Increased cardiovascular risk in people with type 2 diabetes and periodontitis: an analysis from a global real-world federated database.

Oxidative stress (OS) is involved in the development of diabetes, but the genetic mechanisms are not completely understood. We integrated multi-omics data in order to explore the genetic relations between OS-related genes, diabetes mellitus, and microvascular complications using Mendelian randomization and colocalization analysis. Summary-level data related to OS were acquired from respective studies of methylation, expression, and protein abundance quantitative trait loci. Genetic associations concerning diabetes, diabetic nephropathy (DN), and diabetic retinopathy (DR) were derived from the FinnGen study. Summary-data-based Mendelian randomization (SMR) analysis was conducted to evaluate the correlations between molecular features concerned with OS-related genes and diabetes mellitus, along with its microvascular complications. Additionally, we performed colocalization analysis to determine if the detected signal pairs shared a causal genetic variant. At the genetic level, we identified ten potential causal associations of oxidative stress genes with diabetes, along with microvascular complications, through SMR and colocalization analysis. After integrating the DNA methylation quantitative trait loci (mQTL) and expression QTL (eQTL) data, our analyses revealed a correlation between the methylation site cg26343298 and reduced expression of TP53INP1, supporting the protective role of cg26343298 methylation on type 2 diabetes (T2D) and diabetic nephropathy. Similarly, an inverse association was observed between gene methylation and expression in CHEK1 (cg07110182), confirming the beneficial effect of modification of CHEK1 by cg07110182 in diabetic retinopathy. In addition, upregulation of SUOX expression by cg22580629 was linked to a reduced risk of diabetic retinopathy. At circulating protein levels, genetically predicted a higher level of ICAM1 (OR 1.05, 95%CI 1.03-1.08) was positively connected with the risk of diabetic retinopathy. This SMR study elucidated that the TP53INP1 gene was putatively associated with T2D and DN risk, while the SUOX and CHEK1 genes were associated with DR risk through oxidative stress mechanisms. Additionally, our study showed a positive correlation between the ICAM-1 protein and DR. These findings may enhance our understanding of their pathogenesis and suggest new therapeutic targets for clinical practice.

This study aimed to investigate the associations between concurrent atrial fibrillation and diabetes-related complications among patients with diabetes. This nationwide observational cohort study used the health checkup database from the Korean National Health Insurance Service. Patients diagnosed with diabetes who underwent health checkups between 2009 and 2012 were investigated. The patients with atrial fibrillation were matched in a 1:5 ratio with those without atrial fibrillation using propensity scores. Study outcomes included macrovascular, microvascular (diabetic retinopathy and diabetic nephropathy), and diabetic foot complications. The risks of clinical outcomes were measured using hazard ratios (HRs) with 95% CIs. A total of 65,760 patients with diabetes were analyzed (54,800 without atrial fibrillation and 10,960 with atrial fibrillation). After well-balanced propensity score matching, atrial fibrillation was associated with significantly higher risks of macrovascular complications (HR 1.12, 95% CI 1.09-1.16), diabetic nephropathy (HR 1.23, 95% CI 1.16-1.30), and diabetic foot complications (HR 1.13, 95% CI 1.09-1.17) compared with no atrial fibrillation, while the risk of diabetic retinopathy was comparable (HR 0.99, 95% CI 0.96-1.03). Patients with atrial fibrillation had a significantly higher risk of diabetic foot amputation (HR 4.12, 95% CI 1.98-8.56). Among patients with diabetes, concurrent atrial fibrillation was associated with increased risks for diabetes-related macrovascular complications, diabetic nephropathy, and diabetic foot. Such patients require holistic management to reduce the risk of adverse outcomes.

<p dir="ltr">Objective: This study aimed to investigate the associations between concurrent atrial fibrillation and diabetes-related complications among patients with diabetes mellitus.</p><p dir="ltr">Research Design and Methods: This nationwide observational cohort study utilized the health check-up database from the Korean National Health Insurance Service. Patients diagnosed with diabetes mellitus who underwent health check-ups between 2009 and 2012 were investigated. The patients with atrial fibrillation were matched in a 1:5 ratio with those without atrial fibrillation using propensity scores. Study outcomes included macrovascular complications, microvascular complications (diabetic retinopathy and diabetic nephropathy), and diabetic foot. The risks of clinical outcomes were measured using hazard ratios (HRs) with 95% confidence intervals (CIs).</p><p dir="ltr">Results: A total of 65,760 patients with diabetes mellitus were analyzed (54,800 without atrial fibrillation and 10,960 with atrial fibrillation). After well-balanced propensity-score matching, patients with atrial fibrillation were associated with significantly higher risks of macrovascular complications (HR 1.12, 95% CI 1.09–1.16), diabetic nephropathy (HR 1.23, 95% CI 1.16–1.30), and diabetic foot complications (HR 1.13, 95% CI 1.09–1.17) compared to patients without atrial fibrillation, while the risk of diabetic retinopathy was comparable (HR 0.99, 95% CI 0.96–1.03). The patients with atrial fibrillation had a significantly higher risk of diabetic foot amputation (HR 4.12, 95% CI 1.98–8.56).</p><p dir="ltr">Conclusions: Among patients with diabetes mellitus, concurrent atrial fibrillation was associated with increased risks for diabetes-related macrovascular and microvascular complications and diabetic foot complications. Such patients require holistic management to reduce the risk of adverse outcomes.</p>

<p dir="ltr">Objective: This study aimed to investigate the associations between concurrent atrial fibrillation and diabetes-related complications among patients with diabetes mellitus.</p><p dir="ltr">Research Design and Methods: This nationwide observational cohort study utilized the health check-up database from the Korean National Health Insurance Service. Patients diagnosed with diabetes mellitus who underwent health check-ups between 2009 and 2012 were investigated. The patients with atrial fibrillation were matched in a 1:5 ratio with those without atrial fibrillation using propensity scores. Study outcomes included macrovascular complications, microvascular complications (diabetic retinopathy and diabetic nephropathy), and diabetic foot. The risks of clinical outcomes were measured using hazard ratios (HRs) with 95% confidence intervals (CIs).</p><p dir="ltr">Results: A total of 65,760 patients with diabetes mellitus were analyzed (54,800 without atrial fibrillation and 10,960 with atrial fibrillation). After well-balanced propensity-score matching, patients with atrial fibrillation were associated with significantly higher risks of macrovascular complications (HR 1.12, 95% CI 1.09–1.16), diabetic nephropathy (HR 1.23, 95% CI 1.16–1.30), and diabetic foot complications (HR 1.13, 95% CI 1.09–1.17) compared to patients without atrial fibrillation, while the risk of diabetic retinopathy was comparable (HR 0.99, 95% CI 0.96–1.03). The patients with atrial fibrillation had a significantly higher risk of diabetic foot amputation (HR 4.12, 95% CI 1.98–8.56).</p><p dir="ltr">Conclusions: Among patients with diabetes mellitus, concurrent atrial fibrillation was associated with increased risks for diabetes-related macrovascular and microvascular complications and diabetic foot complications. Such patients require holistic management to reduce the risk of adverse outcomes.</p>

POSTER PRESENTATIONS

Objective: Diabetic retinopathy (DR) is one of the most common microvascular complications of type 2 diabetes (T2D). The reported prevalence of DR from different populations in the last decade was 13 - 38.1%. A report from our center 17 years ago showed that DR prevalence was 43.6%. With the all accumulated evidence showing that diabetes control decreases DR risk and the introduction of new drugs that helped better T2D control, we aimed to assess the current prevalence and predictors of DR among patients with T2D attending out-patient department at our tertiary care center. Methods: We conducted a cross-sectional study involving 638 patients. We collected information about their baseline characteristics, confirmed DR with its severity and maculopathy diagnosis, age at T2D diagnosis, duration of T2D, and averages of HbA1C, blood pressure (BP), cholesterol, and vitamin D levels over the previous year. A statistical analysis was performed using the software SPSS 23.0. A multivariate logistic regression analysis examined the independent predictors of DR development. Results: The mean age of the patients was 55.8 ± 10.3 years, and 42.8% were males. The mean BMI was 32.4 ± 12.4 kg/m2 with 58% had obesity. The mean duration of T2D was 11.5 ± 7.7 years, and the mean age at T2D diagnosis was 44.0 ± 9.98 years. The mean HbA1C was 8.3 ± 1.6 % with 77% had average HbA1C above 7% and 51.3% had average HbA1c above 8%. The mean systolic and diastolic BP were 136.37 ± 15.01 mmHg and 74.12 ± 8.078 mmHg, respectively. DR was diagnosed in 223 cases (35%). Of the 638 patients, 24.5% had non-proliferative DR, 9.2% had proliferative DR, and 4.2% had maculopathy. There was no significant difference in DR prevalence between males (36%) and females (34.1%) (P = 0.59). Predictors of DR development were age above 40 years, duration of T2D more than 10 years, early age of T2D diagnosis, average HbA1C more than 8%, and hypertension. Discussion: T2D is a major health challenge to our community with its very high prevalence. The prevalence of DR in T2D patients attending our institution was significant (more than one-third, 35%) in comparison to reports from other centers. However, we showed an improvement in DR development in our patients from 43.6% to 35%, probably due to better T2D and BP control. Similar to previous reports, T2D patients with older age, long T2D duration, younger age at T2D diagnosis, uncontrolled diabetes, and uncontrolled BP were more likely to develop DR. Conclusion: Physicians treating T2D patients should ensure regular retina screening especially for those with risk factors for DR. Also, they should fix the modifiable risk factors of DR; diabetes and BP control.

BackgroundThis study compared the risks of cardiovascular morbidity and mortality between patients with type 2 diabetes (T2D) with and without microvascular diseases, and between matched patients with microvascular diseases.MethodsWe identified newly diagnosed type 2 diabetes patients from National Health Insurance Research Database in Taiwan from January 1, 2008, to December 31, 2019. Propensity score matching was applied to construct matched pairs of patients with diabetic kidney disease, retinopathy, or neuropathy. Multivariable Cox proportional-hazard models were adopted to compare the risks of cardiovascular morbidity and mortality.ResultsPatients with microvascular disease had a significantly higher risk of cardiovascular morbidities and mortality than those without microvascular disease. Among the matched cohorts, patients with diabetic retinopathy had a significantly higher risk of stroke development than those with diabetic kidney disease (aHR 1.11, 95%CI 1.03–1.2). Diabetic neuropathy showed a significantly higher risk of stroke development than diabetic kidney disease (aHR 1.17, 95%CI 1.1–1.25) and diabetic retinopathy (aHR 1.12, 95%CI 1.03–1.21). Diabetic retinopathy had a significantly higher risk of incident heart failure than diabetic kidney disease (aHR 1.43, 95%CI 1.3–1.57), and diabetic neuropathy had a significantly lower risk of incident heart failure than diabetic retinopathy (aHR 0.79, 95%CI 0.71–0.87).ConclusionsT2D patients with microvascular disease have a significantly higher risk of cardiovascular morbidities and mortality than those without microvascular disease. In the matched cohorts, diabetic neuropathy was significantly associated with stroke development, and diabetic retinopathy had a significant association with heart failure compared to other microvascular diseases.

Diabetic retinopathy (DR) is the primary microvascular complication associated with diabetes. Evidence on DR prevalence among children in New Zealand is scarce. We examined DR rates and associated risk factors in youth with type 1 diabetes (T1D) aged <16 years receiving care from a regional diabetes service in January 2006-December 2020. DR diagnosis followed the International Society for Pediatric and Adolescent Diabetes guidelines. The study included 646 participants; mean age (±SD) at T1D diagnosis was 7.4 ± 3.6 years, 47% were female, and 69% identified as NZ Europeans. The initial DR screening occurred at a mean age of 12.6 ± 2.4 years and 5.2 ± 2.2 years after T1D diagnosis. At the first DR screen, 23.5% of participants (152/646) were diagnosed with DR: 69.1% (105/152) with minimal, 30.3% (46/152) with mild, and one moderate case (0.7%). Older age at diagnosis (p=0.029) and longer diabetes duration (p=0.015) were predictors of DR at first screen. Patients with at least one positive DR screen had a higher average HbA1c at their first screen (+2.6 mmol/mol; p=0.042). Overall, 55.6% (359/646) of patients had a positive DR screen, whose worst grade was mostly either minimal (58.2%) or mild (40.7%) DR, with only three moderate cases (0.8%) and one severe (0.3%). Children diagnosed with T1D before age 10 were 72% more likely to have DR than older children (p < 0.0001), and DR risk was 32% and 41% higher among Pacific children than NZ European (p=0.008) and Māori (p=0.014) children. Lastly, the only predictor of DR at discharge from paediatric services was HbA1c at the first screen (p < 0.0001). In this regional cohort of children with T1D, there was a high rate of low-grade DR overall and at first retinal screen, with an increasing rate until transfer to adult services. Our findings underscore the importance of ongoing DR screening, reducing glycaemic levels, and supporting vulnerable high-risk groups.

Background: Diabetic retinopathy, nephropathy and neuropathy in patients with type 1 diabetes (T1D) are microvascular complications that can adversely impact disease prognosis and incur greater healthcare costs. Early identification of patients at risk of these microvascular complications using predictive models through machine learning (ML) can be helpful in T1D management. The objective of current review was to systematically identify and summarize published predictive models that used ML to assess the risk of diabetic nephropathy, retinopathy and neuropathy in T1D patients. Methods: A targeted review of English literature was undertaken in PubMed (http://www.ncbi.nlm.nih. gov/pubmed) and Google Scholar (http://scholar.google.com/) from January 1, 2016 to May 31, 2019. Eligible articles were also identified from cross-references. Following concepts were used in combination to conduct the search queries: diabetes, retinopathy, nephropathy, neuropathy, microvascular complication, risk/predictive model, and ML/artificial intelligence/data mining. Results: A total of 3,769 hits were found from all sources combined, duplicates were removed, titles and abstracts were screened, 61 studies underwent full-text review and a total of six studies met the eligibility criteria. Among them, four studies had developed risk models using data obtained from T1D patients alone, whereas two used data from both T1D and type 2 diabetes (T2D) patients. There was only one study that evaluated all three types of microvascular complications while the other five focused on one individual complication, i.e., either diabetic retinopathy, nephropathy or neuropathy. Only two studies evaluated time to developing a complication. The other four studies assessed complications as either binary (yes/no) or categorical (multiple levels). Prediction models were built using cross-sectional data from survey questionnaire (n=1, Iran) and longitudinal data (n=5) which were further classified as sources of electronic medical records (EMR) (n=3, US: 1, Europe: 2), clinical trial (n=1, US) and prospective study (n=1, Europe). Common predictors across studies as well as across types of microvascular complications included age, gender, diabetes duration, BMI, blood pressure, lipid level, and mean or a single HbA1C value. Commonly used ML algorithms included classification and regression tree (CART) and random forest (RF) (CART/RF, n=3), support vector machines (SVMs, n=2), logistic regression (LR, n=2) and neural networks (NNs, n=1). Model performance was evaluated using area under curve (AUC, n=4) and accuracy (n=2). Only half (n=3) of the included studies tested their developed models in an external dataset of patients with T1D. Conclusions: Overall, very few studies reported predictive models for diabetic retinopathy, nephropathy and neuropathy using ML specifically for T1D patients. Future research that utilizes contemporary clinical data from T1D patients to predict the three types of microvascular complications is needed.

Objective To explore the related risk factors of type 2 diabetic nephropathy,and to provide theoretical basis to make the strategy of prevention of diabetic nephropathy.Methods By case-control study method,98 patients with type 2 diabetic nephropathy were selected as the observation group.98 diabetes mellitus patients without kidney disease were selected as control group.Single factor analysis and non-conditional logistic regression analysis were conducted in two groups.Results The results of single factor analysis showed that type 2 diabetic nephropathy was closely related to family history of diabetes,course of diabetes,high blood pressure,diabetic retinopathy,BMI,coronary heart disease,HbAlc,FPG,2hPG,CRP (P ＜ 0.05).The results of multiple factors of logistic regression showed that type 2 diabetic nephropathy was closely related to course of diabetes and diabetic retinopathy,CRP,HbA1c,FPG(P ＜0.05).Conclusion Course of diabetes and diabetic retinopathy,CRP,HbA1c,FPG are independent risk factors for type 2 diabetic nephropathy. Key words: Diabetic nephropathy; Logistic regression analysis ; Risk factors

Objectives: Atrial fibrillation (AF) is linked to an increased risk of stroke and dementia. Atrial flutter (AFL) is also linked to an increased risk of stroke but at a different level of risk as compared to AF. Little is known about the difference in the risk of dementia between AF and AFL. This study aims to investigate whether the risk of dementia is different between AF and AFL.Methods: Patients with newly diagnosed AF and AFL during 2001–2013 were retrieved from Taiwan's National Health Insurance Research Database. Patients with incomplete demographic data, aged <20 years, history of valvular surgery, rheumatic heart disease, hyperthyroidism, and history of dementia were excluded. The incidence of new-onset dementia was set as the primary outcome and analyzed in patients with AF and AFL after propensity score matching (PSM).Results: A total of 232,425 and 7,569 patients with AF and AFL, respectively, were eligible for analysis. After 4:1 PSM, we included 30,276 and 7,569 patients with AF and AFL, respectively, for analysis. Additionally, patients with AF (n = 29,187) and AFL (n = 451) who received oral anticoagulants were enrolled for comparison. The risk of dementia was higher in patients with AF compared with patients with AFL (subdistribution hazard ratio (SHR) = 1.52, 95% CI 1.39–1.66; p < 0.0001) before PSM and remained higher in patients with AF (SHR = 1.14, 95% CI 1.04–1.25; p = 0.0064) after PSM. The risk of dementia was higher in patients with AF without previous history of stroke after PSM but the risk did not differ between patients with AF and AFL with previous history of stroke. Among patients who received oral anticoagulants, the cumulative incidences of dementia were significantly higher in patients with AF than in patients with AFL before and after PSM (all P < 0.05).Conclusions: This study found that, among patients without history of stroke, the risk of dementia was higher in patients with AF than in patients with AFL, and CHA2DS2-VASc score might be useful for risk stratification of dementia between patients with AF and AFL.

From A Population to Patients: The Wisconsin Epidemiologic Study of Diabetic Retinopathy

This systematic review and meta-analysis aimed to assess the predictive value of diabetic retinopathy (DR) on further diabetic nephropathy (DN) risk in patients with type 2 diabetes (T2D) based on the prospective cohort studies. PubMed, Embase, and the Cochrane Library were systematically searched for eligible prospective cohort studies through March 2020. The predictive value of DR was assessed using sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) through the bivariate generalized linear mixed model and the random-effects model. Ten prospective cohort studies recruited 635 patients with T2D. The pooled sensitivity and specificity of DR for predicted DN were noted to be 0.64 (95% CI, 0.54–0.73) and 0.77 (95% CI, 0.60–0.88), respectively. The pooled PLR and NLR of DR for predicted DN were 2.72 (95% CI, 1.42–5.19) and 0.47 (95% CI, 0.33–0.67), respectively. The summary DOR for the relationship between DR and subsequent DN for T2D patients was 5.53 (95% CI, 2.00–15.30), and the AUC of DR for predicted DN was 0.73 (95% CI, 0.69–0.77). This study found significant associations between DR and subsequent DN risk for patients with T2D. Moreover, the predictive value of DR on subsequent DN risk was relatively lower.

Objective To establish an appropriate diabetic retinopathy (DR) risk assessment model for patients with type 2 diabetes mellitus (T2DM). Methods A retrospective clinical analysis. From January 2016 to December 2017, 753 T2DM patients in the Third Affiliated Hospital of Southern Medical University were analyzed retrospectively. Digital fundus photography was taken in all patients. Fasting plasma glucose (FPG), HbA1c, total bilirubin (TB), blood platelet, total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c), apolipoprotein-A (apoA), apolipoprotein-B (apoB), serum creatinine, blood urea nitrogen (BUN), blood uric acid, fibrinogen (Fg), estimated glomerular filtration (eGFR) were collected. The patients were randomly assigned to model group and testify group, each had 702 patients and 51 patients respectively. Logistic regression was used to screen risk factors of DR and develop an assessment scale that can be used to predict DR. Goodness of fit was examined using the Hosmer- Lemeshow test and the area under the receiver operating characteristic (ROC) curve. Results Among 702 patients in the model group, 483 patients were DR, 219 patients were NDR. The scores for DR risk were duration of diabetes ≥4.5 years, 4 points; total bilirubin <6.65 mol/L, 2 points; apoA≥1.18 g/L, 2 points; blood urea≥ 6.46 mmol/L, 1 points; HbA1c ≥7.75%, 2 points; HDL-c <1.38 mmol/L, 2 points; diabetic nephropathy, 3 points; fibrinogen, 1 point. The area under the receiver operating characteristic curve was 0.787. The logistic regression analysis showed that the risk factors independently associated with DR were duration of diabetes (β=1.272, OR=3.569, 95%CI 2.283−5.578, P<0.001), TB (β=0.744, OR=2.104, 95%CI 1.404−3.152, P<0.001, BUN (β=0.401, OR=1.494, 95%CI 0.996−2.240, P=0.052), HbA1c (β=0.545, OR=1.724, 95%CI 1.165−2.55, P=0.006), HDL-c (β=0.666, OR=1.986, 95%CI 1.149−3.298, P=0.013), diabetic nephropathy (β=1.151, OR=3.162, 95%CI 2.080−4.806, P=0.013), Fg (β=0.333, OR=1.396, 95%CI 0.945−2.061, P=0.094). The risk model was P=1/[1+exp−(−3.799+1.272X1+0.744X2+0.769X3+0.401X4+0.545X5+0.666X6+1.151X7+0.333X8)]. X1= duration of diabetes, X2=TB, X3=apoA, X4=BUN, X5=HbA1c, X6=HDL-c, X7=diabetic nephropathy, X8=Fg. The area under the ROC curve was 0.787 and the Hosmer-Lemeshow test suggested excellent agreement (χ2=10.125, df=8, P=0.256) in model group. The area under the ROC curve was 0.869 and the Hosmer-Lemeshow test suggested excellent agreement (χ2=5.345, df=7, P=0.618) in model group. Conclusion The area under the ROC curve for DR was 0.787. The duration of diabetes, TB, BUN, HbA1c, HDL-c, diabetic nephropathy, apoA, Fg are the risk factors of DR in T2DM patients. Key words: Diabetic retinopathy/prevention & control; Models, statistical; Forecasting

Objective To explore the influence of type 2 diabetes mellitus combined with subclinical hypothyroidism on diabetic vascular complications. Methods One hundred and two patients with type 2 diabetes mellitus were selected. The serum free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH), anti-thyroid peroxidase antibody (TPO-Ab), thyroglobulin antibody (TG-Ab) levels were measured by chemiluminescence method. The patients were divided into type 2 diabetes mellitus combined with subclinical hypothyroidism group (47 cases) and type 2 diabetes mellitus with normal thyroid function group (55 cases) according to the thyroid function. The glycated hemoglobin (HbA1c), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triacylglycerol (TG), high-density lipoprotein cholesterol (HDL-C), urea nitrogen, creatinine and albumin levels were measured. The estimated glomerular filtration rate (eGFR) was calculated according to the formula of modification of diet in renal disease (MDRD). The presence of diabetic retinopathy was examined by fundus examination, and the presence of lower limb artery lesions was measured by vascular ultrasound. All indicators were compared between 2 groups. Results There were no statistical differences in age, disease course, HbA1c, body mass index (BMI), TC, TG, HDL-C, LDL-C, incidence of lower limb artery lesions and incidence of diabetic retinopathy between 2 groups (P>0.05). The eGRF in type 2 diabetes mellitus combined with subclinical hypothyroidism group was significantly lower than that in type 2 diabetes mellitus with normal thyroid function group: (83.74±21.55) ml/(min·1.73 m2) vs. (115.02±12.29) ml/(min·1.73 m2), and there was statistical difference (t=4.274, P<0.01). The incidence of diabetic nephropathy in type 2 diabetes mellitus combined with subclinical hypothyroidism group was significantly higher than that in type 2 diabetes mellitus with normal thyroid function group: 48.9% (23/47) vs. 23.6%(13/55), and there was statistical difference (χ2=7.103, P<0.01). Logistic regression analysis showed that subclinical hypothyroidism was a risk factor for diabetic nephropathy (OR=0.524, 95% CI 0.12-0.93, P<0.05), but it was not the risk factor for diabetic retinopathy (OR=0.618, 95% CI 0.19-2.16, P = 0.475) and lower limb artery lesions (OR=0.485, 95% CI 0.32-2.13, P = 0.689). Conclusion Subclinical hypothyroidism in patients with type 2 diabetes mellitus has no obvious effect on lower limb arterial complications and diabetic retinopathy, but may increase the risk of diabetic nephropathy. Key words: Diabetes mellitus, type 2; Hypothyroidism; Diabetic angiopathies; Diabetic nephropathies