Effects of lunar cycle on fasting plasma glucose, heart rate and blood pressure in type 2 diabetic patients

2020 ◽  
pp. 1-8
Author(s):  
Sutanu Dutta Chowdhury ◽  
Subhasish Pramanik ◽  
Koena Bhattacharjee ◽  
Lakshmi Kanta Mondal
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Lunar Cycle ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fasting Plasma ◽  
Type 2 Diabetic

scholarly journals Impact of the Pro12Ala Polymorphism of the PPAR-Gamma 2 Gene on Metabolic and Clinical Characteristics in the Palestinian Type 2 Diabetic Patients

PPAR Research ◽  
2009 ◽  
Vol 2009 ◽  
pp. 1-5 ◽  
Author(s):  
S. Ereqat ◽  
A. Nasereddin ◽  
K. Azmi ◽  
Z. Abdeen ◽  
R. Amin
Keyword(s):  
Blood Pressure ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Plasma Cholesterol ◽  
Ppar Gamma ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fasting Plasma ◽  
Type 2 Diabetic

Peroxisome proliferators activated receptor-gamma2 (PPARγ2) represents the transcriptional master regulator of adipocyte differentiation and therefore has been suggested as a candidate gene for obesity, insulin resistance, and dyslipidemia. The objective of the study was to investigate for the first time the potential association of the most common variant Pro12Ala (p.P12A) substitution of thePPARγ2 gene with body mass index (BMI), blood pressure, fasting plasma glucose, plasma total cholesterol, LDL and HDL cholesterol, and plasma triglyceride in a sample of 202 (138 females and 64 male) type 2 diabetic Palestinians. Genotyping of thePPARγ2 p.P12A polymorphism was determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. The A12 allele was associated with lower fasting plasma glucose (P=.03) but had no influence on blood pressure, BMI, or other metabolic parameters. In obese patients, the p.P12A substitution was associated with elevated total plasma cholesterol levels (P=.02) and a tendency toward increased LDL cholesterol level (P=.06). In conclusion, the p.P12A variant of thePPARγ2 may influence cardiovascular risk through effects on lipid metabolism in obese T2D Palestinian patients.

Variability of fasting plasma glucose increased risks of diabetic polyneuropathy in T2DM

Neurology ◽  
2017 ◽  
Vol 88 (10) ◽  
pp. 944-951 ◽  
Author(s):  
Chun-Pai Yang ◽  
Chia-Ing Li ◽  
Chiu-Shong Liu ◽  
Wen-Yuan Lin ◽  
Kai-Lin Hwang ◽  
...  
Keyword(s):  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Diabetic Polyneuropathy ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Related Factors ◽  
Fasting Plasma ◽  
Incident Cases ◽  
Type 2 Diabetic

Objective:To examine whether variations in fasting plasma glucose (FPG), as measured by the coefficient of variation (CV), is a predictor of diabetic polyneuropathy (DPN) risk, considering glycated hemoglobin (HbA1c) and other traditional risk factors.Methods:Type 2 diabetic patients enrolled in the National Diabetes Care Management Program were ≥30 years of age and free of DPN (n = 36,152). They were enrolled in 2002–2004 and were monitored until 2011. The related factors were analyzed using Cox proportional hazards regression models.Results:During an average 7.23 years of follow-up, a total of 7,219 incident cases of DPN were identified, with a crude incidence rate of 27.62/1,000 person-years (25.83 for men and 29.31 for women). After multivariate adjustment, both FPG-CV and HbA1c were significant predictors of DPN, with corresponding hazard ratios of 1.14 (95% confidence interval [CI] 1.05–1.23) and 1.15 (95% CI 1.06–1.24) for FPG-CV in the fourth to fifth quintiles and 1.13 (95% CI 1.07–1.20) for HbA1c ≥7%. This finding maintained consistency after excluding potential confounders in the sensitivity analysis, further validating the results.Conclusions:FPG-CV and HbA1c ≥7% were potent predictors of DPN in type 2 diabetic patients. The associations among HbA1c, glycemic variability, and DPN suggest a linked pathophysiologic mechanism, which may play a crucial role in clinical risk assessments.

scholarly journals Fasting plasma glucose variability predicts 10-year survival of type 2 diabetic patients: the Verona Diabetes Study

Diabetes Care ◽  
2000 ◽  
Vol 23 (1) ◽  
pp. 45-50 ◽  
Author(s):  
M. Muggeo ◽  
G. Zoppini ◽  
E. Bonora ◽  
E. Brun ◽  
R. C. Bonadonna ◽  
...  
Keyword(s):  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Glucose Variability ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fasting Plasma ◽  
Type 2 Diabetic

scholarly journals Diagnosis of Muscle Fatigue Using Surface Electromyography and Analysis of Associated Factors in Type 2 Diabetic Patients with Neuropathy: A Preliminary Study

2021 ◽  
Vol 18 (18) ◽  
pp. 9635
Author(s):  
So Young Park ◽  
Chan Hyuk Park
Keyword(s):  
Muscle Fatigue ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Surface Electromyography ◽  
Medial Gastrocnemius ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fasting Plasma ◽  
Type 2 Diabetic

Diabetic neuropathy (DN) is a major complication associated with diabetes mellitus (DM) and results in fatigue. We investigated whether type 2 diabetic patients with or without neuropathy experienced muscle fatigue and determined the most influencing factor on muscle fatigue. Overall, 15 out of 25 patients with type 2 DM were diagnosed with DN using a nerve conduction study in the upper and lower extremities, and the composite score (CS) was calculated. We obtained the duration of DM and body mass index (BMI) from subjects, and they underwent a series of laboratory tests including HbA1c, fasting plasma glucose, triglycerides, and high- and low-density lipoprotein. To qualify muscle fatigue, this study used surface electromyography (sEMG). Anode and cathode electrodes were attached to the medial gastrocnemius. After 100% isometric maximal voluntary contracture of plantarflexion, the root mean square, median frequency (MDF), and mean power frequency (MNF) were obtained. We showed a correlation among laboratory results, duration of DM, BMI, CS, and parameters of muscle fatigue. The duration of DM was related to fatigue of the muscle and CS (p < 0.05). However, CS was not related to fatigue. The MDF and MNF of muscle parameters were positively correlated with HbA1c and fasting plasma glucose (p < 0.05). In conclusion, we suggest that the duration of DM and glycemic control play important roles in muscle fatigue in patients with DN. Additionally, sEMG is useful for diagnosing muscle fatigue in patients with DN.

scholarly journals Achievements of Diabetes Goals and Their Determinants in Type 2 Diabetic Patients Attending Outpatient Diabetic Clinic in Northern Ethiopia

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Ezra Belay ◽  
Abel Abera ◽  
Aman Mehari ◽  
Gidey Gebremeskel ◽  
Asrat Endrias ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Glycemic Control ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Poor Glycemic Control ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Duration Of Diabetes ◽  
Type 2 Diabetic

Background. The aim of this study was to assess target diabetic goal achievements and to explore variables associated with them. Methods. A cross-sectional study was conducted between December 2015 and April 2016 on 188 type 2 diabetic patients attending Ayder Referral Hospital’s outpatient diabetic clinic. Glycemic control was assessed using fasting plasma glucose values and total cholesterol and triglyceride were used to evaluate lipid profiles. Bivariate and multivariate logistic regression analyses were done to identify factors associated with poor glycemic control, hypertension, and dyslipidemia. Result. Mean duration of diabetes was 6.5 years. Combined glycemic, lipid, and blood pressure targets were achieved only in 8.5% of the participants. More males achieved combined targets than females. Separately, while above two-thirds of the patients had poor glycemic control (67%), more than half of the participants have had poor lipid (58.5%) and blood pressure (52.1%) control. A significant portion of the patients (68.1%) had also comorbidities other than hyperglycemia. In bivariate and multivariate analyses, longer duration of diabetes disease (AOR: 3.4; P=0.013) and marked month to month fasting plasma glucose (FPG) variability as measured by large standard deviation (AOR: 2.5; P=0.023) were significantly associated with overall poor mean FPG results. Female sex was also significantly associated with dyslipidemia (AOR: 1.9; P=0.049). Conclusion. The study showed that achievements of combined diabetic goals are generally poor.

scholarly journals Serum Electrolytes Disturbances in Type 2 Diabetic Patients

2021 ◽  
Vol 11 (7) ◽  
pp. 105-110
Author(s):  
Jivanraj Bohara ◽  
Saroj Kunwar ◽  
Govinda Akela Poudel
Keyword(s):  
Serum Sodium ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Diabetic Patients ◽  
Type Ii ◽  
Type 2 Diabetic Patients ◽  
Sodium Potassium ◽  
Fasting Plasma ◽  
Type 2 Diabetic

Introduction: Type II diabetes mellitus is considered as a global epidemic that can lead to the complication related to renal, retinal and vascular system. Measurement of ions like sodium, potassium and chloride can be useful as a marker for the patient’s susceptibility to develop diabetes related complications. Thus, our study focuses on observing the electrolyte imbalances in type II diabetes patients. Methods: This was a comparative cross-sectional study conducted at Star Hospital, Lalitpur, Nepal. A total of 400 (200 type II diabetic and 200 healthy subjects) participants were enrolled. Blood sample was collected and fasting plasma glucose (FPG) was measured by glucose oxidase-peroxidase method and serum sodium (Na+), potassium (K+) and chloride (Cl-) were measured by ion selective electrode method. Results: In type 2 diabetic patients serum sodium was decreased while potassium and chloride was found to be increased than healthy subjects. We found negative correlation between fasting plasma glucose and sodium (r= -0.36, p= 0.001). On the other hand positive correlation was found between fasting plasma glucose with potassium and chloride (r=0.194, p=0.006 and r= 0.36, p=0.001) respectively. Conclusion: The serum sodium was found to be decreased with the rise in fasting plasma glucose. On the flip side, serum potassium and chloride was increased with the increase in fasting plasma glucose level. Therefore management of type 2 diabetes must include electrolyte profile test to monitor increase or decrease of electrolyte concentration to prevent the patient’s risk of developing the diabetes associated complications. Key words: Diabetes mellitus, electrolytes, glucose, sodium, potassium, chloride.

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