Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes

Yuanyuan Fu; Ling Hu; Hong-Wei Ren; Yi Zuo; Shaoqiu Chen; Qiu-Shi Zhang; Chen Shao; Yao Ma; Lin Wu; Jun-Jie Hao; Chuan-Zhen Wang; Zhanwei Wang; Richard Yanagihara; Youping Deng

doi:10.1155/2022/9322332

Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes

Int J Endocrinol. 2022 Jan 17:2022:9322332. doi: 10.1155/2022/9322332. eCollection 2022.

Authors

Yuanyuan Fu¹, Ling Hu², Hong-Wei Ren², Yi Zuo^{1

2}, Shaoqiu Chen¹, Qiu-Shi Zhang², Chen Shao², Yao Ma², Lin Wu², Jun-Jie Hao², Chuan-Zhen Wang², Zhanwei Wang³, Richard Yanagihara⁴, Youping Deng¹

Affiliations

¹ Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.
² Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
³ Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA.
⁴ Department of Pediatrics, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.

Abstract

Background: Type 2 diabetes (T2D) as a worldwide chronic disease combined with the COVID-19 pandemic prompts the need for improving the management of hospitalized COVID-19 patients with preexisting T2D to reduce complications and the risk of death. This study aimed to identify clinical factors associated with COVID-19 outcomes specifically targeted at T2D patients and build an individualized risk prediction nomogram for risk stratification and early clinical intervention to reduce mortality.

Methods: In this retrospective study, the clinical characteristics of 382 confirmed COVID-19 patients, consisting of 108 with and 274 without preexisting T2D, from January 8 to March 7, 2020, in Tianyou Hospital in Wuhan, China, were collected and analyzed. Univariate and multivariate Cox regression models were performed to identify specific clinical factors associated with mortality of COVID-19 patients with T2D. An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration.

Results: Nearly 15% (16/108) of hospitalized COVID-19 patients with T2D died. Twelve risk factors predictive of mortality were identified. Older age (HR = 1.076, 95% CI = 1.014-1.143, p=0.016), elevated glucose level (HR = 1.153, 95% CI = 1.038-1.28, p=0.0079), increased serum amyloid A (SAA) (HR = 1.007, 95% CI = 1.001-1.014, p=0.022), diabetes treatment with only oral diabetes medication (HR = 0.152, 95%CI = 0.032-0.73, p=0.0036), and oral medication plus insulin (HR = 0.095, 95%CI = 0.019-0.462, p=0.019) were independent prognostic factors. A nomogram based on these prognostic factors was built for early prediction of 7-day, 14-day, and 21-day survival of diabetes patients. High concordance index (C-index) was achieved, and the calibration curves showed the model had good prediction ability within three weeks of COVID-19 onset.

Conclusions: By incorporating specific prognostic factors, this study provided a user-friendly graphical risk prediction tool for clinicians to quickly identify high-risk T2D patients hospitalized for COVID-19.

Grants and funding

P30 CA071789/CA/NCI NIH HHS/United States