7 resultados para Glycemic Control
Resumo:
Aims: To evaluate the impact on glycemic control and quality of life of a bolus calculator. Methods: Multicentre randomized prospective crosssectional study. Patients were randomized to control phase (3 months; calculation of prandial insulin according to insulinto-carbohydrate ratio and insulin sensitivity factor using a single strip meter) or intervention phase (3 months; calculation of prandial insulin with a bolus advisor), with a washout period (3 months). Patients wore a continuous glucosensor (7 days) and answered a quality of life questionnaire at the beginning and at the end of each phase. A questionnaire of satisfaction was obtained at the end of both phases. Inclusion criteria: Adults; T1DM> 1 year, HbA1c > 7.5%, basal-bolus therapy with insulin analogs, experience with carbohydrate Results: Data from the first 32 subjects with at least 1 ended phase (27 females, age 38 – 11 years, diabetes duration 16.8 – 7.5 years). Basal characteristics were comparable independently of the starting phase. No differences were found between phases in terms of mean blood glucose, standard deviation (from meter neither from sensor) and satisfaction. Conclusions: The use of a bolus calculator improves glycemic control and quality of life of T1DM subjects.
Resumo:
Glucose control is the cornerstone of Diabetes Mellitus (DM) treatment. Although self-regulation using capillary glycemia (SRCG) still remains the best procedure in clinical practice, continuous glucose monitoring systems (CGM) offer the possibility of continuous and dynamic assessment of interstitial glucose concentration. CGM systems have the potential to improve glycemic control while decreasing the incidence of hypoglycemia but the efficiency, compared with SRCG, is still debated. CGM systems have the greatest potential value in patients with hypoglycemic unawareness and in controlling daily fluctuations in blood glucose. The implementation of continuous monitoring in the standard clinical setting has not yet been established but a new generation of open and close loop subcutaneous insulin infusion devices are emerging making insulin treatment and glycemic control more reliable.
Resumo:
The aims of this study were to check whether different biomarkers of inflammatory, apoptotic, immunological or lipid pathways had altered their expression in the occluded popliteal artery (OPA) compared with the internal mammary artery (IMA) and femoral vein (FV) and to examine whether glycemic control influenced the expression of these genes. The study included 20 patients with advanced atherosclerosis and type 2 diabetes mellitus, 15 of whom had peripheral arterial occlusive disease (PAOD), from whom samples of OPA and FV were collected. PAOD patients were classified based on their HbA1c as well (HbA1c ≤ 6.5) or poorly (HbA1c > 6.5) controlled patients. Controls for arteries without atherosclerosis comprised 5 IMA from patients with ischemic cardiomyopathy (ICM). mRNA, protein expression and histological studies were analyzed in IMA, OPA and FV. After analyzing 46 genes, OPA showed higher expression levels than IMA or FV for genes involved in thrombosis (F3), apoptosis (MMP2, MMP9, TIMP1 and TIM3), lipid metabolism (LRP1 and NDUFA), immune response (TLR2) and monocytes adhesion (CD83). Remarkably, MMP-9 expression was lower in OPA from well-controlled patients. In FV from diabetic patients with HbA1c ≤6.5, gene expression levels of BCL2, CDKN1A, COX2, NDUFA and SREBP2 were higher than in FV from those with HbA1c >6.5. The atherosclerotic process in OPA from diabetic patients was associated with high expression levels of inflammatory, lipid metabolism and apoptotic biomarkers. The degree of glycemic control was associated with gene expression markers of apoptosis, lipid metabolism and antioxidants in FV. However, the effect of glycemic control on pro-atherosclerotic gene expression was very low in arteries with established atherosclerosis.
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BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.
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BACKGROUND: There is a prevalence of diabetes mellitus (DM), unknown DM and stress hyperglycemia among hospital patients, and the nutritional treatment is a key part of care, where carbohydrates (CH) intake is a controversial issue. There is also a discussion on the increase of prevalence for DM, obesity and metabolic disease with refined CH or sugar. OBJECTIVES: This review examines the recommendations from different scientific societies about the percentage of CH in the total calorie intake of the diabetic patient, the CH value in the glycemic index and glycemic load, the new CH included in enteral formulae and the association of refined CH with the high prevalence of DM and metabolic disease. METHODS: Systematic review of literature using the electronic scientific databases Pubmed, Science Direct, Scielo, Scopus and Medline. CONCLUSIONS: Scientific societies are flexible about the CH intake in the diet of diabetic patients, suggesting to customize it according to each metabolic profile. Using the glycemic index and glycemic load can provide an extra benefit in the postprandial glycemic control. The new diabetes-specific enteral formulae, with fructooligosaccharides, resistant maltodextrins and fructose-free show efficacy in improving the glycemic control, although more controlled and long-term studies are needed. There is still some controversy about the links between sugar intake and DM, obesity and metabolic disease, although this relationship would be more linked to an increase of the total calorie intake than to a specific nutrient. .
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BACKGROUND Measurement of HbA1c is the most important parameter to assess glycemic control in diabetic patients. Different point-of-care devices for HbA1c are available. The aim of this study was to evaluate two point-of-care testing (POCT) analyzers (DCA Vantage from Siemens and Afinion from Axis-Shield). We studied the bias and precision as well as interference from carbamylated hemoglobin. METHODS Bias of the POCT analyzers was obtained by measuring 53 blood samples from diabetic patients with a wide range of HbA1c, 4%-14% (20-130 mmol/mol), and comparing the results with those obtained by the laboratory method: HPLC HA 8160 Menarini. Precision was performed by 20 successive determinations of two samples with low 4.2% (22 mmol/mol) and high 9.5% (80 mmol/mol) HbA1c values. The possible interference from carbamylated hemoglobin was studied using 25 samples from patients with chronic renal failure. RESULTS The means of the differences between measurements performed by each POCT analyzer and the laboratory method (95% confidence interval) were: 0.28% (p<0.005) (0.10-0.44) for DCA and 0.27% (p<0.001) (0.19-0.35) for Afinion. Correlation coefficients were: r=0.973 for DCA, and r=0.991 for Afinion. The mean bias observed by using samples from chronic renal failure patients were 0.2 (range -0.4, 0.4) for DCA and 0.2 (-0.2, 0.5) for Afinion. Imprecision results were: CV=3.1% (high HbA1c) and 2.97% (low HbA1c) for DCA, CV=1.95% (high HbA1c) and 2.66% (low HbA1c) for Afinion. CONCLUSIONS Both POCT analyzers for HbA1c show good correlation with the laboratory method and acceptable precision.
Resumo:
BACKGROUND A recent study using a rat model found significant differences at the time of diabetes onset in the bacterial communities responsible for type 1 diabetes modulation. We hypothesized that type 1 diabetes in humans could also be linked to a specific gut microbiota. Our aim was to quantify and evaluate the difference in the composition of gut microbiota between children with type 1 diabetes and healthy children and to determine the possible relationship of the gut microbiota of children with type 1 diabetes with the glycemic level. METHODS A case-control study was carried out with 16 children with type 1 diabetes and 16 healthy children. The fecal bacteria composition was investigated by polymerase chain reaction-denaturing gradient gel electrophoresis and real-time quantitative polymerase chain reaction. RESULTS The mean similarity index was 47.39% for the healthy children and 37.56% for the children with diabetes, whereas the intergroup similarity index was 26.69%. In the children with diabetes, the bacterial number of Actinobacteria and Firmicutes, and the Firmicutes to Bacteroidetes ratio were all significantly decreased, with the quantity of Bacteroidetes significantly increased with respect to healthy children. At the genus level, we found a significant increase in the number of Clostridium, Bacteroides and Veillonella and a significant decrease in the number of Lactobacillus, Bifidobacterium, Blautia coccoides/Eubacterium rectale group and Prevotella in the children with diabetes. We also found that the number of Bifidobacterium and Lactobacillus, and the Firmicutes to Bacteroidetes ratio correlated negatively and significantly with the plasma glucose level while the quantity of Clostridium correlated positively and significantly with the plasma glucose level in the diabetes group. CONCLUSIONS This is the first study showing that type 1 diabetes is associated with compositional changes in gut microbiota. The significant differences in the number of Bifidobacterium, Lactobacillus and Clostridium and in the Firmicutes to Bacteroidetes ratio observed between the two groups could be related to the glycemic level in the group with diabetes. Moreover, the quantity of bacteria essential to maintain gut integrity was significantly lower in the children with diabetes than the healthy children. These findings could be useful for developing strategies to control the development of type 1 diabetes by modifying the gut microbiota.