Cinnamomum cassia on Arterial Stiffness and Endothelial Dysfunction in Type 2 Diabetes Mellitus: Outcomes of a Randomized, Double-Blind, Placebo-Controlled Clinical Trial.

Cinnamomum cassia is a medicinal plant whose use has demonstrated benefits on body weight, blood pressure, glucose, and lipids. This study aimed to evaluate the effect of C. cassia on arterial stiffness and endothelial dysfunction (ED) in patients with type 2 diabetes mellitus (T2DM). A randomized, double-blind, placebo-controlled clinical trial was carried out in 18 subjects aged 40-65 years, with a diagnosis of T2DM of one year or less since diagnosis and treated with Metformin 850 mg daily. Patients were randomly assigned to receive either C. cassia or a placebo in 1000 mg capsules, thrice a day, before each meal for 12 weeks. At baseline and after 12 weeks of intervention, brachial-ankle pulse wave velocity and Flow Mediated Dilation were measured, as well as body weight, body mass index (BMI), blood pressure (BP), fasting glucose (FG), glycated hemoglobin A1c (HbA1c), total cholesterol, high density lipoprotein cholesterol, low density lipoprotein cholesterol, and very low density lipoprotein cholesterol, respectively, triglycerides, creatinine, and transaminases. The Mann-Whitney U test for differences between groups and the Wilcoxon signed-rank test for intragroup differences were used, and a P ≤ .05 was considered statistically significant. After C. cassia administration, statistically significant reductions in body weight (81.4 ± 10.4 kg vs. 79.9 ± 9.0 kg, P = .037), BMI (30.6 ± 4.2 kg/m2 vs. 30.1 ± 4.2 kg/m2, P = .018), and HbA1c (53 ± 5.4 mmol/mol vs. 45 ± 2.1 mmol/mol, P = .036) were observed. No changes statistically significant on arterial stiffness, ED, FG, BP, and lipids were observed. C. cassia administration decreases body weight, BMI, and HbA1c without statistically significant changes on arterial stiffness, ED, FG, BP, and lipids. CTR Number: NCT04259606.

Percentage of change and increment of the glucose level after a normal oral tolerance curve between 24 and 28 weeks of pregnancy.

AIM: To determine the percentage of change and increment in glucose levels after a normal oral glucose tolerance test between 24 and 28 weeks of pregnancy. METHODS: We studied 3510 pregnant women who attended their obstetric delivery at a tertiary care hospital in Guadalajara, Mexico in 2018, according to characteristics and risk 1647 (47%) patients were screened for diabetes diagnosis using the oral glucose tolerance test, 501 patients reported normal values between their 24th and 28th week of pregnancy, only 400 patients had their fasting glucose level measured on the same day of their obstetric delivery, to be compared. RESULTS: Average age was 30 years, with an average of 25.3 weeks of pregnancy. The fasting serum glucose levels taken after 28 weeks of pregnancy and before the obstetrical delivery showed an increase of 1.1 mmol/L in women who develop gestational diabetes mellitus, in contrast to women who did not develop gestational diabetes mellitus after 28 weeks their blood glucose only increased on average 0.4 mmol/L. The incidence of gestational diabetes mellitus in the study population during 2018 was 32.7%. Patients who developed gestational diabetes mellitus after a normal oral glucose tolerance test had greater body mass index before the pregnancy and newborns had a higher weight than babies born to mothers without gestational diabetes mellitus. CONCLUSION: Changes in glucose levels after the oral tolerance test of normal glucose require strict monitoring, in that it was demonstrated that 3% of patients developed gestational diabetes mellitus after week 28 of gestation.

Association of Netrin 1 with hsCRP in Subjects with Obesity and Recent Diagnosis of Type 2 Diabetes.

Netrin 1 (Ntn1) is a cell migration protein with an anti-inflammatory effect, which may play a key role in the pathological development of type 2 diabetes (T2D). In this study, we evaluate the relationships between the serum concentrations of Ntn1, glucose, and high-sensitivity C-reactive Protein (hsCRP). We carried out a cross-sectional study including 90 individuals divided into three groups (n = 30): healthy subjects, individuals with obesity without glucose alterations, and individuals with newly diagnosed T2D. Serum concentrations of Ntn1 and hs-CRP were determined by enzyme-linked immunosorbent assay (ELISA). The serum concentration of Ntn1 was higher in individuals with newly diagnosed T2D (0.33 ± 0.22 ng/mL), in comparison to healthy subjects and individuals with obesity (0.13 ± 0.06 and 0.15 ± 0.07 ng/mL, respectively). In addition, we observed a positive association between the levels of Ntn1 and hsCRP (rho = 0.443; p < 0.001) as well as with serum glucose (rho = −0.110; p = 0.05). The serum concentration of Ntn1 was higher in individuals with T2D, in comparison with the other groups in this study, and presented a positive correlation with hsCRP. Therefore, Ntn1 can be considered a promising risk biomarker and a potential therapeutic target for T2D.

Morbid obesity is associated with mortality and acute kidney injury in hospitalized patients with COVID-19.

BACKGROUND & AIMS: Mexico has one of the highest mortality rates by COVID-19 worldwide. This may be partially explained by the high prevalence of overweight/obesity found in general population; however, there is limited information in this regard. Furthermore, acute kidney injury (AKI) and need for renal replacement therapy (RRT) associated to obesity in patients with COVID-19 are still topics of discussion. AIM: To explore the association of obesity, particularly morbid obesity, with mortality and kidney outcomes in a Mexican population of hospitalized patients with COVID-19. METHODS: Retrospective cohort study of 773 patients with COVID-19 hospitalized in a tertiary-care teaching hospital in the Mexican state of Jalisco. Baseline body mass index was classified as: normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), obesity (30-39.9 kg/m2), and morbid obesity (≥40 kg/m2). AKI was diagnosed according to KDIGO clinical practice guidelines. RESULTS: At baseline, 35% of patients had overweight, 39% obesity and 8% morbid obesity. Patients with obesity were younger, more frequently women and with hypertension than normal weight and overweight patients. Frequency of complications in the univariate analysis were not significantly associated to obesity, however in the multivariate analysis (after adjusting for baseline clinical and biochemical differences), morbid obesity was significantly associated to an increased risk of AKI [OR = 2.70 (1.01-7.26), p = 0.05], RRT [OR = 14.4 (1.46-42), p = 0.02], and mortality [OR = 3.54 (1.46-8.55), p = 0.005]. CONCLUSIONS: Almost half of the sample had obesity and morbid obesity. Morbid obesity was significantly associated to an increased risk of AKI, RRT and mortality in hospitalized patients with COVID-19.

Risk factors for mortality of adult patients with COVID-19 hospitalised in an emerging country: a cohort study.

OBJECTIVE: To describe mortality of in-hospital patients with COVID-19 and compare risk factors between survivors and non-survivors. DESIGN: Prospective cohort of adult inpatients. SETTING: Tertiary healthcare teaching hospital in Guadalajara, Mexico. PARTICIPANTS: All patients with confirmed COVID-19 hospitalised from 25 March to 7 September 2020 were included. End of study: 7 November 2020. PRIMARY OUTCOME MEASURES: Patient survival analysed by the Kaplan-Meier method and comparison of factors by the log-rank test. Mortality risk factors analysed by multivariate Cox's proportional-hazard model. RESULTS: One thousand ten patients included: 386 (38%) died, 618 (61%) alive at discharge and six (0.6%) remained hospitalised. There was predominance of men (63%) and high frequency of overweight-obesity (71%); hypertension (54%); diabetes (40%); and lung (9%), cardiovascular (8%) and kidney diseases (11%); all of them significantly more frequent in non-survivors. Overweight-obesity was not different between groups, but severity of disease (Manchester Triage System and quick Sequential Organ Failure Assessment) was significantly worse in non-survivors, who were also significantly older (65 vs 45 years, respectively) and had haematological, biochemical, coagulation and inflammatory biomarkers more altered than survivors. Mortality predictors were invasive mechanical ventilation (IMV; OR 3.31, p<0.0001), admission to intensive care unit (ICU; OR 2.18, p<0.0001), age (OR 1.02, p<0.0001), Manchester Triage System (urgent OR 1.44, p=0.02; immediate/very urgent OR 2.02, p=0.004), baseline C reactive protein (CRP; OR 1.002, p=0.009) and antecedent of kidney disease (OR 1.58, p=0.04) CONCLUSIONS: Mortality in hospitalised patients with COVID-19 in this emerging country centre seemed to be higher than in developed countries. Patients displayed a high frequency of risk factors for poor outcome, but the need for IMV, ICU admission, older age, more severe disease at admission, antecedent of kidney disease and higher CRP levels significantly predicted mortality.

Chitosan improves insulin sensitivity as determined by the euglycemic-hyperinsulinemic clamp technique in obese subjects.

In accordance with obesity is associated with insulin resistance and dyslipidemia and chitosan decrease weight and lipids, but its effect on insulin sensitivity is unknown. Our hypothesis for the research was that chitosan improves insulin sensitivity estimated with the euglycemic-hyperinsulinemic clamp technique in obesity. We undertook this study with the objective to determine the effect of chitosan on insulin sensitivity using the euglycemic-hyperinsulinemic clamp technique in obese patients during a 3-month period. A randomized, double-blind clinical trial was carried out in 12 obese adults without diabetes mellitus. During a 3-month period, 6 patients received chitosan (750 mg, 3 times per day) 30 minutes before meals, and the other 6 subjects received placebo. Serum glucose, total cholesterol, high-density lipoprotein cholesterol, and triglycerides (TG) were measured. Insulin sensitivity was estimated with the euglycemic-hyperinsulinemic clamp technique before and after the intervention. Insulin sensitivity increased significantly with the administration of chitosan (2.4 +/- 1.4 vs 3.6 +/- 1.4 mg kg(-1) min(-1); P = .043). In addition, there was a decrease in weight (90.7 +/- 14.2 vs 84.7 +/- 13.7 kg; P = .027), body mass index (34.3 +/- 2.7 vs 31.6 +/- 2.2 kg/m(2); P = .028), waist circumference (106 +/- 12 vs 99 +/- 9 cm; P = .028) and TG (2.4 +/- 0.9 vs 1.6 +/- 0.9 mmol/L; P = .028) in the chitosan group. In conclusion, 3-month administration of chitosan increased insulin sensitivity in obese patients and demonstrated a decrease in weight, body mass index, waist circumference, and TG.

The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp.

CONTEXT: To meet the worldwide challenge of emerging diabetes, accessible and inexpensive tests to identify insulin resistance are needed. OBJECTIVE: To evaluate the sensitivity and specificity of the product of fasting, we compared the triglycerides and glucose (TyG) index, a simple measure of insulin resistance, with the euglycemic-hyperinsulinemic clamp test. DESIGN AND SETTING: We conducted a cross-sectional study of the general population and outpatients of the Internal Medicine Department at the Medical Unit of High Specialty of the Specialty Hospital at the West National Medical Center in Guadalajara, Mexico. PATIENTS: Eleven nonobese healthy subjects, 34 obese normal glucose tolerance individuals, 22 subjects with prediabetes, and 32 diabetic patients participated in the study. INTERVENTION: We performed a euglycemic-hyperinsulinemic clamp test. MAIN OUTCOME MEASURES: Sensitivity and specificity of the TyG index [Ln(fasting triglycerides) (mg/dl) x fasting glucose (mg/dl)/2] were measured, as well as the area under the curve of the receiver operating characteristic scatter plot and the correlation between the TyG index and the total glucose metabolism (M) rates. RESULTS: Pearson's correlation coefficient between the TyG index and M rates was -0.681 (P < 0.005). Correlation between the TyG index and M rates was similar between men (-0.740) and women (-0.730), nonobese (-0.705) and obese (-0.710), and nondiabetic (-0.670) and diabetic (-0.690) individuals. The best value of the TyG index for diagnosis of insulin resistance was 4.68, which showed the highest sensitivity (96.5%) and specificity (85.0%; area under the curve + 0.858). CONCLUSIONS: The TyG index has high sensitivity and specificity, suggesting that it could be useful for identification of subjects with decreased insulin sensitivity.

Effect of oral L-carnitine administration on insulin sensitivity and lipid profile in type 2 diabetes mellitus patients.

AIM: It was the aim of this study to evaluate the effect of oral L-carnitine administration on insulin sensitivity and lipid profile in subjects with type 2 diabetes mellitus. SUBJECTS AND METHODS: A randomized, double-blind, placebo-controlled clinical trial was carried out in 12 subjects with type 2 diabetes. Six subjects received L-carnitine 1 g orally 3 times a day before meals for a period of 4 weeks. Six other individuals took a placebo for the same period of time, as the control group. Before and after the intervention, insulin sensitivity and the lipid profile were estimated. To assess insulin sensitivity, the euglycemic-hyperinsulinemic clamp technique was performed. Wilcoxon's signed rank and the Mann-Whitney U test were used for the statistical analyses. RESULTS: There were no significant differences in basal clinical characteristics between the 2 groups. Insulin sensitivity and the basal lipid profile were similar. There were no significant changes in either group after the intervention in insulin sensitivity (3.2 +/- 1.2 vs. 4.5 +/- 1.7 mg/kg/min, p = 0.115, and 3.5 +/- 0.6 vs. 3.5 +/- 0.4 mg/kg/min, p = 0.917, for the placebo and L-carnitine groups, respectively) and in lipid profile. CONCLUSION: L-Carnitine orally administered for a period of 4 weeks did not modify insulin sensitivity or the lipid profile.