Application of the Chinese Expert Consensus on Diabetes Classification in clinical practice
10.3760/cma.j.cn112138-20230131-00043
- VernacularTitle:《糖尿病分型诊断中国专家共识》在糖尿病分型诊断中的临床实践应用
- Author:
Shuting YANG
1
;
Chao DENG
;
Binbin HE
;
Xi CHEN
;
Xia LI
;
Zhiguang ZHOU
Author Information
1. 中南大学湘雅二医院代谢内分泌科 国家代谢性疾病临床医学研究中心 糖尿病免疫学教育部重点实验室，长沙 410011
- Keywords:
Diabetes;
C-peptide;
Diabetes mellitus, type 1;
Islet autoantibodies;
Precision classification
- From:
Chinese Journal of Internal Medicine
2023;62(9):1085-1092
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the diagnostic for classification of newly diagnosed diabetes patients and assess the application of the screening tests recommended by the 2022 Chinese Expert Consensus on Diabetes Classification.Methods:Retrospective case series study. The data from the electronic medical record system of patients with new-onset diabetes mellitus (within 1 year of disease onset) who attending the Diabetes Specialist Outpatient Clinic at the Second Xiangya Hospital of Central South University from January 1, 2018 to December 31, 2021 were collected for the analysis. Based on the consensus, patients were categorized according their age of onset, body mass index (BMI), and suspicion of type 1 diabetes mellitus (T1DM). The chi-square statistic was used to compare key classifier indicators, including C-peptide, islet autoantibodies, and genetic markers, in the subgroups. The diagnosis in suspected T1DM patients was also evaluated. The screening strategy recommended in the consensus was further assessed using a logistic regression model and the area under the receiver-operating curve (AUC).Results:A total of 3 384 patients with new-onset diabetes were included. The average age of disease onset was (46.3±13.9) years, and 61.0% (2 065/3 384) of the patients were male. The proportions of patients who completed C-peptide and glutamic acid decarboxylase antibody (GADA) tests were 36.6% (1 238/3 384) and 37.5% (1 269/3 384), respectively. There were no significant differences in C-peptide test results among the subgroups (all P>0.05). In contrast, the GADA detection rate was higher in patients with young age of onset (<30 years old), in those who were non-obese (BMI<24 kg/m 2), and in those clinically suspected of T1DM (all P<0.05). According to the diagnostic pathway proposed by the consensus, only 57.4% (1 941/3 384) of patients could be subtyped. For a definitive diagnosis, the remaining patients needed completion of C-peptide, islet autoantibody, genetic testing, or follow-up. Furthermore, among patients with clinical features of suspected T1DM, the antibody positivity rate was higher than in non-suspected T1DM patients [24.5% (154/628) vs. 7.1% (46/646), P<0.001]. When the clinical features of suspected T1DM defined in the consensus were taken as independent variables and antibody positivity was considered the outcome variable in the logistic regression model, young onset, non-obese onset, and ketosis onset could enter the model. Based on AUC analysis, the accuracy of the diagnostic model was 0.77 (95% CI 0.73-0.81), suggesting that the clinical features of suspected T1DM in the consensus have good clinical diagnostic value for this patient subgroup. Conclusions:There was a significant discrepancy between the clinical practice of diabetes classification and the process recommended by the consensus, which was specifically reflected in the low proportions of both subtyping indicator testing and definitively subtyped diabetes patients. Attention should be pay to the classification diagnosis process proposed in the consensus and the clinical detection rate of key diabetes subtyping indicators such as C-peptide and islet autoantibodies for diabetes classification should be improved. Noteworthy, the screening strategy for T1DM proposed by the consensus showed good clinical application value.
