Effect of COVID 19 pneumonia on hyperglycemia: Is it different from non COVID pneumonia?

BACKGROUND AND AIMS: Glycemic control in critical illness has been linked to outcomes. We sought to investigate if COVID pneumonia was causing disrupted glycemic control compared to historically similar diseases. METHODS: At Intermountain Healthcare, a 23-hospital healthcare system in the intermountain west, we performed a multicenter, retrospective cohort observational study. We compared 13,268 hospitalized patients with COVID pneumonia to 6673 patients with non -COVID-pneumonia. RESULTS: Patients with COVID-19 were younger had fewer comorbidities, had lower mortality and greater length of hospital stay. Our regression models demonstrated that daily insulin dose, indexed for weight, was associated with COVID-19, age, diabetic status, HgbA1c, admission SOFA, ICU length of stay and receipt of corticosteroids. There was significant interaction between a diagnosis of diabetes and having COVID-19. Time in range for our IV insulin protocol was not correlated with having COVID after adjustment. It was correlated with ICU length of stay, diabetic control (HgbA1C) and prior history of diabetes. Among patients with subcutaneous (SQ) insulin only percent of glucose checks in range was correlated with diabetic status, having Covid-19, HgbA1c, total steroids given and Elixhauser comorbidity score even when controlled for other factors. CONCLUSIONS: Hospitalized patients with COVID-19 pneumonia who receive insulin for glycemic control require both more SQ and IV insulin than the non-COVID-19 pneumonia counterparts. Patients with COVID-19 who received SQ insulin only had a lower percent of glucose checks in range.

The change in glycaemic control immediately after COVID-19 vaccination in people with type 1 diabetes.

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.

Telemedicine and urban diabetes during COVID-19 pandemic in Milano, Italy during lock-down: epidemiological and sociodemographic picture.

BACKGROUND: Since 2010, more than half of World population lives in Urban Environments. Urban Diabetes has arisen as a novel nosological entity in Medicine. Urbanization leads to the accrual of a number of factors increasing the vulnerability to diabetes mellitus and related diseases. Herein we report clinical-epidemiological data of the Milano Metropolitan Area in the contest of the Cities Changing Diabetes Program. Since the epidemiological picture was taken in January 2020, on the edge of COVID-19 outbreak in the Milano Metropolitan Area, a perspective addressing potential interactions between diabetes and obesity prevalence and COVID-19 outbreak, morbidity and mortality will be presented. To counteract lock-down isolation and, in general, social distancing a pilot study was conducted to assess the feasibility and efficacy of tele-monitoring via Flash Glucose control in a cohort of diabetic patients in ASST North Milano. METHODS: Data presented derive from 1. ISTAT (National Institute of Statistics of Italy), 2. Milano ATS web site (Health Agency of Metropolitan Milano Area), which entails five ASST (Health Agencies in the Territories). A pilot study was conducted in 65 screened diabetic patients (only 40 were enrolled in the study of those 36 were affected by type 2 diabetes and 4 were affected by type 1 diabetes) of ASST North Milano utilizing Flash Glucose Monitoring for 3 months (mean age 65 years, HbA1c 7,9%. Patients were subdivided in 3 groups using glycemic Variability Coefficient (VC): a. High risk, VC > 36, n. 8 patients; Intermediate risk 20 < VC < 36, n. 26 patients; Low risk VC < 20, n. 4 patients. The control group was constituted by 26 diabetic patients non utilizing Flash Glucose monitoring. RESULTS: In a total population of 3.227.264 (23% is over 65 y) there is an overall prevalence of 5.65% with a significant difference between Downtown ASST (5.31%) and peripheral ASST (ASST North Milano, 6.8%). Obesity and overweight account for a prevalence of 7.8% and 27.7%, respectively, in Milano Metropolitan Area. We found a linear relationship (R = 0.36) between prevalence of diabetes and aging index. Similarly, correlations between diabetes prevalence and both older people depending index and structural dependence index (R = 0.75 and R = 0.93, respectively), were found. A positive correlation (R = 0.46) with percent of unoccupied people and diabetes prevalence was also found. A reverse relationship between diabetes prevalence and University level instruction rate was finally identified (R = - 0.82). Our preliminary study demonstrated a reduction of Glycated Hemoglobin (p = 0.047) at 3 months follow-up during the lock-down period, indicating Flash Glucose Monitoring and remote control as a potential methodology for diabetes management during COVID-19 lock-down. HYPOTHESIS AND DISCUSSION: The increase in diabetes and obesity prevalence in Milano Metropolitan Area, which took place over 30 years, is related to several environmental factors. We hypothesize that some of those factors may have also determined the high incidence and virulence of COVID-19 in the Milano area. Health Agencies of Milano Metropolitan Area are presently taking care of diabetic patients facing the new challenge of maintaining sustainable diabetes care costs in light of an increase in urban population and of the new life-style. The COVID-19 pandemic will modify the management of diabetic and obese patients permanently, via the implementation of approaches that entail telemedicine technology. The pilot study conducted during the lock-down period indicates an improvement of glucose control utilizing a remote glucose control system in the Milano Metropolitan Area, suggesting a wider utilization of similar methodologies during the present "second wave" lock-down.

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range.

Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted the lives of people with diabetes. Use of real-time continuous glucose monitoring (rtCGM) helped manage diabetes effectively. Some of these disruptions may be reflected in population-scale changes to metrics of glycemic control, such as time-in-range (TIR). Methods: We examined data from 65,067 U.S.-based users of the G6 rtCGM System (Dexcom, Inc., San Diego, CA) who had uploaded data before and during the COVID-19 pandemic. Users associated with three counties that included the cities of Los Angeles, Chicago, and New York or with five regions designated by the Centers for Disease Control and Prevention (CDC) were compared. Public data were used to associate regions with prepandemic and intrapandemic glycemic parameters, COVID-19 mortality, and median household income. Results: Compared with an 8-week prepandemic interval before stay-at-home orders (January 6, 2020, to March 1, 2020), overall mean (standard deviation) TIR improved from 59.0 (20.1)% to 61.0 (20.4)% during the early pandemic period (April 20, 2020 to June 14, 2020, P < 0.001). TIR improvements were noted in all three counties and in all five CDC-designated regions. Higher COVID-19 mortality was associated with higher proportions of individuals experiencing TIR improvements of ≥5 percentage points. Users in economically wealthier zip codes had higher pre- and intrapandemic TIR values and greater relative improvements in TIR. TIR and pandemic-related improvements in TIR varied across CDC-designated regions. Conclusions: Population-level rtCGM data may be used to monitor changes in glycemic control with temporal and geographic specificity. The COVID-19 pandemic is associated with improvements in TIR, which were not evenly distributed across the United States.

Quantifying Worsened Glycemic Control During the COVID-19 Pandemic.

AIMS: We hypothesized that glycemic control in outpatients, measured by HbA1c, was worse during the early months of the COVID-19 pandemic than in 2019. We sought to quantify how much worse and to determine if social determinants of health were associated with these differences. MATERIALS AND METHODS: Data were extracted from the electronic medical records of 2 cohorts of patients seen in the family medicine clinic of a southeastern academic health center. Three hundred patients with baseline HbA1c results as well as HbA1c results in May 2019 or May 2020 were evaluated. RESULTS: The groups had similar mean baseline HbA1c (7.65, SD = 1.50 for 2019; 7.61, SD = 1.71 for 2020; P = .85). Mean May HbA1c decreased from baseline in 2019 (7.19, SD = 1.45) but rose in 2020 (7.63, SD = 1.73), a statistically significant difference (P < .01). Controlling for age, gender, race, and insurance status, HbA1c in May 2020 (meanadj = 7.73) was significantly higher than in May 2019 (meanadj = 7.16). CONCLUSIONS: During the early months of the COVID-19 pandemic, glycemic control in our patient population was significantly worse than during the same period in 2019 (mean HbA1c difference = 0.57). Contrary to our expectations, we did not find associations between patient demographic variables and glycemic control, including race.

Impact of lockdown for COVID-19 pandemic in Indian children and youth with type 1 diabetes from different socio-economic classes.

OBJECTIVES: In March 2020, lockdown was imposed in India to combat spread of Coronavirus, which was extended till 31st May. Implementation of lockdown and limited outdoor activities resulted in changes in routines of children with diabetes. The aim of this study was to assess the impact of lockdown on glycemic control, weight and body mass index (BMI) patterns of children with type 1 diabetes (T1DM) from different socio-economic (SE) classes. METHODS: This observational study included 77 children and youth (5-20 years) with T1DM having disease duration of ≥6 months. Demographic data and investigations were recorded at two time points (post lockdown when the children came for follow up, pre lockdown data from medical records). RESULTS: Glycemic control improved (pre lockdown HbA1C 79.4±19.2 vs. post lockdown Hba1C 74.5±16.9 mmol/mol, p<0.05) and there was weight gain post lockdown (pre lockdown weight z-score -0.4±0.8 vs. post lockdown weight z-score -0.2±0.8, p<0.05) without any significant change in BMI and insulin requirements. Improved glycemic was seen in the lower SE group control post lockdown (p<0.05), whereas in higher SE group, it remained unchanged. Children whose parents were at home during lockdown showed an improved glycemic control (p<0.05) as compared to children whose parents continued to work during lockdown (p>0.01). CONCLUSIONS: During coronavirus lockdown, glycemic control was adequately maintained in children with T1DM, highlighting importance of stronger family support system leading to more steady daily routine.

Glycemic control in children and teenagers with type 1 diabetes around lockdown for COVID-19: A continuous glucose monitoring-based observational study.

AIMS/INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic urged authorities to impose rigorous quarantines and brought considerable changes to people's lifestyles. The impact of these changes on glycemic control has remained unclear, especially the long-term effect. We aimed to investigate the impact of COVID-19 lockdown on glycemic control in children and adolescents with type 1 diabetes. MATERIALS AND METHODS: This observational study enrolled children with type 1 diabetes using continuous glucose monitoring. Continuous glucose monitoring data were extracted from the cloud-based platform before, during and after lockdown. Demographics and lifestyle change-related information were collected from the database or questionnaires. We compared these data before, during and after lockdown. RESULTS: A total of 43 children with type 1 diabetes were recruited (20 girls; mean age 7.45 years; median diabetes duration 1.05 years). We collected 41,784 h of continuous glucose monitoring data. Although time in range (3.9-10.0 mmol/L) was similar before, during and after lockdown, the median time below range <3.9 mmol/L decreased from 3.70% (interquartile range [IQR] 2.25-9.53%) before lockdown to 2.91% (IQR 1.43-5.95%) during lockdown, but reversed to 4.95% (IQR 2.11-9.42%) after lockdown (P = 0.004). Time below range <3.0 mmol/L was 0.59% (IQR 0.14-2.21%), 0.38% (IQR 0.05-1.35%) and 0.82% (IQR 0.22-1.69%), respectively (P = 0.008). The amelioration of hypoglycemia during lockdown was more prominent among those who had less time spent <3.9 mmol/L at baseline. During lockdown, individuals reduced their physical activity, received longer sleep duration and spent more time on diabetes management. In addition, they attended outpatient clinics less and turned to telemedicine more frequently. CONCLUSION: Glycemic control did not deteriorate in children and teenagers with type 1 diabetes around the COVID-19 pandemic. Hypoglycemia declined during lockdown, but reversed after lockdown, and the changes related to lifestyle might not provide a long-term effect.

Association Between Achieving Inpatient Glycemic Control and Clinical Outcomes in Hospitalized Patients With COVID-19: A Multicenter, Retrospective Hospital-Based Analysis.

OBJECTIVE: Diabetes and hyperglycemia are important risk factors for poor outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). We hypothesized that achieving glycemic control soon after admission, in both intensive care unit (ICU) and non-ICU settings, could affect outcomes in patients with COVID-19. RESEARCH DESIGN AND METHODS: We analyzed pooled data from the Glytec national database including 1,544 patients with COVID-19 from 91 hospitals in 12 states. Patients were stratified according to achieved mean glucose category in mg/dL (≤7.77, 7.83-10, 10.1-13.88, and >13.88 mmol/L; ≤140, 141-180, 181-250, and >250 mg/dL) during days 2-3 in non-ICU patients or on day 2 in ICU patients. We conducted a survival analysis to determine the association between glucose category and hospital mortality. RESULTS: Overall, 18.1% (279/1,544) of patients died in the hospital. In non-ICU patients, severe hyperglycemia (blood glucose [BG] >13.88 mmol/L [250 mg/dL]) on days 2-3 was independently associated with high mortality (adjusted hazard ratio [HR] 7.17; 95% CI 2.62-19.62) compared with patients with BG <7.77 mmol/L (140 mg/dL). This relationship was not significant for admission glucose (HR 1.465; 95% CI 0.683-3.143). In patients admitted directly to the ICU, severe hyperglycemia on admission was associated with increased mortality (adjusted HR 3.14; 95% CI 1.44-6.88). This relationship was not significant on day 2 (HR 1.40; 95% CI 0.53-3.69). Hypoglycemia (BG <70 mg/dL) was also associated with increased mortality (odds ratio 2.2; 95% CI 1.35-3.60). CONCLUSIONS: Both hyperglycemia and hypoglycemia were associated with poor outcomes in patients with COVID-19. Admission glucose was a strong predictor of death among patients directly admitted to the ICU. Severe hyperglycemia after admission was a strong predictor of death among non-ICU patients.

Remote continuous glucose monitoring during the COVID-19 pandemic in quarantined hospitalized patients in Denmark: A structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: Patients with diabetes are - compared to people without diabetes - at increased risk of worse outcomes from COVID-19 related pneumonia during hospitalization. We aim to investigate whether telemetric continuous glucose monitoring (CGM) in quarantined hospitalized patients with diabetes and confirmed SARS-CoV-2 infection or another contagious infection can be successfully implemented and is associated with better glycaemic control than usual blood glucose monitoring (finger prick method) and fewer patient-health care worker contacts. Furthermore, we will assess whether glucose variables are associated with the clinical outcome. The hypothesis is that by using remote CGM to monitor glucose levels of COVID-19 infected patients and patients with other contagious infections with diabetes, we can still provide satisfactory (and maybe even better) in-hospital diabetes management despite patients being quarantined. Furthermore, the number of patient-personnel contacts can be lowered compared to standard monitoring with finger-prick glucose. This could potentially reduce the risk of transmitting contagious diseases from the patient to other people and reduces the use of PPE's. Improved glucose control may reduce the increased risk of poor clinical outcomes associated with combined diabetes and infection. TRIAL DESIGN: This is a single centre, open label, exploratory, randomised, controlled, 2-arm parallel group (1:1 ratio), controlled trial. PARTICIPANTS: The trial population is patients with diabetes (both type 1 diabetes, type 2 diabetes, newly discovered diabetes that is not classified yet, and all other forms of diabetes) admitted to Nordsjællands Hospital that are quarantined due to COVID-19 infection or another infection. INCLUSION CRITERIA: 1. Hospitalized with confirmed COVID-19 infection by real-time PCR or another validated method OR hospitalized with a non-COVID-19 diagnosis and quarantined at time of inclusion. 2. A documented clinically relevant history of diabetes or newly discovered during hospitalization as defined by The World Health Organizations diagnostic criteria for diabetes. 3. Written informed consent obtained before any trial related procedures are performed. 4. Male or female aged over 18 years of age. 5. Must be able to communicate with the study personnel. 6. The subject must be willing and able to comply with trial protocol. EXCLUSION CRITERIA: 1. Known hypersensitivity to the band-aid of the Dexcom G6 sensors INTERVENTION AND COMPARATOR: Participants will be randomized to either real-time CGM with the Dexcom G6, a CGM system that does not need to be calibrated, or finger-prick glucose monitoring. Blinded CGM will be mounted in the finger-prick group. In the open CGM group, the glucose values will be transmitted to a Smartdevice in the nurse office where glucose levels can be monitored remotely. MAIN OUTCOMES: The primary endpoint is the difference between groups in distribution of glucose values being in time in range (TIR), defined as 3.9 to 10 mmol/l. In addition, the primary endpoint is reported as the percentage of days of the whole admission, the patient reaches TIR. Secondary endpoints are the estimated number of saved patient-personnel contacts related to blood glucose measurements, incl. time healthcare providers spent on diabetes related tasks and PPE related tasks, during the patients' hospitalization. Furthermore, we will assess additional glucose outcomes and associations of glucose variables and patient outcomes (As specified in the protocol). RANDOMISATION: The service used for generating the randomization lists is www.random.org . Randomization is stratified by COVID-19 status and an allocation ratio of 1:1 to either CGM or finger-prick groups. BLINDING (MASKING): The design of the trial is open, however blinded CGM is recorded in the finger-prick group. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): A sample size of N=72 is required for the primary endpoint analysis based on 80% power to detect a 10% difference between groups in TIR and to allow for a 15% dropout. The 72 participants will be randomized 1:1 to open CGM or finger-prick with 36 in each group. TRIAL STATUS: This structured protocol summary is based on the CGM-ISO protocol version 1.3, dated 13.05.2020. Date of first patient enrolled: 25.05.2020. Expected last recruiting is May 2021. Patients enrolled to date: 20 in total. 8 with confirmed COVID-19 infection and 12 with other infections. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04430608 . Registered 12.06.2020 FULL PROTOCOL: The full protocol is attached as an additional file from the Trial website (Additional file 1). In the interest of expediting dissemination of this material, the familiar formatting has been eliminated; This Letter serves as a summary of the key elements of the full protocol.

Diabetes, obesity and COVID-19: A complex interplay.

With the accumulation of observational data showing an association of metabolic co-morbidities with adverse outcomes from COVID-19, there is a need to disentangle the contributions of pre-existing macro- and microvascular disease, obesity and glycaemia. This article outlines the complex mechanistic and clinical interplay between diabetes and COVID-19, the clinical and research questions which arise from this relationship, and the types of studies needed to answer those questions. The authors are clinicians and academics working in diabetes and obesity medicine, but the article is pitched to an audience of generalists with clinical experience of or interest in the management of COVID-19.

Assessment of the effect of the COVID-19 lockdown on glycaemic control in people with type 1 diabetes using flash glucose monitoring.

AIM: To describe the effect of the stringent lockdown measures, introduced in the UK on 23 March 2020 to curtail the transmission of COVID-19, on glycaemic control in people with type 1 diabetes using flash glucose monitoring. METHODS: We undertook an observational study of 572 individuals with type 1 diabetes for whom paired flash glucose monitoring data were available between early March and May 2020. The primary outcome was change in flash glucose monitoring variables. We also assessed clinical variables associated with change in glycaemic control. RESULTS: Percentage of time in range increased between March and May 2020 [median (interquartile range) 53 (41-64)% vs 56 (45-68)%; P < 0.001], with associated improvements in standard deviation of glucose (P <0.001) and estimated HbA1c (P <0.001). There was a small reduction in the number of individuals meeting the hypoglycaemia target of <5% per day (64% vs 58%; P = 0.004). Comparing changes in flash glucose monitoring data from March to May in 2019 with the same period in 2020 confirmed that these differences were confined to 2020. Socio-economic deprivation was an independent predictor of a ≥5% reduction in time in range during lockdown (odds ratio 0.45 for people in the two most affluent Scottish Index of Multiple Deprivation quintiles; P <0.001). CONCLUSIONS: Lockdown was not associated with a significant deterioration in glycaemic control in people with type 1 diabetes using flash glucose monitoring. However, socio-economic deprivation appeared to increase the risk of decline in glycaemic control, which has implications for how support is focused in challenging times.