METHODS: All English-language medical literature published from inception till October 2014 which met the inclusion criteria were reviewed and analyzed.
RESULTS: A total of nine papers were included, reviewed and analyzed. The total sample size was 4276 patients. All studies used either of the two DPP4 inhibitors - Vildagliptin or Sitagliptin, vs sulphonylurea or meglitinides. Patients receiving DPP4 inhibitors were less likely to develop symptomatic hypoglycemia (risk ratio 0.46; 95% CI, 0.30-0.70), confirmed hypoglycemia (risk ratio 0.36; 95% CI, 0.21-0.64) and severe hypoglycemia (risk ratio 0.22; 95% CI, 0.10-0.53) compared with patients on sulphonylureas. There was no statistically significant difference in HbA1C changes comparing Vildagliptin and sulphonylurea.
CONCLUSION: DPP4 inhibitor is a safer alternative to sulphonylurea in Muslim patients with type 2 diabetes mellitus who fast during the month of Ramadan as it is associated with lower risk of symptomatic, confirmed and severe hypoglycemia, with efficacy comparable to sulphonylurea.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
METHODS: This is a prospective observational study on patients with SIRS. Plasma creatinine (pCr) and NGAL were measured on ICU admission. Patients were classified according to the occurrence of AKI and sepsis.
RESULTS: Of 225 patients recruited, 129 (57%) had sepsis of whom 67 (52%) also had AKI. 96 patients (43%) had non-infectious SIRS, of whom 20 (21%) also had AKI. NGAL concentrations were higher in AKI patients within both the sepsis and non-infectious SIRS cohorts (both P
RESEARCH DESIGN AND METHODS: NIDDM patients of Chinese, Indian, and Malay origin attending a diabetic clinic in Kuala Lumpur, Malaysia, were matched for age, sex, diabetes duration, and glycemic control (n = 34 in each group). Urinary albumin-to-creatinine ratio was measured in an early morning urine sample. Biochemical measurements included markers of the acute-phase response: serum sialic acid, triglyceride, and (lowered) HDL cholesterol.
RESULTS: The frequency of microalbuminuria did not differ among the Chinese, Indian, and Malay patients (44, 41, and 47%, respectively). In Chinese patients, those with microalbuminuria had evidence of an augmented acute-phase response, with higher serum sialic acid and triglyceride and lower HDL cholesterol levels; and urinary albumin-to-creatinine ratio was correlated with serum sialic acid and triglyceride. The acute-phase response markers were not different in Indians, with microalbuminuria being high in even the normoalbuminuric Indians; only the mean arterial blood pressure was correlated with urinary albumin-to-creatinine ratio in the Indians. Malay NIDDM subjects had an association of microalbuminuria with acute-phase markers, but this was weaker than in the Chinese subjects.
CONCLUSIONS: Microalbuminuria is associated with an acute-phase response in Chinese NIDDM patients in Malaysia, as previously found in Caucasian NIDDM subjects. Elevated urinary albumin excretion has different correlates in other racial groups, such as those originating from the Indian subcontinent. The acute-phase response may have an etiological role in microalbuminuria.
PURPOSE: The aim was to determine the metabolic fingerprint that predicts warfarin response based on the international normalized ratio (INR) in patients who are already receiving warfarin (phase I: identification) and to ascertain the metabolic fingerprint that discriminates stable from unstable INR in patients starting treatment with warfarin (phase II: validation).
EXPERIMENTAL APPROACH: A total of 94 blood samples were collected for phase I: 44 patients with stable INR and 50 with unstable INR. Meanwhile, 23 samples were collected for phase II: nine patients with stable INR and 14 with unstable INR. Data analysis was performed using multivariate analysis including principal component analysis and partial least square-discriminate analysis (PLS-DA), followed by univariate and multivariate logistic regression (MVLR) to develop a model to identify unstable INR biomarkers.
KEY RESULTS: For phase I, the PLS-DA model showed the following results: sensitivity 93.18%, specificity 91.49% and accuracy 92.31%. In the MVLR analysis of phase I, ten regions were associated with unstable INR. For phase II, the PLS-DA model showed the following results: sensitivity 66.67%, specificity 61.54% and accuracy 63.64%.
CONCLUSIONS AND IMPLICATIONS: We have shown that the pharmacometabonomics technique was able to differentiate between unstable and stable INR with good accuracy. NMR-based pharmacometabonomics has the potential to identify novel biomarkers in plasma, which can be useful in individualizing treatment and controlling warfarin side effects, thus, minimizing undesirable effects in the future.