Hyperuricemia (HUA) caused by elevated serum uric acid (SUA) has become the fourth most common disease after hyperglycemia, hyperlipidemia, and hypertension, and the second most common metabolic disease after diabetes. It has been shown that elevated SUA levels are significantly associated with the risk of type 2 diabetes mellitus (T2DM). However, there is a lack of studies on Chinese population and studies on HUA combined with unhealthy lifestyle or chronic disease.
To investigate the association between baseline SUA levels, HUA combined with unhealthy lifestyle or chronic diseases and the risk of T2DM in health examination population.
A total of 17 626 individuals meeting the inclusion and exclusion criteria who had underwent at least two physical examinations from 2017 to 2020 in Preventive Treatment & Health Management Center, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine were selected as the subjects. Information about their demographics, lifestyle, physical examination results, and laboratory indicators was collected. A follow-up was carried out with them until the onset of T2DM or the end of follow-up (2020-12-31), during which the onset day of T2DM and clinical visit information for T2DM were collected. The cumulative incidence and incidence density of T2DM in the total population, and cumulative incidence of T2DM in subgroups were calculated. The Cox proportional-hazards model was used to investigate the association between baseline SUA level and the risk of T2DM. And stratified multivariate Cox proportional-hazards regression model was used to further analyze their association in different subgroups.
The subjects had a median age of 38.2 (31.9, 49.6) years, a median baseline SUA level of 304.50 (248.00, 374.00) μmol/L, and an overall prevalence of HUA of 13.12%. The cumulative follow-up was 54 633 person-years, with a median follow-up of 3.10 years. There were 479 new cases of T2DM. The incidence density was 8.77 〔95%CI (8.00, 9.59) 〕 /1 000 person-years and the cumulative incidence rate was 2.72%〔95%CI (2.48%, 2.97%) 〕. Higher cumulative incidence rate of T2DM was found in older age group (≥60 years old), male cases, or those with current smoking, current alcohol drinking, BMI≥28.0 kg/m2, hypertension, dyslipidemia, or HUA. The multivariate-adjusted Cox proportional hazards regression model showed that HUA patients had an increased risk of T2DM, with an HR of 1.32〔95%CI (1.04, 1.67), P=0.023〕. For every 10 μmol/L increase in baseline SUA level, the risk of T2DM increased by 3%〔HR=1.03, 95%CI (1.01, 1.04), P<0.001〕. Stratified analysis of multivariate Cox proportional hazards regression model showed that the risk of T2DM increased in 60-year-olds and above〔HR=6.78, 95%CI (4.16, 11.03), P<0.001〕, females 〔HR=2.31, 95%CI (1.54, 3.45), P<0.001〕, current smokers 〔HR=1.79, 95%CI (1.23, 2.60), P=0.002〕, current alcohol drinkers 〔HR=1.61, 95%CI (1.23, 2.10), P<0.001〕, individuals with BMI≥28.0 kg/m2〔HR=1.69, 95%CI (1.07, 2.68), P=0.026〕, hypertensioners 〔HR=2.89, 95%CI (2.15, 3.89), P<0.001〕, or individuals with dyslipidemia 〔HR=2.39, 95%CI (1.80, 3.16), P<0.001〕with HUA.
Elevated baseline SUA levels are associated with a high risk of T2DM in health examination population, and the risk may be even higher in elderly people, females, current smokers, current drinkers, individuals with obesity, hypertension, or dyslipidemia with HUA.
Type 2 diabetes mellitus increases the risk of early onset of cardiovascular disease in patients, which poses a major threat to human health. Exploring the impact of type 2 diabetes mellitus on prognosis of patients with dilated cardiomyopathy is good for patient management.
To evaluate the effect of type 2 diabetes mellitus on the prognosis of patients with dilated cardiomyopathy.
This study retrospectively analyzed 313 patients with dilated cardiomyopathy who were admitted to the Department of Cardiology in the First Affiliated Hospital of Guangxi Medical University from January 2015 to May 2020. Patients were divided to a diabetic group (n=66) or a non-diabetic group (n=247) according to whether they suffered from type 2 diabetes mellitus. General date and laboratory indices were collected. Follow-up was conducted until December 31, 2021. The primary endpoint was all-cause death. This study used landmark analysis to compare survival rate between these two groups. A multivariate Cox proportional hazards regression model was used to analyze the influencing factors of all-cause mortality in patients with dilated cardiomyopathy.
Landmark analysis showed that there was no significant difference in one-year survival rate between these two groups (χ2=1.520, P=0.218). After 1 year, the survival rate in the diabetic group was lower than that of the non-diabetic group (χ2=4.414, P=0.036). In the multivariate Cox proportional hazards regression model constructed by piecewise fitting method, systolic blood pressure〔HR=0.965, 95%CI (0.948, 0.982) 〕, N-terminal pro-B-type natriuretic peptide〔HR=9.928, 95%CI (4.791, 20.576) 〕 and β-receptor blocker〔HR=0.317, 95%CI (0.168, 0.598) 〕 were the influencing factors of all-cause mortality in patients with dilated cardiomyopathy within one year (P<0.05), while LVEDD〔HR=1.057, 95%CI (1.028, 1.087) 〕and type 2 diabetes mellitus〔HR=1.756, 95%CI (1.011, 3.050) 〕were influencing factors of all-cause mortality in patients with dilated cardiomyopathy after one year (P<0.05) .
Type 2 diabetes mellitus was not associated with adverse outcomes in patients with dilated cardiomyopathy at 1 year of follow-up, but was strongly associated with poor outcomes after 1 year in patients with dilated cardiomyopathy.
In recent years, artificial intelligence (AI) has shown rapid development in the medical field, and its application in diabetic retinopathy (DR) has been expanding.
To summarize the application of AI in DR through bibliometric analysis and elucidate the current status, hot spots and emerging trends of AI-related research in DR, with a view to providing ideas for future research.
The research was performed on the Web of Science database for the researches related to AI applications in DR from inception to 2022-11-04 and used CiteSpace software to conduct bibliometric analysis of the number of articles, countries, institutions, authors, co-citation and keywords in the literature.
A total of 1 770 papers were obtained, with an overall increasing trend in the number of publications and a peak of 402 papers in 2021. China was the top country in terms of the number of publications (440), and the UK was the country with the highest intermediary centrality (0.26). A total of 436 institutions were included in the institutional collaboration network mapping, represented by Sun Yat-sen University and Capital Medical University. A total of 601 authors were included in the author collaboration network mapping, represented by JIA Y L and HWANG T. Three highly cited authors, GULSHAN V, ABRàMOFF M D and TING D W, have made important contributions to the field. Ophthalmology, Invest Ophth Vis Sci and Ieee T Med Imaging are the three most influential journals in the field of AI applied to DR. The research hot spots were mainly focused on lesion segmentation and DR diagnosis. The future research trends may be efficacy prediction of diabetic macular edema as a complication of DR, disease management and improvement of AI algorithm performance.
Researchers can refer to the research hot spots and trends shown by this bibliometric analysis, focusing on AI in DR diagnosis, disease management and improvement of AI algorithm performance.
Diabetic foot ulcer (DFU) is a serious diabetic complication with a high recurrence rate after healing. There is a lack of systematic evidence-based studies on multiple risk factors associated with its recurrence.
To investigate the risk factors for DFU recurrence after healing, providing evidence to inform the prevention and treatment of DFU.
A case-control study design was used. Patients with an initial inpatient diagnosis of DFU were selected from Hospital of Chengdu University of TCM from January 1, 2016 to February 1, 2019 as the source population, among whom those with and without a recurrence within three years after healing were assigned to case and control groups, respectively. Baseline characteristics, information related to diabetes and DFU were collected from both groups. Risk factors for DFU recurrence were screened by unconditional multivariate Logistic regression analysis. The relationships of DFU recurrence with the number of risk factors and the time to recurrence were further analyzed.
Among the source population (n=256), 210 had healed DFU, and 190 of them were included for final analysis after excluding 12 missing cases and 8 with incomplete information. The overall recurrence rate within three years after DFU healing was 45.3% (86/190). Multivariate Logistic regression analysis showed that age >60 years〔OR=3.270, 95%CI (1.335, 8.005), P=0.010〕, HbA1c >7.5%〔OR=2.691, 95%CI (1.242, 7.687), P=0.045〕, peripheral arterial disease (PAD) 〔OR=2.241, 95%CI (1.185, 5.101), P=0.044〕, osteomyelitis〔OR=3.256, 95%CI (1.369, 7.744), P=0.008〕, callus〔OR=2.068, 95%CI (1.262, 4.446), P=0.043〕, ankle-brachial index (ABI) <0.9〔OR=3.616, 95%CI (1.436, 9.102), P=0.006〕, plantar ulcers〔OR=2.192, 95%CI (1.061, 4.998), P=0.042〕, and Wagner grade ≥3〔OR=5.522, 95%CI (2.484, 12.273), P<0.001〕 were risk factors for DFU recurrence. The number of comorbid risk factors mainly ranged from 5 to 9 in the case group (n=86), and 2 to 5 in the control group (n=104). The number of recurrent cases within one, two and three years in the case group was 35, 28 and 23, respectively. The one-, two- and three-year cumulative recurrence rates were 18.4% (35/190), 33.2% (63/190), and 45.3% (86/190), respectively.
The high recurrence rate of DFU may be associated with risk factors such as age >60 years, HbA1c >7.5%, PAD, osteomyelitis, callus, ABI <0.9, plantar ulcers, and Wagner grade ≥3.
