Methods: We searched seven databases up to July 2020 for randomized controlled trials investigating the effectiveness of telemedicine in the delivery of diabetes care in low- and middle-income countries. We extracted data on the study characteristics, primary end-points and effect sizes of outcomes. Using random effects analyses, we ran a series of meta-analyses for both biochemical outcomes and related patient properties.
Findings: We included 31 interventions in our meta-analysis. We observed significant standardized mean differences of -0.38 for glycated haemoglobin (95% confidence interval, CI: -0.52 to -0.23; I2 = 86.70%), -0.20 for fasting blood sugar (95% CI: -0.32 to -0.08; I2 = 64.28%), 0.81 for adherence to treatment (95% CI: 0.19 to 1.42; I2 = 93.75%), 0.55 for diabetes knowledge (95% CI: -0.10 to 1.20; I2 = 92.65%) and 1.68 for self-efficacy (95% CI: 1.06 to 2.30; I2 = 97.15%). We observed no significant treatment effects for other outcomes, with standardized mean differences of -0.04 for body mass index (95% CI: -0.13 to 0.05; I2 = 35.94%), -0.06 for total cholesterol (95% CI: -0.16 to 0.04; I2 = 59.93%) and -0.02 for triglycerides (95% CI: -0.12 to 0.09; I2 = 0%). Interventions via telephone and short message service yielded the highest treatment effects compared with services based on telemetry and smartphone applications.
Conclusion: Although we determined that telemedicine is effective in improving several diabetes-related outcomes, the certainty of evidence was very low due to substantial heterogeneity and risk of bias.
METHOD: A multicenter cross-sectional observational study was conducted in 388 diabetes patients attending daily diabetes clinics and teaching hospitals in Pakistan's twin city between August 2019 and February 2020. The chi-square test and linear regression were used to detect RLS-related factors in type 2 diabetes mellitus.
RESULTS: The prevalence of RLS found was; 3.1% patients with diabetes were suffering from very severe RLS, 23.5% from severe RLS, 34% from moderate RLS, 21.1% from mild RLS and 18.3% from non-RLS. Gender, age, education, blood glucose fasting (BSF), blood glucose random (BSR) and HBA1c were found to be significant predictors of RLS in patients with diabetes.
CONCLUSION: Policy makers can develop local interventions to curb the growing RLS prevalence by keeping in control the risk factors of RLS in people living with type 2 diabetes.
The aim: To establish possible associations of the insulin receptor substrate-1 (IRS-1) gene polymorphism with the severity of the metabolic syndrome components in patients with arterial hypertension (AH).
Material and methods: 187 patients with AH aged 45-55 years and 30 healthy individuals. Methods: anthropometry, reactive hyperemia, color Doppler mapping, biochemical blood analysis, HOMA-insulin resistance (IR), glucose tolerance test, enzyme immunoassay, molecular genetic method.
Results: Among hypertensive patients, 103 had abdominal obesity, 43 - type 2 diabetes, 131 - increased blood triglycerides, 19 - decreased high density lipoproteins, 59 - prediabetes (33 - fasting hyperglycemia and 26 - impaired glucose tolerance), 126 had IR. At the same time, hypertensive patients had the following distribution of IRS-1 genotypes: Gly/Gly - 47.9%, Gly/Arg - 42.2% and Arg/Arg - 10.7%, whereas in healthy individuals the distribution of genotypes was significantly different: Gly/Gly - 86.8% (p <0.01), Gly/ Arg - 9.9% (p <0.01) and Arg/Arg - 3.3% (p <0.05). Hypertensive patients with Arg/Arg and Gly/Arg genotypes had significantly higher HOMA-IR (p <0.01), glucose, insulin and triglycerides levels (p <0.05), than in Gly/Gly genotype. At the same time, body mass index, waist circumference, blood pressure, adiponectin, HDL, interleukin-6, C-reactive protein, degree of endothelium-dependent vasodilation, as well as the frequency of occurrence of impaired glucose tolerance did not significantly differ in IRS-1 genotypes.
Conclusions: In hypertensive patients, the genetic polymorphism of IRS-1 gene is associated with such components of the metabolic syndrome as hypertriglyceridemia and fasting hyperglycemia; it is not associated with proinflammatory state, endothelial dysfunction, dysglycemia, an increase in waist circumference and decrease in HDL.
METHOD: This cross-sectional study involved eighty-three (n=83) adults attending a health screening program at Universiti Putra Malaysia (UPM). Demographic data, anthropometric measurements and blood samples for fasting blood glucose (FBG), fasting lipid profile (FSL), glycated haemoglobin (HbA1c) and hsCRP were taken. Respondents were grouped according to FRS and the Joint Interim Statement into 10-year CVD risk categories (low, intermediate and high) and MetS, respectively.
RESULTS: hsCRP was significantly increased in patients with high body mass index (BMI) (p=0.001), at-risk waist circumference (WC) (p=0.001) and MetS (p=0.009). Spearman's correlation coefficient showed a significant positive correlation between hsCRP level and total FRS score (r=0.26, p<0.05) and HDL-C score (r=0.22, p<0.05).
CONCLUSION: The significant difference of hsCRP levels across obesity levels and MetS with its modest correlation with FRS scores supported the adjunctive role of hsCRP in CVD risk prediction, most likely capturing the inflammatory pathological aspect and thus partly accounting for the residual CVD risk.