scholarly journals Evaluation of the Prognostic Significance of Adipose Tissue Hormones in the Development of Diabetic Retinopathy in Patients With Type 2 Diabetes Mellitus

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A412-A413
Author(s):  
Mykhailo L Kyryliuk ◽  
Sergiy Yu Mogilevskyy ◽  
Valeriy M Serdiuk
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Adipose Tissue ◽  
Diabetic Retinopathy ◽  
Prognostic Significance ◽  
Diabetic Microangiopathy ◽  
Serum Leptin ◽  
Tissue Hormones

Abstract Relevance: There are evidences of the participation of adipose tissue hormones (ATH) in the development of diabetic microangiopathy and retinal neovascularization. The disign of methods for the mathematical evaluation of the prognosis of the development of diabetic retinopathy (DR) with the participation of ATH is an actual problem in modern diabetology. Goal: Elaboration of a mathematical model for assessing the prognostic significance of ATH to study the likelihood of developing and progressing DR in patients with type 2 diabetes mellitus (T2DM). Materials and Methods: An open observational single-center one-stage selective study was conducted. The study was approved by the Local Ethics Committee. 59 patients (187 eyes) with T2DM and DR (men and women; mean age - 58.20±0.18 years; mean T2DM duration - 9.19±0.46 years; mean HbA1C - 9.10±0.17 %), were assigned to 3 groups, based on the stage of DR (according to fundus instrumental examination), and underwent the study. The diagnostic predictive value was assessed by discriminant analysis. Models with linear combinations of the serum leptin, adiponectin and resistin, triglyceride (TG), also HbA1C, type of antidiabetic therapy (ADT) were developed, and, subsequently, formulas for classification-relevant discriminant functions were derived. ADT included metformin, either alone (type 1 ADT), or in combination with oral anti-hyperglycemic medication (type 2 ADT) or insulin therapy (type 3 ADT). The classification functions (CF) computed based on the variables found from the above developed models provided the basis for predicting the development of DR. Results: The formulas for CF from model are as follows: CF1 = 0.29 * TG + 1.55 * HbA1 + 1.81 * ADT_Type + 0.04 * Leptin + 0,34* Adiponectin + 0,91* Resistin – 13,82; CF2 = 0.05*TG + 1.36 * HbA1 + 3.01 * ADT_Type + 0.08 * Leptin + 0,35* Adiponectin + 1,01 * Resistin – 15.95. A step-by-step approach to diagnostic decision making should be used. First, blood samples are tested for serum leptin, adiponectin and resistin, TG, blood HbA1, and the patient is assigned a code for ADT_Type (1, 2 or 3). Second, CF1 and CF2 values are calculated. Finally, the two values are compared to determine which is greater. The predictive decision is made by selecting the classification function with the greater value. Thus, if CF1>CF2, the process can be stabilized at this stage given an adequate glycemic control (through compensation of carbohydrate metabolism) and body-mass control as well as patient compliance. If CF1<CF2, the pathological process may progress to the next stage or even within stage 3, and there is an urgent need to reduce BMI, and to correct the ADT and the blood lipid profile. Conclusion: Informativeness and statistical significance of model is 71.4 % and p=0.040, respectively.

scholarly journals Evaluation of the prognostic significance of leptin, adiponectin and resistin in the development of diabetic retinopathy in type 2 diabetes mellitus patients

2021 ◽  
Vol 17 (3) ◽  
pp. 209-213
Author(s):  
M.L. Kyryliuk
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Prognostic Significance ◽  
Discriminant Functions ◽  
Serum Leptin ◽  
Type 2 Dm ◽  
Antihyperglycemic Therapy

Background. There is evidence of the participation of adipose tissue hormones leptin, adiponectin and resistin in the formation of metabolic disorders in the retina, retinal neovascularization, and diabetic microangiopathy. The development of methods for the mathematical evaluation of the prognosis of diabetic retinopathy (DR) formation with the participation of adipokines is a relevant problem in modern diabetology. Aim. Elaboration of a mathematical model for assessing the prognostic significance of serum leptin, adiponectin and resistin to study the likelihood of deve­loping and progressing DR in patients with type 2 diabetes mellitus (DM). Materials and methods. An open observational single-center one-stage selective study was conducted among patients with type 2 DM and DR. The blood serum concentration of leptin, adiponectin and resistin, HbA1с, lipid metabolism findings were determined, the results of an instrumental examination of the fundus were analyzed. The diagnostic predictive value of serum leptin, adiponectin and resistin was assessed using discriminant analysis. Statistical analyses were conducted using Statistica 9.0 (StatSoft, Tulsa, OK, USA) software. The differences were considered statistically signifi­cant at p < 0.05. A model with linear combinations of the serum leptin, adiponectin and resistin, triglyceride (TG), HbA1с, type of antihyperglycemic therapy (oral anti-hyperglycemic medication or insulin therapy) were developed, and, subsequently, formulas for classification-relevant discriminant functions were derived. Results. Fifty-nine patients (107 eyes) with type 2 DM and DR (men and women; mean age, 58.20 ± 0.18 years; mean diabetes duration, 9.19 ± 0.46 years; mean HbA1с 9.10 ± 0.17 %) were assigned to the basic group and underwent the study. They were divided into three DR groups based on the stage of DR. When performing the ran­king of patients for discriminant analysis, the stage 2 DR group was aggregated with the stage 3 DR group for convenience to form the stage 2 + 3 DR group based on the pathognomonic sign (portents of proliferation or actual proliferation). Anti-diabetic therapy (ADT) included metformin, either alone (type 1 ADT) or in combination with oral anti-hyperglycemic medication (metformin + OAHGM, type 2 ADT) or insulin therapy (metformin + IT, type 3 ADT). Inclusion criteria were informed consent, age above 18 years, pre­sence of T2DM and DR. Exclusion criteria were endocrine or body system disorders leading to obesity (Cushing’s syndrome, hypothyroidism, hypogonadism, polycystic ovarian syndrome, or other endocrine disorders, including hereditary disorders, and hypothalamic obesity), type 1 DM, acute infectious disorders, history of or current cancer, decompensation of comorbidities, mental disorders, treatment with neuroleptics or antidepressants, proteinuria, clinically significant maculopathy, glaucoma or cataract. The study followed the ethical standards stated in the Declaration of Helsinki and was approved by the Local Ethics Committee. The formulas for classification-relevant discriminant functions were derived based on the results of physical examination, imaging and laboratory tests, and subsequent assessment of clinical signs of DM (HbA1с), DR stage and serum leptin, adiponectin, resistin, TG concentrations and taking into account the type of antihyperglycemic therapy. The classification functions (CF) computed based on the variables found from the above developed models provided the basis for predicting the development of DR. The formulas for CF from model are as follows: CF1 = 0.29 • TG + 1.55 • HbA1С + 1.81 • ADT_Type + 0.04 • Leptin + 0,34 • Adiponectin + 0,91 • Resistin – 13,82. CF2= 0.05 • TG + 1.36 • HbA1С + 3.01 • ADT_Type + 0.08 • Leptin + 0,35 • Adiponectin + 1,01 • Resistin – 15.95. A step-by-step approach to a diagnostic decision should be used. First, blood samples are tested for serum leptin, adiponectin and resistin, TG, blood HbA1c, and the patient is assigned a code for ADT Type (metformin only, 1; metformin + OAHGM, 2; or metformin + IT, 3). Second, CF1 and CF2 values are calculated based on clinical and laboratory data. Finally, the two values are compared to determine which is greater. The predictive decision is made by selecting the classification function with the greater value. Thus, if CF1 > CF2, the process can be stabilized at this stage given adequate glycemic control (through compensation of carbohydrate metabolism) and body mass control as well as patient compliance. If CF1 < CF2, the pathological process may progress to the next stage or even within stage 3, and there is an urgent need to reduce BMI, and to correct the ADT and the blood lipid profile. Conclusions. The informative value and statistical significance of the model were 71.4 % and p = 0.040, respectively. Using the formulas, one can determine the probability of progression of DR.

Angiopoietin 1 in patients with type 2 diabetes mellitus and diabetic retinopathy

2015 ◽  
Author(s):  
Sattar El-Deeb Abd El ◽  
Mohamed Halawa ◽  
Ahmed Saad ◽  
Inas Sabry ◽  
Maram Mahdy ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
Angiopoietin 1

Relationship between diabetic retinopathy and cerebral perfusion in type 2 diabetes mellitus

2018 ◽  
Vol 71 (1) ◽  
pp. 49-53
Author(s):  
N. Zherdiova ◽  
◽  
N. Medvedovska ◽  
B Mankovsky ◽  
◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
Cerebral Perfusion

scholarly journals Metabolomics-based multidimensional network biomarkers for diabetic retinopathy identification in patients with type 2 diabetes mellitus

2021 ◽  
Vol 9 (1) ◽  
pp. e001443
Author(s):  
Jingjing Zuo ◽  
Yuan Lan ◽  
Honglin Hu ◽  
Xiangqing Hou ◽  
Jushuang Li ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
Permutation Test ◽  
Linear Regression Models ◽  
Characteristic Analysis ◽  
Network Biomarkers ◽  
Validation Set

IntroductionDespite advances in diabetic retinopathy (DR) medications, early identification is vitally important for DR administration and remains a major challenge. This study aims to develop a novel system of multidimensional network biomarkers (MDNBs) based on a widely targeted metabolomics approach to detect DR among patients with type 2 diabetes mellitus (T2DM) efficiently.Research design and methodsIn this propensity score matching-based case-control study, we used ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry system for serum metabolites assessment of 69 pairs of patients with T2DM with DR (cases) and without DR (controls). Comprehensive analysis, including principal component analysis, orthogonal partial least squares discriminant analysis, generalized linear regression models and a 1000-times permutation test on metabolomics characteristics were conducted to detect candidate MDNBs depending on the discovery set. Receiver operating characteristic analysis was applied for the validation of capability and feasibility of MDNBs based on a separate validation set.ResultsWe detected 613 features (318 in positive and 295 in negative ESI modes) in which 63 metabolites were highly relevant to the presence of DR. A panel of MDNBs containing linoleic acid, nicotinuric acid, ornithine and phenylacetylglutamine was determined based on the discovery set. Depending on the separate validation set, the area under the curve (95% CI), sensitivity and specificity of this MDNBs system were 0.92 (0.84 to 1.0), 96% and 78%, respectively.ConclusionsThis study demonstrates that metabolomics-based MDNBs are associated with the presence of DR and capable of distinguishing DR from T2DM efficiently. Our data also provide new insights into the mechanisms of DR and the potential value for new treatment targets development. Additional studies are needed to confirm our findings.

scholarly journals Adherence to medication among Tunisian adults with type 2 diabetes

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Amara ◽  
R Ghammem ◽  
N Zammit ◽  
S BenFredj ◽  
J Maatoug ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
University Hospital ◽  
Health Concern ◽  
Eligibility Criteria ◽  
Cross Sectional ◽  
Adherence To Medication

Abstract Introduction Diabetes mellitus is a growing public health concern. Despite compelling evidence about the effectiveness of medications, studies have indicated that less than 50% of patients achieved therapeutic targets. The aim of this study was to assess the adherence to type 2 diabetes mellitus treatment and its determinants. Methods A cross-sectional study was conducted between April and June 2017 in the Endocrinology and internal medicine departments of Farhat Hached University Hospital in Sousse, Tunisia. A convenient sample of patients who fulfilled the eligibility criteria was recruited. A pre-tested questionnaire was used to gather information. This was followed by assessing patients' adherence to diabetes medications using the eight-item Morisky Medication Adherence Scale (MMAS-8). Results A total of 330 patients with Type 2 Diabetes Mellitus participated in this study. The mean ±SD age of patients was 58.96±10.3 with female predominance (60.3%). More than half of participants were with high cardiovascular risk. In most cases (70.6 %), participants were moderate adherent. Results showed that patients become non-adherent as the disease gets older (p = 0.001). In addition patients with health insurance were significantly more adherent comparing to those who did not have it (p = 0.01). Regarding self-care practices and other metabolic risk factors' effects, our data revealed that exercising 30 minutes below than 5 times in week and poor self-management of diet were associated with low adherence (p &lt; 10-3). On the other hand, patients who have started insulin therapy were less adherent than those who had not yet (0.01). Patients with diabetic retinopathy or maculopathy were significantly more prone to be non- adherent, with respective percentage of 39.1% and 37.5%. Conclusions This study provides insights into the determinants of non-adherence, ultimately guiding the effective interventions through development of structured long-term policies not yet implemented. Key messages In most cases (70.6 %), participants were moderate adherent. Patients with diabetic retinopathy or maculopathy were significantly more prone to be non- adherent.

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