PDF(Pubmed)
Abstract：
BACKGROUND: C-peptide is considered a peptide with active function in the body, which can affect people\'s health. However, the results of previous studies on the possible association of C-peptide with the risk of cardiometabolic disorders have not been fully understood. This systematic review and meta-analysis aimed to investigate the association between serum C-peptide level and the risk of cardiovascular disease (CVD) events.
METHODS: The various important databases, including PubMed, Scopus, and Web of Science, were searched comprehensively to November 2022 to identify the relevant studies. The HR(95% CI) or OR(95% CI) for observational studies were extracted and converted into log HR or log OR and their standard deviation(SD) was computed. A random-effects model with an inverse variance weighting method was conducted, to calculate the pooled effect size.
RESULTS: Sixteen observational studies, including one case-control study, eight cohort studies, and seven cross-sectional studies were included in the current meta-analysis. The sample size ranged from 90 to 7030, with an age range from 12 to 85 years. During the follow-up time (ranging from 5 to 17 years), 4852 CVD events occurred. Based on cohort and case-control studies, the pooled results showed no significant association between serum C-peptide with CVD events risk (RR = 1.02;95%CI:0.91-1.15, I2 = 34.7%; P-heterogeneity = 0.140). For cross-sectional studies, the pooled results indicated a positive association between serum C-peptide and the odds of CVD outcomes (OR = 1.35;95%CI:1.04-1.76, I2 = 83.6%; P-heterogeneity < 0.001).
CONCLUSIONS: The pooled results of the current study suggested that C-peptide level was not related to the risk of CVD events in cohort studies, however, the meta-analysis of cross-sectional studies showed a significant association between C-peptide and an increased risk of CVD events.
METHODS: The various important databases, including PubMed, Scopus, and Web of Science, were searched comprehensively to November 2022 to identify the relevant studies. The HR(95% CI) or OR(95% CI) for observational studies were extracted and converted into log HR or log OR and their standard deviation(SD) was computed. A random-effects model with an inverse variance weighting method was conducted, to calculate the pooled effect size.
RESULTS: Sixteen observational studies, including one case-control study, eight cohort studies, and seven cross-sectional studies were included in the current meta-analysis. The sample size ranged from 90 to 7030, with an age range from 12 to 85 years. During the follow-up time (ranging from 5 to 17 years), 4852 CVD events occurred. Based on cohort and case-control studies, the pooled results showed no significant association between serum C-peptide with CVD events risk (RR = 1.02;95%CI:0.91-1.15, I2 = 34.7%; P-heterogeneity = 0.140). For cross-sectional studies, the pooled results indicated a positive association between serum C-peptide and the odds of CVD outcomes (OR = 1.35;95%CI:1.04-1.76, I2 = 83.6%; P-heterogeneity < 0.001).
CONCLUSIONS: The pooled results of the current study suggested that C-peptide level was not related to the risk of CVD events in cohort studies, however, the meta-analysis of cross-sectional studies showed a significant association between C-peptide and an increased risk of CVD events.
摘要：
背景：C肽被认为是在体内具有主动功能的肽，这会影响人们的健康。然而,以往关于C肽可能与心脏代谢紊乱风险相关的研究结果尚未完全了解.本系统评价和荟萃分析旨在研究血清C肽水平与心血管疾病（CVD）事件风险之间的关系。
方法：各种重要的数据库，包括PubMed,Scopus,和WebofScience,到2022年11月进行了全面搜索，以确定相关研究。提取观察性研究的HR（95％CI）或OR（95％CI），并将其转换为logHR或logOR，并计算其标准偏差（SD）。采用方差逆加权方法建立了随机效应模型，来计算合并效应的大小。
结果：16项观察性研究，包括一项病例对照研究，8项队列研究,目前的荟萃分析包括7项横断面研究.样本量为90至7030，年龄为12至85岁。在随访期间（5至17年），发生4852例CVD事件。基于队列和病例对照研究，汇总结果显示血清C肽与CVD事件风险之间没有显著关联(RR=1.02;95CI:0.91-1.15,I2=34.7%;P异质性=0.140).对于横断面研究，汇总结果显示血清C肽与CVD结局的几率呈正相关(OR=1.35;95CI:1.04~1.76,I2=83.6%;P异质性<0.001).
结论：当前研究的汇总结果表明，在队列研究中，C肽水平与CVD事件的风险无关。然而,横断面研究的荟萃分析显示,C肽与CVD事件风险增加之间存在显著关联.
方法：各种重要的数据库，包括PubMed,Scopus,和WebofScience,到2022年11月进行了全面搜索，以确定相关研究。提取观察性研究的HR（95％CI）或OR（95％CI），并将其转换为logHR或logOR，并计算其标准偏差（SD）。采用方差逆加权方法建立了随机效应模型，来计算合并效应的大小。
结果：16项观察性研究，包括一项病例对照研究，8项队列研究,目前的荟萃分析包括7项横断面研究.样本量为90至7030，年龄为12至85岁。在随访期间（5至17年），发生4852例CVD事件。基于队列和病例对照研究，汇总结果显示血清C肽与CVD事件风险之间没有显著关联(RR=1.02;95CI:0.91-1.15,I2=34.7%;P异质性=0.140).对于横断面研究，汇总结果显示血清C肽与CVD结局的几率呈正相关(OR=1.35;95CI:1.04~1.76,I2=83.6%;P异质性<0.001).
结论：当前研究的汇总结果表明，在队列研究中，C肽水平与CVD事件的风险无关。然而,横断面研究的荟萃分析显示,C肽与CVD事件风险增加之间存在显著关联.
