Metformin with Versus without Concomitant Probiotic Therapy in Newly Diagnosed Patients with Type 2 Diabetes or Prediabetes: A Comparative Analysis in Relation to Glycemic Control, Gastrointestinal Side Effects, and Treatment Compliance.

BACKGROUND: To evaluate the impact of concomitant use of probiotic BB-12 in metformin-treated patients with type 2 diabetes or prediabetes on glycemic control, metformin-related gastrointestinal side effects, and treatment compliance. METHODS: A total of 156 patients (mean [standard deviation] age: 50.9 [9.9 years], 74.4% females) with newly diagnosed type 2 diabetes or prediabetes were randomly assigned to receive either metformin alone (n = 84, MET group) or metformin plus Bifidobacterium animalis subsp. lactis (BB-12) probiotic (n = 72, MET-PRO group). Data on body mass index (kg/m2), fasting blood glucose (mg/dL), blood lipids, and glycated hemoglobin (HbA1c) levels were recorded at baseline and at the third month of therapy. Data on gastrointestinal intolerance symptoms and treatment noncompliance were also recorded during post-treatment week 1 to week 4. RESULTS: MET-PRO versus MET therapy was associated with a significantly higher rate of treatment compliance (91.7% vs 71.4%, P = .001), greater reduction from baseline HbA1c values (0.9 [0.4-1.6] vs 0.4 [0-1.6] %, P < .001) and lower likelihood of gastrointestinal intolerance symptoms, including abdominal pain (P = .031 to <.001), diarrhea (P = .005 to <.001) and bloating (P = .010 to <.001). Noncompliance developed later (at least 15 days after the therapy) in a significantly higher percentage of patients in the MET group (P = .001 for 15-21 days and P = .002 for 22-28 days). CONCLUSION: In conclusion, the present study proposes the benefit of combining probiotics with metformin in the treatment of patients with T2D or prediabetes in terms of improved glycemic control and treatment adherence rather than correction of dyslipidemia or weight reduction.

Visceral fat index: a novel predictor for coronary collateral circulation.

Objective This study was designed to investigate the role of visceral adiposity along with other clinical parameters in predicting poor coronary collateral circulation (CCC) among patients with severe obstructive coronary artery disease (CAD). Subjects and methods A total of 135 patients with severe obstructive CAD and good (n = 70) or poor (n = 65) CCC were included. Data on angiographically detected CCC, the quality criteria for CCC (Rentrop scores) and visceral fat index (VFI) obtained via bioelectrical impedance were compared between good and poor CCC groups. Independent predictors of poor CCC, the correlation between VFI and Rentrop score and the role of VFI in the identification of CCC were analyzed. Results A significant negative correlation was noted between VFI and Rentrop scores (r = -0.668, < 0.001). The presence of hypertension (OR 4.244, 95% CI 1.184 to 15.211, p = 0.026) and higher VFI (OR 1.955, 95% CI 1.342 to 2.848, p < 0.001) were shown to be independent predictors of an increased risk for poor CCC. ROC analysis revealed a VFI > 9 (AUC [area under the curve] (95% CI): 0.898 (0.834-0.943), p < 0.0001) to be a potential predictor of poor CCC with a sensitivity of 95.38% and specificity of 85.71%. Conclusion In conclusion, our findings revealed comorbid hypertension and higher VFI to significantly predict the risk of poor CCC in patients with severe obstructive CAD.

Visceral fat index: a novel predictor for coronary collateral circulation

ABSTRACT Objective This study was designed to investigate the role of visceral adiposity along with other clinical parameters in predicting poor coronary collateral circulation (CCC) among patients with severe obstructive coronary artery disease (CAD). Subjects and methods A total of 135 patients with severe obstructive CAD and good (n = 70) or poor (n = 65) CCC were included. Data on angiographically detected CCC, the quality criteria for CCC (Rentrop scores) and visceral fat index (VFI) obtained via bioelectrical impedance were compared between good and poor CCC groups. Independent predictors of poor CCC, the correlation between VFI and Rentrop score and the role of VFI in the identification of CCC were analyzed. Results A significant negative correlation was noted between VFI and Rentrop scores (r = -0.668, < 0.001). The presence of hypertension (OR 4.244, 95% CI 1.184 to 15.211, p = 0.026) and higher VFI (OR 1.955, 95% CI 1.342 to 2.848, p < 0.001) were shown to be independent predictors of an increased risk for poor CCC. ROC analysis revealed a VFI > 9 (AUC [area under the curve] (95% CI): 0.898 (0.834-0.943), p < 0.0001) to be a potential predictor of poor CCC with a sensitivity of 95.38% and specificity of 85.71%. Conclusion In conclusion, our findings revealed comorbid hypertension and higher VFI to significantly predict the risk of poor CCC in patients with severe obstructive CAD.

Could Insulin and Hemoglobin A1c Levels be Predictors of Hunger- Related Malnutrition/Undernutrition Without Disease?

BACKGROUND: Malnutrition results in functional changes in the liver and pancreas that negatively affect carbohydrate metabolism. The aim of this study was to evaluate whether insulin hormone and glycated hemoglobin A1c (HbA1c) could serve as predictors of hunger-related malnutrition/undernutrition without disease in adults. METHODS: The Malnutrition Universal Screening Tool (MUST) was used to assess malnutrition in this single-center, cross-sectional study. The malnourished group (n = 67) comprised patients with a MUST score of ≥ 2, and the control group (n = 31) included subjects with a MUST score of 0 - 1. Serum albumin, prealbumin, C-reactive protein (CRP), fasting glucose, fasting insulin, hemoglobin and HbA1c levels, body mass index (BMI), and homoeostatic model for insulin resistance (HOMA-IR) scores were compared between the two groups. RESULTS: No significant difference was determined between the control and malnourished groups in respect of age or gender. HbA1c [5.5% (5 - 6.2) vs. 5.2% (3.9 - 6.7), p = 0.001], insulin levels [7.37 (2.36 - 52.16) vs. 3.91(1.17 - 30.08) µIU/mL, p < 0.001], and BMI [21.7 (14.1 - 34.0) vs. 17.8 (12.0 - 26.6) kg/m2, p < 0.001] were significantly lower in the malnourished group. Logistic regression analysis revealed that BMI was the only significant parameter (odds ratio [95% confidence interval] 0.680 [0.543 - 0.852]). CONCLUSIONS: Plasma insulin and HbA1c levels were significantly decreased in young adult malnourished patients without disease who had normal fasting glucose levels. These two parameters are known to be unaffected by inflammatory states, and therefore warrant further research on larger and different age sub-populations to assess if they might be early predictors of hunger-related malnutrition without disease.