Abstract
AbstractPurposeTo study epidemiology, complications, risk factors, clinical course and treatment patterns of diabetes, the Nanjing Diabetes Cohort (NDC) was established using anonymized electronic medical records from 650 hospitals and primary cares since 2020. This cohort provides valuable data for researchers and policymakers working on diabetes management and public health strategies.ParticipantsDiabetes was defined as having inpatient or outpatient encounters with diagnosis of diabetes ICD-9/10 codes, any use of insulin or oral hypoglycemic drugs, or one encounter with hemoglobin A1C > 4.8mmol/mol or 6.5%. Patients with diabetes have been continuously enrolled from hospitals and primary cares in Nanjing since 2020. Demographic, medications, and comorbidities data were extracted using clinical notes, diagnostic codes, labs, medications, and vital signs among different types of diabetes.Findings to dateThe NDC consisted of 1033904 patients from Jan 1st, 2020 to Dec 31th, 2022, the most part of whom were male (50.62%) and from district Gulou (30.79%). The clinical characteristics and medications usage of patients with type 1 diabetes, type 2 diabetes, gestational diabetes and other diabetes were assessed. The prevalence of hypertension, heart failure, and cerebrovascular disease were 31.20%, 21.46%, and 13.74% respectively.Future plansNDC will enroll eligible patients continuously each year. The data of NDC is maintained by Department of Medical Informatics, Nanjing Medical University.Strengths and limitations of this studyThe NDC is an ongoing population-base, large-sized cohort that contains over 1000000 patients with type 1 diabetes, type 2 diabetes, gestational diabetes, and other diabetes with follow-up records.NDC covers the patients with diabetes from Nanjing with urban and suburban areas, guaranteeing the generalizability of coverage.The NDC captures people with diabetes continuously from the Nanjing healthcare information platform, and provides exhaustive clinical data on clinical report, laboratory results, glucose-lowering drugs, diabetes-related comorbidities, and death report.Patients who had done no measurement of glycemic indexes or suffered prediabetes with normal HbAlc would not be included in the NDC.Data availability statementData are available on reasonable request. Data may be made available from the corresponding author with reasonable request, pending institutional and IRB approval and after completing a data sharing agreement.Funding declarationThis study was supported by the industry prospecting and common key technology key projects of Jiangsu Province Science and Technology Department (Grant no. BE2020721), the industrial and information industry transformation and upgrading special fund of Jiangsu Province in 2021 (Grant no. [2021]92), the key project of smart Jiangsu in 2020 (Grant no. [2021]1), Jiangsu Province Engineering Research Center of big data application in chronic disease and intelligent health service (Grant no. [2020]1460).CollaboratorsThe data of the NDC are not open access but can be shared under conditions of collaboration and endowment. Collaborative research projects are encouraged. For more detailed information on the NDC, please contact: Prof. Yun Liu (yun_liu@njmu.edu.cn)ContributorsStudy concept and design: Wei Feng, Yuechuchu Yin, Chen Wan; acquisition of data: Wei Feng, Yuechuchu Yin, Chunyan Gu, Chen Wan, Yuan Mu, Zhenhuan Tao, Weidong Yin; data analysis and verification: Chunyan Gu, Xin Zhang, Yuzhuo Wang, Yun Yu, Yuan Mu, Duxiao Zhang; drafting of the manuscript: Wei Feng, Yuechuchu Yin, Chen Wan; acquisition of funding: Yun Liu. All authors have read and approved the final version.Competing interestsNone declared.Patient consent for publicationNot required.Ethics approvalThe study was approved by the ethical review board of the First Affiliated Hospital, Nanjing Medical University (IRB#2019-SR-153).
Publisher
Cold Spring Harbor Laboratory
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