Bjerrumwitt3037

Baseline values of HbA1c (7.98±0.19 vs 7.89±0.27%), FPG (8.80 ±0.46 vs 9.11±0.49 mmol/l) and SBP (128.4±1.6 vs 130.2±3.1 mmHg) were not significantly different in Asian vs non-Asian patients, but BW was lower in Asian patients (71.6±4.8 vs 88.0±2.5 kg, p less then 0.001). this website The placebo-adjusted weighed mean differences (WMD, 95% CI) were similar in Asian versus non-Asian patients regarding the reductions in HbA1c -0.60 (-0.68, -0.53) % versus -0.54 (-0.59, -0.49) % (p=0.568), FPG -1.37 (-1.53, -1.22) mmol/l vs -1.37 (-1.47, -1.27) mmol/l (p=0.627), BW when expressed in percentage of baseline BW -2.23 (-2.55, -1.90) % vs -2.16 (-2.37, -1.96) % (p=0.324), and SBP -4.53 (-5.53, -3.53) mmHg vs -4.06 (-4.83, -3.29) mmHg) (p=0.223). In conclusion, clinical efficacy of SGLT2i, as an add-on treatment to metformin monotherapy in patients with T2DM, is similar in Asian versus non-Asian patients, despite known ethnic differences in phenotype and pathophysiology of T2DM.

This study planned to determine( 1) the behavioral intention or profile of patients with type 2 diabetes mellitus (T2DM) based on the stages of the change model, and( 2) to explore the perceived facilitators and barriers of self-management (SM) in a sample of Iranian patients with T2DM.

This was a mixed method study, accomplished in two phases. In the quantitative phase, 246 subjects with T2DM participated. They were classified according to items such as regular use of blood-glucose-lowering drugs, having a healthy diet and performing physical activity to pre-action and action groups. Socio-demographic and anthropometric information were collected, and a phenomenological qualitative study was conducted, and data collection continued until saturation achieved by 10 subjects in pre-action and 12 subjects in action groups. Four focus group discussions in the field of SM were accomplished. Analysis of quantitative and qualitative data was conducted by the SPSS and MAXQDA software, respectively.

The mean age and duration of illness among the subjects were 53.9±7.1 and 6.9±4.9 years, respectively. The barriers of SM in action and pre-action stages were as follows lower socio-economic status, poor performance of treatment team, physical-intellectual factors and lack of planning to change. The facilitators stated in the pre-action and action stage in the field of SM were satisfaction from treatment, planning, belief in diabetes, treatment team's support, nutritional knowledge, and religious beliefs.

This study indicated facilitator and barrier factors in SM based on TTM in action and pre-action groups. Healthcare professionals should consider these findings to improve the patients' outcomes.

This study indicated facilitator and barrier factors in SM based on TTM in action and pre-action groups. Healthcare professionals should consider these findings to improve the patients' outcomes.

To determine the prevalence of metabolic syndrome (MetS) in older adults and assess the association of MetS and adverse outcomes with handgrip strength (HGS), HGS/body weight (BWT), and HGS/body mass index (BMI).

A cross-sectional population study in Singapore. Data were collected on demographics, HGS, Timed-Up and Go (TUG), fasting glucose, lipid profile, blood pressure, waist circumference, frailty status, and cognition in 722 older adults ≥65 years old. MetS was defined using the Modified ATP III for Asians where at least three of the following conditions must be fulfilled, central obesity, high blood glucose (or diagnosed diabetes mellitus), high blood pressure (or diagnosed hypertension), low high-density lipoprotein, and high triglycerides. The waist circumference in the Modified ATP III for Asians is ≥90 cm for males or ≥80 cm for females. HGS and HGS normalized by BWT or BMI were used for the association.

The prevalence of MetS in older adults was 41.0%, and those ≥85 years old 50.0%. The prevalociation with MetS, its components, and adverse effects. Further studies are needed to validate the association and to determine optimal cutoffs of HGS/BWT and HGS/BMI for MetS, and the effectiveness of interventions in averting the risk.

Overweight and obesity are associated with metabolic diseases. However, a subgroup of the overweight/obese population does not present metabolic abnormalities. Hence, there is an urgent need to identify biomarkers that can distinguish different obesity phenotypes and metabolic status.

A total of 98 individuals were divided into three groups metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Participants were evaluated for anthropometric and biochemical parameters and serum BMPR1A concentration and miR-503 level. Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were performed.

The level of miR-503 was significantly higher in the MHO group compared with that in the MUO group, but no difference was observed between the MHNW and MHO groups. Meanwhile, no significant differences in serum BMPR1A concentration were observed between the three groups. ROC curve analysis showed that miR-503 could be used as a marker to distinguish the MUO from the MHO. Logistic regression analysis suggested that miR-503 was an important related factor associated with an unhealthy metabolic state in overweight/obese subjects.

miR-503 can be considered as a suitable biomarker to distinguish between the MUO and MHO, which may be a related factor for the incidence of metabolic disorders in overweight/obese subjects.

miR-503 can be considered as a suitable biomarker to distinguish between the MUO and MHO, which may be a related factor for the incidence of metabolic disorders in overweight/obese subjects.

The research on heterogeneity among obese individuals has identified the metabolically healthy, but obese (MHO) phenotype as a distinct group that does not experience the typical cardiovascular-related diseases (CVD). It is unclear if this group differs with regard to preconditions for CVDs. Our aim was to assess differences in echocardiographic parameters and inflammatory biomarkers between MHO and metabolically healthy, normal weight individuals (MHNW).

The analyses used data from 1412 elderly participants from a German population-based cohort study (CARLA), which collected detailed information on demographic, biochemical, and echocardiographic variables. Participants were subdivided into four groups (MHNW, MHO, MUNW (metabolically unhealthy, normal weight) and MUO (metabolically unhealthy, obese)) based on BMI≥30 kg/m

(obese or normal weight) and presence of components of the metabolic syndrome. The clinical characteristics of the 4 groups were compared with ANOVA or Chi-Square test, in addition to two linear regression models for 16 echocardiographic parameters.