Cohort profile: the Nanjing Diabetes Cohort database - a population-based surveillance cohort.

Purpose: To study epidemiology, complications, risk factors, clinical course and treatment patterns of diabetes, the Nanjing Diabetes Cohort (NDC) was established using anonymised electronic health records from 650 hospitals and primary care since 2020. This cohort provides valuable data for researchers and policy-makers focused on diabetes management and public health strategies.

Participants: Diabetes was defined as having inpatient or outpatient encounters with a diagnosis of diabetes International Classification of Diseases-9/10 codes, any use of insulin or oral hypoglycaemic drugs, or one encounter with haemoglobin A1C >4.

Applying contrastive pre-training for depression and anxiety risk prediction in type 2 diabetes patients based on heterogeneous electronic health records: a primary healthcare case study.

Objective: Due to heterogeneity and limited medical data in primary healthcare services (PHS), assessing the psychological risk of type 2 diabetes mellitus (T2DM) patients in PHS is difficult. Using unsupervised contrastive pre-training, we proposed a deep learning framework named depression and anxiety prediction (DAP) to predict depression and anxiety in T2DM patients.

Materials And Methods: The DAP model consists of two sub-models.