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1.
Int J Environ Res Public Health ; 19(7)2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1785646

ABSTRACT

Introduction: Telemedicine interventions are gradually being used in primary health care to help patients with type 2 diabetes receive ongoing medical guidance. The purpose of this study was to analyze the effectiveness of using telemedicine in primary health care for the management of patients with type 2 diabetes. Methods: A systematic search was conducted from database inception to August 2021 in nine databases, including PubMed, Web of Science, Cochrane Library, EMBASE, EBSCO, CNKI, Wanfang Data, VIP, and CBM. Data extraction and quality assessment were performed for studies that met the inclusion criteria. The meta-analysis was performed using Review Manager 5.4 (Cochrane) and Stata v.16.0SE (College Station, TX, USA). Results: A total of 32 articles were included in this study. Analysis showed a reduction in glycated hemoglobin, fasting glucose, and postprandial glucose after the telemedicine intervention. Systolic blood pressure and self-efficacy improved significantly, but there was no significant improvement in weight, lipid metabolism, or diabetes awareness. Subgroup analysis based on the duration of intervention showed significant improvement in glycated hemoglobin at 6 months of intervention. Conclusions: Telemedicine interventions may help patients with type 2 diabetes to effectively control blood glucose and improve self-management in primary health care. There is only moderate benefit, and the benefit may not be sustained beyond 6 months. However, the evidence for the improvement in lipid metabolism is insufficient and further studies are needed.


Subject(s)
Diabetes Mellitus, Type 2 , Telemedicine , Blood Glucose/metabolism , Diabetes Mellitus, Type 2/therapy , Glycated Hemoglobin A/metabolism , Humans , Primary Health Care
2.
Front Public Health ; 10: 850191, 2022.
Article in English | MEDLINE | ID: covidwho-1785450

ABSTRACT

Objective: To investigate whether first-trimester fasting plasma glucose (FPG), blood coagulation function and lipid metabolism could predict gestational diabetes mellitus (GDM) risk. Methods: From October 2020 to May 2021, a total of 584 pregnant women who took prenatal care in Shanghai Jiaotong University Affiliated Sixth People's Hospital were chosen as the observation subjects. The clinical information and serum samples of all pregnant women were collected at 10-13 weeks of gestation and the blood coagulation function, fasting blood glucose and lipid profiles of the pregnant women were detected. A 75 g oral glucose tolerance test was performed up to 24-28 weeks of gestation. One hundred forty-two pregnant women with GDM and 442 pregnant women without GDM were detected. Data were expressed by x ± s or median (interquartile range) and were analyzed using student's t-test, Wilcoxon rank sum test and Logistic regression analysis. The area under the curve (AUC) was calculated by receiver operating characteristic curve (ROC) to analyze the predictive values. Results: Compared with non-GDM group, age, pre-pregnancy BMI, FPG, FIB, D-Dimer, FDP, FPG, TC, TG, LDL-C, sdLDL-C, APOB and APOE in GDM group were significantly higher than those in non-GDM group, while PT, INR, APTT and TT were significantly lower than those in non-GDM group. Univariate logistic regression analysis was used to explore the risk factors of GDM. Gestational age, pre-pregnancy BMI, FPG, PT, INR, APTT, FIB, TT, D-Dimer, TC, TG, LDL-C, sdLDL-C, APOB and APOE were all independent predictors of GDM. Multivariatelogistic regression showed that pre-pregnancy BMI, FPG, APTT, TT, TG, LDL-C, sdLDL-C and APOB were risk factors for GDM. The AUC of the established GDM risk prediction model was 0.892 (0.858-0.927), and the sensitivity and specificity were 80.71 and 86.85%, respectively; which were greater than that of pre-pregnancy BMI, FPG, APTT, TT,TG, LDL-C, sdLDL-C, APOB alone, and the difffference was statistically signifificant (P < 0.05). Conclusions: FPG, APTT, TT, TG, LDL-C, sdLDL-C, APOB and pre-pregnancy BMI in early pregnancy has important clinical value for the prediction of GDM, We combined these laboratory indicators and established a GDM risk prediction model, which is conducive to the early identification, intervention and treatment of GDM, so as to reduce the morbidity of maternal and infant complications.


Subject(s)
Diabetes, Gestational , Apolipoproteins B/metabolism , Apolipoproteins E/metabolism , Blood Coagulation , Blood Glucose/analysis , Blood Glucose/metabolism , Body Mass Index , Cholesterol, LDL/metabolism , Diabetes, Gestational/diagnosis , Early Diagnosis , Female , Glycolipids , Humans , Lipid Metabolism , Pregnancy
3.
Endocrinol Diabetes Nutr (Engl Ed) ; 69(3): 201-208, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1778114

ABSTRACT

INTRODUCTION: Metabolic control in type 1 diabetes (T1D) depends on many factors such as eating habits, exercise and lifestyle. The objective of this study was to investigate how these factors were affected during the coronavirus disease 2019 (COVID-19) lockdown and impacted metabolic control in children with T1D. MATERIALS AND METHOD: One hundred children with T1D were enrolled in the study. Anthropometric measurements, snack and meal frequency, carbohydrate consumption, HbA1c levels, and exercise patterns were recorded and compared before and after the lockdown. Subjects were divided into two subgroups-patients with decreased and patients with increased HbA1c levels after the lockdown-and comparisons of the same parameters were also made between these two subgroups. RESULTS: In the overall group, the mean HbA1c level was significantly higher after the lockdown compared to before (p=0.035). Meal schedules changed due to delayed sleep and waking times, and total daily carbohydrate consumption increased in the subgroup with increased HbA1c while it decreased in the subgroup with decreased HbA1c (p<0.001 for both). CONCLUSION: Our study supports the notion that blood sugar management in children with T1D worsened during the COVID-19 pandemic. Although it is not possible to explain this with any one factor, some behavioral changes observed in our study, such as inactivity, irregular meal frequency and timing, and irregular sleep and waking patterns appeared to be associated with blood sugar management.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 1 , Adolescent , Blood Glucose/metabolism , Child , Communicable Disease Control , Glycated Hemoglobin A , Humans , Pandemics/prevention & control , Quarantine , SARS-CoV-2
4.
Diabetes Metab J ; 46(2): 260-272, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1732345

ABSTRACT

BACKGROUND: Abrupt implementation of lockdowns during the coronavirus disease 2019 (COVID-19) pandemic affected the management of diabetes mellitus in patients worldwide. Limited access to health facilities and lifestyle changes potentially affected metabolic parameters in patients at risk. We conducted a meta-analysis to determine any differences in the control of metabolic parameters in patients with diabetes, before and during lockdown. METHODS: We performed searches of five databases. Meta-analyses were carried out using random- or fixed-effect approaches to glycaemic control parameters as the primary outcome: glycosylated hemoglobin (HbA1c), random blood glucose (RBG), fasting blood glucose (FBG), time-in-range (TIR), time-above-range (TAR), time-below-range (TBR). Mean difference (MD), confidence interval (CI), and P value were calculated. Lipid profile was a secondary outcome and is presented as a descriptive analysis. RESULTS: Twenty-one studies enrolling a total of 3,992 patients with type 1 or type 2 diabetes mellitus (T1DM or T2DM) were included in the study. Patients with T1DM showed a significant improvement of TIR and TAR (MD=3.52% [95% CI, 0.29 to 6.74], I2=76%, P=0.03; MD=-3.36% [95% CI, -6.48 to -0.25], I2=75%, P=0.03), while FBG among patients with T2DM significantly worsened (MD=3.47 mg/dL [95% CI, 1.22 to 5.73], I2=0%, P<0.01). No significant difference was found in HbA1c, RBG, and TBR. Use of continuous glucose monitoring in T1DM facilitated good glycaemic control. Significant deterioration of lipid parameters during lockdown, particularly triglyceride, was observed. CONCLUSION: Implementation of lockdowns during the COVID-19 pandemic did not worsen glycaemic control in patients with diabetes. Other metabolic parameters improved during lockdown, though lipid parameters, particularly triglyceride, worsened.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 1 , Diabetes Mellitus, Type 2 , Blood Glucose/metabolism , Blood Glucose Self-Monitoring , COVID-19/prevention & control , Communicable Disease Control , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 2/epidemiology , Glycated Hemoglobin A/analysis , Humans , Pandemics/prevention & control , Triglycerides
5.
Nutrients ; 13(11)2021 Nov 08.
Article in English | MEDLINE | ID: covidwho-1732137

ABSTRACT

Associations between habitual dietary intake of minerals and glucose metabolism have been extensively studied in relation to metabolic disorders. However, similar research has yet to be conducted in individuals after acute pancreatitis (AP). The main aim was to investigate the associations between habitual intake of 13 minerals and glycaemic status: new-onset prediabetes/diabetes after AP (NODAP), pre-existing prediabetes/type 2 diabetes (T2DM), and normoglycaemia after AP (NAP). Associations between the dietary intake of minerals and markers of glucose metabolism (glycated haemoglobin and fasting plasma glucose) were also studied. The EPIC-Norfolk food frequency questionnaire was used in a cross-sectional fashion to determine the habitual intake of 13 dietary minerals. ANCOVA as well as multiple linear regression analyses were conducted and five statistical models were built to adjust for covariates. The study included 106 individuals after AP. In the NODAP group, intake of 4 minerals was significantly less when compared with the NAP group: iron (B = -0.076, p = 0.013), nitrogen (B = -0.066, p = 0.003), phosphorous (B = -0.046, p = 0.006), and zinc (B = -0.078, p = 0.001). Glycated haemoglobin was significantly associated with iodine intake (B = 17.763, p = 0.032) and manganese intake (B = -17.147, p = 0.003) in the NODAP group. Fasting plasma glucose was significantly associated with manganese intake (B = -2.436, p = 0.027) in the NODAP group. Habitual intake of minerals differs between individuals with NODAP, T2DM, and NAP. Prospective longitudinal studies and randomised controlled trials are now warranted to further investigate the associations between mineral intake and NODAP.


Subject(s)
Diabetes Mellitus/etiology , Diet , Minerals/administration & dosage , Pancreatitis/complications , Prediabetic State/etiology , Biomarkers/blood , Blood Glucose/metabolism , Cross-Sectional Studies , Diabetes Mellitus/metabolism , Diabetes Mellitus, Type 2/metabolism , Female , Glucose/metabolism , Humans , Insulin/blood , Male , Middle Aged , Pancreatitis/metabolism , Prediabetic State/metabolism , Prospective Studies
6.
Diabetologia ; 65(3): 506-517, 2022 03.
Article in English | MEDLINE | ID: covidwho-1610630

ABSTRACT

AIMS/HYPOTHESIS: Lifestyle modification and weight loss are cornerstones of type 2 diabetes management. However, carbohydrate restriction may have weight-independent beneficial effects on glycaemic control. This has been difficult to demonstrate because low-carbohydrate diets readily decrease body weight. We hypothesised that carbohydrate restriction enhances the beneficial metabolic effects of weight loss in type 2 diabetes. METHODS: This open-label, parallel RCT included adults with type 2 diabetes, HbA1c 48-97 mmol/mol (6.5-11%), BMI >25 kg/m2, eGFR >30 ml min-1 [1.73 m]-2 and glucose-lowering therapy restricted to metformin or dipeptidyl peptidase-4 inhibitors. Participants were randomised by a third party and assigned to 6 weeks of energy restriction (all foods were provided) aiming at ~6% weight loss with either a carbohydrate-reduced high-protein diet (CRHP, percentage of total energy intake [E%]: CH30/P30/F40) or a conventional diabetes diet (CD, E%: CH50/P17/F33). Fasting blood samples, continuous glucose monitoring and magnetic resonance spectroscopy were used to assess glycaemic control, lipid metabolism and intrahepatic fat. Change in HbA1c was the primary outcome; changes in circulating and intrahepatic triacylglycerol were secondary outcomes. Data were collected at Copenhagen University Hospital (Bispebjerg and Herlev). RESULTS: Seventy-two adults (CD 36, CRHP 36, all white, 38 male sex) with type 2 diabetes (mean duration 8 years, mean HbA1c 57 mmol/mol [7.4%]) and mean BMI of 33 kg/m2 were enrolled, of which 67 (CD 33, CRHP 34) completed the study. Body weight decreased by 5.8 kg (5.9%) in both groups after 6 weeks. Compared with the CD diet, the CRHP diet further reduced HbA1c (mean [95% CI] -1.9 [-3.5, -0.3] mmol/mol [-0.18 (-0.32, -0.03)%], p = 0.018) and diurnal mean glucose (mean [95% CI] -0.8 [-1.2, -0.4] mmol/l, p < 0.001), stabilised glucose excursions by reducing glucose CV (mean [95% CI] -4.1 [-5.9, -2.2]%, p < 0.001), and augmented the reductions in fasting triacylglycerol concentration (by mean [95% CI] -18 [-29, -6]%, p < 0.01) and liver fat content (by mean [95% CI] -26 [-45, 0]%, p = 0.051). However, pancreatic fat content was decreased to a lesser extent by the CRHP than the CD diet (mean [95% CI] 33 [7, 65]%, p = 0.010). Fasting glucose, insulin, HOMA2-IR and cholesterol concentrations (total, LDL and HDL) were reduced significantly and similarly by both diets. CONCLUSIONS/INTERPRETATION: Moderate carbohydrate restriction for 6 weeks modestly improved glycaemic control, and decreased circulating and intrahepatic triacylglycerol levels beyond the effects of weight loss itself compared with a CD diet in individuals with type 2 diabetes. Concurrent differences in protein and fat intakes, and the quality of dietary macronutrients, may have contributed to these results and should be explored in future studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814694. FUNDING: The study was funded by Arla Foods amba, The Danish Dairy Research Foundation, and Copenhagen University Hospital Bispebjerg Frederiksberg.


Subject(s)
Diabetes Mellitus, Type 2 , Adult , Blood Glucose/metabolism , Blood Glucose Self-Monitoring , Diabetes Mellitus, Type 2/therapy , Dietary Carbohydrates , Glycemic Control , Humans , Liver/metabolism , Male , Weight Loss
7.
Int J Environ Res Public Health ; 19(2)2022 01 10.
Article in English | MEDLINE | ID: covidwho-1633070

ABSTRACT

Type 1 diabetes requires treatment with insulin injections and monitoring glucose levels in affected individuals. We explored the utility of two mathematical models in predicting glucose concentration levels in type 1 diabetic mice and determined disease pathways. We adapted two mathematical models, one with ß-cells and the other with no ß-cell component to determine their capability in predicting glucose concentration and determine type 1 diabetes pathways using published glucose concentration data for four groups of experimental mice. The groups of mice were numbered Mice Group 1-4, depending on the diabetes severity of each group, with severity increasing from group 1-4. A Markov Chain Monte Carlo method based on a Bayesian framework was used to fit the model to determine the best model structure. Akaike information criteria (AIC) and Bayesian information criteria (BIC) approaches were used to assess the best model structure for type 1 diabetes. In fitting the model with no ß-cells to glucose level data, we varied insulin absorption rate and insulin clearance rate. However, the model with ß-cells required more parameters to match the data and we fitted the ß-cell glucose tolerance factor, whole body insulin clearance rate, glucose production rate, and glucose clearance rate. Fitting the models to the blood glucose concentration level gave the least difference in AIC of 1.2, and a difference in BIC of 0.12 for Mice Group 4. The estimated AIC and BIC values were highest for Mice Group 1 than all other mice groups. The models gave substantial differences in AIC and BIC values for Mice Groups 1-3 ranging from 2.10 to 4.05. Our results suggest that the model without ß-cells provides a more suitable structure for modelling type 1 diabetes and predicting blood glucose concentration for hypoglycaemic episodes.


Subject(s)
Diabetes Mellitus, Experimental , Diabetes Mellitus, Type 1 , Animals , Bayes Theorem , Blood Glucose/metabolism , Insulin , Mice , Models, Theoretical
8.
Diabet Med ; 39(4): e14774, 2022 04.
Article in English | MEDLINE | ID: covidwho-1583592

ABSTRACT

AIMS: Evidence suggests that some people with type 1 diabetes mellitus (T1DM) experience temporary instability of blood glucose (BG) levels after COVID-19 vaccination. We aimed to assess this objectively. METHODS: We examined the interstitial glucose profile of 97 consecutive adults (age ≥ 18 years) with T1DM using the FreeStyle Libre® flash glucose monitor in the periods immediately before and after their first COVID-19 vaccination. The primary outcome measure was percentage (%) interstitial glucose readings within the target range 3.9-10 mmol/L for 7 days prior to the vaccination and the 7 days after the vaccination. Data are mean ± standard error. RESULTS: There was a significant decrease in the % interstitial glucose on target (3.9-10.0) for the 7 days following vaccination (mean 52.2% ± 2.0%) versus pre-COVID-19 vaccination (mean 55.0% ± 2.0%) (p = 0.030). 58% of individuals with T1DM showed a reduction in the 'time in target range' in the week after vaccination. 30% showed a decrease of time within the target range of over 10%, and 10% showed a decrease in time within target range of over 20%. The change in interstitial glucose proportion on target in the week following vaccination was most pronounced for people taking metformin/dapagliflozin + basal bolus insulin (change -7.6%) and for people with HbA1c below the median (change -5.7%). CONCLUSION: In T1DM, we have shown that initial COVID-19 vaccination can cause temporary perturbation of interstitial glucose, with this effect more pronounced in people talking oral hypoglycaemic medication plus insulin, and when HbA1c is lower.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Diabetes Mellitus, Type 1/blood , Glycemic Control , Vaccination , Adolescent , Adult , Aged , Blood Glucose/analysis , Blood Glucose/metabolism , Blood Glucose Self-Monitoring , COVID-19/epidemiology , Cohort Studies , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 1/therapy , Female , Glycated Hemoglobin A/analysis , Glycated Hemoglobin A/metabolism , Glycemic Control/methods , Glycemic Control/statistics & numerical data , Humans , Male , Middle Aged , Treatment Outcome , United Kingdom/epidemiology , Vaccination/methods , Vaccination/statistics & numerical data , Young Adult
9.
Front Endocrinol (Lausanne) ; 12: 791476, 2021.
Article in English | MEDLINE | ID: covidwho-1581361

ABSTRACT

Background: We aimed to understand how glycaemic levels among COVID-19 patients impact their disease progression and clinical complications. Methods: We enrolled 2,366 COVID-19 patients from Huoshenshan hospital in Wuhan. We stratified the COVID-19 patients into four subgroups by current fasting blood glucose (FBG) levels and their awareness of prior diabetic status, including patients with FBG<6.1mmol/L with no history of diabetes (group 1), patients with FBG<6.1mmol/L with a history of diabetes diagnosed (group 2), patients with FBG≥6.1mmol/L with no history of diabetes (group 3) and patients with FBG≥6.1mmol/L with a history of diabetes diagnosed (group 4). A multivariate cause-specific Cox proportional hazard model was used to assess the associations between FBG levels or prior diabetic status and clinical adversities in COVID-19 patients. Results: COVID-19 patients with higher FBG and unknown diabetes in the past (group 3) are more likely to progress to the severe or critical stage than patients in other groups (severe: 38.46% vs 23.46%-30.70%; critical 7.69% vs 0.61%-3.96%). These patients also have the highest abnormal level of inflammatory parameters, complications, and clinical adversities among all four groups (all p<0.05). On day 21 of hospitalisation, group 3 had a significantly higher risk of ICU admission [14.1% (9.6%-18.6%)] than group 4 [7.0% (3.7%-10.3%)], group 2 [4.0% (0.2%-7.8%)] and group 1 [2.1% (1.4%-2.8%)], (P<0.001). Compared with group 1 who had low FBG, group 3 demonstrated 5 times higher risk of ICU admission events during hospitalisation (HR=5.38, 3.46-8.35, P<0.001), while group 4, where the patients had high FBG and prior diabetes diagnosed, also showed a significantly higher risk (HR=1.99, 1.12-3.52, P=0.019), but to a much lesser extent than in group 3. Conclusion: Our study shows that COVID-19 patients with current high FBG levels but unaware of pre-existing diabetes, or possibly new onset diabetes as a result of COVID-19 infection, have a higher risk of more severe adverse outcomes than those aware of prior diagnosis of diabetes and those with low current FBG levels.


Subject(s)
Blood Glucose/metabolism , COVID-19/blood , Adult , Aged , Aged, 80 and over , Fasting/blood , Female , Hospitalization , Humans , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors
10.
Biomed Res Int ; 2021: 1676914, 2021.
Article in English | MEDLINE | ID: covidwho-1533104

ABSTRACT

OBJECTIVES: This study screened for factors affecting coronavirus disease 2019 (COVID-19) incidence in type 1 diabetes mellitus (T1DM) patients, appraised vitamin D's efficacy in preventing COVID-19, and assessed the effects of clinical characteristics, glycemic status, vitamin D, and hydroxychloroquine administration on COVID-19's progression and severity in T1DM patients. METHODS: This retrospective research on 150 adults was conducted at Security Forces Hospital, Riyadh, KSA. Participants were allocated to three groups (50/group): control, T1DM, and T1DM with COVID-19. Participants' fasting blood glucose (FBG), glycated hemoglobin (HbA1c), complete blood count, vitamin D, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), ferritin, lactate dehydrogenase (LDH), prothrombin time, activated partial thromboplastin time, D-dimer, liver and kidney function, and hydroxychloroquine treatment were retrieved and analyzed. RESULTS: The percentages of comorbidities and not taking hydroxychloroquine were significantly higher among T1DM patients with COVID-19 than patients with T1DM only. Mean vitamin D level was significantly lower in T1DM with COVID-19 patients than in the other two groups. Vitamin D showed a significant negative correlation with LDH, CRP, ESR, ferritin, and D-dimer, which was the most reliable predictor of COVID-19 severity in T1DM patients. CONCLUSION: Comorbidities and vitamin D deficiency are risk factors for COVID-19 in patients with T1DM. Patients who do not take hydroxychloroquine and have higher FBG and HbA1c levels are vulnerable to COVID-19. Vitamin D may be useful for preventing COVID-19 in T1DM patients. Comorbidities, higher FBG and HbA1c levels, not taking hydroxychloroquine, and vitamin D inadequacy elevate COVID-19 progression and severity in patients with T1DM.


Subject(s)
Biomarkers/blood , COVID-19/drug therapy , COVID-19/epidemiology , Diabetes Mellitus, Type 1/epidemiology , Hydroxychloroquine/therapeutic use , Vitamin D/therapeutic use , Adult , Blood Cell Count , Blood Glucose/metabolism , Blood Sedimentation , C-Reactive Protein/metabolism , COVID-19/blood , Comorbidity , Cross-Sectional Studies , Diabetes Mellitus, Type 1/blood , Disease Progression , Female , Glycated Hemoglobin A/metabolism , Humans , Incidence , Male , Retrospective Studies , SARS-CoV-2 , Saudi Arabia/epidemiology , Severity of Illness Index
12.
J Endocrinol Invest ; 45(2): 445-452, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1392054

ABSTRACT

PURPOSE: This study is aimed at evaluating changes in metrics of glucose control in home-isolated patients with type 1 diabetes and COVID-19 using a continuous glucose monitoring (CGM) system. METHODS: We included adults aged 18-45 years with type 1 diabetes, using CGM, followed by telemedicine at a Southern Italian University Hospital. Thirty-two home-quarantined subjects with SARS-CoV-2 positive swab constituted the COVID-19 group. Thirty age-matched diabetic individuals without COVID-19 formed the control group. The effects of COVID-19 on glycemic control in patients infected were assessed at different time points [2 weeks before-COVID-19 (Time 1), 2 weeks during-COVID-19 (Time 2) and 2 weeks after COVID-19 (Time 3)] and compared with those without infection. RESULTS: A significant reduction of TIR (Time 1 vs Time 2, %, 60.1 ± 16.6 vs 55.4 ± 19.2, P = 0.03), associated with a significant increase of TAR level 2 (10.1 ± 7.3 vs 16.7 ± 12.9, P < 0.001), GMI (7.1 ± 0.6 vs 7.5 ± 0.8, P < 0.001), CV (37.3 ± 7.1 vs 39.6 ± 7.0, P = 0.04), mean glucose values (mg/dL, 160.2 ± 26.5 vs 175.5 ± 32.6, P = 0.001) and standard deviation (59.2 ± 13.1 vs 68.6 ± 17.7, P = 0.001) was observed in patients with COVID-19. No significant change of glycemic metrics was found in the NO COVID-19 group across the time. CONCLUSION: Young home-isolated patients with type 1 diabetes and COVID-19 showed a worsening of glucose control during COVID-19, as compared with age-matched diabetic subjects without the infection.


Subject(s)
COVID-19/therapy , Diabetes Mellitus, Type 1/therapy , Glycemic Control , Quarantine , Adolescent , Adrenal Cortex Hormones/therapeutic use , Adult , Blood Glucose/drug effects , Blood Glucose/metabolism , Blood Glucose Self-Monitoring , COVID-19/blood , COVID-19/complications , Case-Control Studies , Diabetes Mellitus, Type 1/blood , Diabetes Mellitus, Type 1/complications , Female , Glycated Hemoglobin A/drug effects , Glycated Hemoglobin A/metabolism , Humans , Insulin/administration & dosage , Insulin Infusion Systems , Italy , Male , Retrospective Studies , Telemedicine , Young Adult
13.
Front Endocrinol (Lausanne) ; 12: 703905, 2021.
Article in English | MEDLINE | ID: covidwho-1376692

ABSTRACT

Importance: There is no consensus on the impact of the 2020 COVID-19 pandemic lockdown on glycemic control in children and adolescents with type 1 diabetes (T1D) in the US. Aim: To determine the impact of the pandemic lockdown of March 15th through July 6th, 2020 on glycemic control after controlling for confounders. Subjects and Methods: An observational study of 110 subjects of mean age 14.8 ± 4.9 years(y), [male 15.4 ± 4.0y, (n=57); female 14.1 ± 3.8y, (n=53), p=0.07] with T1D of 6.31 ± 4.3y (95% CI 1.0-19.7y). Data were collected at 1-4 months before the lockdown and 1-4 months following the lifting of the lockdown at their first post-lockdown clinic visit. Results: There was no significant change in A1c between the pre- and post-pandemic lockdown periods, 0.18 ± 1.2%, (95% CI -0.05 to 0.41), p=0.13. There were equally no significant differences in A1c between the male and female subjects, -0.16 ± 1.2 vs -0.19 ± 1.2%, p=0.8; insulin pump users and non-pump users, -0.25 ± 1.0 vs -0.12 ± 1.4%, p=0.5; and pubertal vs prepubertal subjects, 0.18 ± 1.3 vs -0.11 ± 0.3%, p=0.6. The significant predictors of decrease in A1c were pre-lockdown A1c (p<0.0001) and the use of CGM (p=0.019). The CGM users had significant reductions in point-of-care A1c (0.4 ± 0.6%, p=0.0012), the CGM-estimated A1c (p=0.0076), mean glucose concentration (p=0.022), a significant increase in sensor usage (p=0.012), with no change in total daily dose of insulin (TDDI). The non-CGM users had significantly increased TDDI (p<0.0001) but no change in HbA1c, 0.06 ± 1.8%, p=0.86. Conclusions: There was no change in glycemic control during the pandemic lockdown of 2020 in US children.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus, Type 1/blood , Glycemic Control , Quarantine , Adolescent , Age Factors , Blood Glucose/metabolism , Blood Glucose Self-Monitoring/instrumentation , Blood Glucose Self-Monitoring/methods , COVID-19/prevention & control , Child , Communicable Disease Control/organization & administration , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 1/therapy , Female , Glycated Hemoglobin A/metabolism , Glycemic Control/instrumentation , Glycemic Control/methods , History, 21st Century , Humans , Insulin/administration & dosage , Insulin Infusion Systems , Male , Pandemics , Quarantine/organization & administration , Retrospective Studies , United States/epidemiology
14.
Endocrinol Metab (Seoul) ; 36(2): 240-255, 2021 04.
Article in English | MEDLINE | ID: covidwho-1359307

ABSTRACT

Continuous glucose monitors (CGMs) have suddenly become part of routine care in many hospitals. The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. The use of CGMs to automatically and remotely supplement or replace assisted monitoring of blood glucose by bedside nurses can decrease: the amount of necessary nursing exposure to COVID-19 patients with diabetes; the amount of time required for obtaining blood glucose measurements, and the amount of personal protective equipment necessary for interacting with patients during the blood glucose testing. The United States Food and Drug Administration (FDA) is now exercising enforcement discretion and not objecting to certain factory-calibrated CGMs being used in a hospital setting, both to facilitate patient care and to obtain performance data that can be used for future regulatory submissions. CGMs can be used in the hospital to decrease the frequency of fingerstick point of care capillary blood glucose testing, decrease hyperglycemic episodes, and decrease hypoglycemic episodes. Most of the research on CGMs in the hospital has focused on their accuracy and only recently outcomes data has been reported. A hospital CGM program requires cooperation of physicians, bedside nurses, diabetes educators, and hospital administrators to appropriately select and manage patients. Processes for collecting, reviewing, storing, and responding to CGM data must be established for such a program to be successful. CGM technology is advancing and we expect that CGMs will be increasingly used in the hospital for patients with diabetes.


Subject(s)
Blood Glucose Self-Monitoring/trends , Blood Glucose/metabolism , COVID-19/epidemiology , Diabetes Mellitus/blood , Diabetes Mellitus/epidemiology , Hospitals/trends , Blood Glucose Self-Monitoring/methods , COVID-19/prevention & control , Humans , Hypoglycemia/blood , Hypoglycemia/epidemiology , Hypoglycemia/prevention & control , Monitoring, Ambulatory/methods , Monitoring, Ambulatory/trends
15.
Diabetes Metab Syndr ; 15(5): 102244, 2021.
Article in English | MEDLINE | ID: covidwho-1356196

ABSTRACT

BACKGROUND: We aim to provide a practical guidance on the use of intravenous insulin infusion for managing inpatient hyperglycemia. METHODS AND RESULTS: This document was formulated based on the review of available literature and personal experience of authors. We have used various case scenarios to illustrate variables which should be taken into account when deciding adjustments in infusion rate, including but not restricted to ambient blood glucose level and magnitude of blood glucose change in the previous hour. CONCLUSION: The guidance can be generalized to any situation where dedicated protocols are lacking, trained manpower is not available and resource constraints are present.


Subject(s)
Hospitalization , Hyperglycemia/drug therapy , Insulin/administration & dosage , Blood Glucose/metabolism , Glycemic Control/methods , Glycemic Control/standards , Humans , Hyperglycemia/blood , Infusions, Intravenous , Inpatients , Practice Guidelines as Topic
16.
Int J Mol Sci ; 22(15)2021 Jul 31.
Article in English | MEDLINE | ID: covidwho-1346501

ABSTRACT

17,18-Epoxyeicosatetraenoic acid (17,18-EEQ) and 19,20-epoxydocosapentaenoic acid (19,20-EDP) are bioactive epoxides produced from n-3 polyunsaturated fatty acid eicosapentaenoic acid and docosahexaenoic acid, respectively. However, these epoxides are quickly metabolized into less active diols by soluble epoxide hydrolase (sEH). We have previously demonstrated that an sEH inhibitor, t-TUCB, decreased serum triglycerides (TG) and increased lipid metabolic protein expression in the brown adipose tissue (BAT) of diet-induced obese mice. This study investigates the preventive effects of t-TUCB (T) alone or combined with 19,20-EDP (T + EDP) or 17,18-EEQ (T + EEQ) on BAT activation in the development of diet-induced obesity and metabolic disorders via osmotic minipump delivery in mice. Both T + EDP and T + EEQ groups showed significant improvement in fasting glucose, serum triglycerides, and higher core body temperature, whereas heat production was only significantly increased in the T + EEQ group. Moreover, both the T + EDP and T + EEQ groups showed less lipid accumulation in the BAT. Although UCP1 expression was not changed, PGC1α expression was increased in all three treated groups. In contrast, the expression of CPT1A and CPT1B, which are responsible for the rate-limiting step for fatty acid oxidation, was only increased in the T + EDP and T + EEQ groups. Interestingly, as a fatty acid transporter, CD36 expression was only increased in the T + EEQ group. Furthermore, both the T + EDP and T + EEQ groups showed decreased inflammatory NFκB signaling in the BAT. Our results suggest that 17,18-EEQ or 19,20-EDP combined with t-TUCB may prevent high-fat diet-induced metabolic disorders, in part through increased thermogenesis, upregulating lipid metabolic protein expression, and decreasing inflammation in the BAT.


Subject(s)
Anti-Obesity Agents/therapeutic use , Arachidonic Acids/therapeutic use , Benzoates/therapeutic use , Obesity/drug therapy , Phenylurea Compounds/therapeutic use , Adipogenesis , Adipose Tissue, Brown/cytology , Adipose Tissue, Brown/drug effects , Adipose Tissue, Brown/metabolism , Animals , Anti-Obesity Agents/administration & dosage , Anti-Obesity Agents/pharmacology , Arachidonic Acids/administration & dosage , Arachidonic Acids/pharmacology , Benzoates/administration & dosage , Benzoates/pharmacology , Blood Glucose/metabolism , Carnitine O-Palmitoyltransferase/metabolism , Diet, High-Fat , Epoxide Hydrolases/antagonists & inhibitors , Fatty Acids/metabolism , Male , Mice , Mice, Inbred C57BL , NF-kappa B/metabolism , Obesity/etiology , Obesity/metabolism , Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/metabolism , Phenylurea Compounds/administration & dosage , Phenylurea Compounds/pharmacology
18.
Vitam Horm ; 117: 253-318, 2021.
Article in English | MEDLINE | ID: covidwho-1330459

ABSTRACT

The immune and endocrine systems collectively control homeostasis in the body. The endocrine system ensures that values of essential factors and nutrients such as glucose, electrolytes and vitamins are maintained within threshold values. The immune system resolves local disruptions in tissue homeostasis, caused by pathogens or malfunctioning cells. The immediate goals of these two systems do not always align. The immune system benefits from optimal access to nutrients for itself and restriction of nutrient availability to all other organs to limit pathogen replication. The endocrine system aims to ensure optimal nutrient access for all organs, limited only by the nutrients stores that the body has available. The actual state of homeostatic parameters such as blood glucose levels represents a careful balance based on regulatory signals from the immune and endocrine systems. This state is not static but continuously adjusted in response to changes in the current metabolic needs of the body, the amount of resources it has available and the level of threats it encounters. This balance is maintained by the ability of the immune and endocrine systems to interact and co-regulate systemic metabolism. In context of metabolic disease, this system is disrupted, which impairs functionality of both systems. The failure of the endocrine system to retain levels of nutrients such as glucose within threshold values impairs functionality of the immune system. In addition, metabolic stress of organs in context of obesity is perceived by the immune system as a disruption in local homeostasis, which it tries to resolve by the excretion of factors which further disrupt normal metabolic control. In this chapter, we will discuss how the immune and endocrine systems interact under homeostatic conditions and during infection with a focus on blood glucose regulation. In addition, we will discuss how this system fails in the context of metabolic disease.


Subject(s)
Blood Glucose/immunology , Blood Glucose/metabolism , Endocrine System/immunology , Endocrine System/metabolism , Infections/immunology , Infections/metabolism , Humans
19.
J Diabetes Investig ; 12(12): 2242-2246, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1329011

ABSTRACT

During the coronavirus disease 2019 pandemic, the Japanese Society of Diabetes and Pregnancy proposed the use of random plasma glucose and glycated hemoglobin measured 1 month after delivery combined with pre-pregnancy body mass index to detect postpartum glucose intolerance instead of carrying out the oral glucose tolerance test in women with gestational diabetes. We retrospectively evaluated the clinical utility of this strategy to detect postpartum glucose intolerance evaluated by the oral glucose tolerance test after delivery. A total of 275 Japanese women with gestational diabetes were included in the present study. The specificity of 1-month postpartum random plasma glucose and glycated hemoglobin combined with pre-pregnancy body mass index to predict postpartum glucose intolerance was 98.0%, with a negative predictive value of 72.6%. However, sensitivity was 6.4%, with a positive predictive value of 55.6%. In conclusion, this Japanese Society of Diabetes and Pregnancy strategy showed high specificity, but low sensitivity, for detecting glucose intolerance postpartum.


Subject(s)
Blood Glucose/metabolism , Body Mass Index , Diabetes, Gestational/blood , Glucose Intolerance/blood , Glycated Hemoglobin A/metabolism , Postpartum Period/blood , Adult , Diabetes, Gestational/diagnosis , Diabetes, Gestational/epidemiology , Female , Glucose Intolerance/diagnosis , Glucose Intolerance/epidemiology , Humans , Japan/epidemiology , Pregnancy , Retrospective Studies , Time Factors
20.
PLoS One ; 16(7): e0254847, 2021.
Article in English | MEDLINE | ID: covidwho-1320548

ABSTRACT

IMPORTANCE: Patients with diabetes are known to be at increased risk for infections including severe coronavirus disease 2019 (COVID-19) but the relationship between COVID-19 severity and specific pre-infection glucose levels is not known. OBJECTIVE: To assess the differential effects of pre-infection glucose levels on the risk for severe COVID-19 amongst patients with and without diabetes. DESIGN: Population based historical cohort study. SETTING: National state-mandated HMO. PATIENTS: All adult patients with a positive SARS-COV2 test between March-October 2020. EXPOSURE: Recent fasting blood glucose (FBG) and glycated hemoglobin (HBA1C), age, gender, body mass index (BMI) and diagnoses of diabetes, hypertension, ischemic heart disease. OUTCOME: Risk for severe COVID-19, defined as resulting in ≥10 hospitalization days, ICU admission or death. RESULTS: 37,121 patients with a positive SARS-COV2 test were identified; 707 defined as severe (1.9%). Unadjusted risk factors for severe disease were age (OR = 1.1 for every year increase; 95% CI 1.09-1.11, p < 0.001), male gender (OR = 1.34, 95% CI 1.06-1.68, p = 0.012); BMI (OR = 1.02 for 1 kg/m2 increase, 95% CI 1.00-1.04, p = 0.025). Controlling for these factors, we found an association between pre-infection FBG and the risk of severe COVID-19, with a differential effect in patients with and without a diagnosis of diabetes. For patients without diabetes, elevated FBG in the pre-diabetes range (106-125 mg/dl) was associated with severe COVID-19 (OR 1.55 95% CI 1.04-2.26 p = 0.027). For patients with a diagnosis of diabetes, we found a J-shaped association between pre-infection glucose control and the risk for severe COVID-19 where the lowest risk for was for patients with FBG 106-125 mg/dl; the risk increased with higher pre-infection glucose levels but strikingly also for patients with a low pre-infection FBG (<100mg/dl) or HbA1C (<5.7%). CONCLUSIONS AND RELEVANCE: Elevated pre-infection blood glucose is a risk factor for severe COVID-19 even in non-diabetics. For patients with a diagnosis of diabetes both high as well as low pre-infection glucose levels are risk factors for severe COVID-19. Further research is required to assess whether these associations are causal, but we believe these findings can already have clinical implications for COVID-19 risk assessment and stratification.


Subject(s)
Blood Glucose/metabolism , COVID-19/blood , COVID-19/epidemiology , Adult , Aged , Cohort Studies , Fasting/blood , Female , Hospitalization , Humans , Male , Middle Aged , Risk Factors
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