Dataset Information

Visfatin associated with major adverse cardiovascular events in patients with acute myocardial infarction.

ABSTRACT:

Background

Visfatin is an adipokine that related with the inflammation in atherosclerosis and the destabilization of atherosclerotic plaque. The aim of this study was to observe the relationship between visfatin and major adverse cardiovascular events (MACEs) in acute myocardial infarction (AMI) patients.

Methods

We enrolled a total of 238 patients (183 AMI and 55 control) who underwent coronary angiography. Patients with AMI were followed for an average of 19.3?months and 159 patients were finally included in the study.

Results

It was observed patients with AMI had higher serum visfatin levels than controls. The total incidence of MACEs was 11.32% (18/159) in AMI patients. After calculation of the Youden index, the best cut-off value of visfatin on the curve of receiver-operating characteristic was 8.799?ng/mL for predicting the occurrence of MACEs. The occurrence of MACEs was elevated in high-visfatin group (?8.799?ng/mL) compared with low-visfatin group (?8.799?ng/mL). The time to MACEs was correlated with visfatin (HR?=?1.235, 95%CI 1.051-1.451, P?=?0.01) and high-visfatin group had an earlier time to MACEs and a shorter time of cumulative survival.

Conclusions

Increased serum visfatin levels were observed in AMI patients, and correlated with an earlier onset and higher incidence of MACEs.

SUBMITTER: Zheng M

PROVIDER: S-EPMC7275306 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Visfatin associated with major adverse cardiovascular events in patients with acute myocardial infarction.

Zheng Meifan M Lu Nan N Ren Meixia M Chen Haifeng H

BMC cardiovascular disorders 20200605 1

<h4>Background</h4>Visfatin is an adipokine that related with the inflammation in atherosclerosis and the destabilization of atherosclerotic plaque. The aim of this study was to observe the relationship between visfatin and major adverse cardiovascular events (MACEs) in acute myocardial infarction (AMI) patients.<h4>Methods</h4>We enrolled a total of 238 patients (183 AMI and 55 control) who underwent coronary angiography. Patients with AMI were followed for an average of 19.3 months and 159 pat ...[more]

PMID: 32503436

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Project description:Background:Risk stratification models with incorporation of biochemical markers have received attention recently. In acute myocardial infarction (AMI) one such marker is lipoprotein(a) (Lp(a)). Lp(a) has prothrombotic and proinflammatory properties. High levels of Lp(a) probably contribute to the additional adverse effects in AMI, as it enhances the damaging effect of acute thrombosis. This study aimed to evaluate serum Lp(a) as a predictor of major adverse cardiovascular events (MACE) in hospitalized-acute myocardial infarction patients. Methods:A prospective cohort study was conducted at Sanglah Hospital, Denpasar, during June-August 2018, among 66 people by consecutive sampling. Samples that met the inclusion and exclusion criteria were examined for serum Lp(a) at the time of admission and the occurrence of MACE during hospitalization was observed. Data regarding serum Lp(a), demography, smoking history, dyslipidemia, hypertension, diabetes mellitus, and MACE were collected. Log rank test and Cox proportional hazards regression were conducted with SPSS version 20 for Windows. Results:During observation, MACE occurred in 25 (38%) patients, including cardiogenic shock in 7 (10.6%) patients, heart failure in 20 (30.3%) patients, cardiovascular death in 5 (7, 6%) patients, malignant arrhythmias in 5 (7.6%) patients, and postinfarction angina in 5 (7.6%) patients. After the Log rank test, a significant difference in survival was observed (p = 0.001) between groups of high Lp(a) (survival rate of 60.6 hours; 95% CI 43.3-77.9) and low Lp(a) (average survival of 104.3 hours, 95% CI 91.4-117.2). The hazard ratio of high Lp(a) against MACE was 4.63 (p=0.002), and it increased to 4.69 in multivariate analysis with Cox proportional hazards regression test (p=0.003). Conclusion:The high level of Lp(a) in AMI patients was a risk factor for the occurrence of MACE during hospitalization. Patients with high Lp(a) also had worse survival compared to patients with low Lp(a).

Project description:ImportancePatients who survive acute myocardial infarction (AMI) have a high risk of subsequent major cardiovascular events. Efforts to identify risk factors for recurrence have primarily focused on the period immediately following AMI admission.ObjectivesTo identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.Design, setting, and participantsProspective cohort study. Patients with AMI (n?=?4227), aged 18 years or older, discharged alive from 53 acute-care hospitals across China from January 1, 2013, to July 17, 2014. Patients were randomly divided into samples: training (50% [2113 patients]), test (25% [1057 patients]), and validation (25% [1057 patients]). Risk factors were identified by a Cox model with Markov chain Monte Carlo simulation and further evaluated by latent class analysis. Analyses were conducted from May 1, 2017, to January 21, 2018.Main outcomes and measuresMajor cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.ResultsThe mean (SD) age of the cohort was 60.8 (11.8) years and 994 of 4227 patients (23.5%) were female. Common comorbidities included hypertension (2358 patients [55.8%]), coronary heart disease (1798 patients [42.5%]), and dyslipidemia (1290 patients [30.5%]). One-year event rates were 8.1% (95% CI, 6.91%-9.24%), 9.0% (95% CI, 7.22%-10.70%), and 6.4% (95% CI, 4.89%-7.85%) for the training, test, and validation samples, respectively. Nineteen risk factors comprising 15 unique variables (age, education, prior AMI, prior ventricular tachycardia or fibrillation, hypertension, angina, prearrival medical assistance, >4 hours from onset of symptoms to admission, ejection fraction, renal dysfunction, heart rate, systolic blood pressure, white blood cell count, blood glucose, and in-hospital complications) were identified. In the training, test, and validation samples, respectively, the risk model had C statistics of 0.79 (95% CI, 0.75-0.83), 0.73 (95% CI, 0.68-0.78), and 0.77 (95% CI, 0.70-0.83) and a predictive range of 1.2% to 33.9%, 1.2% to 37.9%, and 1.3% to 34.3%. The C statistic was 0.69 (95% CI, 0.65-0.74) for the latent class model in the training data. The risk model stratified 11.3%, 81.0%, and 7.7% of patients to high-, average-, and low-risk groups, with respective probabilities of 0.32, 0.06, and 0.01 for 1-year events.Conclusions and relevanceNineteen risk factors were identified, and a model was developed and evaluated to predict risk of 1-year cardiovascular events after AMI. This may aid clinicians in identifying high-risk patients who would benefit most from intensive follow-up and aggressive risk factor reduction.

Project description:BACKGROUND/OBJECTIVES:Pericoronary adipose tissue inflammation might lead to the development and destabilization of coronary plaques in prediabetic patients. Here, we evaluated inflammation and leptin to adiponectin ratio in pericoronary fat from patients subjected to coronary artery bypass grafting (CABG) for acute myocardial infarction (AMI). Furthermore, we compared the 12-month prognosis of prediabetic patients compared to normoglycemic patients (NG). Finally, the effect of metformin therapy on pericoronary fat inflammation and 12-months prognosis in AMI-prediabetic patients was also evaluated. METHODS:An observational prospective study was conducted on patients with first AMI referred for CABG. Participants were divided in prediabetic and NG-patients. Prediabetic patients were divided in two groups; never-metformin-users and current-metformin-users receiving metformin therapy for almost 6 months before CABG. During the by-pass procedure on epicardial coronary portion, the pericoronary fat was removed from the surrounding stenosis area. The primary endpoints were the assessments of Major-Adverse-Cardiac-Events (MACE) at 12-month follow-up. Moreover, inflammatory tone was evaluated by measuring pericoronary fat levels of tumor necrosis factor-α (TNF-α), sirtuin 6 (SIRT6), and leptin to adiponectin ratio. Finally, inflammatory tone was correlated to the MACE during the 12-months follow-up. RESULTS:The MACE was 9.1% in all prediabetic patients and 3% in NG-patients. In prediabetic patients, current-metformin-users presented a significantly lower rate of MACE compared to prediabetic patients never-metformin-users. In addition, prediabetic patients showed higher inflammatory tone and leptin to adiponectin ratio in pericoronary fat compared to NG-patients (P < 0.001). Prediabetic never-metformin-users showed higher inflammatory tone and leptin to adiponectin ratio in pericoronary fat compared to current-metformin-users (P < 0.001). Remarkably, inflammatory tone and leptin to adiponectin ratio was significantly related to the MACE during the 12-months follow-up. CONCLUSION:Prediabetes increase inflammatory burden in pericoronary adipose tissue. Metformin by reducing inflammatory tone and leptin to adiponectin ratio in pericoronary fat may improve prognosis in prediabetic patients with AMI. Trial registration Clinical Trial NCT03360981, Retrospectively Registered 7 January 2018.

Project description:Aim:Inflammation-based Glasgow Prognostic Scores (GPS) have been reported to predict the prognosis of patients with acute ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). The goal of this study was to investigate whether three kinds of GPSs can effectively predict major cardiovascular adverse events (MACEs) in STEMI or non-ST-segment elevation myocardial infarction (NSTEMI) patients undergoing PPCI, elective PCI (EPCI) or conservative drug therapy during hospitalization. Methods:In this retrospective cohort study, patients with acute myocardial infarction (AMI) were divided into 0, 1 or 2 score according to the GPSs. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of GPSs for MACE and all-cause mortality during hospitalization. Three kinds of GPSs, Inflammation-based Glasgow Prognostic Score (GPS), modified GPS (MGPS) and high-sensitivity CRP-modified GPS (HS-MGPS) and Global Registry of Acute Coronary Events (GRACE) score were applied in this study. Results:A total of 188 patients were enrolled. The ROC curve with MACE showed that the AUC of GPS (0.820 (95% confidence interval (CI) [0.754-0.885]), P < 0.001) was larger than that of MGPS (0.789 (95% CI [0.715-0.863]), P < 0.001), HS-MGPS (0.787 (95% CI [0.717-0.856]), P < 0.001) and GRACE score (0.743 (95% CI [0.672-0.814]), P < 0.001). The ROC curve with all-cause mortality showed that the AUC of GPS (0.696 (95% CI [0.561-0.831]), P = 0.005) was similar to the HS-MGPS (0.698 (95% CI [0.569-0.826]), P = 0.005) and higher than the MGPS (0.668 (95% CI [0.525-0.812]), P = 0.016), but lower than the GRACE score (0.812 (95% CI [0.734-0.889]), P < 0.001). Multivariate logistic regression analysis showed that the GPS was an independent risk factor for the incidence of MACE during hospitalization. Compared with the odds ratio (OR) value for a GPS of 0, the OR for a GPS of 1 was 7.173 (95% CI [2.425-21.216]), P < 0.001), and that for a GPS of 2 was 18.636 (95% CI [5.813-59.746]), P < 0.001), but not an independent risk factor for all-cause mortality (P = 0.302). GRACE score was an independent risk factor for MACE (1.019 (95% CI [1.004-1.035]), P = 0.015) and all-cause mortality (1.040 (95% CI [1.017-1.064]), P = 0.001). In the subgroups classified according to the type of AMI, the presence of disease interference GPSs and the type of PCI, the ability of GPS to predict the occurrence of MACE seemed to be greater than that of MGPS and HS-MGPS. Conclusion:The GPS has a good predictive value for the occurrence of MACE during hospitalization in patients with AMI, regardless of STEMI or NSTEMI, the choice of PCI mode and the presence or absence of diseases that interfere with GPS. However, GPS is less predictive of all-cause mortality during hospitalization than GRACE score, which may be due to the interference of patients with other diseases.

Project description:ObjectivesPatients admitted to hospital with acute myocardial infarction (AMI) have considerable variability in in-hospital risks, resulting in higher demands on healthcare resources. Simple risk-assessment tools are important for the identification of patients with higher risk to inform clinical decisions. However, few risk assessment tools have been built that are suitable for populations with AMI in China. We aim to develop and validate a risk prediction model, and further build a risk scoring system.DesignData from a nationally representative retrospective study was used to develop the model. Patients from a prospective study and another nationally representative retrospective study were both used for external validation.Setting161 nationally representative hospitals, and 53 and 157 other hospitals were involved in the above three studies, respectively.Participants8010 patients hospitalised for AMI were included as development sample, and 4485 and 11 223 other patients were included as validation samples in their corresponding studies.Primary and secondary outcome measuresThe in-hospital major adverse cardiovascular events (MACE) was defined as death from any cause, recurrent AMI, or ischaemic stroke.ResultsThe proportion of in-hospital MACE was 11.7%, 8.8% and 11.4% among the development sample and two external-validation samples, respectively. Nine predictors (ie, age, sex, left ventricular ejection fraction, Killip class, systolic blood pressure, creatinine, white blood cell count, heart rate and blood glucose) were independently associated with in-hospital MACE. The model performed well on both discrimination and calibration capability, with areas under the Receiver Operating Characteristic Curve (ROC) curve of 0.85, 0.74 and 0.80, and calibration slopes of 0.98, 0.84 and 0.97 in the development sample and two external validation samples, respectively. A point-based risk scoring system was built with good discrimination and reclassification ability.ConclusionsA prediction model using readily available clinical parameters was developed and externally validated to estimate risks of in-hospital MACE among patients with AMI, thereby better informing decision-making in improving clinical care.

Dataset Information

Visfatin associated with major adverse cardiovascular events in patients with acute myocardial infarction.

Background

Methods

Results

Conclusions

Publications

Visfatin associated with major adverse cardiovascular events in patients with acute myocardial infarction.

Similar Datasets

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