Displaying publications 41 - 48 of 48 in total

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  1. Rama Chandran S, Tay WL, Lye WK, Lim LL, Ratnasingam J, Tan ATB, et al.
    Diabetes Technol Ther, 2018 05;20(5):353-362.
    PMID: 29688755 DOI: 10.1089/dia.2017.0388
    BACKGROUND: Hypoglycemia is the major impediment to therapy intensification in diabetes. Although higher individualized HbA1c targets are perceived to reduce the risk of hypoglycemia in those at risk of hypoglycemia, HbA1c itself is a poor predictor of hypoglycemia. We assessed the use of glycemic variability (GV) and glycemic indices as independent predictors of hypoglycemia.

    METHODS: A retrospective observational study of 60 type 1 and 100 type 2 diabetes subjects. All underwent professional continuous glucose monitoring (CGM) for 3-6 days and recorded self-monitored blood glucose (SMBG). Indices were calculated from both CGM and SMBG. Statistical analyses included regression and area under receiver operator curve (AUC) analyses.

    RESULTS: Hypoglycemia frequency (53.3% vs. 24%, P Index (LBGI)CGM, Glycemic Risk Assessment Diabetes Equation (GRADE)HypoglycemiaCGM, and Hypoglycemia IndexCGM predicted hypoglycemia well. %CVCGM and %CVSMBG consistently remained a robust discriminator of hypoglycemia in type 1 diabetes (AUC 0.88). In type 2 diabetes, a combination of HbA1c and %CVSMBG or LBGISMBG could help discriminate hypoglycemia.

    CONCLUSION: Assessment of glycemia should go beyond HbA1c and incorporate measures of GV and glycemic indices. %CVSMBG in type 1 diabetes and LBGISMBG or a combination of HbA1c and %CVSMBG in type 2 diabetes discriminated hypoglycemia well. In defining hypoglycemia risk using GV and glycemic indices, diabetes subtypes and data source (CGM vs. SMBG) must be considered.

    Matched MeSH terms: Glycemic Index
  2. Al-Mahmood AK, Ismail AA, Rashid FA, Azwany YN, Singh R, Gill G
    J Atheroscler Thromb, 2007 Jun;14(3):122-7.
    PMID: 17587763 DOI: 10.5551/jat.14.122
    AIM: To determine the effects of lipid lowering by TLC on insulin sensitivity and secretory status of non-obese normoglycemic hyperlipidemic subjects.
    METHODS: An intervention study was undertaken on 16 non-obese normoglycemic hyperlipidemic subjects. They underwent 6 months of a TLC regimen. Their insulin sensitivity and lipid status were assessed at baseline and after six months. A control group containing 16 age, sex and body mass index (BMI) matched normolipidemic subjects was also enrolled to compare the change in lipid levels and insulin sensitivity in the hyperlipidemic subjects.
    RESULTS: The intervention showed significant reductions in insulin resistance (HOMA-IR reduced from 3.8 to 1.4, p<0.001) and improvement of insulin sensitivity (HOMA%S increased from 50.1% to 121.2%, p=0.004) in hyperlipidemic subjects with associated reductions in lipid levels.
    CONCLUSION: Lipid lowering in non-obese hyperlipidemic subjects may be associated with improvement of insulin sensitivity.
    Study site: Staff of university and offices, Kelantan, Malaysia
    Matched MeSH terms: Glycemic Index
  3. Ng SH, Robert SD, Wan Ahmad WA, Wan Ishak WR
    Food Chem, 2017 Jul 15;227:358-368.
    PMID: 28274444 DOI: 10.1016/j.foodchem.2017.01.108
    The purpose of this study was to determine the effects of Pleurotus sajor-caju (PSC) powder addition at 0, 4, 8 and 12% levels on the nutritional values, pasting properties, thermal characteristics, microstructure, in vitro starch digestibility, in vivo glycaemic index (GI) and sensorial properties of biscuits. Elevated incorporation levels of PSC powder increased the dietary fibre (DF) content and reduced the pasting viscosities and starch gelatinisation enthalpy value of biscuits. The addition of DF-rich PSC powder also interfered with the integrity of the starch granules by reducing the sizes and inducing the uneven spherical shapes of the starch granules, which, in turn, resulted in reduced starch susceptibility to digestive enzymes. The restriction starch hydrolysis rate markedly reduced the GI of biscuits. The incorporation of 8% PSC powder in biscuits (GI=49) could be an effective way of developing a nutritious and low-GI biscuit without jeopardizing its desirable sensorial properties.
    Matched MeSH terms: Glycemic Index
  4. Zamora-Ros R, Rinaldi S, Tsilidis KK, Weiderpass E, Boutron-Ruault MC, Rostgaard-Hansen AL, et al.
    Int J Cancer, 2016 Jan 01;138(1):65-73.
    PMID: 26190646 DOI: 10.1002/ijc.29693
    Incidence rates of differentiated thyroid carcinoma (TC) have increased in many countries. Adiposity and dietary risk factors may play a role, but little is known on the influence of energy intake and macronutrient composition. The aim of this study was to investigate the associations between TC and the intake of energy, macronutrients, glycemic index (GI) and glycemic load in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The study included 477,274 middle-age participants (70.2% women) from ten European countries. Dietary data were collected using country-specific validated dietary questionnaires. Total carbohydrates, proteins, fats, saturated, monounsaturated and polyunsaturated fats (PUFA), starch, sugar, and fiber were computed as g/1,000 kcal. Multivariable Cox regression was used to calculate multivariable adjusted hazard ratios (HR) and 95% confidence interval (CI) by intake quartile (Q). After a mean follow-up time of 11 years, differentiated TC was diagnosed in 556 participants (90% women). Overall, we found significant associations only with total energy (HRQ4 vs .Q1 , 1.29; 95% CI, 1.00-1.68) and PUFA intakes (HRQ4 vs .Q1 , 0.74; 95% CI, 0.57-0.95). However, the associations with starch and sugar intake and GI were significantly heterogeneous across body mass index (BMI) groups, i.e., positive associations with starch and GI were found in participants with a BMI ≥ 25 and with sugar intake in those with BMI 
    Matched MeSH terms: Glycemic Index
  5. Robert SD, Ismail AA, Rosli WI
    Eur J Nutr, 2016 Oct;55(7):2275-80.
    PMID: 26358163 DOI: 10.1007/s00394-015-1037-4
    PURPOSE: This study aimed to determine whether fenugreek seed powder could reduce the glycemic response and glycemic index (GI) when added to buns and flatbreads.

    METHODS: In a randomised, controlled crossover trial, ten healthy human subjects (five men, five women) were given 50 g glucose (reference food, twice); buns (0 and 10 % fenugreek seed powder); and flatbreads (0 and 10 % fenugreek seed powder) on six different occasions. Finger prick capillary blood samples were collected at 0, 15, 30, 45, 60, 90 and 120 min after the start of the meal. The palatability of the test meals was scored using Likert scales.

    RESULTS: The incremental areas under the glucose curve value of buns and flatbreads with 10 % fenugreek (138 ± 17 mmol × min/L; 121 ± 16 mmol × min/L) were significantly lower than those of 0 % fenugreek bun and flatbreads (227 ± 15 mmol × min/L; 174 ± 14 mmol × min/L, P = <0.01). Adding 10 % fenugreek seed powder reduced the GI of buns from 82 ± 5 to 51 ± 7 (P 

    Matched MeSH terms: Glycemic Index
  6. Robert SD, Ismail AA
    Ann Nutr Metab, 2012;60(1):27-32.
    PMID: 22212476 DOI: 10.1159/000335224
    Our purpose was to determine whether the glycemic index (GI) of individual foods applies to mixed meals.
    Matched MeSH terms: Glycemic Index
  7. Wong JS, Rahimah N
    Med J Malaysia, 2004 Aug;59(3):411-7.
    PMID: 15727390 MyJurnal
    Achieving glycaemic goals in diabetics has always been a problem, especially in a developing country with inadequate facilities such as in Sarawak in Malaysia. There are no reported studies on the control of diabetes mellitus in a diabetic clinic in the primary health care setting in Sarawak. This paper describes the profile of 1031 patients treated in Klinik Kesihatan Tanah Puteh Health Centre. The mean age was 59 years, the mean BMI 27 kg/m2. There was a female preponderance and mainly type-2 diabetes. Mean HbA1c was 7.4%. Glycaemic control was optimal in 28% (HbA1c <6.5%), fair in 34% (HbA1c 6.5-7.5%) and poor in 38% (HbA1c >7.5%). Reasonable glycaemic control can be achieved in the primary health care setting in Sarawak.
    Study site: Klinik Kesihatan Tanah Puteh, Sarawak, Malaysia
    Matched MeSH terms: Glycemic Index
  8. Mottalib A, Mohd-Yusof BN, Shehabeldin M, Pober DM, Mitri J, Hamdy O
    Nutrients, 2016 Jul 22;8(7).
    PMID: 27455318 DOI: 10.3390/nu8070443
    Diabetes-specific nutritional formulas (DSNFs) are frequently used as part of medical nutrition therapy for patients with diabetes. This study aims to evaluate postprandial (PP) effects of 2 DSNFs; Glucerna (GL) and Ultra Glucose Control (UGC) versus oatmeal (OM) on glucose, insulin, glucagon-like peptide-1 (GLP-1), free fatty acids (FFA) and triglycerides (TG). After an overnight fast, 22 overweight/obese patients with type 2 diabetes were given 200 kcal of each of the three meals on three separate days in random order. Blood samples were collected at baseline and at 30, 60, 90, 120, 180 and 240 min. Glucose area under the curve (AUC0-240) after GL and UGC was lower than OM (p < 0.001 for both). Insulin positive AUC0-120 after UGC was higher than after OM (p = 0.02). GLP-1 AUC0-120 and AUC0-240 after GL and UGC was higher than after OM (p < 0.001 for both). FFA and TG levels were not different between meals. Intake of DSNFs improves PP glucose for 4 h in comparison to oatmeal of similar caloric level. This is achieved by either direct stimulation of insulin secretion or indirectly by stimulating GLP-1 secretion. The difference between their effects is probably related to their unique blends of amino acids, carbohydrates and fat.
    Matched MeSH terms: Glycemic Index
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