Fasting blood glucose at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes: a multi-centre retrospective study

Diabetes and coronavirus (SARS-CoV-2): Molecular mechanism of Metformin intervention and the scientific basis of drug repurposing

Coronavirus Disease 2019 (COVID-19), caused by a new strain of coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was declared a pandemic by WHO on March 11, 2020. Soon after its emergence in late December 2019, it was noticed that diabetic individuals were at an increased risk of COVID-19-associated complications, ICU admissions, and mortality. Maintaining proper blood glucose levels using insulin and/or other oral antidiabetic drugs (such as Metformin) reduced the detrimental effects of COVID-19. Interestingly, in diabetic COVID-19 patients, while insulin administration was associated with adverse outcomes, Metformin treatment was correlated with a significant reduction in disease severity and mortality rates among affected individuals. Metformin was extensively studied for its antioxidant, anti-inflammatory, immunomodulatory, and antiviral capabilities that would explain its ability to confer cardiopulmonary and vascular protection in COVID-19. Here, we describe the various possible molecular mechanisms that contribute to Metformin therapy's beneficial effects and lay out the scientific basis of repurposing Metformin for use in COVID-19 patients.

COVID-19 in People With Schizophrenia: Potential Mechanisms Linking Schizophrenia to Poor Prognosis

As the global burden of mortality from COVID-19 continues to rise, an understanding of who is most at risk of adverse outcomes is of paramount importance. Pre-existing cardiometabolic, renal and respiratory diseases as well as old age are well-established risk factors associated with disease severity and mortality among patients with COVID-19. However, mounting evidence also indicates an increased susceptibility to, and risk of adverse outcomes from COVID-19 in people with schizophrenia, independent of age and comorbidity. Therefore, elucidating the underlying pathophysiological mechanisms which may increase the risk of poor outcomes in people with schizophrenia is of crucial importance. Here, we provide a narrative on the current understanding of COVID-19 in patients with schizophrenia and propose potential mechanisms which may link schizophrenia with an increased susceptibility to, and greater risk of adverse outcomes from COVID-19. Given the existing knowledge gaps, robust clinical and biological studies are required to further our understanding of some of these underlying mechanisms, so that effective prevention and treatment strategies for COVID-19 in patients with schizophrenia can be developed.

COVID-19 and hyperglycemia/diabetes

In early studies regarding coronavirus disease 2019 (COVID-19), type 2 diabetes mellitus was considered to contribute substantially to the disease’s inflammatory response. Subsequently, even hyperglycemia, regardless of insulin resistance or diabetes mellitus, was found to be additionally harmful. Recent studies have shown inflammation of the pancreatic β cells in COVID-19, even leading to new onset diabetes mellitus. We hereby summarize core literature on glycemia and COVID-19, and present implicated pathways and mechanisms.

Dysnatremia is a Predictor for Morbidity and Mortality in Hospitalized Patients with COVID-19

CONTEXT

Dysnatremia is an independent predictor of mortality in patients with bacterial pneumonia. There is paucity of data about the incidence and prognostic impact of abnormal sodium concentration in patients with coronavirus disease 2019 (COVID-19).

OBJECTIVE

This work aimed to examine the association of serum sodium during hospitalization with key clinical outcomes, including mortality, need for advanced respiratory support and acute kidney injury (AKI), and to explore the role of serum sodium as a marker of inflammatory response in COVID-19.

METHODS

This retrospective longitudinal cohort study, including all adult patients who presented with COVID-19 to 2 hospitals in London over an 8-week period, evaluated the association of dysnatremia (serum sodium < 135 or > 145 mmol/L, hyponatremia, and hypernatremia, respectively) at several time points with inpatient mortality, need for advanced ventilatory support, and AKI.

RESULTS

The study included 488 patients (median age, 68 years). At presentation, 24.6% of patients were hyponatremic, mainly due to hypovolemia, and 5.3% hypernatremic. Hypernatremia 2 days after admission and exposure to hypernatremia at any time point during hospitalization were associated with a 2.34-fold (95% CI, 1.08-5.05; P = .0014) and 3.05-fold (95% CI, 1.69-5.49; P < .0001) increased risk of death, respectively, compared to normonatremia. Hyponatremia at admission was linked with a 2.18-fold increase in the likelihood of needing ventilatory support (95% CI, 1.34-3.45, P = .0011). Hyponatremia was not a risk factor for in-hospital mortality, except for the subgroup of patients with hypovolemic hyponatremia. Sodium values were not associated with the risk for AKI and length of hospital stay.

CONCLUSION

Abnormal sodium levels during hospitalization are risk factors for poor prognosis, with hypernatremia and hyponatremia being associated with a greater risk of death and respiratory failure, respectively. Serum sodium values could be used for risk stratification in patients with COVID-19.

Loss of FOXO transcription factors in the liver mitigates stress-induced hyperglycemia

Objective

Stress-induced hyperglycemia is associated with poor outcomes in nearly all critical illnesses. This acute elevation in glucose after injury or illness is associated with increased morbidity and mortality, including multiple organ failure. Stress-induced hyperglycemia is often attributed to insulin resistance as controlling glucose levels via exogenous insulin improves outcomes, but the mechanisms are unclear. Forkhead box O (FOXO) transcription factors are direct targets of insulin signaling in the liver that regulate glucose homeostasis via direct and indirect pathways. Loss of hepatic FOXO transcription factors reduces hyperglycemia in chronic insulin resistance; however, the role of FOXOs in stress-induced hyperglycemia is unknown.

Methods

We subjected mice lacking FOXO transcription factors in the liver to a model of injury known to cause stress-induced hyperglycemia. Glucose, insulin, glycerol, fatty acids, cytokines, and adipokines were assessed before and after injury. Liver and adipose tissue were analyzed for changes in glycogen, FOXO target gene expression, and insulin signaling.

Results

Stress-induced hyperglycemia was associated with reduced hepatic insulin signaling and increased hepatic FOXO target gene expression while loss of FOXO1, 3, and 4 in the liver attenuated hyperglycemia and prevented hyperinsulinemia. Mechanistically, the loss of FOXO transcription factors mitigated the stress-induced hyperglycemia response by directly altering gene expression and glycogenolysis in the liver and indirectly suppressing lipolysis in adipose tissue. Reductions were associated with decreased IL-6, TNF-α, and follistatin and increased FGF21, suggesting that cytokines and FOXO-regulated hepatokines contribute to the stress-induced hyperglycemia response.

Conclusions

This study implicates FOXO transcription factors as a predominant driver of stress-induced hyperglycemia through means that include cross-talk between the liver and adipose, highlighting a novel mechanism underlying acute hyperglycemia and insulin resistance in stress.

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Liver forkhead box O (FOXO) target gene expression is increased in critical illness.

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Loss of FOXO1, 3, and 4 in the liver mitigates stress-induced hyperglycemia (SIH).

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Hepatic FOXO drives SIH via direct and indirect means in the liver and adipose.

The prognostic role of hyperglycemia and glucose variability in covid-related acute respiratory distress Syndrome

AIMS

Due to heterogeneity on the prognostic role of glucose values and glucose variability in Novel Coronavirus (COVID) disease, we aimed at assessing the prognostic role for Intensive Care Unit (ICU) death of admission hyperglycaemia, peak glycemia and glucose variability in critically ill COVID patients: METHODS: 83 patients consecutively admitted for COVID-related Acute Respiratory Distress Syndrome (ARDS) from from 1st March to 1st October 2020.

RESULTS

Non survivors were older, with more comorbidities and a more severe disease. Corticosteroids were used in the majority of patients (54/83, 65%) with no difference between survivors and non survivors. Mean blood glucose values, (during the first 24 and 48 h, respectively), were comparable between the two subgroups, as well as SD 24 and CV 24. During the first 48 h, survivors showed significantly lower values of SD 48 (p < 0.001) and CV 48, respectively (p < 0.001) than non survivors.

CONCLUSIONS

in consecutive COVID-related ARDS patients admitted to ICU hyperglycemia (>180 mg/dl) is more common in non survivors who also showed a significantly higher glucose variability in the first 48 h since ICU admission. Our findings point to the clinical significance of in-ICU glucose control in severe COVID patients.

Severity of COVID-19 and Treatment Strategy for Patient With Diabetes

Coronavirus disease 2019 (COVID-19), which was named by the World Health Organization (WHO) in February 2020, has quickly spread to more than 200 countries around the world and was declared as a global pandemic in March 2020. The severity of the disease makes it more prone to severe symptoms and higher mortality rates in patients, especially those who are with comorbidities, including high blood pressure, cardiovascular disease, obesity, and diabetes, increases the concern over the consequences of this pandemic. However, initial reports do not clearly describe whether diabetes itself or associated comorbidities or treatment strategies contribute to the severe prognosis of COVID-19 infections. Various clinical trials are being conducted on glucose-lowering agents but to date, there is no standard treatment protocol approved for COVID-19 cases with pre-existing diabetes. This review is aimed to decipher the potential risk factors of COVID-19 involved from existing evidence. Identification of a novel therapeutic strategy could be beneficial for combating SARS-CoV-2, which might be dreadful to debilitating people who have diabetes.

Prognostic value of fasting hyperglycemia in patients with COVID-19 - Diagnostic test accuracy meta-analysis

Aims

This meta-analysis aimed to assess the prognostic value of fasting hyperglycemia in patients with COVID-19.

Methods

A systematic literature search on PubMed, Embase, and Scopus were performed up until February 18, 2021. Fasting hyperglycemia was defined as fasting plasma glucose level above the reference value. The outcome of interest was poor outcome, which was a composite of mortality and severe COVID-19. The effect estimate was in odds ratio (OR).

Results

There were 9045 patients from 12 studies included in this systematic review and meta-analysis. The prevalence of fasting hyperglycemia was 29%. The incidence of poor outcome was 15%. Fasting hyperglycemia was associated with poor outcome in COVID-19 (OR 4.72 [3.32, 6.72], p < 0.001; I²: 69.8%, p < 0.001). Subgroup analysis in patients without prior history of diabetes showed that fasting hyperglycemia was associated with poor outcome in COVID-19 (OR 3.387 [2.433, 4.714], p < 0.001; I²: 0, p = 0.90). Fasting hyperglycemia has a sensitivity of 0.57 [0.45, 0.68], specificity of 0.78 [0.70, 0.84], PLR of 2.6 [2.0, 3.3], NLR of 0.55 [0.44, 0.69], DOR of 5 [3, 7], and AUC of 0.74 [0.70, 0.78] for predicting poor outcome. In this pooled analysis, fasting hyperglycemia has a 32% post-test probability for poor outcome, and absence of fasting hyperglycemia confers to a 9% post-test probability. Meta-regression and subgroup analysis showed that the sensitivity and specificity varies by chronic kidney disease but not by age, male (gender), hypertension, and chronic kidney disease.

Conclusion

Fasting hyperglycemia was associated with mortality in COVID-19 patients, with or without diabetes.

Prospero

CRD42021237997.

Predictors of hospital discharge and mortality in patients with diabetes and COVID-19: updated results from the nationwide CORONADO study

AIMS/HYPOTHESIS

This is an update of the results from the previous report of the CORONADO (Coronavirus SARS-CoV-2 and Diabetes Outcomes) study, which aims to describe the outcomes and prognostic factors in patients with diabetes hospitalised for coronavirus disease-2019 (COVID-19).

METHODS

The CORONADO initiative is a French nationwide multicentre study of patients with diabetes hospitalised for COVID-19 with a 28-day follow-up. The patients were screened after hospital admission from 10 March to 10 April 2020. We mainly focused on hospital discharge and death within 28 days.

RESULTS

We included 2796 participants: 63.7% men, mean age 69.7 ± 13.2 years, median BMI (25th-75th percentile) 28.4 (25.0-32.4) kg/m². Microvascular and macrovascular diabetic complications were found in 44.2% and 38.6% of participants, respectively. Within 28 days, 1404 (50.2%; 95% CI 48.3%, 52.1%) were discharged from hospital with a median duration of hospital stay of 9 (5-14) days, while 577 participants died (20.6%; 95% CI 19.2%, 22.2%). In multivariable models, younger age, routine metformin therapy and longer symptom duration on admission were positively associated with discharge. History of microvascular complications, anticoagulant routine therapy, dyspnoea on admission, and higher aspartate aminotransferase, white cell count and C-reactive protein levels were associated with a reduced chance of discharge. Factors associated with death within 28 days mirrored those associated with discharge, and also included routine treatment by insulin and statin as deleterious factors.

CONCLUSIONS/INTERPRETATION

In patients with diabetes hospitalised for COVID-19, we established prognostic factors for hospital discharge and death that could help clinicians in this pandemic period.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT04324736.

Association of Early-Phase In-Hospital Glycemic Fluctuation With Mortality in Adult Patients With Coronavirus Disease 2019

OBJECTIVE

To investigate the association of in-hospital early-phase glycemic control with adverse outcomes among inpatients with coronavirus disease 2019 (COVID-19) in Wuhan, China.

RESEARCH DESIGN AND METHODS

The study is a large case series, and data were obtained regarding consecutive patients hospitalized with COVID-19 in the Central Hospital of Wuhan between 2 January and 15 February 2020. All patients with definite outcomes (death or discharge) were included. Demographic, clinical, treatment, and laboratory information were extracted from electronic medical records. We collected daily fasting glucose data from standard morning fasting blood biochemistry to determine glycemic status and fluctuation (calculated as the square root of the variance of daily fasting glucose levels) during the 1st week of hospitalization.

RESULTS

A total of 548 patients were included in the study (median age 57 years; 298 [54%] were women, and n = 99 had diabetes [18%]), 215 suffered acute respiratory distress syndrome (ARDS), 489 survived, and 59 died. Patients who had higher mean levels of glucose during their 1st week of hospitalization were older and more likely to have a comorbidity and abnormal laboratory markers, prolonged hospital stays, increased expenses, and greater risks of severe pneumonia, ARDS, and death. Compared with patients with the lowest quartile of glycemic fluctuation, those who had the highest quartile of fluctuation magnitude had an increased risk of ARDS (risk ratio 1.97 [95% CI 1.01, 4.04]) and mortality (hazard ratio 2.73 [95% CI 1.06, 7.73]).

CONCLUSIONS

These results may have implications for optimizing glycemic control strategies in COVID-19 patients during the early phase of hospitalization.

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.

COVID-19 and Diabetic Ketoacidosis: Report of Eight Cases

Aim To describe the clinical characteristics and outcome of hospitalized COVID-19 patients with diabetic ketoacidosis (DKA). Methods We report eight cases of diabetic ketoacidosis in COVID-19 who presented to our institution in New Jersey, USA. COVID-19 was diagnosed by nasopharyngeal swab reverse transcription polymerase chain reaction (RT-PCR). The patients' electronic medical records were reviewed. Data on patients' age, sex, ethnicity, laboratory values, glycosylated hemoglobin level, oral antihyperglycemic agents (OHAs), insulin, and clinical outcomes were collected. Results The median age of the patient was 42.5 years, and seven were males and one was female. Out of eight patients, five had type 2 diabetes mellitus (DM), two had undiagnosed DM, and one had type 1 DM. Median value of initial glucose on presentation was 454 mg/dL. Median value of HbA1c on presentation was 11.4% and of anion gap was 26.5 mEq/L. Four patients had large ketonemia, one patient had moderate ketonemia, and three patients had small ketonemia. All the patients were started on standard treatment protocol for DKA with intravenous fluids and IV insulin infusion. Acute kidney injury (AKI) was seen in four patients, and one patient required renal replacement therapy. Out of eight patients, three required mechanical ventilation, and the same three patients died. Conclusion Our case series shows that COVID-19 infection can precipitate DKA in patients with known diabetes mellitus patients or as a first manifestation in undiagnosed DM patients; COVID-19 with DKA is associated with substantial mortality. Further studies are needed to characterize poor risk factors associated with mortality in these patients.

Hyperglycemia in Acute COVID-19 is Characterized by Adipose Tissue Dysfunction and Insulin Resistance

COVID-19 has proven to be a metabolic disease resulting in adverse outcomes in individuals with diabetes or obesity. Patients infected with SARS-CoV-2 and hyperglycemia suffer from longer hospital stays, higher risk of developing acute respiratory distress syndrome (ARDS), and increased mortality compared to those who do not develop hyperglycemia. Nevertheless, the pathophysiological mechanism(s) of hyperglycemia in COVID-19 remains poorly characterized. Here we show that insulin resistance rather than pancreatic beta cell failure is the prevalent cause of hyperglycemia in COVID-19 patients with ARDS, independent of glucocorticoid treatment. A screen of protein hormones that regulate glucose homeostasis reveals that the insulin sensitizing adipokine adiponectin is reduced in hyperglycemic COVID-19 patients. Hamsters infected with SARS-CoV-2 also have diminished expression of adiponectin. Together these data suggest that adipose tissue dysfunction may be a driver of insulin resistance and adverse outcomes in acute COVID-19.

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.

Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study

BACKGROUND

Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases).

METHOD

We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method.

RESULTS

We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval.

CONCLUSION

We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.

Metabolic consequences of obesity and type 2 diabetes: Balancing genes and environment for personalized care

The prevalence of type 2 diabetes and obesity has risen dramatically for decades and is expected to rise further, secondary to the growing aging, sedentary population. The strain on global health care is projected to be colossal. This review explores the latest work and emerging ideas related to genetic and environmental factors influencing metabolism. Translational research and clinical applications, including the impact of the COVID-19 pandemic, are highlighted. Looking forward, strategies to personalize all aspects of prevention, management and care are necessary to improve health outcomes and reduce the impact of these metabolic diseases.

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.

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.

Global pandemics interconnected - obesity, impaired metabolic health and COVID-19

Obesity and impaired metabolic health are established risk factors for the non-communicable diseases (NCDs) type 2 diabetes mellitus, cardiovascular disease, neurodegenerative diseases, cancer and nonalcoholic fatty liver disease, otherwise known as metabolic associated fatty liver disease (MAFLD). With the worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), obesity and impaired metabolic health also emerged as important determinants of severe coronavirus disease 2019 (COVID-19). Furthermore, novel findings indicate that specifically visceral obesity and characteristics of impaired metabolic health such as hyperglycaemia, hypertension and subclinical inflammation are associated with a high risk of severe COVID-19. In this Review, we highlight how obesity and impaired metabolic health increase complications and mortality in COVID-19. We also summarize the consequences of SARS-CoV-2 infection for organ function and risk of NCDs. In addition, we discuss data indicating that the COVID-19 pandemic could have serious consequences for the obesity epidemic. As obesity and impaired metabolic health are both accelerators and consequences of severe COVID-19, and might adversely influence the efficacy of COVID-19 vaccines, we propose strategies for the prevention and treatment of obesity and impaired metabolic health on a clinical and population level, particularly while the COVID-19 pandemic is present.

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.

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.

Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study

BACKGROUND

During a pandemic, it is important for clinicians to stratify patients and decide who receives limited medical resources. Machine learning models have been proposed to accurately predict COVID-19 disease severity. Previous studies have typically tested only one machine learning algorithm and limited performance evaluation to area under the curve analysis. To obtain the best results possible, it may be important to test different machine learning algorithms to find the best prediction model.

OBJECTIVE

In this study, we aimed to use automated machine learning (autoML) to train various machine learning algorithms. We selected the model that best predicted patients' chances of surviving a SARS-CoV-2 infection. In addition, we identified which variables (ie, vital signs, biomarkers, comorbidities, etc) were the most influential in generating an accurate model.

METHODS

Data were retrospectively collected from all patients who tested positive for COVID-19 at our institution between March 1 and July 3, 2020. We collected 48 variables from each patient within 36 hours before or after the index time (ie, real-time polymerase chain reaction positivity). Patients were followed for 30 days or until death. Patients' data were used to build 20 machine learning models with various algorithms via autoML. The performance of machine learning models was measured by analyzing the area under the precision-recall curve (AUPCR). Subsequently, we established model interpretability via Shapley additive explanation and partial dependence plots to identify and rank variables that drove model predictions. Afterward, we conducted dimensionality reduction to extract the 10 most influential variables. AutoML models were retrained by only using these 10 variables, and the output models were evaluated against the model that used 48 variables.

RESULTS

Data from 4313 patients were used to develop the models. The best model that was generated by using autoML and 48 variables was the stacked ensemble model (AUPRC=0.807). The two best independent models were the gradient boost machine and extreme gradient boost models, which had an AUPRC of 0.803 and 0.793, respectively. The deep learning model (AUPRC=0.73) was substantially inferior to the other models. The 10 most influential variables for generating high-performing models were systolic and diastolic blood pressure, age, pulse oximetry level, blood urea nitrogen level, lactate dehydrogenase level, D-dimer level, troponin level, respiratory rate, and Charlson comorbidity score. After the autoML models were retrained with these 10 variables, the stacked ensemble model still had the best performance (AUPRC=0.791).

CONCLUSIONS

We used autoML to develop high-performing models that predicted the survival of patients with COVID-19. In addition, we identified important variables that correlated with mortality. This is proof of concept that autoML is an efficient, effective, and informative method for generating machine learning-based clinical decision support tools.

Clinical Characteristics and Risk Factors for Mortality in Very Old Patients Hospitalized With COVID-19 in Spain

BACKGROUND

Advanced age is a well-known risk factor for poor prognosis in COVID-19. However, few studies have specifically focused on very old inpatients with COVID-19. This study aims to describe the clinical characteristics of very old inpatients with COVID-19 and identify risk factors for in-hospital mortality at admission.

METHODS

We conducted a nationwide, multicenter, retrospective, observational study in patients ≥ 80 years hospitalized with COVID-19 in 150 Spanish hospitals (SEMI-COVID-19) Registry (March 1-May 29, 2020). The primary outcome was in-hospital mortality. A uni- and multivariate logistic regression was performed to assess predictors of mortality at admission.

RESULTS

A total of 2772 consecutive patients (49.4% men, median age 86.3 years) were analyzed. Rates of atherosclerotic cardiovascular disease, diabetes mellitus, dementia, and Barthel Index < 60 were 30.8%, 25.6%, 30.5%, and 21.0%, respectively. The overall case-fatality rate was 46.9% (n: 1301) and increased with age (80-84 years: 41.6%; 85-90 years: 47.3%; 90-94 years: 52.7%; ≥95 years: 54.2%). After analysis, male sex and moderate-to-severe dependence were independently associated with in-hospital mortality; comorbidities were not predictive. At admission, independent risk factors for death were: oxygen saturation < 90%; temperature ≥ 37.8°C; quick sequential organ failure assessment (qSOFA) score ≥ 2; and unilateral-bilateral infiltrates on chest x-rays. Some analytical findings were independent risk factors for death, including estimated glomerular filtration rate < 45 mL/min/1.73 m2; lactate dehydrogenase ≥ 500 U/L; C-reactive protein ≥ 80 mg/L; neutrophils ≥ 7.5 × 103/μL; lymphocytes < 0.8 × 103/μL; and monocytes < 0.5 × 103/μL.

CONCLUSIONS

This first large, multicenter cohort of very old inpatients with COVID-19 shows that age, male sex, and poor preadmission functional status-not comorbidities-are independently associated with in-hospital mortality. Severe COVID-19 at admission is related to poor prognosis.

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 Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations

There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities—foreign-born, immigrant, refugee, and culturally marginalized—are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, several factors may predispose AI to ethnoracial bias. To better understand whether diabetes AI interventions are being designed in an ethnoracially equitable manner, we conducted a secondary analysis of 141 articles included in a 2018 review by Contreras and Vehi entitled “Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.” Two members of our research team independently reviewed each article and selected those reporting ethnoracial data for further analysis. Only 10 articles (7.1%) were ultimately selected for secondary analysis in our case study. Of the 131 excluded articles, 118 (90.1%) failed to mention participants’ ethnic or racial backgrounds. The included articles reported ethnoracial data under various categories, including race (n=6), ethnicity (n=2), race/ethnicity (n=3), and percentage of Caucasian participants (n=1). Among articles specifically reporting race, the average distribution was 69.5% White, 17.1% Black, and 3.7% Asian. Only 2 articles reported inclusion of Native American participants. Given the clear ethnic and racial differences in diabetes biomarkers, prevalence, and outcomes, the inclusion of ethnoracial training data is likely to improve the accuracy of predictive models. Such considerations are imperative in AI-based tools, which are predisposed to negative biases due to their black-box nature and proneness to distributional shift. Based on our findings, we propose a short questionnaire to assess ethnoracial equity in research describing AI-based diabetes interventions. At this unprecedented time in history, AI can either mitigate or exacerbate disparities in health care. Future accounts of the infancy of diabetes AI must reflect our early and decisive action to confront ethnoracial inequities before they are coded into our systems and perpetuate the very biases we aim to eliminate. If we take deliberate and meaningful steps now toward training our algorithms to be ethnoracially inclusive, we can architect innovations in diabetes care that are bound by the diverse fabric of our society.

Diabetes predicts severity of COVID-19 infection in a retrospective cohort: A mediatory role of the inflammatory biomarker C-reactive protein

Diabetes is a risk factor for developing severe COVID-19, but the pathogenesis remains unclear. We investigated if the association of diabetes and COVID-19 severity may be mediated by inflammation. We also hypothesized that this increased risk may extend to prediabetes. Hospitalized patients in Singapore with COVID-19 were subdivided into three groups in a retrospective cohort: normoglycemia (HbA1c: ≤5.6%), prediabetes (HbA1c: 5.7%-6.4%) and diabetes (HbA1c: ≥6.5%). The primary outcome of severe COVID-19 was defined by respiratory rate ≥30, SpO2 ≤93% or intensive care unit admission. The association between clinical factors on severe COVID-19 outcome was analyzed by cox regression. Adjusted mediation analysis of C-reactive protein (CRP) on the relationship between diabetes and severe COVID-19 was performed. Of 1042 hospitalized patients, mean age 39 ± 11 years, 13% had diabetes, 9% prediabetes and 78% normoglycemia. Severe COVID-19 occurred in 4.9% of subjects. Compared to normoglycemia, diabetes was significantly associated with severe COVID-19 on both univariate (hazard ratio [HR]: 9.94; 95% confidence interval [CI]: 5.54-17.84; p < .001) and multivariate analysis (HR: 3.99; 95% CI: 1.92-8.31; p < .001), while prediabetes was not a risk factor (HR: 0.94; 95% CI: 0.22-4.03; p = .929). CRP, a biomarker of inflammation, mediated 32.7% of the total association between diabetes and severe COVID-19 outcome. In conclusion, CRP is a partial mediator of the association between diabetes and severe COVID-19 infection, confirming that inflammation is important in the pathogenesis of severe COVID-19 in diabetes.

Why Is COVID-19 More Severe in Patients With Diabetes? The Role of Angiotensin-Converting Enzyme 2, Endothelial Dysfunction and the Immunoinflammatory System

Meta-analyses have indicated that individuals with type 1 or type 2 diabetes are at increased risk of suffering a severe form of COVID-19 and have a higher mortality rate than the non-diabetic population. Patients with diabetes have chronic, low-level systemic inflammation, which results in global cellular dysfunction underlying the wide variety of symptoms associated with the disease, including an increased risk of respiratory infection. While the increased severity of COVID-19 amongst patients with diabetes is not yet fully understood, the common features associated with both diseases are dysregulated immune and inflammatory responses. An additional key player in COVID-19 is the enzyme, angiotensin-converting enzyme 2 (ACE2), which is essential for adhesion and uptake of virus into cells prior to replication. Changes to the expression of ACE2 in diabetes have been documented, but they vary across different organs and the importance of such changes on COVID-19 severity are still under investigation. This review will examine and summarise existing data on how immune and inflammatory processes interplay with the pathogenesis of COVID-19, with a particular focus on the impacts that diabetes, endothelial dysfunction and the expression dynamics of ACE2 have on the disease severity.

How do routine laboratory tests change in coronavirus disease 2019?

How the routine laboratory tests change in terms of coronavirus disease 2019 (COVID-19) was retrospectively analyzed in a large group of patients. Biochemical, hematological and inflammatory variables of a totaly 555 (n = 532 in non-intensive care unit (non-ICU), n = 23 in ICU) patients diagnosed with COVID-19 were analyzed accessing them through the laboratory information system. White blood cell (WBC), neutrophil (NEU), platelet large cell ratio, neutrophil to lymphocyte ratio (NLR), derived NLR (d-NLR), aspartate aminotransferase, urea, creatine kinase (CK) myocardial band (CK-MB), procalcitonin (PCT) values were high whereas lymphocyte (LYM), eosinophil, red blood cells (RBC), hemoglobin, lymphocyte to monocyte ratio, estimated glomerular filtration rate values were low in the ICU group when compared with non-ICU. WBC, NEU, red cell distribution width, alanine transaminase, creatinine, urea, CK-MB, CK, direct bilirubin, lactate dehydrogenase, glucose, C-reactive protein, erythrocyte sedimentation rate, ferritin, D-dimer, PCT and international normalized ratio values increased while RBC, hemoglobin, hematocrit, mean corpuscular volume and total bilirubin values decreased in a significant proportion of patients in both groups based on the normal reference ranges. LYM count was found to be low in a significant number of patients (57.5%) especially in the ICU group and as an important risk factor and diagnostic parameter on admission to ICU (OR: 125, AUC: 0.74). Routine laboratory tests provide important information in terms of both diagnosis and severity of COVID-19. Lymphopenia is a condition that should be monitored which indicates the severity of the disease.

Impact of undiagnosed type 2 diabetes and pre-diabetes on severity and mortality for SARS-CoV-2 infection

INTRODUCTION

Diabetes and hyperglycemia are risk factors for critical COVID-19 outcomes; however, the impact of pre-diabetes and previously unidentified cases of diabetes remains undefined. Here, we profiled hospitalized patients with undiagnosed type 2 diabetes and pre-diabetes to evaluate its impact on adverse COVID-19 outcomes. We also explored the role of de novo and intrahospital hyperglycemia in mediating critical COVID-19 outcomes.

RESEARCH DESIGN AND METHODS

Prospective cohort of 317 hospitalized COVID-19 cases from a Mexico City reference center. Type 2 diabetes was defined as previous diagnosis or treatment with diabetes medication, undiagnosed diabetes and pre-diabetes using glycosylated hemoglobin (HbA1c) American Diabetes Association (ADA) criteria and de novo or intrahospital hyperglycemia as fasting plasma glucose (FPG) ≥140 mg/dL. Logistic and Cox proportional regression models were used to model risk for COVID-19 outcomes.

RESULTS

Overall, 159 cases (50.2%) had type 2 diabetes and 125 had pre-diabetes (39.4%), while 31.4% of patients with type 2 diabetes were previously undiagnosed. Among 20.0% of pre-diabetes cases and 6.1% of normal-range HbA1c had de novo hyperglycemia. FPG was the better predictor for critical COVID-19 compared with HbA1c. Undiagnosed type 2 diabetes (OR: 5.76, 95% CI 1.46 to 27.11) and pre-diabetes (OR: 4.15, 95% CI 1.29 to 16.75) conferred increased risk of severe COVID-19. De novo/intrahospital hyperglycemia predicted critical COVID-19 outcomes independent of diabetes status.

CONCLUSIONS

Undiagnosed type 2 diabetes, pre-diabetes and de novo hyperglycemia are risk factors for critical COVID-19. HbA1c must be measured early to adequately assess individual risk considering the large rates of undiagnosed type 2 diabetes in Mexico.

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.

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.

A guidance on diagnosis and management of hyperglycemia at COVID care facilities in India

BACKGROUND AND AIMS

Diabetes and coronavirus disease 2019 (COVID-19) share a bidirectional relationship. Hyperglycemia occurring in the setting of either previously diagnosed or undiagnosed diabetes is known to be associated with poor outcomes. Here, we aim to provide a simple and practical guidance on the diagnosis and management of hyperglycemia in admitted patients with COVID-19.

METHODS

The guidance is formulated based on experience of authors and relevant literature on the subject searched using Pubmed.

RESULTS

Every patient admitted to a COVID care facility should be investigated for hyperglycemia using a combination of tests including capillary blood glucose, fasting plasma glucose and HbA1c. Oral glucose lowering drugs can be considered in patients with mild COVID illness who have mild hyperglycemia [pre-meal blood glucose of <180 mg/dl (10 mmol/L) and post-meal blood glucose of <250 mg/dl (13.9 mmol/L)] and no contraindication to the use of these agents.. All patients with moderate-severe disease and/or hyperglycemia of greater severity should be initiated on insulin therapy. Hyperglycemia should be aggressively screened for and managed in patients receiving systemic glucocorticoids.

CONCLUSION

This document provides a broad overview on the diagnosis and management of hyperglycemia at COVID care facilities and should be useful to a wide range of healthcare personnel involved in care of patients with COVID-19.

Association Between Longitudinal Change in Abnormal Fasting Blood Glucose Levels and Outcome of COVID-19 Patients Without Previous Diagnosis of Diabetes

This retrospective study examined changes in fasting blood glucose (FBG) levels during hospitalization and their effect on risk of death for Coronavirus disease 2019 (COVID-19) patients without previously diagnosed diabetes. A model with low- and high-stable pattern trajectories was established based on a longitudinal change in FBG levels. We analyzed FBG trajectory-associated clinical features and risk factors for death due to COVID-19. Of the 230 enrolled patients, 44 died and 87.83% had a low-stable pattern (average FBG range: 6.63-7.54 mmol/L), and 12.17% had a high-stable pattern (average FBG range: 12.59-14.02 mmol/L). There were statistical differences in laboratory findings and case fatality between the two FBG patterns. Multivariable logistic regression analysis showed that increased neutrophil count (odds ratio [OR], 25.43; 95% confidence interval [CI]: 2.07, 313.03), elevated direct bilirubin (OR, 5.80; 95%CI: 1.72, 19.58), elevated creatinine (OR, 26.69; 95% CI: 5.82, 122.29), lymphopenia (OR, 8.07; 95% CI: 2.70, 24.14), and high-stable FBG pattern (OR, 8.79; 95% CI: 2.39, 32.29) were independent risk factors for higher case fatality in patients with COVID-19 and hyperglycemia but no history of diabetes. FBG trajectories were significantly associated with death risk in patients with COVID-19 and no diabetes.

Adverse outcomes in COVID-19 and diabetes: a retrospective cohort study from three London teaching hospitals

INTRODUCTION

Patients with diabetes mellitus admitted to hospital with COVID-19 have poorer outcomes. However, the drivers of poorer outcomes are not fully elucidated. We performed detailed characterization of patients with COVID-19 to determine the clinical and biochemical factors that may be drivers of poorer outcomes.

RESEARCH DESIGN AND METHODS

This is a retrospective cohort study of 889 consecutive inpatients diagnosed with COVID-19 between March 9 and April 22, 2020 in a large London National Health Service Trust. Unbiased multivariate logistic regression analysis was performed to determine variables that were independently and significantly associated with increased risk of death and/or intensive care unit (ICU) admission within 30 days of COVID-19 diagnosis.

RESULTS

62% of patients in our cohort were of non-white ethnic background and the prevalence of diabetes was 38%. 323 (36%) patients met the primary outcome of death/admission to the ICU within 30 days of COVID-19 diagnosis. Male gender, lower platelet count, advancing age and higher Clinical Frailty Scale (CFS) score (but not diabetes) independently predicted poor outcomes on multivariate analysis. Antiplatelet medication was associated with a lower risk of death/ICU admission. Factors that were significantly and independently associated with poorer outcomes in patients with diabetes were coexisting ischemic heart disease, increasing age and lower platelet count.

CONCLUSIONS

In this large study of a diverse patient population, comorbidity (ie, diabetes with ischemic heart disease; increasing CFS score in older patients) was a major determinant of poor outcomes with COVID-19. Antiplatelet medication should be evaluated in randomized clinical trials among high-risk patient groups.

Blood Hemoglobin Substantially Modulates the Impact of Gender, Morbid Obesity, and Hyperglycemia on COVID-19 Death Risk: A Multicenter Study in Italy and Spain

BACKGROUND

Hyperglycemia and obesity are associated with a worse prognosis in subjects with COVID-19 independently. Their interaction as well as the potential modulating effects of additional confounding factors is poorly known. Therefore, we aimed to identify and evaluate confounding factors affecting the prognostic value of obesity and hyperglycemia in relation to mortality and admission to the intensive care unit (ICU) due to COVID-19.

METHODS

Consecutive patients admitted in two Hospitals from Italy (Bologna and Rome) and three from Spain (Barcelona and Girona) as well as subjects from Primary Health Care centers. Mortality from COVID-19 and risk for ICU admission were evaluated using logistic regression analyses and machine learning (ML) algorithms.

RESULTS

As expected, among 3,065 consecutive patients, both obesity and hyperglycemia were independent predictors of ICU admission. A ML variable selection strategy confirmed these results and identified hyperglycemia, blood hemoglobin and serum bilirubin associated with increased mortality risk. In subjects with blood hemoglobin levels above the median, hyperglycemic and morbidly obese subjects had increased mortality risk than normoglycemic individuals or non-obese subjects. However, no differences were observed among individuals with hemoglobin levels below the median. This was particularly evident in men: those with severe hyperglycemia and hemoglobin concentrations above the median had 30 times increased mortality risk compared with men without hyperglycemia. Importantly, the protective effect of female sex was lost in subjects with increased hemoglobin levels.

CONCLUSIONS

Blood hemoglobin substantially modulates the influence of hyperglycemia on increased mortality risk in patients with COVID-19. Monitoring hemoglobin concentrations seem of utmost importance in the clinical settings to help clinicians in the identification of patients at increased death risk.

Blood glucose levels should be considered as a new vital sign indicative of prognosis during hospitalization

BACKGROUND AND AIMS

The measurement of vital signs is an important part of clinical work up. Presently, measurement of blood glucose is a factor for concern mostly when treating individuals with diabetes. Significance of blood glucose measurement in prognosis of non-diabetic and hospitalized patients is not clear.

METHODS

A systematic search of literature published in the Electronic databases, PubMed and Google Scholar was performed using following keywords; blood glucose, hospital admissions, critical illness, hospitalizations, cardiovascular disease (CVD), morbidity, and mortality. This literature search was largely restricted to non-diabetic individuals.

RESULTS

Blood glucose level, even when in high normal range, or in slightly high range, is an important determinant of morbidity and mortality, especially in hospitalized patients. Further, even slight elevation of blood glucose may increase mortality in patients with COVID-19. Finally, blood glucose variability and hypoglycemia in critically ill individuals without diabetes causes excess in-hospital complications and mortality.

CONCLUSION

In view of these data, we emphasize the significance of blood glucose measurement in all patients admitted to the hospital regardless of presence of diabetes. We propose that blood glucose be included as the "fifth vital sign" for any hospitalized patient.

Newly-Diagnosed Diabetes and Sustained Hyperglycemia are Associated with Poorer Outcomes in COVID-19 Inpatients Without Pre-Existing Diabetes

PURPOSE

To analyze the impact of hyperglycemia on the clinical outcome of COVID-19 in patients with newly diagnosed diabetes (NDD).

PATIENTS AND METHODS

We performed a retrospective study of 3114 cases of COVID-19 without pre-existing diabetes, 351 of which had NDD, in Hubei Province, China. The Cox regression model was used to calculate the risk of adverse clinical outcomes comparing the NDD vs non-NDD group before and after propensity score-matched (PSM) analysis. Patients with NDD were further divided into a sustained hyperglycemia group, a fluctuating group, and a remitted group based on their blood glucose levels during hospitalization as well as into hypoglycemic agent users and nonusers.

RESULTS

Compared to the non-NDD individuals, individuals with NDD had a significantly increased risk of all-cause mortality (adjusted HR after PSM, 2.65; 95% CI, 1.49-4.72; P = 0.001) and secondary outcomes involving organ damage during the 28-day follow-up period. Subgroup analyses indicated that among individuals with NDD, the individuals with remitted hyperglycemia had the lowest 28-day mortality, whereas those with sustained hyperglycemia had the highest (IRR 24.27; 95% CI, 3.21-183.36; P < 0.001). Moreover, individuals treated with hypoglycemic agents had significantly lower all-cause mortality than those not treated with hypoglycemic agents (IRR 0.08; 95% CI, 0.01-0.56; P < 0.001).

CONCLUSION

Our study reinforces the clinical message that NDD is strongly associated with poor outcomes in COVID-19 patients. Furthermore, resolved hyperglycemia in the later phase of the disease and the use of hypoglycemic agents were associated with improved prognosis in patients with NDD.

Heterogeneity in presentation of hyperglycaemia during COVID-19 pandemic: A proposed classification

Diabetes and hyperglycemia occurring during COVID-19 era have implications for COVID-19 related morbidity/mortality. In this brief review, we have attempted to categorise and classify such heterogenous hyperglycemic states. During COVID-19 pandemic broadly two types of hyperglycemia were seen: one in patients without COVID-19 infection and second in patients with COVID-19 infection. Patients not inflicted with COVID-19 infection and diagnosed with either type 2 diabetes mellitus (T2DM) or type 1 diabetes mellitus (T1DM) show more severe hyperglycemia and more ketoacidosis, respectively. In former, it could be attributed to weight gain, decreased exercise, stress and in both type of diabetes, due to delayed diagnosis during lockdown and pandemic. In patients with COVID-19 and associated pneumonia, altered glucose metabolism leading to hyperglycemia could be due to corticosteroids, cytokine storm, damage to pancreatic beta cells, or combination of these factors. Some of these patients present with diabetic ketoacidosis, hyperglycemic hyperosmolar state or both. We have provided a framework for categorisation of hyperglycemic states, which could be consolidated/revised in future based on new research data.

High admission blood glucose independently predicts poor prognosis in COVID-19 patients: A systematic review and dose-response meta-analysis

AIMS

To investigate the prognostic value of admission blood glucose (BG) in predicting COVID-19 outcomes, including poor composite outcomes (mortality/severity), mortality, and severity.

METHODS

Eligible studies evaluating the association between admission fasting BG (FBG) and random BG (RBG) levels with COVID-19 outcomes were included and assessed for risk of bias with the Quality in Prognosis Studies tool. Random-effects dose-response meta-analysis was conducted to investigate potential linear or non-linear exposure-response gradient.

RESULTS

The search yielded 35 studies involving a total of 14,502 patients. We discovered independent association between admission FBG and poor COVID-19 prognosis. Furthermore, we demonstrated non-linear relationship between admission FBG and severity (Pnon-linearity < 0.001), where each 1 mmol/L increase augmented the risk of severity by 33% (risk ratio 1.33 [95% CI: 1.26-1.40]). Albeit exhibiting similar trends, study scarcity limited the evidence strength on the independent prognostic value of admission RBG. GRADE assessment yielded high-quality evidence for the association between admission FBG and COVID-19 severity, and moderate-quality evidence for its association with mortality and poor outcomes.

CONCLUSION

High admission FBG level independently predicted poor COVID-19 prognosis. Further research to confirm the prognostic value of admission RBG and to ascertain the estimated dose-response risk between admission FBG and COVID-19 severity are required.