structures by partial least squares (OPLS) analysis was used to identify biomarker patterns that correlate with myocardial perfusion reserve (MPR) and extracellular volume (ECV) mapping.

Results

A PLS-DA could differentiate between HFpEF and normal controls with two significant components explaining 79% (Q2 = 0.47) of the differences. For OPLS, there were 7 biomarkers that significantly correlated with ECV (R2 = 0.85, Q = 0.53) and 6 biomarkers that significantly correlated with MPR (R2 = 0.92, Q2 = 0.32). Only 1 biomarker significantly correlated with both ECV and MPR.

Discussion

Patients with HFpEF have unique imaging and biomarker patterns that suggest mechanisms associated with metabolic disease, inflammation, fibrosis and microvascular dysfunction.

The pathophysiological role of circulating adhesion molecules in schizophrenia: A systematic review and meta-analysis

BACKGROUND

Increasing evidence suggests an association between schizophrenia and atherosclerosis. We conducted a systematic review and meta-analysis of cell adhesion molecules, critically involved in early atherosclerosis, in schizophrenia.

METHODS

We searched electronic databases from inception to 11 November 2023 for case-control studies assessing vascular cell, VCAM-1, intercellular, ICAM-1, platelet endothelial cell, PECAM-1, neural cell, NCAM, and Down syndrome cell, DSCAM, adhesion molecules, selectins (E-, L-, and P-selectin), integrins, and cadherins in patients with schizophrenia and healthy controls. Risk of bias and certainty of evidence were assessed using the JBI checklist and GRADE, respectively.

RESULTS

In 19 eligible studies, there were non-significant between-group differences in the concentrations of cell adhesion molecules, barring higher P-selectin in patients with schizophrenia (standard mean difference, SMD = 2.05, 95 % CI 0.72 to 3.38, p = 0.003; I2 = 97.2 %, p<0.001; very low certainty of evidence). Limited or no information was available regarding PECAM-1, DSCAM, ESAM, integrins, and cadherins. In meta-regression and subgroup analysis, there were significant associations between the SMD of ICAM-1 and matrix used (plasma or serum) and pharmacological treatment of schizophrenia, and between the SMD of VCAM-1 and pharmacological treatment, but not with other study and patient characteristics.

CONCLUSIONS

The results of our systematic review and meta-analysis do not support a significant role of immunoglobulin-like adhesion molecules, selectins, integrins, or cadherins in mediating the associations between schizophrenia, atherosclerosis, and cardiovascular disease. Further studies are warranted to investigate these associations in patients with different cardiovascular risk and the effects of antipsychotic treatments on cell adhesion molecules and surrogate markers of atherosclerosis (PROSPERO registration number: CRD42023463916).

Prognostic Value of GRACE Risk Score Combined With Systemic Immune-Inflammation Index in Patients With ST-Segment Elevation Myocardial Infarction After Percutaneous Coronary Intervention

The Global Registry of Acute Coronary Events (GRACE) score and the systemic immune-inflammation index (SII) were used independently to predict adverse outcomes in patients with ST-elevation myocardial infarction (STEMI). In this study, 1041 patients with STEMI were divided into 4 groups based on GRACE scores and optimal cutoff values for SII. SII was positively correlated with GRACE score (r = 0.164; P < .001). SII (HR, hazard ratio: 2.051; 95%CI: 1.249-3.368; P = .005) and GRACE score (HR: 7.625; 95%CI: 3.692-15.746; P < .001) were independent risk predictors of short-term major adverse cardiovascular events (MACEs). Taking the low SII+low GRACE group as the reference group, the short-term MACE HR of the high SII+high GRACE group was 40.470 (95%CI: 5.547-295.253). Comparing the area under the curve, the combined use of SII and GRACE scores can significantly improve the prediction efficiency of short-term MACE compared with the single use of SII and GRACE scores. In conclusion, SII may be positively correlated with GRACE score, and the combination of the two accurately predicted the occurrence of short-term MACE in STEMI patients after percutaneous coronary intervention (PCI).

Association of the Systemic Immune-Inflammation Index with Outcomes in Acute Coronary Syndrome Patients with Chronic Kidney Disease

Background

The systemic immune-inflammation index (SII; neutrophil × platelet/lymphocyte) is a novel marker for immune and inflammatory status and is associated with adverse prognosis in cardiovascular disease.

Methods

In total, 744 patients diagnosed with acute coronary syndrome (ACS) and chronic kidney disease (CKD) were included in our study, received standard therapies, and were followed up. Patients were divided into high and low SII groups according to the baseline SII. The primary endpoint was major cardiovascular events (MACEs), defined as cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke.

Results

During a median follow-up of 2.5 years, a total of 185 (24.9%) MACEs were recorded. Analysis of the ROC curve revealed that the best cutoff value of SII was 1159.84×10⁹/L for predicting MACEs. The Kaplan-Meier analysis showed that those patients in the low SII group had higher survival rates than those in the high SII group (p < 0.001). Compared to those in the low SII group, patients in the high SII group were at significantly higher risk of MACEs (134 (38.8%) vs 51 (12.8%), p < 0.001). Univariate and multivariable Cox regression analyses revealed that a high SII level was independently associated with MACEs in ACS patients with CKD (adjusted hazard ratio [HR]: 1.865, 95% confidence interval [CI]: 1.197-2.907, p = 0.006).

Conclusion

The present study showed that an elevated SII is associated with adverse cardiovascular outcomes in ACS with CKD patients, suggesting that SII may be a valuable predictor of poor prognosis in ACS with CKD patients. Further studies are needed to confirm our findings.

Persistent Depletion of Neuroprotective Factors Accompanies Neuroinflammatory, Neurodegenerative, and Vascular Remodeling Spectra in Serum Three Months after Non-Emergent Cardiac Surgery

We hypothesized that the persistent depletion of neuroprotective markers accompanies neuroinflammation and neurodegeneration in patients after cardiac surgery. A total of 158 patients underwent elective heart surgery with their blood collected before surgery (tbaseline) and 24 h (t24hr), seven days (t7d), and three months (t3m) post-surgery. The patients' serum was measured for markers of neurodegeneration (τau, τaup181-183, amyloid β1-40/β2-42, and S100), atypical neurodegeneration (KLK6 and NRGN), neuro-injury (neurofilament light/heavy, UC-HL, and GFAP), neuroinflammation (YKL-40 and TDP-43), peripheral nerve damage (NCAM-1), neuroprotection (apoE4, BDNF, fetuin, and clusterin), and vascular smoldering inflammation (C-reactive protein, CCL-28 IL-6, and IL-8). The mortality at 28 days, incidence of cerebrovascular accidents (CVA), and functional status were followed for three months. The levels of amyloid β1-40/β1-42 and NF-L were significantly elevated at all time points. The levels of τau, S100, KLK6, NRGN, and NCAM-1 were significantly elevated at 24 h. A cluster analysis demonstrated groupings around amyloids, KLK6, and NCAM-1. YKL-40, but not TDP-43, was significantly elevated across all time points. BDNF, apoE4, fetuin, and clusterin levels were significantly diminished long-term. IL-6 and IL-8 levles returned to baseline at t3m. The levels of CRP, CCL-28, and Hsp-70 remained elevated. At 3 months, 8.2% of the patients experienced a stroke, with transfusion volume being a significant variable. Cardiac-surgery patients exhibited persistent peripheral and neuronal inflammation, blood vessel remodeling, and the depletion of neuroprotective factors 3 months post-procedure.

N, Adigal S, Lukose J, Kartha VB, Chidangil S. Cardiovascular biomarkers in body fluids: progress and prospects in optical sensors

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases. Expert opinion. Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient's short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques.

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Background

Calcified aortic valve disease (CAVD) is one of the most common valvular heart diseases in the elderly population. However, no effective medical treatments have been found to interfere with the progression of CAVD, and specific molecular mechanisms of CAVD remain unclear.

Materials and Methods

Transcriptome sequencing data of GSE55492 and GSE148219 were downloaded from the European Nucleotide Archive, and the microarray dataset, GSE12644 was acquired from the Gene Expression Omnibus database. Software, including FastQC, HISAT2, samtools, and featureCounts was applied to generate the read count matrix. The “Limma” package in R was utilized to analyze differentially expressed genes (DEGs). Thereafter, weighted gene co-expression network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network were used to identify hub genes associated with CAVD, which were further validated by receiver operating characteristic curve (ROC) analysis using GSE12644. The long non-coding RNA (LncRNA)-mediated regulatory network was established based on the differentially expressed LncRNAs and hub genes, which were detected using quantitative real-time PCR (qRT-PCR) in clinical samples and valve interstitial cells. Moreover, CIBERSORT was used to calculate the expression distribution of immune cell infiltration in CAVD.

Results

A total of 126 DEGs were included in the PPI network. PI3K-Akt signaling pathway, ECM-receptor interaction, hematopoietic cell lineage, cell adhesion molecules, and focal adhesion were the most enriched pathways revealed by KEGG. Four LncRNAs, including TRHDE-AS1, LINC00092, LINC01094, and LINC00702 were considered the differentially expressed LncRNA. SPP1, TREM1, GPM6A, CCL19, CR1, NCAM1, CNTN1, TLR8, SDC1, and COL6A6 were the 10 hub genes identified to be associated with CAVD. Moreover, the calcified aortic valve samples had a greater level of Tregs, naïve B cells, and M0 macrophages than the noncalcified ones, whereas CAVD samples had a lower M2 macrophage expression compared to the noncalcified valve tissues.

Conclusion

The current study identified SPP1, TREM1, TLR8, SDC1, GPM6A, and CNTN1 as hub genes that could potentially be associated with CAVD. The LINC00702–miR-181b-5p–SPP1 axis might participate in the development of CAVD. Additionally, M2 macrophages, Tregs, naïve B cells, and M0 macrophages might possibly play a role in the initiation of CAVD.

A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk

A reliable, individualized, and dynamic surrogate of cardiovascular risk, synoptic for key biologic mechanisms, could shorten the path for drug development, enhance drug cost-effectiveness and improve patient outcomes. We used highly multiplexed proteomics to address these objectives, measuring about 5000 proteins in each of 32,130 archived plasma samples from 22,849 participants in nine clinical studies. We used machine learning to derive a 27-protein model predicting 4-year likelihood of myocardial infarction, stroke, heart failure, or death. The 27 proteins encompassed 10 biologic systems, and 12 were associated with relevant causal genetic traits. We independently validated results in 11,609 participants. Compared to a clinical model, the ratio of observed events in quintile 5 to quintile 1 was 6.7 for proteins versus 2.9 for the clinical model, AUCs (95% CI) were 0.73 (0.72 to 0.74) versus 0.64 (0.62 to 0.65), c-statistics were 0.71 (0.69 to 0.72) versus 0.62 (0.60 to 0.63), and the net reclassification index was +0.43. Adding the clinical model to the proteins only improved discrimination metrics by 0.01 to 0.02. Event rates in four predefined protein risk categories were 5.6, 11.2, 20.0, and 43.4% within 4 years; median time to event was 1.71 years. Protein predictions were directionally concordant with changed outcomes. Adverse risks were predicted for aging, approaching an event, anthracycline chemotherapy, diabetes, smoking, rheumatoid arthritis, cancer history, cardiovascular disease, high systolic blood pressure, and lipids. Reduced risks were predicted for weight loss and exenatide. The 27-protein model has potential as a "universal" surrogate end point for cardiovascular risk.

Systemic immune-inflammation index predicts in-hospital and long-term outcomes in patients with ST-segment elevation myocardial infarction

OBJECTIVE

This study examines the predictive value of the novel systemic immune-inflammation index (SII) in patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

A total of 1660 patients with STEMI who underwent primary percutaneous coronary intervention (pPCI) were enrolled in the study. In-hospital and 3-year outcomes were compared between the four groups (Q1-4). The SII was calculated using the following formula: neutrophil*platelet/lymphocyte.

RESULTS

The frequency of in-hospital cardiogenic shock, acute respiratory failure, acute kidney injury, ventricular arrhythmia, stent thrombosis, recurrent myocardial infarction, major adverse cardiac events and mortality were significantly higher in the high SII groups (Q3 and Q4). Logistic regression models demonstrated that Q3 and Q4 had an independent risk of mortality and Q4 had an independent risk of cardiogenic shock compared to Q1. Receiver operating characteristic analysis showed that the best cutoff value of SII to predict the in-hospital mortality was 1781 with 66% sensitivity and 74% specificity. Kaplan-Meier overall survivals for Q1, Q2, Q3 and Q4 were 97.6, 96.9, 91.6 and 81.0%, respectively. Cox proportional analysis for 3-year mortality demonstrated that Q3 and Q4 had an independent risk for mortality compared to Q1.

CONCLUSION

SII, a novel inflammatory index, was found to be a better predictor for in-hospital and long-term outcomes than traditional risk factors in patients with STEMI undergoing pPCI.

Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study

Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.

Cerebrospinal fluid NCAM-1 concentration is associated with neurodevelopmental outcome in post-hemorrhagic hydrocephalus of prematurity

OBJECTIVE

Efforts directed at mitigating neurological disability in preterm infants with intraventricular hemorrhage (IVH) and post hemorrhagic hydrocephalus (PHH) are limited by a dearth of quantifiable metrics capable of predicting long-term outcome. The objective of this study was to examine the relationships between candidate cerebrospinal fluid (CSF) biomarkers of PHH and neurodevelopmental outcomes in infants undergoing neurosurgical treatment for PHH.

STUDY DESIGN

Preterm infants with PHH were enrolled across the Hydrocephalus Clinical Research Network. CSF samples were collected at the time of temporizing neurosurgical procedure (n = 98). Amyloid precursor protein (APP), L1CAM, NCAM-1, and total protein (TP) were compared in PHH versus control CSF. Fifty-four of these PHH subjects underwent Bayley Scales of Infant Development-III (Bayley-III) testing at 15-30 months corrected age. Controlling for false discovery rate (FDR) and adjusting for post-menstrual age (PMA) and IVH grade, Pearson's partial correlation coefficients were used to examine relationships between CSF proteins and Bayley-III composite cognitive, language, and motor scores.

RESULTS

CSF APP, L1CAM, NCAM-1, and TP were elevated in PHH over control at temporizing surgery. CSF NCAM-1 was associated with Bayley-III motor score (R = -0.422, p = 0.007, FDR Q = 0.089), with modest relationships noted with cognition (R = -0.335, p = 0.030, FDR Q = 0.182) and language (R = -0.314, p = 0.048, FDR Q = 0.194) scores. No relationships were observed between CSF APP, L1CAM, or TP and Bayley-III scores. FOHR at the time of temporization did not correlate with Bayley-III scores, though trends were observed with Bayley-III motor (p = 0.0647 and R = -0.2912) and cognitive scores (p = 0.0506 and R = -0.2966).

CONCLUSION

CSF NCAM-1 was associated with neurodevelopment in this multi-institutional PHH cohort. This is the first report relating a specific CSF protein, NCAM-1, to neurodevelopment in PHH. Future work will further investigate a possible role for NCAM-1 as a biomarker of PHH-associated neurological disability.

Identification of Genetic Biomarkers for Diagnosis of Myocardial Infarction Compared with Angina Patients

Background

Myocardial infarction (MI) is the most terrible appearance of cardiovascular disease. The incidence of heart failure, one of the complications of MI, has increased in the past few decades. Therefore, the identification of MI from angina patients and the determination of new diagnoses and therapies of MI are increasingly important. The present study was aimed at identifying differentially expressed genes and miRNAs as biomarkers for the clinical and prognosis factors of MI compared with angina using microarray data analysis.

Methods

Differentially expressed miRNAs and genes were manifested by GEO2R. The biological function of differentially expressed genes (DEGs) was examined by GO and KEGG. The construction of a protein-protein network was explored by STRING. cytoHubba was utilized to screen hub genes. Analysis of miRNA-gene pairs was executed by the miRWalk 3.0 database. The miRNA-target pairs overlapped with hub genes were seen as key genes. Logistic regressive analysis was performed by SPSS.

Results

A number of 779 DEGs were recorded. The biological function containing extracellular components, signaling pathways, and cell adhesion was enriched. Twenty-four hub genes and three differentially expressed miRNAs were noted. Eight key genes were demonstrated, and 6 out of these 8 key genes were significantly related to clinical and prognosis factors following MI.

Conclusions

CALCA, CDK6, MDM2, NRXN1, SOCS3, VEGFA, SMAD4, NCAM1, and hsa-miR-127-5p were thought to be potential diagnosis biomarkers for MI. Meanwhile, CALCA, CDK6, NRXN1, SMAD4, SOCS3, and NCAM1 were further identified to be potential diagnosis and therapy targets for MI.

Systemic immune-inflammation index (SII) predicted clinical outcome in patients with coronary artery disease

BACKGROUND

This study examines the predictive value of a novel systemic immune-inflammation index (SII, platelet × neutrophil/lymphocyte ratio) in coronary artery disease (CAD) patients.

METHODS

A total of 5602 CAD patients who had undergone a percutaneous coronary intervention (PCI) were enrolled. They were divided into two groups by baseline SII score (high SII vs low SII) to analyse the relationship between SII groups and the long-term outcome. The primary outcomes were major cardiovascular events (MACE) which includes nonfatal myocardial infarction (MI), nonfatal stroke and cardiac death. Secondary outcomes included a composite of MACE and hospitalization for congestive heart failure.

RESULTS

An optimal SII cut-off point of 694.3 × 10⁹ was identified for MACE in the CAD training cohort (n = 373) and then verified in the second larger CAD cohort (n = 5602). Univariate and multivariate analyses showed that a higher SII score (≥694.3) was independently associated with increased risk of developing cardiac death (HR: 2.02; 95% CI: 1.43-2.86), nonfatal MI (HR: 1.42; 95% CI: 1.09-1.85), nonfatal stroke (HR: 1.96; 95% CI: 1.28-2.99), MACE (HR: 1.65; 95% CI: 1.36-2.01) and total major events (HR: 1.53; 95% CI: 1.32-1.77). In addition, the SII significantly improved risk stratification of MI, cardiac death, heart failure, MACE and total major events than conventional risk factors in CAD patients by the significant increase in the C-index (P < .001) and reclassification risk categories by significant NRI (P < .05) and IDI (P < .05).

CONCLUSIONS

SII had a better prediction of major cardiovascular events than traditional risk factors in CAD patients after coronary intervention.