IMR Press / RCM / Volume 24 / Issue 11 / DOI: 10.31083/j.rcm2411319
Open Access Original Research
Correlation Analysis of Gensini Score in Diabetic Patients with Coronary Heart Disease
Jinyue Qi1,2,3,4,†Yunzhe Wang1,2,3,4,†Zhiyu Liu1,2,3,4Fengyi Yu1,2,3,4Junnan Tang1,2,3,4,*Jinying Zhang1,2,3,4,*
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1 Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, 450052 Zhengzhou, Henan, China
2 Henan Province Key Laboratory of Cardiac Injury and Repair, 450052 Zhengzhou, Henan, China
3 Henan Province Clinical Research Center for Cardiovascular Diseases, 450018 Zhengzhou, Henan, China
4 Clinical Big Data Center, The First Affiliated Hospital of Zhengzhou University, 450052 Zhengzhou, Henan, China
*Correspondence: (Junnan Tang); (Jinying Zhang)
These authors contributed equally.
Rev. Cardiovasc. Med. 2023, 24(11), 319;
Submitted: 12 February 2023 | Revised: 26 April 2023 | Accepted: 15 May 2023 | Published: 17 November 2023
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: Assessment of risk factors is essential for clinical diagnosis and prevention in patients with both diabetes mellitus (DM) and coronary heart disease (CHD). In the present study we investigated correlation of the Gensini score with the incidence of major adverse cardiac and cerebrovascular events (MACCEs) in patients with DM and CHD. Methods: A total of 802 DM patients with CHD admitted to the First Affiliated Hospital of Zhengzhou University and who met the inclusion criteria were enrolled in the study. The median follow-up time for these patients was 3000 days (range 382.5–3000). Receiver operating characteristic (ROC) curves for the Gensini score were generated and the area under the curve (AUC) was calculated. Patients were divided into two groups based on the Gensini score cut-off value. Univariate and multivariate Cox proportional hazard regression analysis was used to identify the risk factors associated with MACCEs. The incidence of MACCEs in the two groups was compared using Kaplan-Meier analysis. Results: The AUC of the ROC curve was 0.675. The maximum Youden’s index was 0.248 at a Gensini score cut-off value of 74.8605. This gave a sensitivity and specificity for the prediction of MACCE of 68.8% and 56%, respectively. A high Gensini score was a risk factor for MACCEs, and the incidence of MACCEs was significantly greater in the high Gensini score group compared to the low Gensini score group. Conclusions: A high Gensini score is a risk factor for patients with DM and CHD and is associated with a high incidence of MACCEs. Clinical Trial Registration: The details of study design are registered on (identifier: ChiCTR-2200055450).

diabetes mellitus
cardiovascular heart disease
Gensini score
82222007/National Natural Science Foundation of China
82170281/National Natural Science Foundation of China
82100281/National Natural Science Foundation of China
U2004203/National Natural Science Foundation of China
ZYQR201912131/Henan Thousand Talents Program
202300410362/Excellent Youth Science Foundation of Henan Province
LHGJ20200362/Medical Science and Technology project of Henan Province
2021-CCA-ACCESS-125/Central Plains Youth Top Talent and Advanced funds
Fig. 1.
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