Study on Risk Factors of Diabetic Nephropathy in Obese Patients with Type 2 Diabetes Mellitus

Association of body iron stores and anemia in a Ghanaian type-2 diabetes mellitus population: A multicentered cross-sectional study

Background and Aims

Anemia has been a common comorbidity in most chronic diseases, but has not been well monitored in type 2 diabetes mellitus (T2DM) patients. In this study, we investigated the prevalence of anemia and its nexus with iron stores among T2DM patients in health facilities in the Ashanti Region of Ghana.

Methods

This multicenter cross-sectional study recruited 213 T2DM out-patients attending the diabetic clinics at the Kumasi South Hospital and St. Michaels Hospital, Jachie Pramso, Ghana, for routine check-ups. Self-reported questionnaires were used to collect sociodemographic, lifestyle, and clinical data from study participants. Blood samples were collected to estimate hematological parameters and iron stores. Mann-Whitney U test was used to assess the difference in hematological parameters and iron stores between anemic and nonanemic patients. All p < 0.05 were considered statistically significant.

Results

Of the 213 T2DM participants, the prevalence of anemia was 31.9%. More females 145 (68.1%) were registered than males 68 (31.9%). Anemic patients had significantly lower levels of mean cell volume [79.30/fL vs. 82.60/fL, p = 0.001], mean cell hemoglobin [26.60/pg vs. 27.90/pg, p < 0.0001], and mean cell hemoglobin concentration [33.10/g/dL) vs. 33.80/g/dL, p < 0.0001] than those without anemia. Serum levels of ferritin (p = 0.1140), transferrin (p = 0.5070), iron (p = 0.7950), and total iron binding capacity (p = 0.4610) did not differ significantly between T2DM patients with or without anemia.

Conclusion

Despite the high prevalence of anemia among the T2DM patients in our cohort, patients present with apparently normal iron stores. This unrecognized mild anemia must be frequently monitored among T2DM patients.

Dose-response association of diabetic kidney disease with routine clinical parameters in patients with type 2 diabetes mellitus: a systematic review and meta-analysis

Background

Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease and is associated with high mortality rates. The influence of routine clinical parameters on DKD onset in patients with type 2 diabetes mellitus (T2DM) remains uncertain.

Methods

In this systematic review and meta-analysis, we searched multiple databases, including PubMed, Embase, Scopus, Web of Science, and Cochrane Library, for studies published from each database inception until January 11, 2024. We included cohort studies examining the association between DKD onset and various clinical parameters, including body mass index (BMI), hemoglobin A1c (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and serum uric acid (UA). Random-effect dose-response meta-analyses utilizing one-stage and/or cubic spline models, were used to estimate correlation strength. This study is registered in PROSPERO (CRD42022326148).

Findings

This analysis of 46 studies involving 317,502 patients found that in patients with T2DM, the risk of DKD onset increased by 3% per 1 kg/m2 increase in BMI (relative risk (RR) = 1.03, confidence interval (CI) [1.01-1.04], I2 = 70.07%; GRADE, moderate); a 12% increased risk of DKD onset for every 1% increase in HbA1c (RR = 1.12, CI [1.07-1.17], I2 = 94.94%; GRADE, moderate); a 6% increased risk of DKD onset for every 5 mmHg increase in SBP (RR = 1.06. CI [1.03-1.09], I2 = 85.41%; GRADE, moderate); a 2% increased risk of DKD onset per 10 mg/dL increase in TG (RR = 1.02, CI [1.01-1.03], I2 = 78.45%; GRADE, low); an 6% decreased risk of DKD onset per 10 mg/dL increase in HDL (RR = 0.94, CI [0.92-0.96], I2 = 0.33%; GRADE, high), and a 11% increased risk for each 1 mg/dL increase in UA (RR = 1.11, CI [1.05-1.17], I2 = 79.46%; GRADE, moderate). Subgroup analysis revealed a likely higher risk association of clinical parameters (BMI, HbA1c, LDL, and UA) in patients with T2DM for less than 10 years.

Interpretation

BMI, HbA1c, SBP, TG, HDL and UA are potential predictors of DKD onset in patients with T2DM. Given high heterogeneity between included studies, our findings should be interpreted with caution, but they suggest monitoring of these clinical parameters to identify individuals who may be at risk of developing DKD.

Funding

Shenzhen Science and Innovation Fund, the Hong Kong Research Grants Council, and the HKU Seed Funds, and Scientific and technological innovation project of China Academy of Chinese Medical Sciences.

The Management of Diabetes with Hyperuricemia: Can We Hit Two Birds with One Stone?

Serum urate (SU) is an independent predictor for the incidence of diabetes. In current diabetes treatment regimens, there is insufficient appreciation of the importance of hyperuricemia (HU) in disease control and prevention. To summarize the updated knowledge on the effects of SU on β-cell function, insulin resistance and chronic diabetic complications, as well as to evaluate the management of patients with both HU and diabetes, we searched the MEDLINE PubMed database, and included 285 journal articles. An inverted U-shaped relationship between fasting plasma glucose and SU levels was established in this review. Elevated SU levels may enhance the development of chronic diabetic complications, including macrovascular and microvascular dysfunction. Diet and exercise are essential parts of the lifestyle changes necessary for HU and diabetes management. Glucose- and urate-lowering drug selection and combination should be made with the principle of ameliorating, and at least not deteriorating, diabetes and HU. Medical artificial intelligence technology and monitoring systems can help to improve the effectiveness of long-term management of HU and diabetes through digital healthcare. This study comprehensively reviews and provides a scientific and reliable basis for and viewpoints on the clinical management of diabetes and HU.

Validation of a risk prediction model for early chronic kidney disease in patients with type 2 diabetes: Data from the German/Austrian Diabetes Prospective Follow-up registry

AIM

To validate a recently proposed risk prediction model for chronic kidney disease (CKD) in type 2 diabetes (T2D).

MATERIALS AND METHODS

Subjects from the German/Austrian Diabetes Prospective Follow-up (DPV) registry with T2D, normoalbuminuria, an estimated glomerular filtration rate of 60 ml/min/1.73m² or higher and aged 39-75 years were included. Prognostic factors included age, body mass index (BMI), smoking status and HbA1c. Subjects were categorized into low, moderate, high and very high-risk groups. Outcome was CKD occurrence.

RESULTS

Subjects (n = 10 922) had a mean age of 61 years, diabetes duration of 6 years, BMI of 31.7 kg/m² , HbA1c of 6.9% (52 mmol/mol); 9.1% had diabetic retinopathy and 16.3% were smokers. After the follow-up (~59 months), 37.4% subjects developed CKD. The area under the curve (AUC; unadjusted base model) was 0.58 (95% CI 0.57-0.59). After adjustment for diabetes and follow-up duration, the AUC was 0.69 (95% CI 0.68-0.70), indicating improved discrimination. After follow-up, 15.0%, 20.1%, 27.7% and 40.2% patients in the low, moderate, high and very high-risk groups, respectively, had developed CKD. Increasing risk score correlated with increasing cumulative risk of incident CKD over a median of 4.5 years of follow-up (P < .0001).

CONCLUSIONS

The predictive model achieved moderate discrimination but good calibration in a German/Austrian T2D population, suggesting that the model may be relevant for determining CKD risk.

Expression of pro-inflammatory cytokines (IL-6 & IL-18) exacerbate the risk of diabetic nephropathy in the Pakistani population

BACKGROUND

Diabetic nephropathy (DN) is a micro-chronic diabetic consequence induced by metabolic and hemodynamic abnormalities. Free radicals react with other critical cellular components, causing progression of aberrant renal function.

OBJECTIVE

This case control study was aimed to determine the role of IL-6 and IL-18 in diabetic nephropathy in Pakistani population.

METHODS AND MATERIALS

The study's subjects (n = 180 from Lahore, Gujranwala, and Karachi) were divided into control, diabetes mellitus (DM) and diabetic nephropathy (DN) groups. The serum concentration of IL-6 & IL-18 were determined by enzyme-linked immunosorbent assay (ELISA). The expression analysis of IL-6 & IL-18 were performed by Real Time PCR.

RESULTS

The significant increase in serum levels of IL-6 were observed among the control, DM and DN groups (15.3 ± 24.1 pg/ml, 34.7 ± 24.0 pg/ml, 52.6 ± 33.2 pg/ml) whereas no significant difference was observed in serum levels of IL-18. The expression analysis of IL-6 was increased by more than forty three fold in DN group (n-fold = ~43.6) as compared to DM & control whereas the expression profile of IL-18 decreased in DN group (n-fold = ~0.89). In DN group the correlation analysis revealed direct association of GFR with serum IL-6 (r = 0.1114) & inverse relationship with serum IL-18 (r = - 0.097). In multiple regression analysis using GFR as the dependent variable, BMI and expression of IL-18 were determinants in DM subjects, but only uric acid in DN subjects.

CONCLUSION

The present study implicates that increased expression of IL-6 and decreased of IL-18 was associated with development of DN in Pakistani population.

Development and validation of a nomogram model for individualized prediction of hypertension risk in patients with type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) with hypertension (DH) is the most common diabetic comorbidity. Patients with DH have significantly higher rates of cardiovascular disease morbidity and mortality. The objective of this study was to develop and validate a nomogram model for the prediction of an individual's risk of developing DH. A total of 706 T2DM patients who met the criteria were selected and divided into a training set (n = 521) and a validation set (n = 185) according to the discharge time of patients. By using multivariate logistic regression analysis and stepwise regression, the DH nomogram prediction model was created. Calibration curves were used to evaluate the model's accuracy, while decision curve analysis (DCA) and receiver operating characteristic (ROC) curves were used to evaluate the model's clinical applicability and discriminatory power. Age, body mass index (BMI), diabetic nephropathy (DN), and diabetic retinopathy (DR) were all independent risk factors for DH (P < 0.05). Based on independent risk factors identified by multivariate logistic regression, the nomogram model was created. The model produces accurate predictions. If the total nomogram score is greater than 120, there is a 90% or higher chance of developing DH. In the training and validation sets, the model's ROC curves are 0.762 (95% CI 0.720-0.803) and 0.700 (95% CI 0.623-0.777), respectively. The calibration curve demonstrates that there is good agreement between the model's predictions and the actual outcomes. The decision curve analysis findings demonstrated that the nomogram model was clinically helpful throughout a broad threshold probability range. The DH risk prediction nomogram model constructed in this study can help clinicians identify individuals at high risk for DH at an early stage, which is a guideline for personalized prevention and treatments.

The analysis of risk factors for diabetic kidney disease progression: a single-centre and cross-sectional experiment in Shanghai

OBJECTIVE

To identify the risk factors for diabetic kidney disease (DKD) development, especially the difference between patients with different courses.

PATIENTS AND METHODS

791 patients were considered to be eligible and were enrolled in the cross-sectional study from Shanghai Tongren Hospital Inpatient Department. 36 variables were initially screened by univariate analysis. The risk factors affecting progression of DKD were determined by logistics regression analysis. Subgroups were grouped according to the course of diabetes disease, and multivariate logistics regression analysis was performed to find out the different risk factors in two subgroups. Finally, the receiver operating characteristics curve is used to verify the result.

RESULTS

The logistic regression model indicated age (OR=1.020, p=0.017, 95% CI 1.004 to 1.040), systolic blood pressure (OR=1.013, p=0.006, 95% CI 1.004 to 1.022), waist circumference (OR=1.021, p=0.015, 95% CI 1.004 to 1.038), white blood cells (WBC, OR=1.185, p=0.001, 95% CI 1.085 to 1.295) and triglycerides (TG, OR=1.110, p=0.047, 95% CI 1.001 to 1.230) were risk factors for DKD, while free triiodothyronine (fT3, OR=0.711, p=0.011, 95% CI 0.547 to 0.926) was a protective factor for DKD in patients with type 2 diabetes mellitus (T2DM). Subgroup analysis revealed that in patients with a short duration of diabetes (<8 years), WBC (OR=1.306, p<0.001, 95% CI 1.157 to 1.475) and TG (OR=1.188, p=0.033, 95% CI 1.014 to 1.393) were risk factors for DKD,fT3 (OR=0.544, p=0.002, 95% CI 0.367 to 0.804) was a protective factor for DKD; whereas for patients with disease course more than 8 years, age (OR=1.026, Pp=0.012, 95%CI=95% CI[ 1.006- to 1.048]) was identified as the only risk factor for DKD and fT3 (OR=0.036, Pp=0.017, 95%CI=95% CI[ 0.439- to 0.922]) was a protective factor for DKD.

CONCLUSION

The focus of attention should especially be on patients with a prolonged course of T2DM, and those with comorbid hypertension and hypertriglyceridaemia waist phenotype. More potential clinical indexes such as thyroid function and inflammatory indicators might be considered as early warning factors for DKD in T2DM. Women should pay attention to controlling inflammation and TGs, and men should strictly control blood pressure. Avoiding abdominal obesity in both men and women will bring great benefits.

Hypertriglyceridemia and Other Risk Factors of Chronic Kidney Disease in Type 2 Diabetes: A Hospital-Based Clinic Population in Greece

Aims/Introduction: Several reports indicate an increasing prevalence of chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM). Hyperglycemia and hypertension are the main risk factors for CKD development and progression. However, despite the achievement of recommended targets for blood glucose and blood pressure (BP), the residual risk of diabetic chronic kidney disease (DCKD) remains relatively high. The aim of this study is to examine dyslipidemia and other major risk factors to provide support for the prevention and treatment of DCKD. Materials and Methods: Participants are from the Redit-2-Diag study that examines 1759 subjects within a period of 6 months. DCKD severity is staged according to KDIGO criteria. Results: An increase in hemoglobin A_1c (1 unit) and systolic blood pressure (1 mm Hg) increases the probability of being classified into a higher CKD stage by 14% and 26%, respectively. Moreover, an increase of triglycerides by 88.5 mg/dL increases the risk of classification to a worse CKD stage by 24%. Conclusions: Elevated triglycerides, systolic blood pressure, and poor glycemic control increase the risk of CKD in T2DM and should be addressed in the treatment strategies.

The interaction analysis between advanced age and longer dialysis vintage on the survival of patients receiving maintenance hemodialysis

Objective

To compare the all-cause mortality of aged and younger patients undergoing maintenance hemodialysis (MHD) over the long or short term, and to identify independent risk factors.

Methods

We performed a retrospective cohort study using the medical records of 181 patients undergoing MHD. We compared the clinical characteristics and laboratory data of survivors and participants who died, according to their age and the duration of MHD. Binary stepwise logistic regression was used to identify independent risk factors for all-cause mortality.

Results

Cardiovascular and cerebrovascular diseases were the principal causes of mortality. The number of aged participants with hypertensive nephropathy as their primary kidney disease was significantly higher than the number of younger participants. The proportion with chronic glomerulonephritis was significantly higher for participants undergoing long-term MHD. Logistic regression analysis revealed that low body mass index, single-pool Kt/V, serum albumin, platelet count, and total iron-binding capacity; and high intact parathyroid hormone and N terminal pro B type natriuretic peptide were independent risk factors for all-cause mortality.

Conclusions

Aged patients are more susceptible to hypertensive nephropathy than younger patients. In addition, the survival of patients with chronic glomerulonephritis undergoing MHD is superior to that of those with hypertensive or diabetic nephropathy.

Risk factors associated with the development of diabetic kidney disease in Sudanese patients with type 2 diabetes mellitus: A case-control study

BACKGROUND AND AIMS

Limited data are available regarding the risk factors associated with the development of diabetic kidney disease (DKD) among Sudanese adults with type 2 diabetes mellitus (T2DM).

METHODS

A case-control study was conducted at Dr. Salma Center for Kidney Diseases between April and September 2019. Patients with T2DM and DKD were compared to age and sex-matched T2DM patients with no kidney disease (NKD). Socio-demographic features, clinical findings, and laboratory investigations of the study subjects and controls were analyzed using SPSS.

RESULTS

A total of 372 patients with DKD were compared to 364 T2DM patients with NKD. The mean age of the DKD patients was 58 ± 13.4 years, their median eGFR was 37.3 ± 4.9 ml/min/1.73 m²; they had their T2DM at a significantly younger age compared to controls (P = 0.014). Logistic regression analysis revealed that a family history of diabetes mellitus, a family history of chronic kidney disease, the presence of hypertension, obesity, hypercholesterolemia, hyperuricemia, smoking, recurrent urinary tract infection, and the regular use of non-steroidal anti-inflammatory drugs were significantly associated with the development of DKD (P values < 0.05).

CONCLUSION

A series of modifiable risk factors were found to be significant determinants for developing DKD. Primary care physicians are expected to pay considerable attention to their control.

Antidiabetic and Other Therapies Used in Subjects with Diabetes and Chronic Kidney Disease in a Hospital-Based Clinic Population in Greece

(1) Background: Type 2 diabetes mellitus (T2DM) is the main cause of chronic kidney disease (CKD). In Greece, in a population from hospital-based diabetes clinics (n = 1759), the overall prevalence of diabetic chronic kidney disease (DCKD) was 45% including mild, moderate, and severe CKD. The aim of this study was to describe and analyze how T2DM patients with mild-to-severe CKD are managed by diabetologists in Greece and assess the achievement rates in glycemic, blood pressure and low-density lipoprotein-cholesterol (LDL-C) control. (2) Methods: This cross-sectional multicenter study took place from June 2015 to March 2016 and collected data from diabetes centers in public hospitals all over Greece. (3) Results: With regard to the anti-diabetes treatment, most participants were on metformin, DPP-4 (Dipeptidyl Peptidase-4 inhibitors) inhibitors and insulin. Angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers were the most prescribed medications for hypertension. For the management of dyslipidemia, most participants were on statins. For patients with DCKD, the levels of HbA1c, blood pressure and LDL-C were 7.2%, 137.7/76.9 mmHg and 95.9 mg/dL, respectively (mean values). (4) Conclusions: The outcomes of this study suggest that management of DCKD can be further improved and should be enhanced. These results may contribute to the whole health care system in Greece. In addition, the better understanding of therapeutic strategies used by diabetologists treating these patients offers educational benefits to primary care physicians, which can result in an overall more successful and efficient management of subjects with T2DM and DCKD.

A Nomogram Model that Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Retrospective Study

OBJECTIVE

To construct a novel nomogram model that predicts the risk of diabetic nephropathy (DN) incidence in Chinese patients with type 2 diabetes mellitus (T2DM).

METHODS

Questionnaire surveys, physical examinations, routine blood tests, and biochemical index evaluations were conducted on 1095 patients with T2DM from Guilin. A least absolute contraction selection operator (LASSO) regression and multivariable logistic regression analysis were used to screen out DN risk factors. A logistic regression analysis incorporating the screened risk factors was used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using the C-index, an area under the receiver operating characteristic curve (AUC), calibration plots, and a decision curve analysis. Bootstrapping was applied for internal validation.

RESULTS

Independent predictors for DN incidence risk included gender, age, hypertension, medicine use, duration of diabetes, body mass index, blood urea nitrogen level, serum creatinine level, neutrophil to lymphocyte ratio, and red blood cell distribution width. The nomogram model exhibited moderate prediction ability with a C-index of 0.819 (95% confidence interval (CI): 0.783-0.853) and an AUC of 0.813 (95%CI: 0.778-0.848). The C-index from internal validation reached 0.796 (95%CI: 0.763-0.829). The decision curve analysis displayed that the DN risk nomogram was clinically applicable when the risk threshold was between 1 and 83%.

CONCLUSION

Our novel and simple nomogram containing 10 factors may be useful in predicting DN incidence risk in T2DM patients.