Family history of diabetes is associated with diabetic foot complications in type 2 diabetes

Evaluation of Factors Affecting Neuropathy in Patients With Type 2 Diabetes Using Artificial Neural Networks

INTRODUCTION

Neuropathy is a common and debilitating complication in type 2 diabetes, affecting quality of life and increasing healthcare costs. Identifying risk factors is essential for early intervention and management. This study aims to evaluate the factors influencing the occurrence of neuropathy in patients with type 2 diabetes using artificial neural networks.

METHODS

In this cohort study, data from 371 patients with type 2 diabetes from Fereydunshahr, Iran, were analyzed over a 12-year follow-up period. Participants were selected based on diabetes screenings conducted in 2008 and 2009. Artificial neural networks with varying architectures were trained and validated, and their performance was compared to logistic regression models using receiver operating characteristic (ROC) curve analysis.

RESULTS

The prevalence of neuropathy in this cohort study was 31.2%. The best-fitted artificial neural network and logistic regression model had area under the curve (AUC) values of 0.903 and 0.803, respectively. Significant risk factors identified included gender, race, family history of diabetes, type of diabetes treatment, cholesterol levels, triglyceride levels, high-density lipoprotein (HDL) levels, and duration of diabetes. Notably, women, patients with a family history of diabetes, and those using injectable or combined injectable and oral medications were at higher risk of developing neuropathy.

CONCLUSION

These findings highlight the importance of vigilant monitoring and proactive management of neuropathy risk factors, especially in women, patients with a family history of diabetes, and those using injectable or combined diabetic medications.

The interaction of perfluoroalkyl acids and a family history of diabetes on arthritis: analyses of 2011-2018 NHANES

Whether a family history of diabetes (FHD) and exposure to perfluoroalkyl acids (PFAAs) are correlated with an increased risk of developing arthritis remains unclear. This cross-sectional study was conducted to explore the correlations between FHD or exposure to PFAAs and arthritis as well as their interaction using the National Health and Nutrition Examination Survey (NHANES). In total, 6,194 participants aged ≥ 20 years from the 2011-2018 NHANES were enrolled. PFAAs are a cluster of synthetic chemicals, including perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorodecanoic acid (PFDA) and perfluorohexane sulfonic acid (PFHxS). FHD was evaluated using self-reported questionnaires. Arthritis was classified into three types, rheumatoid arthritis (RA), osteoarthritis (OA), and others, which were diagnosed using questionnaires. Generalized linear models (GLMs) were used to test the correlation between FHD and arthritis. To examine the joint effects of PFAAs and FHD on arthritis, interaction terms were applied in the GLM. Arthritis incidence was 26.7% among all participants. FHD was associated with both RA [OR = 1.70 (95% CI: 1.15-2.50)] and other types of arthritis [OR = 1.62 (95% CI: 1.21-2.16)]. However, the relationship between FHD and OA was not significant after adjustment (P = 0.18). Interaction outcomes indicated that higher PFDA levels increased the association between FHD and arthritis. FHD is associated with an increased incidence of arthritis, which may be increased by PFDA. Given the heavy burden of arthritis, preventive measures for arthritis and reduction of PFAAs exposure for patients with FHD are required.

Interaction analysis of lipid accumulation product and family history of diabetes on impaired fasting glucose and diabetes risk in population with normotension in Eastern China: a community-based cross-sectional survey

BACKGROUND

Lipid accumulation product (LAP) is considered to be a new convenient useful indicator to assess the visceral fat. Therefore, we aimed to evaluate the risk factors of impaired fasting glucose (IFG) and diabetes, and explore the possible interacting influences of LAP with other factors on the risk of IFG and diabetes among Chinese normotension adults.

METHODS

A multistage stratified cluster sampling method was conducted to select urban residents in Bengbu, China. For each eligible participant, data on questionnaire survey, anthropometric measurements and laboratory tests were obtained. The effects of body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR) and LAP for predicting IFG and diabetes were performed by multiple logistic regressions and receiver operating characteristic (ROC) analyses. The interaction effects were evaluated by relative excess risk of interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI).

RESULTS

Six thousand, four hundred sixty-seven normotension subjects (2695 men and 3772 women) were enrolled in our study, the prevalence of IFG and diabetes were 9.37% and 14.33%, respectively. When assessed using ROC curve analysis, LAP exhibited higher diagnostic accuracy for identifying IFG and diabetes than BMI, the area under the AUC curve was 0.650 (95% CI: 0.637 to 0.662). After adjustment for age, sex, educational level and other confounding factors, multivariate logistic regression analyses indicated that subjects with the fourth quartile of LAP were more likely to develop IFG (adjusted OR: 2.735, 95% CI: 1.794-4.170) and diabetes (adjusted OR: 1.815, 95% CI: 1.297-2.541) than those with the first quartile. A significant interaction between LAP and family history of diabetes was observed in participants (RERI = 1.538, 95%CI: 0.167 to 3.612; AP = 0.375, 95%CI: 0.118 to 0.631; SI = 1.980, 95%CI: 1.206 to 3.251). However, a significant interaction between LAP and abdominal obesity was indicated by the value of RERI (1.492, 95%CI: 0.087 to 3.723) and AP (0.413, 95%CI: 0.014 to 0.756), but not the value of SI (1.824, 95%CI: 0.873 to 3.526).

CONCLUSION

Our results demonstrated that there might be synergistic effect between LAP and family history of diabetes on the risk of IFG and diabetes.

A prediction model for worsening diabetic retinopathy after panretinal photocoagulation

BACKGROUND

As one of the severe complications of diabetes mellitus, diabetic retinopathy (DR) is the leading cause of blindness in the working age worldwide. Although panretinal photocoagulation (PRP) was standard treatment, PRP-treated DR still has a high risk of progression. Hence, this study aimed to assess the risk factors and establish a model for predicting worsening diabetic retinopathy (DR-worsening) within five years after PRP.

METHODS

Patients who were diagnosed with severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy and treated with PRP were included, and those patients were randomly assigned to either a training or validation cohort. The multivariate logistic regression analysis was used to screen potential risk factors for DR-worsening in the training cohort. Then the model was established after including significant independent risk factors and further validated using discrimination and calibration.

RESULTS

A total of 271 patients were included, and 56.46% of patients had an outcome of DR-worsening. In the training cohort (n = 135), age (odds ratio [OR] = 0.94, 95% confidence interval [CI] 0.90-0.98), baseline best corrected visual acuity (logMAR) (OR = 10.74, 95% CI 1.84-62.52), diabetic nephropathy (OR = 9.32, 95% CI 1.49-58.46), and hyperlipidemia (OR = 3.34, 95% CI 1.05-10.66) were screened out as the independent risk factors, which were incorporated into the predictive model. The area under the receiver operating characteristic curve and calibration slope in the training and validation cohort were 0.79, 0.96 (95% CI 0.60-1.31), and 0.79, 1.00 (95% CI 0.66-1.34), respectively. Two risk groups were developed depending on the best cut-off value of the predicted probability, and the actual probability was 34.90% and 82.79% in the low-risk and high-risk groups, respectively (P < 0.001).

CONCLUSIONS

This study developed and internally validated a new model to predict the probability of DR-worsening after PRP treatment within five years. The model can be used as a rapid risk assessment system for clinical prediction of DR-worsening and identify individuals at a high risk of DR-worsening at an early stage and prescribe additional treatment.

Knowledge and practice of diabetic foot care and the prevalence of diabetic foot ulcers among diabetic patients of selected hospitals in the Volta Region, Ghana

Diabetic foot ulcers (DFUs) are a common but serious complication of diabetes mellitus (DM). The factors distressing the worth of diabetic foot care (DFC) are knowledge and practice. Foot ulcers are the main cause of amputation and death in people suffering from DM. This study assessed the knowledge and practice of DFC and the prevalence of DFUs and its associated factors among diabetic patients of selected hospitals in the Volta Region, Ghana. A multihospital-based cross-sectional study was conducted among 473 patients with DM who were recruited using the systematic sampling method. Data were collected using a validated, pretested, and structured questionnaire, while medical variables were obtained from patient folders and analysed using SPSS version 23. All statistically significant parameters in bivariate analysis were incorporated in the multivariate logistic regression analysis. The results showed that 63% of diabetic patients had good knowledge of DFC, while 49% competently practiced it. A negative correlation was found between knowledge and practice levels of DFC (r = -0.15, P = <.01). The prevalence of DFUs was 8.7% among the studied diabetic patients. Male diabetic patients were 3.4 times more likely to develop DFUs than female diabetic patients (crude odd ratio [cOR] = 3.35; 95% confidence interval [CI] = 1.75-6.43; P = <.001). Type 1 diabetic patients were five times more likely to develop DFUs than those who had type 2 diabetes (cOR = 5.00; 95% CI = 2.50-10.00; P = <.001). Diabetic patients who had a family history of diabetes were 4.7 times more likely to develop DFUs than those without family history (adjusted odd ratio [aOR] = 4.66; 95% CI = 1.55-13.89; P = .006). Those who had diabetes for 5 to 10 years were 3.3 times more likely to develop DFUs than those who had diabetes for less than 5 years (aOR = 3.28; 95% CI = 1.40-7.67; P = .006). Diabetic patients who had comorbidity were 3.4 times more likely to develop DFUs than those without comorbidity (cOR = 3.35; 95% CI = 1.74-6.45; P = <.001). The study found that there was good knowledge but poor practices of DFC among patients. Health care providers are expected to better educate patients and emphasise self-care practices to patients. Health care providers should also give more attention to patients with associated risk factors to avoid further complications and reduce the occurrence of DFUs.