Glycemic Characteristics and Clinical Outcomes of COVID-19 Patients Hospitalized in the United States

Characteristics, Management, and Outcomes of Elderly Patients with Diabetes in a Covid-19 Unit: Lessons Learned from a Pilot Study

Background and objectives: Diabetes may affect in-hospital mortality of patients with Coronavirus disease 2019 (COVID-19). We have retrospectively evaluated clinical characteristics, diabetes management, and outcomes in a sample of COVID-19 patients with diabetes admitted to our hospital. Materials and Methods: All patients admitted to the Infectious Diseases Unit from 28 March 2020, to 16 June 2020, were enrolled. Clinical information and biochemical parameters were collected at the time of admission. Patients were ranked according to diabetes and death. Results: Sixty-one patients with COVID-19 were analyzed. Most of them were from a long-term health care facility. Mean age was 77 ± 16 years, and 19 had type 2 diabetes (T2D). Eighteen patients died, including 8 with T2D and 10 without T2D (p = 0.15). Patients with diabetes were significantly older, had a higher prevalence of cardiovascular diseases, and a significantly lower lymphocyte count. No significant relationship was found between diabetes and in-hospital mortality (Odds Ratio OR 2.3; Confidence Interval CI 0.73–7.38, p = 0.15). Patients with diabetes were treated with insulin titration algorithm. Severe hypoglycemic events, ketoacidosis and hyperosmolar hyperglycemias did not occur during hospitalization. Mean pre-meal capillary blood glucose was 157 ± 45 mg/dL, and the coefficient of variation of glycaemia was 29%. Conclusions: Our study, albeit limited by the small number of subjects, did not describe any significant association between T2D diabetes and mortality. Clinical characteristics of patients, and acceptable glucose control prior and during hospitalization may have influenced the result. The use of an insulin titration algorithm should be pursued during hospitalization.

Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept

OBJECTIVE

The use of remote real-time continuous glucose monitoring (CGM) in the hospital has rapidly emerged to preserve personal protective equipment and reduce potential exposures during coronavirus disease 2019 (COVID-19).

RESEARCH DESIGN AND METHODS

We linked a hybrid CGM and point-of-care (POC) glucose testing protocol to a computerized decision support system for continuous insulin infusion and integrated a validation system for sensor glucose values into the electronic health record. We report our proof-of-concept experience in a COVID-19 intensive care unit.

RESULTS

All nine patients required mechanical ventilation and corticosteroids. During the protocol, 75.7% of sensor values were within 20% of the reference POC glucose with an associated average reduction in POC of 63%. Mean time in range (70-180 mg/dL) was 71.4 ± 13.9%. Sensor accuracy was impacted by mechanical interferences in four patients.

CONCLUSIONS

A hybrid protocol integrating real-time CGM and POC is helpful for managing critically ill patients with COVID-19 requiring insulin infusion.

Unexpectedly lower mortality rates in COVID-19 patients with and without type 2 diabetes in Istanbul

AIMS

Type 2 diabetes mellitus (T2DM) is a risk factor for severe COVID-19. Our aim was to compare the clinical outcomes of patients with and without T2DM during the first hit of COVID-19 in Istanbul.

METHODS

A retrospective population-based study was conducted including all consecutive adult symptomatic COVID-19 cases. Patients were confirmed with rt-PCR; treated and monitored in accordance with standard protocols. The primary endpoints were hospitalization and 30-day mortality.

RESULTS

Of the 93,571 patients, 22.6% had T2DM, with older age and higher BMI. Propensity Score matched evaluation resulted in significantly higher rates of hospitalization (1.5-fold), 30-day mortality (1.6-fold), and pneumonia (1.4-fold). They revealed more severe laboratory deviations, comorbidities, and frequent drug usage than the Non-DM group. In T2DM age, pneumonia, hypertension, obesity, and insulin-based therapies were associated with an increased likelihood of hospitalization; whereas age, male gender, lymphopenia, obesity, and insulin treatment were considerably associated with higher odds of death.

CONCLUSIONS

COVID-19 patients with T2DM had worse clinical outcomes with higher hospitalization and 30-day mortality rates than those without diabetes. Compared to most territories of the world, COVID-19 mortality was much lower in Istanbul, which may be associated with accessible healthcare provision and the younger structure of the population.

Glucagon-like peptide-1 receptor agonists in the era of COVID-19: Friend or foe?

The aim of the present manuscript is to discuss on potential pros and cons of glucagon-like peptide-1 receptor agonists (GLP-1RAs) as glucose-lowering agents during COVID-19 pandemic, and what is more to evaluate them as potential candidates for the treatment of patients, affected by COVID-19 infection, with or even without diabetes mellitus type 2. Besides being important glucose-lowering agents, GLP-1RAs pose promising anti-inflammatory and anti-obesogenic properties, pulmonary protective effects, as well as beneficial impact on gut microbiome composition. Hence, taking everything previously mentioned into consideration, GLP-1RAs seem to be potential candidates for the treatment of patients, affected by COVID-19 infection, with or even without type 2 diabetes mellitus, as well as excellent antidiabetic (glucose-lowering) agents during COVID-19 pandemic times.

Association of hyperglycaemia with hospital mortality in nondiabetic COVID-19 patients: A cohort study

Objective

Diabetes is a known risk factor for mortality in Coronavirus disease 2019 (COVID-19) patients. Our objective was to identify prevalence of hyperglycaemia in COVID-19 patients with and without prior diabetes and quantify its association with COVID-19 disease course.

Research design and methods

This observational cohort study included all consecutive COVID-19 patients admitted to John H Stroger Jr. Hospital, Chicago, IL from March 15, 2020 to May 3, 2020 and followed till May 15, 2020. The primary outcome was hospital mortality, and the studied predictor was hyperglycaemia [any blood glucose ≥7.78 mmol/L (140 mg/dL) during hospitalization].

Results

Of the 403 COVID-19 patients studied, 51 (12.7%) died; 335 (83.1%) were discharged while 17 (4%) were still in hospital. Hyperglycaemia occurred in 228 (56.6%) patients; 83 of these hyperglycaemic patients (36.4%) had no prior history of diabetes. Compared to the reference group no-diabetes/no-hyperglycaemia patients the no-diabetes/hyperglycaemia patients showed higher mortality [1.8% versus 20.5%, adjusted odds ratio 21.94 (95% confidence interval 4.04–119.0), P < 0.001]; improved prediction of death (P = 0.01) and faster progression to death (P < 0.01). Hyperglycaemia within the first 24 and 48 h was also significantly associated with mortality (odds ratio 2.15 and 3.31, respectively).

Conclusions

Hyperglycaemia without prior diabetes was common (20.6% of hospitalized COVID-19 patients) and was associated with an increased risk of and faster progression to death. Development of hyperglycaemia in COVID-19 patients who do not have diabetes is an early indicator of progressive disease.

Diabetes and COVID-19

Several factors are linked with a higher risk of mortality from Coronavirus disease-19 (COVID-19), including male gender, increased age, hypertension, diabetes mellitus, obesity, cardiovascular diseases, chronic obstructive pulmonary disease, and cancer. Hyperglycemic COVID-19 patients have severe clinical problems, increased ICU admittance, machine-driven ventilation, and a substantial rise in inflammatory markers. Among all patients, those with diabetes or hyperglycemia have a two- to four-fold increase in mortality and severity of COVID-19 than those without diabetes. The primary cause of mortality in COVID-19 patients with diabetes is compromised immune response to viral infections. Increased blood sugar level probably affects intracellular degradation of bacteria, neutrophil chemotaxis, and phagocytosis, thus improving viral binding affinity and entry and decreasing virus clearance. In addition, it has significant effects on the proteins by inducing glycosylation and altering the composition of complements, and glycosylation renders cells susceptible to viral inflammation and damage. The treatment of COVID-19 in patients with diabetes requires an integrated team approach to minimize the risk of medical complications and mortality. Moreover, physicians should adopt proactive strategies to care for persons with comorbidities. This strategy would help reduce the frequency of complications and mortality among patients and load on the healthcare system.

A single arm trial using passive simulated jogging for blunting acute hyperglycemia

Glycemic fluctuations increase oxidative stress, promote endothelial dysfunction and cardiovascular disease. Reducing glycemic fluctuations is beneficial. We previously reported that a portable motorized passive simulated jogging device, (JD) reduces 24 h glycemic indices in type 2 and non-diabetic subjects. This study evaluates effectiveness and feasibility of JD in blunting large glycemic fluctuation induced by an oral glucose tolerance test (OGTT). The study was performed in 10 adult participants mean age 41.3 ± 13.5 year using interstitial glucose monitor (IG). Each participant fasted for 8 h. followed by an OGTT (Pre-JD), thereafter JD was used for 90 min per day for 7 days, without change to diet or activities of daily living. A repeat OGTT (Post-JD) was performed after completion. The integrated area under the curve (iAUC_2h–4h) was computed for the OGTT Pre-JD and Post-JD. Seven days of JD blunted the glucose fluctuation produced by OGTT. JD decreased AUC_2h by 17 ± 4.7% and iAUC_4h by 15 ± 5.9% (p < 0.03). In healthy mostly obese participants 7 days of JD blunts the hyperglycemic response produced by an OGTT. JD may be an adjunct to current glycemic management, it can be applied in different postures for those who cannot (due to physical or cognitive limitations) or will not exercise.

Trial registration:ClinicalTrials.gov NCT03550105 (08-06-2018).

Hyperglycemia and Correlated High Levels of Inflammation Have a Positive Relationship with the Severity of Coronavirus Disease 2019

Objective

Coronavirus disease 2019 (COVID-19) is a considerable global public health threat. This study sought to investigate whether blood glucose (BG) levels or comorbid diabetes are associated with inflammatory status and disease severity in patients with COVID-19.

Methods

In this retrospective cohort study, the clinical and biochemical characteristics of COVID-19 patients with or without diabetes were compared. The relationship among severity of COVID-19, inflammatory status, and diabetes or hyperglycemia was analyzed. The severity of COVID-19 in all patients was determined according to the diagnostic and treatment guidelines issued by the Chinese National Health Committee (7th edition).

Results

Four hundred and sixty-one patients were enrolled in our study, and 71.58% of patients with diabetes and 13.03% of patients without diabetes had hyperglycemia. Compared with patients without diabetes (n = 366), patients with diabetes (n = 95) had a higher leucocyte count, neutrophil count, neutrophil to lymphocyte ratio (NLR), and erythrocyte sedimentation rate (ESR). There was no association between severity of COVID-19 and known diabetes adjusted for age, sex, body mass index (BMI), known hypertension, and coronary heart disease. The leucocyte count, NLR, and C-reactive protein (CRP) level increased with increasing BG level. Hyperglycemia was an independent predictor of critical (OR 4.00, 95% CI 1.72-9.30) or severe (OR 3.55, 95% CI 1.47-8.58) COVID-19, and of increased inflammatory levels (high leucocyte count (OR 4.26, 95% CI 1.65-10.97), NLR (OR 2.76, 95% CI 1.24-6.10), and CRP level (OR 2.49, 95% CI 1.19-5.23)), after adjustment for age, sex, BMI, severity of illness, and known diabetes.

Conclusion

Hyperglycemia was positively correlated with higher inflammation levels and more severe illness, and it is a risk factor for the increased severity of COVID-19. The initial measurement of plasma glucose levels after hospitalization may help identify a subset of patients who are predisposed to a worse clinical course.

A Retrospective Study Assessing the Effect of Diabetes on Mortality in Patients With COVID-19 at a Teaching Hospital in the United Kingdom

Aim

The aim of the study was to compare the clinical characteristics and outcomes (mortality, intensive care admission, mechanical ventilation, and length of stay, LoS) of patients with and without diabetes with confirmed COVID-19. 

Methods

This retrospective study evaluated clinical and laboratory variables in adult inpatients from Brighton and Sussex University Hospitals NHS Trust with laboratory-confirmed COVID-19 between March 10, 2020, and June 30, 2020. Univariate and multivariate analyses were performed to compare the outcomes of patients with and without diabetes. 

Results

Over 457 patients were included in this study (140 with diabetes and 317 without diabetes), of which 143 (31.9%) died. The median age was 80 years and were predominantly males (59.1%). Baseline characteristics at the time of COVID-19 diagnosis demonstrated that the patients with diabetes were younger than those without diabetes (p=0.008). Mortality increased with age. There was no difference in adverse outcomes in those with and without diabetes. However, subgroup analysis of patients aged ≤60 years demonstrated a significantly increased mortality in those with diabetes (p=0.016). Patients with diabetes had an increased length-of-stay compared to those without diabetes, which was more evident in those aged ≤60 years.

Conclusion

Age is the most important predictor of mortality. Patients with diabetes did not have increased mortality from COVID-19, which is likely due to their younger age in our cohort. More patients with diabetes stayed in the hospital longer than seven days than those without diabetes.

Diabetes and COVID-19: Diseases of racial, social and glucose intolerance

Diabetes and coronavirus disease 2019 (COVID-19) are worldwide pandemics that have had a major impact on public health throughout the globe. Risk factors for developing diabetes and having adverse outcomes of COVID-19 appear to be similar; metabolic factors (such as obesity), non-White ethnicity and poorer socioeconomic status appear to be risk factors for both. Diabetes and COVID-19 have a significant effect on populations adversely affected by health inequality. Whilst we hope that COVID-19 will be mitigated by widespread use of vaccines, no such prospect exists for mitigating the pandemic of diabetes. In this brief opinion review, I compare risk factors for diabetes and adverse outcomes of COVID-19 and argue that tackling health and social inequality is likely to play a major role in solving the global diabetes pandemic and improve outcomes of COVID-19.

Therapeutic Potential of Metformin in COVID-19: Reasoning for Its Protective Role

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections present with increased disease severity and poor clinical outcomes in diabetic patients compared with their nondiabetic counterparts. Diabetes/hyperglycemia-triggered endothelial dysfunction and hyperactive inflammatory and immune responses are correlated to twofold to threefold higher intensive care hospitalizations and more than twice the mortality among diabetic coronavirus disease 2019 (COVID-19) patients. While comorbidities such as obesity, cardiovascular disease, and hypertension worsen the prognosis of diabetic COVID-19 patients, COVID-19 infections are also associated with new-onset diabetes, severe metabolic complications, and increased thrombotic events in the backdrop of aberrant endothelial function. While several antidiabetic medications are used to manage blood glucose levels, we discuss the multifaceted ability of metformin to control blood glucose levels and possibly attenuate endothelial dysfunction, inhibit viral entry and infection, and modify inflammatory and immune responses during SARS-CoV-2 infections. These actions make metformin a viable candidate drug to be considered for repurposing and gaining ground against the SARS-CoV-2-induced tsunami in diabetic COVID-19 patients.

Association between antecedent statin use and severe disease outcomes in COVID-19: A retrospective study with propensity score matching

Background

Statins have been associated with a reduction in inflammatory markers and improved endothelial function. Whether statins offer any benefit in COVID-19 needs to be elucidated.

Objective

To determine the association between antecedent statin use and severe disease outcomes among COVID-19 patients.

Methods

A retrospective cohort study on 1014 patients with confirmed COVID-19 diagnosis. Outcomes were mortality, need for mechanical ventilation, and intensive care admission. Patients were classified into statin-users vs statin non-users based on antecedent use of statins. Multivariable regression analysis was performed adjusting for confounders such as age, sex, race, BMI, smoking, insurance, and comorbidities. Propensity score matching was performed to achieve a 1:1 balanced cohort.

Results

A total of 1014 patients (Median age 65 (IQR 53–73); 530 (52.3%) males; 753 (74.3%) African Americans; median BMI 29.4 (IQR 25.1–35.9); 615 (60.7%) with Medicare insurance) were included in the study. About 454 patients (44.77%) were using statins as home medication. Antecedent statin use was associated with significant decrease in mortality in the total cohort (OR, 0.66; 95% CI, 0.46 – 0.95; p = 0.03). Among the propensity score matched (PSM) cohort of 466 patients (233 statin users and 233 statin non-users), all the baseline characteristics had similar distribution among the two groups. Statin users had significant reduction in mortality in the PSM cohort as well (OR, 0.56; 95% CI, 0.37 – 0.83; p = 0.004).

Conclusions

Statin use was associated with significant reduction in mortality among COVID-19 patients. These findings support the pursuit of randomized clinical trials to explore the possible benefits of statins in COVID-19.

Mechanisms and Potential Roles of Glucose-Lowering Agents in COVID-19: A Review

OBJECTIVE

To explore mechanistic benefits of glucose-lowering agents that extend beyond glycemic control with the potential to mitigate coronavirus disease 2019 (COVID-19) complications.

DATA SOURCES

The following PubMed literature search terms were used from July 2020 to January 2, 2021: diabetes, COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), glucose-lowering agents, and pharmacology.

STUDY SELECTION AND DATA EXTRACTION

English-language studies reporting on the association between diabetes, COVID-19 adverse outcomes, and the potential roles of glucose-lowering agents were reviewed.

DATA SYNTHESIS

Selected glucose-lowering agents have benefits beyond glycemic control, with the potential to reduce the risks of severe complications during SARS-CoV-2 infection. Key benefits include anti-inflammatory, anticoagulant, immune modulating, and enzyme/receptor effects.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

This review summarizes the current knowledge of glucose-lowering agents and their potential roles in COVID-19 outcomes. Considering beneficial mechanisms on COVID-19 outcomes that extend beyond glycemic control as well as safety profiles, current data suggest that dipeptidyl peptidase-IV (DPP-IV) inhibitors and metformin may have the most promise and warrant further investigation.

CONCLUSIONS

Certain glucose-lowering agents may offer additional benefits beyond glucose control-namely, by modulating the mechanisms contributing to adverse outcomes related to COVID-19 in patients with diabetes. DPP-IV inhibitors and metformin appear to have the most promise. However, current published literature on diabetes medications and COVID-19 should be interpreted with caution. Most published studies are retrospective and consist of convenience samples, and some lack adequate analytical approaches with confounding biases. Ongoing trials aim to evaluate the effects of glucose-lowering agents in reducing the severity of COVID-19 outcomes.

Insights into the possible impact of COVID-19 on the endocrine system

The novel 2019 coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly transmissible and pathogenic coronavirus. Because of the novelty of the COVID-19 pandemic, few data are available on the impact of the SARS-CoV-2 on the different endocrine glands. Previous studies of severe acute respiratory syndrome (SARS) have shown a harmful effect on endocrine function. Notably, the angiotensin-converting enzyme-2 receptor, which is the entry route of coronaviruses to the host cell, is widely expressed in the endocrine organs including testis, endocrine pancreas, thyroid, and adrenal, and pituitary glands. Clinical and biochemical manifestations have been recorded in COVID-19 patients resulting in changes in endocrine activities, which were also recorded during the SARS outbreak in 2003. This review aims to explore the impact of SARS-CoV-2 infection on the function of endocrine glands, based on the latest research in the field.

Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning

The increased prevalence of obesity, diabetes, and cardiovascular risk factors in people hospitalized with severe COVID-19 illness has engendered considerable interest in the metabolic aspects of SARS-CoV-2-induced pathophysiology. Here, I update concepts informing how metabolic disorders and their co-morbidities modify the susceptibility to, natural history, and potential treatment of SARS-CoV-2 infection, with a focus on human biology. New data informing genetic predisposition, epidemiology, immune responses, disease severity, and therapy of COVID-19 in people with obesity and diabetes are highlighted. The emerging relationships of metabolic disorders to viral-induced immune responses and viral persistence, and the putative importance of adipose and islet ACE2 expression, glycemic control, cholesterol metabolism, and glucose- and lipid-lowering drugs is reviewed, with attention to controversies and unresolved questions. Rapid progress in these areas informs our growing understanding of SARS-CoV-2 infection in people with diabetes and obesity, while refining the therapeutic strategies and research priorities in this vulnerable population.

Clinical Characteristics and Factors Associated with Poor Outcomes in Hospitalized Patients with Novel Coronavirus Infection COVID-19

Aim      To evaluate the clinical picture and factors associated with unfavorable outcomes in admitted patients with COVID-19.Material and methods This study included all patients admitted to the COVID Center of the National Research Center of Cardiology of the Russian Ministry of Health Care from May 1 through May 31, 2020. Clinical demographic, laboratory, and instrumental indexes and associated factors were studied with one-way and multivariate logistic regression analysis.Results This study included 402 patients aged 18 to 95 years (mean age, 62.9±14.6 years); 43.0 % of them were older than 65 years. COVID-19 was frequently associated with chronic comorbidities, including arterial hypertension (74.4 %), obesity (41.6 %), history of ischemic heart disease (12.9 %), atrial fibrillation (18.9 %), type 2 diabetes mellitus (DM) (13.0 %), and oncological diseases (9.2 %). 13.0 % of patients were smokers; less than 10% had chronic lung diseases. 3.9% of patients had a combination of COVID-19 and acute coronary pathology, including acute myocardial infarction (MI) in 3.2 % (13) and unstable angina in 0.7 % (3). The most frequent clinical manifestation of COVID-19 were four symptoms: cough (81.1 %), weakness (80.3 %), shortness of breath (71.6 %), and fever (62.7 %). 46.5% of patients had shortage of breath and chest pain/compression, 40.3% had headache, 31.1% had myalgia, 28.8% had anosmia, and 25.5% had ageusia. Arterial oxygen saturation was &lt;93.0 % in 55.7 % of cases. According to laboratory blood tests the patients had anemia (58.2 %), lymphopenia (34.8 %), neutropenia (19.2 %), thrombocytopenia (11.9 %), and increased levels of high-sensitivity C-reactive protein (hsCRP, 87.3 %), interleukin-6 (89.3 %), ferritin (62.1 %), and D-dimer (49.2 %). 56.2% of patients required various regimens of oxygen support. 83 (20.6%) patients were admitted to intensive care and resuscitation units; invasive artificial ventilation was performed only for 34 (8.5 %) patients. In-hospital mortality was 7.7 % (31 / 402). One-way regression analysis identified major factors associated with death during the stay in the hospital: age &gt;55 years, NEWS scale score &gt;4.0, oxygen saturation &lt;92.0 %, blood glucose &gt;5.4 mmol/l, hs-CRP &gt;25.7 mg/l, and creatinine clearance &lt;72.0 ml/min. Furthermore, the risk increased with increasing degree of changes in each factor. According to results of the multivariate regression analysis, three most significant predictors of the hard endpoint, all-cause death during the stay in the hospital, were more than 5-fold increases in aspartate aminotransferase and/or alanine aminotransferase compared to normal levels (relative risk (RR) 16.8 at 95 % confidence interval (CI) 5.0-56.3, р&lt;0.001), pronounced changes in the lungs consistent with a CT-4 picture as shown by computed tomography (CT) (RR 13.4; 95 % CI 3.9-45.5, р&lt;0.001), and MI/unstable angina during the stay in the hospital (RR 11.3; 95 % CI 1.4-90.6, р=0.023). The probability of death was also considerably increased by chronic obstructive pulmonary disease, impaired kidney function (creatinine clearance estimated by Cockcroft-Gault &lt;60.0 ml/min), type 2 DM, oncological diseases, and dementia.Conclusion      This study established factors associated with unfavorable outcomes in admitted patients with COVID-19. This will allow identifying in advance patients with a high risk of complications that require increased attention to take more active diagnostic and therapeutic measures at prehospital and hospital stages.

Association of metformin with mortality or ARDS in patients with COVID-19 and type 2 diabetes: A retrospective cohort study

AIMS

To determine the association between metformin use and mortality and ARDS incidence in patients with COVID-19 and type 2 diabetes.

METHODS

This study was a multi-center retrospective analysis of COVID-19 patients with type 2 diabetes and admitted to four hospitals in Hubei province, China from December 31st, 2019 to March 31st, 2020. Patients were divided into two groups according to their exposure to metformin during hospitalization. The outcomes of interest were 30-day all-cause mortality and incidence of ARDS. We used mixed-effect Cox model and random effect logistic regression to evaluate the associations of metformin use with outcomes, adjusted for baseline characteristics.

RESULTS

Of 328 patients with COVID-19 and type 2 diabetes included in the study cohort, 30.5% (100/328) were in the metformin group. In the mixed-effected model, metformin use was associated with the lower incidence of ARDS. There was no significant association between metformin use and 30-day all-cause mortality. Propensity score-matched analysis confirmed the results. In the subgroup analysis, metformin use was associated with the lower incidence of ARDS in females.

CONCLUSIONS

Metformin may have potential benefits in reducing the incidence of ARDS in patients with COVID-19 and type 2 diabetes. However, this benefit differs significantly by gender.

Impact of COVID-19 on Health Economics and Technology of Diabetes Care: Use Cases of Real-Time Continuous Glucose Monitoring to Transform Health Care During a Global Pandemic

Background: The coronavirus disease 2019 (COVID-19) pandemic has exposed vulnerabilities and placed tremendous financial pressure on nearly all aspects of the U.S. health care system. Diabetes care is an example of the confluence of the pandemic and heightened importance of technology in changing care delivery. It has been estimated the added total direct U.S. medical cost burden due to COVID-19 to range between $160B (20% of the population infected) and $650B (80% of the population infected) over the course of the pandemic. The corresponding range for the population with diabetes is between $16B and $65B, representing between 5% and 20% of overall diabetes expenditure in the United States. We examine the evidence to support allocating part of this added spend to infrastructure capabilities to accelerate remote monitoring and management of diabetes. Methods and Results: We reviewed recent topical literature and COVID-19-related analyses in the public health, health technology, and health economics fields in addition to databases and surveys from government sources and the private sector. We summarized findings on use cases for real-time continuous glucose monitoring in the community, for telehealth, and in the hospital setting to highlight the successes and challenges of accelerating the adoption of a digital technology out of necessity during the pandemic and beyond. Conclusions: One critical and lasting consequence of the pandemic will be the accelerated adoption of digital technology in health care delivery. We conclude by discussing ways in which the changes wrought by COVID-19 from a health care, policy, and economics perspective can add value and are likely to endure postpandemic.

How to Best Protect People With Diabetes From the Impact of SARS-CoV-2: Report of the International COVID-19 and Diabetes Summit

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has rapidly involved the entire world and exposed the pressing need for collaboration between public health and other stakeholders from the clinical, scientific, regulatory, pharmaceutical, and medical device and technology communities. To discuss how to best protect people with diabetes from serious outcomes from COVID-19, Diabetes Technology Society, in collaboration with Sansum Diabetes Research Institute, hosted the "International COVID-19 and Diabetes Virtual Summit" on August 26-27, 2020. This unique, unprecedented real-time conference brought together physicians, scientists, government officials, regulatory experts, industry representatives, and people with diabetes from six continents to review and analyze relationships between COVID-19 and diabetes. Over 800 attendees logged in. The summit consisted of five sessions: (I) Keynotes, (II) Preparedness, (III) Response, (IV) Recovery, and (V) Surveillance; eight parts: (A) Background, (B) Resilience, (C) Outpatient Care, (D) Inpatient Care, (E) Resources, (F) High-Risk Groups, (G) Regulation, and (H) The Future; and 24 sections: (1) Historic Pandemics and Impact on Society, (2) Pathophysiology/Risk Factors for COVID-19, (3) Social Determinants of COVID-19, (4) Preparing for the Future, (5) Medications and Vaccines, (6) Psychology of Patients and Caregivers, (7) Outpatient Treatment of Diabetes Mellitus and Non-Pharmacologic Intervention, (8) Technology and Telehealth for Diabetes Outpatients, (9) Technology for Inpatients, (10) Management of Diabetes Inpatients with COVID-19, (11) Ethics, (12) Accuracy of Diagnostic Tests, (13) Children, (14) Pregnancy, (15) Economics of Care for COVID-19, (16) Role of Industry, (17) Protection of Healthcare Workers, (18) People with Diabetes, (19) International Responses to COVID-19, (20) Government Policy, (21) Regulation of Tests and Treatments, (22) Digital Health Technology, (23) Big Data Statistics, and 24) Patient Surveillance and Privacy. The two keynote speeches were entitled (1) COVID-19 and Diabetes-Meeting the Challenge and (2) Knowledge Gaps and Research Opportunities for Diabetes and COVID-19. While there was an emphasis on diabetes and its interactions with COVID-19, the panelists also discussed the COVID-19 pandemic in general. The meeting generated many novel ideas for collaboration between experts in medicine, science, government, and industry to develop new technologies and disease treatment paradigms to fight this global pandemic.

Interrelations between COVID-19 and other disorders

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a respiratory tract virus that causes Coronavirus disease (COVID-19). The virus originated in Wuhan, China, in December 2019 and has spread across the globe to-date. The disease ranges from asymptomatic carriers to symptoms such as fever, sore throat, cough, lung infections, and in severe cases, acute respiratory distress syndrome, sepsis, and death. As many as 50% of patients reported having at least one comorbidities with COVID-19 upon hospital admission. Hypertension, diabetes, chronic obstructive pulmonary disease, obesity, and cardiovascular diseases are among the most commonly reported. Comorbidities are contributing to acute disease prognosis and increased risk of severe symptoms. Around 70% of patients who require ICU care have been observed to have comorbidities. This review intends to understand how some of these comorbidities affect the disease's prognosis and how severe the outcome can be expected.

Does inpatient hyperglycemia predict a worse outcome in COVID-19 intensive care unit patients?

BACKGROUND

We undertook this study to evaluate the association between hyperglycemia and outcomes in patients with coronavirus disease 2019 (COVID-19) admitted to the intensive care unit (ICU).

METHODS

We conducted a multicenter retrospective study involving all adults with COVID-19 admitted to the ICU between March and May 2020. Patients were divided into normoglycemic (average blood glucose <140 mg/dL) and hyperglycemic (average blood glucose ≥140 mg/dL) groups. Outcomes such as mortality, need and duration of mechanical ventilation, and length of hospital and ICU stays were measured.

RESULTS

Among 495 patients, 58.4% were male with a median age of 68 years (interquartile range [IQR]: 58.00-77.00), and baseline average blood glucose was 186.6 (SD ± 130.8). Preexisting diabetes was present in 35.8% of the studied cohort. Combined ICU and hospital mortality rates were 23.8%; mortality and mechanical ventilation rates were significantly higher in the hyperglycemic group with 31.4% vs 16.6% (P = .001) and 50.0% vs 37.2% (P = .004), respectively. Age above 60 years (hazard ratio [HR] 3.21; 95% CI 1.78, 5.78) and hyperglycemia (HR 1.79; 95% CI 1.14, 2.82) were the only significant predictors of in-hospital mortality. Increased risk for hyperglycemia was found in patients with steroid use (odds ratio [OR] 1.521; 95% CI 1.054, 2.194), triglycerides ≥150 mg/dL (OR 1.62; 95% CI 1.109, 2.379), and African American race (OR 0.79; 95% CI 0.65, 0.95).

CONCLUSIONS

Hyperglycemia in patients with COVID-19 is significantly associated with a prolonged ICU length of stay, higher need of mechanical ventilation, and increased risk of mortality in the critical care setting. Tighter blood glucose control (≤140 mg/dL) might improve outcomes in COVID-19 critically ill patients; evidence from ongoing clinical trials is needed.

Management of diabetes and hyperglycaemia in the hospital

Hyperglycaemia in people with and without diabetes admitted to the hospital is associated with a substantial increase in morbidity, mortality, and health-care costs. Professional societies have recommended insulin therapy as the cornerstone of inpatient pharmacological management. Intravenous insulin therapy is the treatment of choice in the critical care setting. In non-intensive care settings, several insulin protocols have been proposed to manage patients with hyperglycaemia; however, meta-analyses comparing different treatment regimens have not clearly endorsed the benefits of any particular strategy. Clinical guidelines recommend stopping oral antidiabetes drugs during hospitalisation; however, in some countries continuation of oral antidiabetes drugs is commonplace in some patients with type 2 diabetes admitted to hospital, and findings from clinical trials have suggested that non-insulin drugs, alone or in combination with basal insulin, can be used to achieve appropriate glycaemic control in selected populations. Advances in diabetes technology are revolutionising day-to-day diabetes care and work is ongoing to implement these technologies (ie, continuous glucose monitoring, automated insulin delivery) for inpatient care. Additionally, transformations in care have occurred during the COVID-19 pandemic, including the use of remote inpatient diabetes management-research is needed to assess the effects of such adaptations.

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.

Children and youth with diabetes are not at increased risk for hospitalization due to COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), responsible for the coronavirus disease COVID-19, was first identified in Wuhan, China in December 2019. Diabetes, as well as other cardiovascular comorbidities, has been recognized as a major risk factor for outcomes and mortality in adults with COVID-19, particularly in the elderly with type 2 diabetes. Based on these conclusions, COVID-19 data on adults have been generalized to youth with diabetes. Nevertheless, experience from pediatric diabetes practices in China (Wuhan), Italy, Spain (Catalonia), and the United States (San Francisco Bay Area) consistently report only a single severe case of COVID-19 in a 20-year-old female youth with type 1 diabetes (T1D) that was hospitalized for bilateral pneumonia and was subsequently discharged without complications. In Italy, information on COVID-19 in all children with diabetes is collected on a weekly basis and those with positive swab test or infection-related symptoms reported to a dedicated national registry. Of a total of 15 500 children tested, 11 subjects with T1D (age 8-17y) tested positive for COVID-19; 6/11 were asymptomatic and the rest presented with mild symptoms. In the rest of locations, youths with T1D diagnosed with COVID-19 were based on clinical suspicion and a confirmatory PCR test (Wuhan:0; Catalonia-HSJD:3; California-Stanford:2). All of them were asymptomatic or had a mild course. We suggest that COVID-19 data from adults should not be generalized to children, adolescents, and youth with diabetes as their outcomes and prognosis seem to be similar to their non-diabetic-peers and consistently milder than adults with diabetes.

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute Respiratory Distress Syndrome (ARDS). According to the World Health Organization (WHO), people who are at least 60 years old or have comorbidities that have primarily been targeted are at the highest risk from SARS-CoV-2. Medical imaging provides a non-invasive, touch-free, and relatively safer alternative tool for diagnosis during the current ongoing pandemic. Artificial intelligence (AI) scientists are developing several intelligent computer-aided diagnosis (CAD) tools in multiple imaging modalities, i.e., lung computed tomography (CT), chest X-rays, and lung ultrasounds. These AI tools assist the pulmonary and critical care clinicians through (a) faster detection of the presence of a virus, (b) classifying pneumonia types, and (c) measuring the severity of viral damage in COVID-19-infected patients. Thus, it is of the utmost importance to fully understand the requirements of for a fast and successful, and timely lung scans analysis. This narrative review first presents the pathological layout of the lungs in the COVID-19 scenario, followed by understanding and then explains the comorbid statistical distributions in the ARDS framework. The novelty of this review is the approach to classifying the AI models as per the by school of thought (SoTs), exhibiting based on segregation of techniques and their characteristics. The study also discusses the identification of AI models and its extension from non-ARDS lungs (pre-COVID-19) to ARDS lungs (post-COVID-19). Furthermore, it also presents AI workflow considerations of for medical imaging modalities in the COVID-19 framework. Finally, clinical AI design considerations will be discussed. We conclude that the design of the current existing AI models can be improved by considering comorbidity as an independent factor. Furthermore, ARDS post-processing clinical systems must involve include (i) the clinical validation and verification of AI-models, (ii) reliability and stability criteria, and (iii) easily adaptable, and (iv) generalization assessments of AI systems for their use in pulmonary, critical care, and radiological settings.

Glycemic control metrics using flash glucose monitoring and hospital complications in patients with COVID-19

BACKGROUND AND AIMS

Few studies have reported on the use of continuous glucose monitoring (CGM) during the Covid-19 pandemic. We aimed to examine glycemic control metrics using flash glucose monitoring during insulin treatment and the clinical outcome in hospitalized patients with COVID-19.

METHODS

Prospective, single-center cohort of adult patients diagnosed with type 2 diabetes or hyperglycemia and COVID-19 infection treated with basal bolus insulin regimen. Glycemic control was assessed with the use of intermittent Freestyle Libre flash glucose monitoring during the hospital stay. Outcome of interest were time in range [TIR], time above [TAR] and below [TBR] range, glycemic variability [coefficient of variation [% CV]), and differences in a composite of complications including ICU admission, acute respiratory distress syndrome (ARDS) and acute kidney injury.

RESULTS

A total of 60 patients were included (44 known diabetes and 16 new onset hyperglycemia). In total 190,080 data points of CGM were available, of which 72.5% of values were within the target area [TIR (70-180 mg/dL)], 22% TAR (>180 mg/dL), and 3% were TBR (<70 mg/dL). During treatment, the coefficient of variation (% CV) was 30%. There were no association with TIR, but patients with TAR >180 mg/dl had higher rates of a composite of complications (22.5% vs 16%, p = 0.04).

CONCLUSIONS

Basal bolus insulin regimen was safe and effective in achieving inpatient glycemic control in most patients with COVID-19. The association between TAR and complications indicates the need for improved inpatient glycemic control in hospitalized patients with COVID-19.

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

BACKGROUND

Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.

METHODS AND FINDINGS

We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10-8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10-5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10-5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.

CONCLUSIONS

In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

Digital Health Services among Patients with Diabetes during the COVID-19 Pandemic: A Scoping Review

BACKGROUND AND AIMS

COVID-19 pandemic causes massive disruption of the global health system. The diabetic patients are the vulnerable parts population who are predicted to have a significant issue during the pandemic regarding the conventional type of consultation by face-to-face which may result in the higher risk of COVID-19 exposure. This study aims to observe the use of digital health services for diabetes management during COVID-19 pandemic.

METHODS

A scoping review was conducted in PubMed, ScienceDirect, and Google Scholar during August until September 2020. The keywords that are used on the searching process are diabetes AND digital service OR telemedicine OR technology AND COVID-19. The criteria included the selection of scientific publication as an original research and reviews.

RESULTS

All published articles were gathered from 3 search engines; PubMed, Science Direct, and Google Scholar. The discussion explicates the practical considerations that are in accordance with the current condition of each country. In order to do so, the evidence is classified based on the level of global digital health framework in the developed and developing countries. It was found that the minimal level of digital health that connects diabetes patients with healthcare providers was at level 2, which is by using the video mode. The most advanced is at level 3B, which is applied by using the CGM devices, which provide active monitoring, diagnosis, and treatment based on timely clinical judgment.

CONCLUSION

It is feasible to utilize the digital health service during the COVID-19. This review is projected to be beneficial for the patient and health care providers to select the most feasible approach of digital health that merits the contextual resource.

Elevated glucose level leads to rapid COVID-19 progression and high fatality

Objectives

We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients.

Methods

We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality.

Results

The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8–5.5), 3.0 (1.0–7.0), 3.0 (1.0–8.0), and 6.5 (4.0–16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19.

Conclusions

Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.

Hyperglycemia at admission is a strong predictor of mortality and severe/critical complications in COVID-19 patients: a meta-analysis

BACKGROUND

Hyperglycemia at admission has been demonstrated to exacerbate the outcomes of coronavirus disease 2019 (COVID-19) but a meta-analysis is lacking to further confirm this hypothesis. The purpose of this meta-analysis was to summarize the evidence on the association between hyperglycemia at admission and the development of COVID-19.

METHOD

Four databases namely, PubMed, Web of Science, Embase and Cochrane Library, were screened for eligible studies. STATA software was utilized to pool data for this meta-analysis. The primary outcomes included mortality and severity. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with random-effects models, and the quality of evidence was appraised by the Newcastle-Ottawa Scale (NOS). This meta-analysis was prospectively registered online on PROSPERO, CRD42020191763.

RESULTS

Sixteen observational studies with 6386 COVID-19 patients relating hyperglycemia at admission to COVID-19 outcomes were included. The overall data demonstrated that, compared with the control, the hyperglycemia at admission group was more likely to have increased mortality (OR = 3.45, 95% CI, 2.26-5.26) and severe/critical complications (OR = 2.08, 95% CI, 1.45-2.99) of COVID-19.

CONCLUSION

Hyperglycemia at admission in COVID-19 patients may be a strong predictor of mortality and complications.

The excess insulin requirement in severe COVID-19 compared to non-COVID-19 viral pneumonitis is related to the severity of respiratory failure and pre-existing diabetes

Introduction

Severe COVID‐19 has been anecdotally associated with high insulin requirements. It has been proposed that this may be driven by a direct diabetogenic effect of the virus that is unique to SARS‐CoV‐2, but evidence to support this is limited. To explore this, we compared insulin requirements in patients with severe COVID‐19 and non‐COVID‐19 viral pneumonitis.

Methods

This is a retrospective cohort study of patients with severe COVID‐19 admitted to our intensive care unit between March and June 2020. A historical control cohort of non‐COVID‐19 viral pneumonitis patients was identified from routinely collected audit data.

Results

Insulin requirements were similar in patients with COVID‐19 and non‐COVID‐19 viral pneumonitis after adjustment for pre‐existing diabetes and severity of respiratory failure.

Conclusions

In this single‐centre study, we could not find evidence of a unique diabetogenic effect of COVID‐19. We suggest that high insulin requirements in this disease relate to its propensity to cause severe respiratory failure in patients with pre‐existing metabolic disease.

Hospital care: improving outcomes in type 1 diabetes

PURPOSE OF REVIEW

Caring for patients with type 1 diabetes (T1D) in the hospital presents unique challenges. This review provides an update on significant issues relevant to the inpatient management of T1D. Topics include trends in diabetic ketoacidosis (DKA), hypoglycemia, and adapting ambulatory technologies for inpatient use.

RECENT FINDINGS

Rates of DKA in the United States are rising. Although socioeconomic status, health insurance coverage, and hemoglobin A1c are persistently associated with DKA in individuals with T1D, newer risk factors have also emerged. These include the off-label use of sodium-glucose cotransporter inhibitor medications, immune checkpoint inhibitor-induced diabetes, and infection with severe acute respiratory syndrome coronavirus 2. Hypoglycemia is common among hospitalized patients with T1D. Use of validated hypoglycemia risk prediction models and multidisciplinary care initiatives can reduce the risk of inpatient hypoglycemia. Finally, continuous glucose monitoring is being adapted for use in the hospital setting and has shown promise during the coronavirus disease 2019 (COVID-19) pandemic.

SUMMARY

Evidence-based treatment algorithms, risk prediction calculators, multidisciplinary interventions, and wearable technology hold promise for improved outcomes in hospitalized patients with T1D.

Risk factors for severe and critically ill COVID-19 patients: A review

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1β, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.

Management of patients with diabetes and obesity in the COVID-19 era: Experiences and learnings from South and East Europe, the Middle East, and Africa

The COVID-19 pandemic has had a major effect on healthcare during 2020. Current evidence suggests that, while individuals with diabetes and obesity are no more prone to SARS-CoV-2 infection than those without, the risk of hospitalisation if someone has diabetes or obesity and then contracts COVID-19 is three times higher - and 4.5 times higher if they have diabetes and obesity. We assembled a panel of experts from South and East Europe, the Middle East, and Africa to discuss the challenges to management of diabetes and obesity during and post the COVID-19 pandemic. The experience and learnings of this panel cover a heterogeneous patient population, wide range of clinical settings, healthcare organisations, disease management strategies, and social factors. We discuss the importance of timely and effective disease management via telemedicine, providing reassurance and guidance for patients unable or unwilling to visit healthcare settings at this time. We address the use of novel therapies and their role in managing diabetes and obesity during the pandemic, as well as the importance of controlling hypoglycaemia and preventing cardiovascular complications, particularly in vulnerable people. Finally, we consider post-COVID-19 management of diabetes and obesity, and how these learnings and experiences should impact upon future clinical guidelines.

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.

Facilitators and Barriers to Nursing Implementation of Continuous Glucose Monitoring (CGM) in Critically Ill Patients With COVID-19

OBJECTIVE

We describe our implementation of a continuous glucose monitoring (CGM) guideline to support intravenous insulin administration and reduce point of care (POC) glucose monitoring frequency in the coronavirus disease 2019 medical intensive care unit (MICU) and evaluate nurses' experience with implementation of CGM and hybrid POC + CGM protocol using the Promoting Action on Research in Health Services framework.

METHODS

A multidisciplinary team created a guideline providing criteria for establishing initial sensor-meter agreement within each individual patient followed by hybrid use of CGM and POC. POC measures were obtained hourly during initial validation, then every 6 hours. We conducted a focus group among MICU nurses to evaluate initial implementation efforts with content areas focused on initial assessment of evidence, context, and facilitation to identify barriers and facilitators. The focus group was analyzed using a qualitative descriptive approach.

RESULTS

The protocol was integrated through a rapid cycle review process and ultimately disseminated nationally. The Diabetes Consult Service performed device set-up and nurses received just-in-time training. The majority of barriers centered on contextual factors, including limitations of the physical environment, complex device set-up, hospital firewalls, need for training, and CGM documentation. Nurses' perceived device accuracy and utility were exceptionally high. Solutions were devised to maximize facilitation and sustainability for nurses while maintaining patient safety.

CONCLUSION

Outpatient CGM systems can be implemented in the MICU using a hybrid protocol implementation science approach. These efforts hold tremendous potential to reduce healthcare worker exposure while maintaining glucose control during the COVID-19 pandemic.

Predictors of mortality in a multiracial urban cohort of persons with type 2 diabetes and novel coronavirus 19

BACKGROUND

Diabetes has been identified as a risk factor for intubation and mortality in patients with coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We seek to examine the impact of clinical variables such as glycosylated hemoglobin (HbA1c) on mortality and need for intubation, as well as demographic variables such as age, sex, and race on persons with type 2 diabetes and COVID-19.

METHODS

Analyses were conducted on 4413 patients with an International Classification of Diseases and Related Health Problems (ICD-10) diagnosis of type 2 diabetes and COVID-19. Survival analysis was conducted using Kaplan-Meier curves and the log-rank test to compare subgroup analyses.

RESULTS

In this multivariate analysis, male gender, older age, and hyperglycemia at admission were associated with increased mortality and intubation, but this was not seen for race, ethnicity, insurance type, or HbA1c. Based on Kaplan-Meier analysis, having comorbid conditions such as hypertension, chronic kidney disease, and coronary artery disease was associated with a statistically significant increased risk of mortality.

CONCLUSIONS

Glycemic levels at admission have a greater impact on health outcomes than HbA1c. Older men and those with comorbid disease are also at greater risk for mortality. Further longitudinal studies need to be done to evaluate the impact of COVID-19 on type 2 diabetes.

Peripheral Inflammatory Cytokines and Lymphocyte Subset Features of Deceased COVID-19 Patients

OBJECTIVE

To compare the difference of inflammatory cytokines and lymphocyte subsets between deceased patients and survivors with COVID-19.

METHODS

This retrospective study included 254 confirmed patients from 10 January to 11 March, 2020, at Tongji Hospital of Wuhan, China. Laboratory and immunologic features were collected and analyzed, and the main outcomes focused on inflammatory cytokines and lymphocyte subsets.

RESULTS

A trend of markedly higher levels of inflammatory cytokines as well as lower lymphocyte subset levels in deceased patients was observed compared with survivors. ROC curve analyses indicated that inflammatory cytokines and the decrease levels of T cell, Th (helper T cells) cell, Ts (suppressor T cells) cell, B cell, and NK cell along with Th/Ts ratio increase could be used to predict the death of COVID-19. Multivariate analyses showed that higher levels of IL-6, IL-8, and IL-10 remained significantly correlated with shorter survival time and that the amount of Ts cells was negatively associated with the possibility of death in COVID-19 patients. In conclusion, SARS-CoV-2 would cause lymphopenia and result in decreased lymphocyte subset cells, particularly in Ts cell counts, which further induces hyperinflammatory response and cytokine storm. IL-6, IL-8, IL-10, and Ts cell might be independent predictors for the poor outcome of COVID-19.

Glycemia, Beta-Cell Function and Sensitivity to Insulin in Mildly to Critically Ill Covid-19 Patients

Background and objectives: Critically and non-critically ill patients with SARS-CoV-2 infection (Covid-19) may present with higher-than-expected glycemia, even in the absence of diabetes. With this study we aimed to assess glucose, glycemic gap (GlyG) and insulin secretion/sensitivity measures in patients with Covid-19. Materials and Methods: We studied, upon admission, 157 patients with Covid-19 (84: in wards and 73: in intensive care units; ICU); 135 had no history of diabetes. We measured blood glucose upon admission as well as glycated hemoglobin (A1c), plasma insulin and C-peptide. We calculated the GlyG and the Homeostasis Model Assessment 2 (HOMA2) estimates of steady state beta cell function (HOMA2%B) and insulin sensitivity (HOMA2%S). Statistical assessment was done with analysis or the Kruskal-Wallis test. Results: Compared to patients in the wards without diabetes, patients with diabetes in the wards, as well as patients in the ICU (without or with diabetes) had higher admission glycemia. The GlyG was significantly higher in patients without diabetes in the ICU compared to patients without diabetes in the wards, while HOMA2%B based on glucose and insulin was significantly higher in the ICU patients compared to patients in the wards. Of all the parameters, HOMA2%S based on C-peptide/glucose was higher in survivors (n = 133). Conclusions: In our series of patients with Covid-19, a substantial number of patients with and without diabetes had admission hyperglycemia and those who were critically ill may have had compromised insulin secretion and lowered sensitivity to insulin. These findings lend credence to reports of association between Covid-19 and hyperglycemia/secondary diabetes.

Diabetology Care During COVID-19 Lockdown in Bosnia and Herzegovina - Diabetologists and Patients Perspective

Introduction:

COVID-19 pandemic suddenly affected all countries and health care systems from different perspectives including severe disruption of chronic disease services including diabetes. Diabetes is a serious condition and highly present in Bosnia and Herzegovina population, so provision of diabetes care is a important part of good control. Countries had different responses to adopt diabetes care under new circumstances as well as Bosnia and Herzegovina.

Aim:

To investigate and evaluate the impact of the COVID-19 pandemic on the provision of diabetology care in Bosnia and Herzegovina from the perspective of patients and diabetologists.

Methods:

Online survey for diabetologists and patient organizations have been developed with adopted question for different perspectives. The survey has been conducted online early September 2020. Collected data were analyzed in SPSS software for descriptive statistics.

Results:

25 diabetologists and 24 diabetes patient organizations responded. 72% of diabetologists believe that pandemic has partially altered work with patients and 56% believe that the organization of diabetes care has successfully responded to the new circumstances but 80% believe that the diabetes care system should change. 75% of patient organizations thought that the organization of diabetes care did not adequately respond and 87.5% believe system should change.

Conclusion:

No significant differences found between RS and FBiH when it comes to majority of questions. Both diabetologists and patients consider that system of diabetes care in Bosnia and Herzegovina should be improved in future. It has been also found that diabetologists in Bosnia and Herzegovina responded and adopted their practices similar to other countries.

'BhAVI-23'-A spice-herb based dietary infusion possessing in-vitro anti-viral potential

Background

Viruses cause many life threatening human diseases. Recently, COVID-19 pandemic has challenged the health care systems worldwide. As a disease preventive approach and to bring relief to the severity of the symptoms, a infusion termed as Bhabha Anti-Viral Infusion-23 (‘BhAVI-23’) was conceptualized and formulated which comprised of 23 selected spices and herbals.

Objective

The present study was conducted to assess the in vitro antiviral potential of the formulation, BhaAVI-23.

Material and methods

The in-vitro anti-viral potential of BhAVI-23 was assessed through inhibition of HIV1 reverse transcriptase (RT) as well as through a novel P1 (virulent) bacteriphage based screening assay system. Anti-diabetic potential was assessed by non-enzymatic glycosylation of haemoglobin and the bioactive volatile components were detected through headspace gas chromatography followed by molecular docking analysis.

Results

The infusion displayed prominent anti-viral activity as evident from significant (57%) inhibition of the HIV1-RT as well as through reduction in the infectivity of P1 (virulent) bacteriophage. The infusion also exerted profound protection (∼64%) to non-enzymatic glycosylation of haemoglobin. Headspace gas chromatography and mass spectrometric analysis confirmed the presence of at least 47 major compounds. Docking analysis indicated possible interaction of α-pinene and eugenol with SARS-CoV spike protein.

Conclusion

This ‘BhAVI-23’ infusion displayed prominent in-vitro anti-viral and anti-diabetic potential in different model systems. These attributes have relevance as diabetic patients are more prone to COVID-19 morbidity. ‘BhAVI-23’ opens the avenue for its potential inclusion as a supportive health care system upon due regulatory approval during the current pandemic.

Insulin Treatment Is Associated with Increased Mortality in Patients with COVID-19 and Type 2 Diabetes

COVID-19 caused by SARS-COV-2 infection can lead to multi-organ injuries and significant mortality in severe and critical patients, especially among those individuals with type 2 diabetes (T2D) as a comorbidity. While attenuated mortality was observed with aggressive glucose control, it was unclear whether therapeutic regimens including insulin treatment were beneficial for patients with COVID-19 and T2D. This retrospective study investigated 689 patients with COVID-19 and T2D from a cohort of 3,305 cases from Wuhan, China. Unexpectedly, we found that insulin treatment for patients with COVID-19 and T2D was associated with a significant increase in mortality (27.2% versus 3.5%; adjusted HR, 5.38 [2.75-10.54]). Further analysis showed that insulin treatment was associated with enhanced systemic inflammation and aggravated injuries of vital organs. Therefore, insulin treatment for patients with COVID-19 and T2D should be used with caution.

High prevalence of diabetes and other comorbidities in hospitalized patients with COVID-19 in Delhi, India, and their association with outcomes

BACKGROUND AND AIMS

To study the prevalence and impact of diabetes mellitus and other comorbidities among hospitalized patients with COVID-19.

METHODS

In a prospective, observational study including consecutive adults hospitalized with COVID-19, clinical outcomes and inflammatory markers were compared in those with and without diabetes. Participants were classified as having mild or severe COVID-19 disease using the WHO ordinal scale.

RESULTS

401 patients (125 females) with median age of 54 years (range 19-92) were evaluated. Of them 189 (47.1%) had pre-existing diabetes and21 (5.2%) had new-onset hyperglycaemia. Overall, 344 (85.8%) and 57 (14.2%) cases had mild and severe COVID-19 disease respectively. The group with diabetes had a higher proportion of severe cases (20.1% vs 9%, p-0.002), mortality (6.3 vs 1.4%, p-0.015), ICU admission (24.3 vs 12.3%, p-0.002), and oxygen requirement (53.4 vs 28.3%, p < 0.001). Baseline Hba1c (n = 331) correlated significantly with outcome severity scores (r 0.136, p-0.013) and 12/15 (80%) of those who succumbed had diabetes. Hypertension, coronary artery disease, and chronic kidney disease were present in 164 (40.9%), 35 (8.7%) and 12 (2.99%) patients respectively. Hypertension was associated with a higher proportion of severe cases, mortality, ICU admission and oxygen administration.

CONCLUSIONS

We report a high prevalence of diabetes in a hospitalized COVID-19 population. Patients with diabetes or hypertension had more severe disease and greater mortality.

Metformin and Covid-19: Focused Review of Mechanisms and Current Literature Suggesting Benefit

Metformin is the first-line medication for type 2 diabetes, but it also has a long history of improved outcomes in infectious diseases, such as influenza, hepatitis C, and in-vitro assays of zika. In the current Covid-19 pandemic, which has rapidly spread throughout the world, 4 observational studies have been published showing reduced mortality among individuals with home metformin use. There are several potential overlapping mechanisms by which metformin may reduce mortality from Covid-19. Metformin's past anti-infectious benefits have been both against the infectious agent directly, as well as by improving the underlying health of the human host. It is unknown if the lower mortality suggested by observational studies in patients infected with Covid-19 who are on home metformin is due to direct activity against the virus itself, improved host substrate, or both.

COVID-19 associated with diabetes and other noncommunicable diseases led to a global health crisis

COVID-19 has gravely threatened high-risk populations, such as people with diabetes and other noncommunicable diseases, leading to disproportionate hospitalizations and deaths worldwide. It is well documented from previous outbreaks that diabetes increases the risk for poor outcomes due to SARS infection. In the present review, we bring evidence that the country and global level health crisis caused by COVID-19 could have been avoided or extremely minimized if measures to protect high-risk populations were implemented timely. In addition to general lockdowns, testing, tracing, isolation and hygiene measures, other specific interventions for diabetes and comorbidities management were shown crucial to allow the continuation of care services during the pandemic. These interventions included: teleconsultation, digital remote education andmonitoring, e-prescriptions, medicine delivery options, mobile clinics, and home point-of-care tests. In conclusion, we recommend prompt actions to protect the most vulnerable groups, valuing knowledge and experiences from previous outbreaks and lessons learned during the COVID-19 pandemic, in order to shield communities, health systems and the global economy.