Aim: To investigate the related factors of diabetic retinopathy (DR) and explore the correlation between smoking and DR in patients with newly diagnosed type 2 diabetes mellitus (T2DM). Design: A single-centre cross-sectional study. Setting: Tianjin 4th Central Hospital. Participants: Patients with newly diagnosed T2DM who visited the outpatient department of the hospital from December 2018 to April 2019. Methods: A total of 947 patients were enrolled in the study. They were divided into two groups according to whether they were diagnosed with DR (diabetic retinopathy group, DR group; non-diabetic retinopathy group, NDR group). The smoking index (SI) was calculated to assess smoking status. Factors such as sex, age, hypertension, T2DM diagnosed age, family history of diabetes, drinking history, haemoglobin A1c (HbA1c), body mass index (BMI) and smoking status were compared between the two groups. Logistic regression was used to analyse the relationship between DR and the above factors. Results: There was no statistically significant difference between the two groups in sex, age, hypertension, DM diagnosed age, family history of diabetes, drinking history and HbA1c. BMI was significantly higher in DR patients (27.7±4.2 vs 26.7±4.4, p=0.004). Smoking status was also different between the two groups (χ ² =6.350, p=0.042). BMI was shown to be a related factor for DR in patients with newly diagnosed diabetes (OR=0.592, p=0.004). When BMI was ≥28 kg/m ² , heavy smoking was significantly associated with DR (OR=2.219, p=0.049), and there was a negative correlation between DR and the age of diagnosis of diabetes ≥60 years (OR=0.289, p=0.009). Conclusions: Heavy smoking was an important related factor for DR in patients with newly diagnosed diabetes mellitus when BMI was ≥28 kg/m ² . Delaying the age of diabetes might prevent the occurrence of DR. To elucidate the correlation, long-term cohort studies with large samples are needed.

Background: Type 2 diabetes mellitus (T2DM) was previously considered a common disease in middle-aged and older people, but the age of diagnosis of T2DM is advancing every year, and the trend toward a younger age is obvious. Early-onset T2DM is a clinical syndrome caused by genetic and environmental factors. This study aimed to investigate the association between diabetic family history and gender with the diagnosed age of T2DM. Methods: The newly diagnosed T2DM patients admitted to the diabetes identification center of Tianjin 4th Central Hospital (TJ4thch) from October 2017 to June 2020 were registered. According to whether the diagnosis age is over 40 years old, patients were divided into 2 groups (early-onset T2DM group and late-onset T2DM group). In the study, the T2DM family history was divided into 5 types: ( a) Father T2DM: father with T2DM, but not the mother; ( b) Mother T2DM: mother with T2DM, but not the father; ( c) Both parents with T2DM; ( d) Another relative(s) (other than the parents) with a history of T2DM; and ( e) Without a family history of T2DM. The diagnosed age with different genders and diabetic family history was compared. Multivariate logistic regression analysis was used to investigate the association factors of early-onset T2DM. Results: A total of 3725 patients completed the survey. There were 589 patients (15.8%) with early-onset T2DM, and 2469 patients (66.3%) had a diabetic family history. The T2DM-diagnosed age in males was lower than in females (51.7 ± 11.2 vs 54.0 ± 10.2, P = .000). The result was also reflected in the different T2DM family histories (with Both parents T2DM, 46.7 ± 11.1 vs 48.5 ± 10.3, P = .271; with Father T2DM, 46.8 ± 10.8 vs 49.8 ± 11.3, P = .005; with Mother T2DM, 50.4 ± 10.6 vs 52.3 ± 10.2, P = .019; with Other T2DM family history, 54.0 ± 10.8 vs 55.7 ± 9.5, P = .008; with no T2DM family history, 53.0 ± 11.0 vs 55.9 ± 9.3, P = .000). The order of the T2DM-diagnosed age in the different groups was Both parents T2DM (47.5 ± 11.0) and Father T2DM (47.9 ± 11.1) family history < that with Mother T2DM family history (51.1 ± 10.5) < that with Other T2DM family history (54.7 ± 10.3) and no T2DM family history (54.1 ± 10.5). Logistic regression analysis indicated that gender (OR, 1.733; P = .000), Father T2DM history (OR, 2.738; P = .000), Mother T2DM history (OR, 1.536; P = .001), Both parents T2DM (OR, 2.866; P = .000) and body mass index (OR, 1.108, P = .000) were correlated with early-onset T2DM. Conclusion: Patients with early-onset T2DM tend to have a more obvious T2DM family history in China. This survey shows that when a parent has a T2DM family history, especially the father with T2DM, male patients are diagnosed with T2DM earlier. We need more intensive screening for diabetes in children with a family history of diabetes, especially in male children.

Background: We aimed to determine the role of non-mydriatic fundus examination and artificial intelligence (AI) in screening diabetic retinopathy (DR) in patients with diabetes in the Metabolic Disease Management Center (MMC) in Tianjin, China. Methods: Adult patients with type 2 diabetes mellitus who were first treated by MMC in Tianjin First Central Hospital and Tianjin 4th Center Hospital were divided into two groups according to the time that MMC was equipped with the non-mydriatic ophthalmoscope and AI system and could complete fundus examination independently (the former was the control group, the latter was the observation group). The observation indices were as follows: the incidence of DR, the fundus screening rate of the two groups, and fundus screening of diabetic patients with different course of disease. Results: A total of 5039 patients were enrolled in this study. The incidence rate of DR was 18.6%, 29.8%, and 49.6% in patients with diabetes duration of ⩽1 year, 1–5 years, and >5 years, respectively. The screening rate of fundus in the observation group was significantly higher compared with the control group (81.3% versus 28.4%, χ² = 1430.918, p < 0.001). The DR screening rate of the observation group was also significantly higher compared with the control group in patients with diabetes duration of ⩽1 year (77.3% versus 20.6%; χ² = 797.534, p < 0.001), 1–5 years (82.5% versus 31.0%; χ² = 197.124, p < 0.001) and ⩾5 years (86.9% versus 37.1%; χ² = 475.609, p < 0.001). Conclusions: In the case of limited medical resources, MMC can carry out one-stop examination, treatment, and management of DR through non-mydratic fundus examination and AI assistance, thus incorporating the DR screening process into the endocrine clinic, so as to facilitate early diagnosis.

Objective: To observe the consistency of a preliminary report of artificial intelligence (AI) in the clinical practice of fundus screening for diabetic retinopathy (DR) using non-mydriatic fundus photography. Methods: Patients who underwent DR screening in the Metabolic Disease Management Center (MMC) of our hospital were selected as research participants. The degree of coincidence of the AI preliminary report and the ophthalmic diagnosis was compared and analyzed, and the kappa value was calculated. Fundus fluorescein angiography (FFA) was performed in patients referred to the out-of-hospital ophthalmology department, and the consistency between fluorescein angiography and AI diagnosis was evaluated. Results: In total, 6146 patients (12,263 eyes) completed the non-mydriasis fundus examination. The positive DR screening rate was 24.3%. When considering moderate nonproliferative retinopathy as the cut-off point, the kappa coefficient was 0.75 ( p < 0.001), the sensitivity was 0.973, and the precision was 0.642, which was shown in the precision–recall curve. Fifty-nine patients referred to receive FFA were compared with non-mydriatic AI diagnoses. The kappa coefficient was 0.53, and the coincidence rate was 66.9%. Conclusion: Non-mydriasis fundus examination combined with AI has a medium-high consistency with ophthalmologists in DR diagnosis, conducive to early DR screening. Combining diagnosis and treatment modes with the Internet can promote the development of telemedicine, alleviate the shortage of ophthalmology resources, and promote the process of blindness prevention and treatment projects.