Journal of Diabetes and Metabolic Disorders最新文献

Objectives: Diabetic retinopathy (DR) is one of the leading causes of blindness. It is important to use a comprehensive learning method to identify the DR. However, comprehensive learning methods often rely heavily on encrypted data, which can be costly and time consuming. Also, the DR function is not displayed and is scattered in the high-definition image below.

Methods: Therefore, learning how to distribute such DR functions is a big challenge. In this work, we proposed a hybrid adaptive deep learning classifier for early detection of diabetic retinopathy (HADL-DR). First, we provide an improved multichannel-based generative adversarial network (MGAN) with semi-maintenance to detect blood vessels segmentation.

Results: By reducing the reliance on the encoded data, the following high-resolution images can be used to detect the indivisible features of some semi-observed MGAN references. Scale invariant feature transform (SIFT) function is then extracted and the best function is selected using the improved sequential approximation optimization (SAO) algorithm. After that, a hybrid recurrent neural network with long short-term memory (RNN-LSTM) is utilized for DR classification. The proposed RNN-LSTM classifier evaluated through standard benchmark Kaggle and Messidor datasets.

Conclusion: Finally, the simulation results are compared with the existing state-of-art classifiers in terms of accuracy, precision, recall, f-measure and area under cover (AUC), it is seen that more successful results are obtained.

Background: Metabolic syndrome (MetS) consists of a cluster of cardiometabolic risk factors and is an important determining factor for cardiovascular diseases (CVDs). We intended to use latent class analysis to classify the study population into several clusters.

Methods: The baseline information of 6,814 participants of the Multi-Ethnic Study of Atherosclerosis (MESA) aged 45-84 years in 2000-2002 was used. The latent class analysis was conducted to extract different patterns of components. SAS 9.2 and Stata 12 software were used for analysis.

Results: The components of MetS tend to accumulate, hence it would be feasible to categorize the population into three classes: [1] Non-Metabolic Syndrome Latent Class (NonMetS-LC), [2] Low Risk Latent Class (LowR-LC), and [3] Metabolic Syndrome Latent Class (MetS-LC). In women, adding high-density lipoprotein (HDL) component to the two-component combinations of NonMetS-LC will transfer the individual to MetS-LC, and it was found in 100% of combinations of MetS-LC. However, in men, blood pressure (BP) played such a similar role, which was found in 97.36% of combinations of MetS-LC.

Conclusion: Results showed that clinical value of each MetS component is different by gender. The main component in men was elevated BP; while low HDL and elevated fasting blood sugar (FBS) were in next ranks. However, the main component in women was low HDL; while elevated BP and FBS were in next ranks. Special attention should be paid to BP and HDL components, because these can be useful for clinicians and health policy-makers in diagnosis and screening. In conclusion, this study showed that revisions might be needed for the MetS definitions.

Graphical abstract:

Background: Despite the vulnerability of pulmonary tissue to diabetic conditions, there are few reports related to the detrimental effects of hyperglycemia and therapeutic modalities on lung parenchyma. Here, the apoptotic changes were monitored in the diabetic pulmonary tissue of mice (DM1) subjected to a four‒week swimming plan.

Methods: The mice were randomly allocated into Control; Control + Swimming (S); Diabetic group (D); and Diabetic + Swimming (D + S) groups (each in 8 mice). In the D and D + S groups, mice received intraperitoneally 50 mg/kg of streptozotocin (STZ). After 14 days, swimming exercise was done for four weeks. The expression of il-1β, bcl-2, bax, and caspase-3 was investigated using real-time PCR analysis. A histological examination was performed using H&E staining.

Results: DM1 significantly upregulated il-1β, bax, and caspase-3, and down-regulated bcl-2 compared to the non-diabetic mice (p < 0.05). We noted that swimming exercises reversed the expression pattern of all genes in the diabetic mice and closed to basal levels (p < 0.05). Data indicated that swimming exercise could diminish emphysematous changes, and interstitial pneumonitis induced by STZ. Along with these changes, swimming exercise had protective effects to reduce the thickness of the inter-alveolar septum and mean alveolar area in diabetic mice.

Conclusion: These data demonstrated that swimming exercises could decrease DM1-related pathologies in mouse lungs by regulating apoptosis and inflammatory response.

Purpose: The higher costs of insulin analogs including short-acting insulin aspart (IAsp) and long-acting insulin glargine (IGla) have restricted their widespread uptake despite having improved pharmacokinetic and pharmacodynamic properties and patient convenience. This study aims to evaluate the cost-effectiveness of IAsp versus Regular Insulin (RI) and IGla versus NPH Insulin in type 1 and 2 diabetes from the perspective of the Iranian healthcare system.

Methods: Clinical data including HbA1c levels, hypoglycemia, weight gain, and health-related quality of life were derived from the included systematic review and meta-analysis studies. Different methods of pharmacoeconomic evaluation were used for an annual time horizon. Utility decrements for diabetes-related complications were extracted from the literature. Direct medical costs were calculated in 2022 prices. A one-way sensitivity analysis was also performed.

Results: In type 1 diabetes, IAsp was associated with more costs and effects in terms of reducing HbA1c compared with RI. An incremental cost of $83 was estimated to obtain an additional 1% reduction in HbA1c per patient per year. Similarly, an incremental cost of $16 was estimated for IGla compared with NPH. In type 2 diabetes, IAsp and RI were associated with equal efficacy and safety. For IGla versus NPH, the incremental cost-effectiveness ratio was calculated at $1975 per quality-adjusted life-year. The robustness of the result was confirmed through sensitivity analysis.

Conclusion: Insulin analogs, IAsp and IGla, are cost-effective for type 1 diabetes versus human insulins, RI and NPH. For type 2 diabetes, IAsp is not cost-effective when compared with RI. For IGla versus NPH, however, the incremental cost-effectiveness ratio seems to be within the accepted thresholds.

Purpose: To assess the effects of exercise training parameters on cardiorespiratory fitness of individuals with type 2 diabetes mellitus (T2DM).

Methods: This systematic review was registered on PROSPERO (CRD42020210470). Searches were performed on PubMed, PEDro EMBASE, MEDLINE (Ovid), LILACS, PsycINFO, SCIELO, CINAHL, and Cochrane Library. The primary outcome was cardiorespiratory fitness, defined as maximal oxygen uptake (VO_2max) during a maximal or submaximal exercise test. Two independent reviewers extracted data and assessed the risk of bias. Data were pooled using a random effects model and expressed as mean difference (MD) and 95% confidence interval (95%CI). Heterogeneity (I²) was assessed using Cochran's Q test. The risk of bias and quality of evidence was assessed using the Cochrane risk of bias tool and GRADE.

Results: Twenty-two studies comparing exercise and control groups were included. The risk of bias indicated some concerns in most studies, and the quality of evidence was rated very low. Interventions with moderate (MD = 1.91, 95%CI = .58 to 3.34) and progressive exercise intensity (MD = 2.70, 95%CI = 2.43 to 2.96) and volume (MD = 1.72, 95%CI = .59 to 2.85) showed greater improvements in VO_2max.

Conclusions: Protocols that progressively increased exercise training parameters improved the cardiorespiratory fitness response. Progressive exercise might be more suitable for individuals with T2DM. Our conclusion may be limited due to the very low quality of evidence.

Supplementary information: The online version contains supplementary material available at 10.1007/s40200-023-01205-5.

Purpose: There is plenty of evidence on the interventions that can improve outcomes of diabetes. Thus, there is an urgent need to innovate and provide cost-effective ways to optimize the best care for diabetes. The aim was to examine the components of diabetes courses to extract training virtual modules for training primary health care professionals (PHCPs) (i.e. general practitioners, nurses and nutritionists).

Methods: In this scoping review, a systematic approach based on the Arksey and O'Malley method was used. In order to develop the modules for diabetes courses, search strategy was developed using main keywords. Also, databases including PubMed, Web of Science, Scopus, CINAHL, ERIC and Embase, and Google search engine were searched up to April 10th 2021. Two researchers independently screened the retrieved courses. After removing duplicates, and according to the eligibility criteria, the components of each retrieved course were extracted.

Results: Diabetes training courses have been selected to examine their components to extract training modules. Initially, we found 120 courses related to the training of PHCPs. All information about 44 courses were available online. The researchers reviewed the courses according to tool approved by panel of experts, inclusion criteria, and purpose of the study. Thus, we first extracted 23 eligible programs and 15 final programs were considered for extracting the modules. According to the tool developed by the panel of experts, we extracted 9 virtual modules for diabetes courses including principles, prevention or delay, management, complications, education, special conditions, information technology, referral system of diabetes for training PHCPs.

Conclusion: Education is an important part of diabetes and needs of PHCPs should be addressed in educational programs in the future. The design of the diabetes training course based on extracted modules in this research for the training of PHCPs can help in this field.

Purpose: In the management of type 2 diabetes (T2D), dietary intervention has been proposed to be highly effective. This study, therefore, investigated the effect of bitter leaf-flavored non-alcoholic wheat beer (NAWB) on insulin secretion and GLUT-2 expression in the pancreas of STZ-induced diabetic rats.

Methods: In this study, the rats received a single intraperitoneal injection (i.p.) of STZ (35 mg/kg) after being fed a high-fat diet for 14 days to induce T2D. The rats were treated with bitter leaf flavored NAWB samples (100%HP- Hops only, 100%BL-Bitter leaf only, 75,25BL- 75% Hops, 25% Bitter Leaf, 50:50BL- 50% Hops:50% Bitter Leaf, and 25:75BL-25%Hops:75% Bitter Leaf) and Acarbose for 14 days. The superoxide dismutase, catalase, and glutathione peroxidase activity were also determined.

Results: The results from this study showed a correlation between GLUT-2 and Insulin expression. There was an upregulation of Insulin as GLUT-2 expression was upregulated. Furthermore, the treated groups showed better antioxidant activity when compared with the diabetic control.

Conclusion: Bitter leaf-flavored NAWB might thus be a good dietary intervention for type 2 diabetics.

Objectives: The objective of the present study is to discuss the use of nanomaterials like nanosensors for diagnosing Diabetes and highlight their applications in the treatment of Diabetes.

Methods: Diabetes mellitus (D.M.) is a group of metabolic diseases characterized by hyperglycemia. Orally administered antidiabetic drugs like glibenclamide, glipalamide, and metformin can partially lower blood sugar levels, but long-term use causes kidney and liver damage. Recent breakthroughs in nanotheranostics have emerged as a powerful tool for diabetes treatment and diagnosis.

Results: Nanotheranostics is a rapidly developing area that can revolutionize diabetes diagnosis and treatment by combining therapy and imaging in a single probe, allowing for pancreas-specific drug and insulin delivery. Nanotheranostic in Diabetes research has facilitated the development of improved glucose monitoring and insulin administration modalities, which promise to improve the quality of life for people with Diabetes drastically. Further, nanomaterials like nanocarriers and unique functional nanomaterials used as nano theranostics tools for treating Diabetes will also be highlighted.

Conclusion: The nanosensors discussed in this review article will encourage researchers to develop innovative nanomaterials with novel functionalities and properties for diabetes detection and treatment.

Purpose: The prevalence of diabetes is increasing worldwide. Studies have shown that poor blood sugar control is associated with the complications of diabetes, we aimed to determine the prevalence of uncontrolled diabetes mellitus (UDM) and its related factors.

Methods: This multicenter cross-sectional study was conducted in 2021 on type 2 diabetic patients in three cities; Rasht (in Gillan province), Borujerd (in Lorestan province), and Khodabandeh (in Zanjan province). A predesigned checklist was used to extract the basic characteristics of participants, their hemoglobin A1C, and other required data from their medical records. The prevalence of uncontrolled diabetes was reported with a 95% Confidence Interval.

Results: In this study, the medical records of 460 patients with type 2 diabetes were included. The mean and standard deviation (SD) of the age of participants was 59.17 (11.59), and 73.2% (337) of participants were female. The prevalence of UDM in Rasht, Borujerd, and Khodabandeh was 58.27%, 69.38%, and 45.65% respectively. The prevalence of UDM in obese patients was 64.78% (57.03, 71.82). Based on the results of the adjusted model, an increase in diastolic blood pressure was significantly associated with UDM, meaning each unit increase in diastolic blood pressure was associated with a 3% increase in UDM (95% CI: 1.01, 1.06), adjusted for age, gender and education.

Conclusion: According to these results, the prevalence of UDM among patients with diabetes is high. Diastolic blood pressure and low level of education were associated with UDM in diabetic patients.