Rui Shi,1,* Wenbo Xu,1 Lei Feng,2,* Dan Ye,1 Beibei Luo,1 Yanmei Liu,2,3 Huiying Cao,1 Lingtong Tang1 

1Department of Laboratory, The Sixth Affiliated Hospital of Kunming Medical University, Yuxi City, Yunnan Province, People’s Republic of China; 2Clinical Laboratory, Yan’an Hospital of Kunming City, Kunming City, Yunnan Province, People’s Republic of China; 3Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Wenbo Xu, Department of Laboratory, The Sixth Affiliated Hospital of Kunming, Medical University, Yuxi City, Yunnan Province, People’s Republic of China, Tel +86 877 2014128, Email xwb103196@sina.com Lei Feng, Clinical Laboratory, Yan’an Hospital of Kunming City, Kunming City, Yunnan Province, People’s Republic of China, Tel +86 871 63612494, Email fngj2004@163.com

Aim: This investigation aims to assess the predictive value of the glycemic dispersion index (GDI), calculated by incorporating glycated hemoglobin, fasting plasma glucose, and 2-hour postprandial plasma glucose, in predicting major adverse cardiovascular events (MACE) within a 12-month timeframe for diabetic patients with concomitant acute coronary syndrome (ACS).
Methods: A retrospective study was conducted on 3261 diabetic patients with ACS who were hospitalized in the Department of Cardiology, the Sixth Affiliated Hospital of Kunming Medical University, from January 2016 to July 2022. Based on the inclusion and exclusion criteria, 512 patients were ultimately enrolled in the study. Their general information and laboratory test indicators were collected, and the occurrence of MACE within 12 months after admission was followed up and recorded for the enrolled patients, With the last follow-up having been concluded on July 31, 2023. The enrolled patients were stratified into four groups (Q1, Q2, Q3, Q4) based on their GDI values, from the lowest to the highest. Cox proportional hazards regression analysis and Kaplan-Meier survival analysis were employed to investigate the risk factors associated with MACE occurrence across these groups and to assess the cumulative risk of MACE over time within each group.
Results: The percentages of enrolled patients experiencing MACE in groups Q1 to Q4 were 10.16%, 12.50%, 15.63%, and 16.41%, respectively. GDI independently predicted the hazards for MACE in enrolled patients. The cumulative risk of MACE over time was considerably more significant in those with a GDI> 4.21 than those with a GDI≤ 4.21.
Conclusion: The elevated GDI is correlated with an augmented risk of MACE in diabetic patients with concomitant ACS, thereby serving as an early indicator for assessing the unfavorable clinical prognosis of patients. This study offers novel insights into glycemic variability monitoring, enhancing prevention and treatment strategies for cardiovascular disease in people with diabetes.

Keywords: diabetes, acute coronary syndrome, major adverse cardiovascular events, glycemic dispersion index, glycemic variability