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Glycosylated hemoglobin levels and clinical outcomes in nondiabetic patients with coronary artery disease: A meta-analysis

A number of studies assessed the prognostic value of HbA1c level in nondiabetic patients with coronary artery disease (CAD). The purpose of this meta-analysis was to assess the association between the HbA1c level and clinical outcomes. We searched PubMed, EMBASE, MEDLINE, and the Cochrane Library fr...

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Detalles Bibliográficos
Autores principales: Geng, Jin, Zhang, Yanchun, Wang, Bingjian, Xie, Jun, Xu, Biao, Li, Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5413281/
https://www.ncbi.nlm.nih.gov/pubmed/28445316
http://dx.doi.org/10.1097/MD.0000000000006784
Descripción
Sumario:A number of studies assessed the prognostic value of HbA1c level in nondiabetic patients with coronary artery disease (CAD). The purpose of this meta-analysis was to assess the association between the HbA1c level and clinical outcomes. We searched PubMed, EMBASE, MEDLINE, and the Cochrane Library from their inception to 10 April 2016. Studies evaluated the outcomes according to HbA1c levels in CAD patients without diabetes mellitus were eligible. Twenty studies involving 22,428 patients were included. In nondiabetic patients with CAD, a high HbA1c level was associated with a higher rate of long-term death (odds ratio 1.76, 95% confidence interval 1.44–2.16, P < .001), and myocardial infarction (MI, odds ratio 1.69, 95% confidence interval 1.07–2.67, P = .026), but not a higher rate of early deaths (odds ratio 1.08, 95% confidence interval 0.92–1.27, P = .359). These findings for death remained the same after sensitivity analyses and the trim and fill method, but the risk difference for MI became nonsignificant after adjustment for potential publication bias. Elevated HbA1c level increased the risks of long-term mortality and MI, but not the risk for early deaths in nondiabetic patients with CAD. High-quality large-scale studies with less bias are needed to confirm these findings.