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首页> 外文期刊>Immunological Investigations: A Journal of Molecular and Cellular Immunology >Predictive Value of Blood Interleukin-6 Level in Patients with Acute Coronary Syndrome: A Meta-analysis
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Predictive Value of Blood Interleukin-6 Level in Patients with Acute Coronary Syndrome: A Meta-analysis

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摘要

Objective Conflicting results have been reported on the association between blood level of interleukin-6 and adverse outcomes in patients with acute coronary syndrome (ACS). The current meta-analysis aimed to evaluate the predictive utility of elevated blood interleukin-6 level in patients with ACS. Methods A systematically literature search was performed using PubMed and Embase databases up to December 31, 2019. Observational studies or post hoc analysis of randomized controlled trials investigating the values of blood interleukin-6 level for predicting major adverse cardiovascular events (MACE including death, re-infarction, revascularization, angina, heart failure, malignant arrhythmia, or stroke), all-cause mortality or cardiovascular mortality in ACS patients were eligible. The predictive values were summarized by pooling the multivariable-adjusted risk ratio (RR) and 95 confidence intervals (CI) for the highest versus lowest category of interleukin-6 level. Results Thirteen studies enrolling 30,289 patients with ACS were included. When comparing the highest with lowest category of interleukin-6 level, the pooled RR was 1.29 (95 CI 1.12-1.48) for MACE, 1.50 (95 CI 1.35-1.67) for all-cause mortality, and 1.55 (95 CI 1.06-2.28) for cardiovascular mortality, respectively. Moreover, the predictive values of interleukin-6 level on MACE were consistently found in different study designs, subtypes of patients, sample sizes, follow-up duration, and cutoff value of interleukin-6 elevation subgroups. Conclusion Increased blood level of interleukin-6may be independently associated with higher risk of MACE, cardiovascular and all-cause mortality in patients with ACS. Measurement of blood interleukin-6 level has potential to improve risk stratification of ACS.

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