METHODS: After obtaining data on food consumption of palm and soya oils and mortality burdens of CBVDs and DM, correlations between the consumption of oils and mortality burdens of diseases were explored.
RESULTS: There was a positive correlation between the consumption of soya oil with the mortality burden of CBVDs in Australia, Switzerland, and Indonesia, as well as the mortality burden of DM in the USA. The consumption of palm oil had a positive correlation with the mortality burden of DM in Jordan only.
CONCLUSIONS: Food consumption of soya oil in several countries possibly contributes to the mortality burden of CBVDs or DM more than food consumption of palm oil, which could be a possible risk factor in the mortality burdens of CBVDs and DM.
METHODOLOGY: One thousand two hundred and sixteen prospectively enrolled patients with ACLF (males 98%, mean age 42.5 ± 9.4 years, mean CTP, MELD and AARC scores of 12 ± 1.4, 29.7 ± 7 and 9.8 ± 2 respectively) from the Asian Pacific Association for the Study of the Liver (APASL) ACLF Research Consortium (AARC) database were analysed retrospectively. Patients with or without metabolic risk factors were compared for severity (CTP, MELD, AARC scores) and day 30 and 90 mortality. Information on overweight/obesity, type 2 diabetes mellitus (T2DM), hypertension and dyslipidaemia were available in 1028 (85%), 1019 (84%), 1017 (84%) and 965 (79%) patients respectively.
RESULTS: Overall, 392 (32%) patients died at day 30 and 528 (43%) at day 90. Overweight/obesity, T2DM, hypertension and dyslipidaemia were present in 154 (15%), 142 (14%), 66 (7%) and 141 (15%) patients, respectively, with no risk factors in 809 (67%) patients. Patients with overweight/obesity had higher MELD scores (30.6 ± 7.1 vs 29.2 ± 6.9, P = .007) and those with dyslipidaemia had higher AARC scores (10.4 ± 1.2 vs 9.8 ± 2, P = .014). Overweight/obesity was associated with increased day 30 mortality (HR 1.54, 95% CI 1.06-2.24, P = .023). None of other metabolic risk factors, alone or in combination, had any impact on disease severity or mortality. On multivariate analysis, overweight or obesity was significantly associated with 30-day mortality (aHR 1.91, 95% CI 1.41-2.59, P
PURPOSE: This study provides new insights on the changes of endogenous metabolites caused by I. aquatica ethanolic extract and improves the understanding on the therapeutic efficacy and mechanism of I. aquatica ethanolic extract.
METHODS: By using a combination of 1H nuclear magnetic resonance (NMR) with multivariate analysis (MVDA), the changes of metabolites due to I. aquatica ethanolic extract administration in obese diabetic-induced Sprague Dawley rats (OB+STZ+IA) were identified.
RESULTS: The results suggested 19 potential biomarkers with variable importance projections (VIP) above 0.5, which include creatine/creatinine, glucose, creatinine, citrate, carnitine, 2-oxoglutarate, succinate, hippurate, leucine, 1-methylnicotinamice (MNA), taurine, 3-hydroxybutyrate (3-HB), tryptophan, lysine, trigonelline, allantoin, formiate, acetoacetate (AcAc) and dimethylamine. From the changes in the metabolites, the affected pathways and aspects of metabolism were identified.
CONCLUSION: I. aquatica ethanolic extract increases metabolite levels such as creatinine/creatine, carnitine, MNA, trigonelline, leucine, lysine, 3-HB and decreases metabolite levels, including glucose and tricarboxylic acid (TCA) intermediates. This implies capabilities of I. aquatica ethanolic extract promoting glycolysis, gut microbiota and nicotinate/nicotinamide metabolism, improving the glomerular filtration rate (GFR) and reducing the β-oxidation rate. However, the administration of I. aquatica ethanolic extract has several drawbacks, such as unimproved changes in amino acid metabolism, especially in reducing branched chain amino acid (BCAA) synthesis pathways and lipid metabolism.
METHODS: This is a controlled, intervention based study. It was run on three phases: before, during, and after Ramadan on 262 type 2 diabetes patients. The intervention group (n = 140) received RFEP on medications doses & timing adjustment before and after Ramadan, while the control group (n = 122) received standard care.
RESULTS: The dose of insulin glargine was reduced from 42.51 ± 22.16 at the baseline to 40.11 ± 18.51-units during Ramadan (p = 0.002) in the intervention group while it remained the same in the control group before Ramadan and during Ramadan (38.51 ± 18.63 and 38.14 ± 18.46, P = 0.428, respectively). The hypoglycemia score was 14.2 ± (8.5) pre-Ramadan in the intervention and reduced to 6.36 ± 6.17 during Ramadan (p
OBJECTIVE: To investigate the impact of customized CMI (C-CMI) on health-related quality of life (HRQoL) among type 2 diabetes mellitus (T2DM) patients in Qatar.
METHODS: This was a randomized controlled intervention study, in which the intervention group patients received C-CMI and the control group patients received usual care. HRQoL was measured using the EQ-5D-5L questionnaire and EQ visual analog scale (EQ-VAS) at three intervals [i.e. baseline, after 3 months and 6 months].
RESULTS: The EQ-5D-5L index value for the intervention group exhibited sustained improvement from baseline to the third visit. There was a statistically significant difference between groups in the HRQoL utility value (represented as EQ index) at 6 months (0.939 vs. 0.796; p = 0.019). Similarly, the intervention group compared with the control group had significantly greater EQ-VAS at 6 months (90% vs. 80%; p = 0.003).
CONCLUSIONS: The impact of C-CMI on health outcomes of T2DM patients in Qatar reported improvement in HRQoL indicators among the intervention patients. The study built a platform for health policymakers and regulatory agencies to consider the provision of C-CMI in multiple languages.
MATERIALS AND METHODS: This was an investigator-initiated, single-center, randomized, controlled, clinical trial in patients with T2DM and DKD, comparing 12-weeks of low carbohydrate diet (<20g daily intake) versus standard low protein (0.8g/kg/day) and low salt diet. Patients in the VLCBD group underwent 2-weekly monitoring including their 3-day food diaries. In addition, Dual-energy x-ray absorptiometry (DEXA) was performed to estimate body fat percentages.
RESULTS: The study population (n = 30) had a median age of 57 years old and a BMI of 30.68kg/m2. Both groups showed similar total calorie intake, i.e. 739.33 (IQR288.48) vs 789.92 (IQR522.4) kcal, by the end of the study. The VLCBD group showed significantly lower daily carbohydrate intake 27 (IQR25) g vs 89.33 (IQR77.4) g, p<0.001, significantly higher protein intake per day 44.08 (IQR21.98) g vs 29.63 (IQR16.35) g, p<0.05 and no difference in in daily fat intake. Both groups showed no worsening of serum creatinine at study end, with consistent declines in HbA1c (1.3(1.1) vs 0.7(1.25) %) and fasting blood glucose (1.5(3.37) vs 1.3(5.7) mmol/L). The VLCBD group showed significant reductions in total daily insulin dose (39(22) vs 0 IU, p<0.001), increased LDL-C and HDL-C, decline in IL-6 levels; with contrasting results in the control group. This was associated with significant weight reduction (-4.0(3.9) vs 0.2(4.2) kg, p = <0.001) and improvements in body fat percentages. WC was significantly reduced in the VLCBD group, even after adjustments to age, HbA1c, weight and creatinine changes. Both dietary interventions were well received with no reported adverse events.
CONCLUSION: This study demonstrated that dietary intervention of very low carbohydrate diet in patients with underlying diabetic kidney disease was safe and associated with significant improvements in glycemic control, anthropometric measurements including weight, abdominal adiposity and IL-6. Renal outcomes remained unchanged. These findings would strengthen the importance of this dietary intervention as part of the management of patients with diabetic kidney disease.