J-shaped association between fasting blood glucose levels and COVID-19 severity in patients without diabetes

Neurological Sequelae of COVID-19: A Biochemical Perspective

Exogenous factors can induce protein expression and modify the proteome which sustains for a certain period of time. The proteins of SARS-CoV-2 are high in valine plus glycine, which possess potent affinity to divalent cations such as calcium. Calcium buildup changes the protein expression profile by enabling the efficient synthesis of proteins rich in amino acids with calcium affinity. Subsequent formation of insoluble and stiff calcium oxalate and aggregates confers cellular stress and causes cell senescence. This scenario accounts for sequelae seen in some patients following recovery from COVID-19.

COVID-19 and metabolic syndrome

Convergence of the two pandemics: metabolic syndrome and COVID-19 over last two years has posed unprecedented challenges to individuals as well as healthcare systems. Epidemiological data suggest a close association between metabolic syndrome and COVID-19 while variety of possible pathogenic connections have been proposed while some have been proven. Despite the evidence of high risk for adverse COVID-19 outcomes in people with metabolic syndrome, little is known about the differences in efficacy and safety among people with metabolic syndrome and without. It is important to recognize that among people with metabolic syndrome This review summarizes the current knowledge and epidemiological evidence on the association between metabolic syndrome and adverse COVID-19 outcomes, pathogenic interrelationships, management considerations for acute COVID-19 and post-COVID sequalae and sustaining care of people living with metabolic syndrome with appraisal of evidence and gaps in knowledge.

Naturopathic Management of Acute Pediatric Respiratory Infections: A Modified Delphi Study

Objective: Both the United Nations and the World Health Organization have identified antimicrobial resistance as a significant threat to global health. The Centers for Disease Control and Prevention identified five pediatric respiratory conditions as requiring particular scrutiny in terms of antibiotic stewardship. This study sought to identify strategies used by experienced naturopathic practitioners to treat acute respiratory infections in children. The authors theorize that naturopathic strategies safely fill the gap between watchful waiting and antibiotic prescription, thus reducing the use of antibiotics. Methods: Naturopathic practitioners in Canada, the United States, and Australia with a minimum of 5 years of experience in clinical naturopathic care of children were recruited for a modified Delphi study. A 14-person panel of practitioners was selected to complete a series of four iterative surveys assessing agreement to statements in five domains of knowledge/attitudes, assessment/diagnosis, management, monitoring, and education. Items were deemed to have reached consensus if they reached a predetermined threshold of 70% agreement, or failed to reach a threshold of 40% agreement. Items between these boundaries were modified and retested until either consensus was reached or the four surveys had been completed. Results: Results yielded a large degree of agreement on core naturopathic approaches to the management of acute pediatric respiratory infections, especially lifestyle strategies, including adequate rest and dietary recommendations. The use of vitamins C and D was strongly supported, as were herbs, particularly echinacea and elderberry. Some hydrotherapy and topical applications specific to the individual focus on infection also reached consensus. Results suggested that most respondents, even if they have the authority to prescribe antibiotics, rarely deem it necessary to do so. Conclusion: Findings of this study provide (1) clarity on the role of naturopathic doctors in the management of pediatric health concerns and the stewardship of antibiotics; and (2) initial guidance to less experienced naturopathic practitioners. The findings also identify key priorities for research into the safety and effectiveness of naturopathic interventions to reduce the unnecessary prescribing of antibiotics.

The syndromic triad of COVID-19, type 2 diabetes, and malnutrition

The coronavirus disease 2019 (COVID-19) pandemic challenges our collective understanding of transmission, prevention, complications, and clinical management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Risk factors for severe infection, morbidity, and mortality are associated with age, environment, socioeconomic status, comorbidities, and interventional timing. Clinical investigations report an intriguing association of COVID-19 with diabetes mellitus and malnutrition but incompletely describe the triphasic relationship, its mechanistic pathways, and potential therapeutic approaches to address each malady and their underlying metabolic disorders. This narrative review highlights common chronic disease states that interact epidemiologically and mechanistically with the COVID-19 to create a syndromic phenotype-the COVID-Related Cardiometabolic Syndrome-linking cardiometabolic-based chronic disease drivers with pre-, acute, and chronic/post-COVID-19 disease stages. Since the association of nutritional disorders with COVID-19 and cardiometabolic risk factors is well established, a syndromic triad of COVID-19, type 2 diabetes, and malnutrition is hypothesized that can direct, inform, and optimize care. In this review, each of the three edges of this network is uniquely summarized, nutritional therapies discussed, and a structure for early preventive care proposed. Concerted efforts to identify malnutrition in patients with COVID-19 and elevated metabolic risks are needed and can be followed by improved dietary management while simultaneously addressing dysglycemia-based chronic disease and malnutrition-based chronic disease.

J-shaped associations and joint effects of fasting glucose with inflammation and cytokines on COVID-19 mortality

OBJECTIVES

The aim of this study was to investigate the dose-response relationship of admission fasting glucose (FBG) with corona virus disease 2019 (COVID-19) mortality and to further evaluate potential interactions of hyperglycemia with inflammation and hypercoagulation on COVID-19 outcomes.

METHODS

This retrospective study included 2555 consecutively hospitalized patients with COVID-19, until death or discharge, in Wuhan Union hospital between January 1 and April 9, 2020. The poor early outcomes included admission to intensive care unit, intubation, and deaths occurring within 28 days. We used splines nested in Cox regression to visualize dose-response associations and generalized additive models to fit three-dimensional (3D) trend plots for joint effects of FBG with markers of inflammation and coagulation.

RESULTS

J-shaped associations existed between hospitalized mortality or poor early outcomes and FBG with a nadir at 5 mmol/L, which were more evident in women. 3D plots demonstrated significant joint effect trends, and patients with hyperglycemia and high neutrophil-lymphocyte ratio, C-reactive protein, lactate dehydrogenase, procalcitonin, d-dimer, and interleukin-6 had 7.4-25.3-fold risks; the proportions of joint associations attributed to additive interactions reached 30% to 54%.

CONCLUSIONS

FBG was associated with hospitalized mortality and poor early outcomes in a J-shaped manner, and a combination of hyperglycemia, inflammation, hypercoagulation, and cytokines conferred a dramatically higher risk.

Associations between cardiometabolic disease severity, social determinants of health (SDoH), and poor COVID-19 outcomes

OBJECTIVE

This study aimed to determine the ability of retrospective cardiometabolic disease staging (CMDS) and social determinants of health (SDoH) to predict COVID-19 outcomes.

METHODS

Individual and neighborhood SDoH and CMDS clinical parameters (BMI, glucose, blood pressure, high-density lipoprotein, triglycerides), collected up to 3 years prior to a positive COVID-19 test, were extracted from the electronic medical record. Bayesian logistic regression was used to model CMDS and SDoH to predict subsequent hospitalization, intensive care unit (ICU) admission, and mortality, and whether adding SDoH to the CMDS model improved prediction was investigated. Models were cross validated, and areas under the curve (AUC) were compared.

RESULTS

A total of 2,873 patients were identified (mean age: 58 years [SD 13.2], 59% were female, 45% were Black). CMDS, insurance status, male sex, and higher glucose values were associated with increased odds of all outcomes; area-level social vulnerability was associated with increased odds of hospitalization (odds ratio: 1.84, 95% CI: 1.38-2.45) and ICU admission (odds ratio 1.98, 95% CI: 1.45-2.85). The AUCs improved when SDoH were added to CMDS (p < 0.001): hospitalization (AUC 0.78 vs. 0.82), ICU admission (AUC 0.77 vs. 0.81), and mortality (AUC 0.77 vs. 0.83).

CONCLUSIONS

Retrospective clinical markers of cardiometabolic disease and SDoH were independently predictive of COVID-19 outcomes in the population.

Long COVID, neuropsychiatric disorders, psychotropics, present and future

Long COVID refers to the lingering symptoms which persist or appear after the acute illness. The dominant long COVID symptoms in the two years since the pandemic began (2020-2021) have been depression, anxiety, fatigue, concentration and cognitive impairments with few reports of psychosis. Whether other symptoms will appear later on is not yet known. For example, dopamine-dependent movement disorders generally take many years before first symptoms are seen. Post-stroke depression and anxiety may explain many of the early long COVID cases. Hemorrhagic, hypoxic and inflammatory damages of the central nervous system, unresolved systematic inflammation, metabolic impairment, cerebral vascular accidents such as stroke, hypoxia from pulmonary damages and fibrotic changes are among the major causes of long COVID. Glucose metabolic and hypoxic brain issues likely predispose subjects with pre-existing diabetes, cardiovascular or lung problems to long COVID as well. Preliminary data suggest that psychotropic medications may not be a danger but could instead be beneficial in combating COVID-19 infection. The same is true for diabetes medications such as metformin. Thus, a focus on sigma-1 receptor ligands and glucose metabolism is expected to be useful for new drug development as well as the repurposing of current drugs. The reported protective effects of psychotropics and antihistamines against COVID-19, the earlier reports of reduced number of sigma-1 receptors in post-mortem schizophrenic brains, with many antidepressant and antipsychotic drugs being antihistamines with significant affinity for the sigma-1 receptor, support the role of sigma and histamine receptors in neuroinflammation and viral infections. Literature and data in all these areas are accumulating at a fast rate. We reviewed and discussed the relevant and important literature.

Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis synthesized the evidence on the impacts of demographics and comorbidities on the clinical outcomes of COVID-19, as well as the sources of the heterogeneity and publication bias of the relevant studies. Two authors independently searched the literature from PubMed, Embase, Cochrane library, and CINAHL on 18 May 2021; removed duplicates; screened the titles, abstracts, and full texts by using criteria; and extracted data from the eligible articles. The variations among the studies were examined by using Cochrane, Q.; I2, and meta-regression. Out of 11,975 articles that were obtained from the databases and screened, 559 studies were abstracted, and then, where appropriate, were analyzed by meta-analysis (n = 542). COVID-19-related severe illness, admission to the ICU, and death were significantly correlated with comorbidities, male sex, and an age older than 60 or 65 years, although high heterogeneity was present in the pooled estimates. The study design, the study country, the sample size, and the year of publication contributed to this. There was publication bias among the studies that compared the odds of COVID-19-related deaths, severe illness, and admission to the ICU on the basis of the comorbidity status. While an older age and chronic diseases were shown to increase the risk of developing severe illness, admission to the ICU, and death among the COVID-19 patients in our analysis, a marked heterogeneity was present when linking the specific risks with the outcomes.

Comparison of Analytical Values D-Dimer, Glucose, Ferritin and C-Reactive Protein of Symptomatic and Asymptomatic COVID-19 Patients

Those infected by COVID-19 develop various kinds of complications with varying degrees of severity. For this reason, it is necessary to evaluate its analytical values to predict and reduce the risks and complications derived from this pathology. A cross-sectional study was carried out a population in Almeria (south-eastern Spain) who had a positive Polymerase Chain Reaction test result from 1 March 2020 to 30 November 2020. The study involved 4575 patients, with 1346 who were asymptomatic, 1653 mildly symptomatic (no hospitalisation needed) and 1576 severely symptomatic (symptomatic patients hospitalised). Laboratory values for D-dimer, glucose, serum ferritin, and C-reactive protein were analysed. The mean age of the participants in the study was 53.60 (16.89) years old. A total of 70.6% of the patients were symptomatic, of which 36.1% had mild symptoms. For all of the laboratory predictors analysed (D-dimer, glucose, serum ferritin, and C-reactive protein), it was found that severe alterations in the parameters were more frequent in severely symptomatic patients with statistically significant differences (p < 0.001), although these alterations also occurred in asymptomatic patients. Age correlated with analytical values (D-dimer, glucose, serum ferritin, and C-reactive protein) with statistically significant differences. Patients with severe symptoms presented alterations in the analytical values of D-dimer, glucose, serum ferritin, and C-reactive protein. Asymptomatic patients presented alterations in the analysed parameters, though with less frequency and severity than patients with severe symptoms.

Glucose dysregulation and its association with COVID-19 mortality and hospital length of stay

BACKGROUND AND AIMS

We investigate the impact of blood glucose on mortality and hospital length of stay (HLOS) among COVID-19 patients.

METHODS

Retrospective study of 456 patients with confirmed COVID-19 and glycemic dysregulation in the New York City area.

RESULTS

We found that impaired glucose adjusted for other organs systems involved (OR:1.87; 95% CI:1.36-2.57, p < 0.001), increased glucose nadir (OR:34.28; 95% CI:3.97-296.05, p < 0.01) and abnormal blood glucose levels at discharge (OR:5.07; 95% CI:2.31-11.14, p < 0.001) were each significantly associated with increased odds for mortality. New or higher from baseline insulin requirement during hospitalization (OR:0.34; 95% CI:0.15-0.78; p < 0.05) was significantly associated with decreased odds for mortality. Increased glucose peak (B = 0.001, SE=<0.001, p < 0.001), new or higher from baseline insulin requirement during hospitalization (B = 0.11, SE = 0.03, p < 0.001), and increased days to dysglycemia (B = 0.15, SE = 0.04, p < 0.001) were each significantly associated with increased HLOS. Increased glucose nadir (B = -0.67, SE = 0.07, p < 0.001), insulin intravenous drip (B = -0.10, SE = 0.05, p < 0.05), and increased proportion days endocrine system involved (B = -0.25, SE = 0.06, p < 0.001) were each significantly associated with decreased HLOS.

CONCLUSION

Glucose dysregulation adversely affects mortality and HLOS in COVID-19. These data can help clinicians to guide patient treatment and management in COVID-19 patients.

[Dysglycemia in COVID-19 and Type 2 Diabetes Mellitus: Peculiarities of the Glycemic Profile in Hospitalized Patients and the Role of Steroid-Induced Disorders]

BACKGROUND

There is a lack of data on the features of dysglycemia in hospitalized patients with COVID-19 and concomitant diabetes mellitus (DM) confirmed by continuous glucose monitoring (CGM).

AIM

to study the glycemic profile in hospitalized patients with COVID-19 and type 2 diabetes mellitus by continuous glucose monitoring and the role of steroid therapy in dysglycemiadevelopment.

MATERIALS AND METHODS

We examined 21 patients with COVID-19 and DM 2 and 21 patients with DM 2 without COVID-19 (control group) using a professional 4-7-day CGM. We also compared two subgroups of patients with COVID-19 and DM 2: 1) patients received systemic glucocorticosteroids (GCS) during CGM and 2) patients in whomCGMwas performed after discontinuation of GCS.

RESULTS

Compared with controls, patients with COVID-19 and DM2 had lesser values of glycemic «time in range» (32.7 ± 20.40 vs 48.0 ± 15.60%, p = 0.026) andhigher parameters of mean glycemia (p &lt;0.05) but similar proportion of patients with episodes of hypoglycemia (33.3% vs 38.1%, p = 0.75). Patients who received dexamethasone during CGM were characterized by higher hyperglycemia and the absence of episodes of hypoglycemia. In patients who hadCGM after dexamethasone discontinuation, hyperglycemia was less pronounced, but 60% of them had episodes of hypoglycemia, often nocturnal, clinically significant and not detected by routine methods.

CONCLUSION

Patients with COVID-19 and DM 2had severe and persistent hyperglycemia but a third of them hadalso episodes of hypoglycemia. During therapy with dexamethasone, they had the most pronounced hyperglycemia without episodes of hypoglycemia. In patients who underwent CGM after discontinuation of dexamethasone, hyperglycemia was less pronounced but 60% of them have episodes of hypoglycemia, often nocturnal, clinically significant and not diagnosed by routine methods. It would be advisable to recommend at least a 5-6-fold study of the blood glucose level (with its obligatory assessment at night) even for stable patients with COVID-19 and DM 2after the end of GCS treatment.

The Prognostic Role of Metabolic and Endocrine Parameters for the Clinical Severity of COVID-19

Objective

An outbreak of coronavirus disease-19 (COVID-19) began in December 2019 and spread globally, overwhelming the entire world. COVID-19 is a public health emergency of international concern. Due to its high morbidity and mortality rate, recognition of its risk and prognostic factors is important. We aimed to understand the relationship between metabolic and endocrine parameters and the prognosis of COVID-19.

Methods and Materials

This was a cross-sectional clinical study. A total of 70 patients with severe COVID-19 were enrolled. Laboratory results at the first admission time (including complete blood count, C-reactive protein, lactate dehydrogenase, blood glucose, calcium, phosphate, albumin, creatinine, magnesium, lipid profiles, liver enzymes, thyroid hormones, cortisol, and vitamin D) and outcome data were recorded. We divided patients into (1) intensive care unit- (ICU-) admitted and non-ICU-admitted and (2) survivors and nonsurvivors for estimation of severity and prognosis. We determined the risk factors associated with critical illness and poor prognosis.

Results

Patients with higher white blood cell (WBC) count and phosphate levels had significantly higher ICU admission rates. According to univariate analysis, serum levels of T3, phosphate, and WBC as well as the duration of hospitalization were associated with mortality. Multivariate analysis revealed that only WBC and duration of hospitalization were independent predictors for mortality rate in COVID-19 patients.

Conclusion

Our findings suggest that longer duration of hospitalization and higher WBC count are associated with poor outcomes in patients with COVID-19.

ACTIV SARS-CoV-2 registry (Analysis of Chronic Non-infectious Diseases Dynamics After COVID-19 Infection in Adult Patients). Assessment of impact of combined original comorbid diseases in patients with COVID-19 on the prognosis

Aim. Study the impact of various combinations of comorbid original diseases in patients infected with COVID-19 later on the disease progression and outcomes of the new coronavirus infection. Materials and methods. The ACTIV registry was created on the Eurasian Association of Therapists initiative. 5,808 patients have been included in the registry: men and women with COVID-19 treated at hospital or at home. ClinicalTrials.gov ID NCT04492384. Results. Most patients with COVID-19 have original comorbid diseases (oCDs). Polymorbidity assessed by way of simple counting of oCDs is an independent factor in negative outcomes of COVID-19. Search for most frequent combinations of 2, 3 and 4 oCDs has revealed absolute domination of cardiovascular diseases (all possible variants). The most unfavorable combination of 2 oCDs includes atrial hypertension (AH) and chronic heart failure (CHF). The most unfavorable combination of 3 oCDs includes AH, coronary heart disease (CHD) and CHF; the worst combination of 4 oCDs includes AH, CHD, CHF and diabetes mellitus. Such combinations increased the risk of lethal outcomes 3.963, 4.082 and 4.215 times respectively. Conclusion. Polymorbidity determined by way of simple counting of diseases may be estimated as a factor in the lethal outcome risk in the acute phase of COVID-19 in real practice. Most frequent combinations of 2, 3 and 4 diseases in patients with COVID-19 primarily include cardiovascular diseases (AH, CHD and CHF), diabetes mellitus and obesity. Combinations of such diseases increase the COVID-19 lethal outcome risk.

Excess Body Mass-A Factor Leading to the Deterioration of COVID-19 and Its Complications-A Narrative Review

Currently, the world is facing two serious pandemics: obesity and COVID-19. It is well-established that the prevalence of obesity has risen dramatically, causing a deterioration in the health quality of the population and increasing susceptibility for the unfavourable course of acute infections. It has been observed that excess body mass significantly influences the COVID-19 outcome. The aim of this review is to present the latest scientific reports on the impact of excess body mass on the course and complications of COVID-19. The Web of Science, PubMed, and Google Scholar databases were searched. Only studies reporting patients stated to be COVID-19 positive based on the results of a nasopharyngeal swab and the ribonucleic acid test were included. It is shown that thromboembolic and ischemic complications, namely stroke, disseminated intravascular coagulation, severe hyperglycaemia, and leukoencephalopathy are more likely to appear in COVID-19 positive patients with obesity compared to non-obese subjects. COVID-19 complications such as cardiomyopathy, dysrhythmias, endothelial dysfunction, acute kidney injury, dyslipidaemia, lung lesions and acute respiratory distress syndrome have a worse outcome among obese patients.

The SARS-CoV-2 pandemic is associated with increased severity of presentation of childhood onset type 1 diabetes mellitus: A multi-centre study of the first COVID-19 wave

OBJECTIVE

Children are usually mildly affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19). However, the pandemic has caused collateral damage to those with non-COVID-19 diseases. We aimed to determine the impact of the COVID-19 pandemic on the presentation of newly diagnosed childhood onset type 1 diabetes.

METHODS

This was a cross-sectional study conducted over a 1-year period. We compared the severity of presentation of new-onset type 1 diabetes in children under the age of 18 presenting to the multi-centre North Central London diabetes network before (1 July 2019 to 22 March 2020) and during (23 March 2020 to 30 June 2020) the first wave of the COVID-19 pandemic in the United Kingdom.

RESULTS

Over the 1-year study period, a total of 30 children presented with new-onset type 1 diabetes during the pre-pandemic period and 17 presented during the first COVID-19 wave. Children presented more frequently in diabetic ketoacidosis (DKA) during the first COVID-19 wave compared with pre-pandemic (pre-pandemic: mild 13%, moderate 6.7%, severe 10%; first COVID-19 wave: mild 5.9%, moderate 24%, severe 47%; p = 0.002). During the first COVID-19 wave, DKA presentations in children with a family history of type 1 diabetes were fewer compared to those without a family history (33.3% vs. 100.0%; p = 0.006). Children presenting in severe DKA pre-pandemic were younger than those not in severe DKA (3.9 years vs. 12.2 years, p < 0.001) but this difference was not significant during the first COVID-19 wave (10.1 years vs. 11.2 years, p = 0.568). Presenting HbA1c measurement was higher in those presenting during the first COVID-19 wave (13.0 ± 1.7 vs. 10.4 ± 3.2%; 119 ± 19 vs. 90 ± 35 mmol/mol; p = 0.008).

CONCLUSION

The COVID-19 pandemic is associated with increased severity of presentation of childhood onset type 1 diabetes. Whatever the context, young people with suspected new-onset type 1 diabetes should be referred for urgent clinical review.

Data-driven identification of temporal glucose patterns in a large cohort of nondiabetic patients with COVID-19 using time-series clustering

Objective

Hyperglycemia has emerged as an important clinical manifestation of coronavirus disease 2019 (COVID-19) in diabetic and nondiabetic patients. Whether these glycemic changes are specific to a subgroup of patients and persist following COVID-19 resolution remains to be elucidated. This work aimed to characterize longitudinal random blood glucose in a large cohort of nondiabetic patients diagnosed with COVID-19.

Materials and Methods

De-identified electronic medical records of 7502 patients diagnosed with COVID-19 without prior diagnosis of diabetes between January 1, 2020, and November 18, 2020, were accessed through the TriNetX Research Network. Glucose measurements, diagnostic codes, medication codes, laboratory values, vital signs, and demographics were extracted before, during, and after COVID-19 diagnosis. Unsupervised time-series clustering algorithms were trained to identify distinct clusters of glucose trajectories. Cluster associations were tested for demographic variables, COVID-19 severity, glucose-altering medications, glucose values, and new-onset diabetes diagnoses.

Results

Time-series clustering identified a low-complexity model with 3 clusters and a high-complexity model with 19 clusters as the best-performing models. In both models, cluster membership differed significantly by death status, COVID-19 severity, and glucose levels. Clusters membership in the 19 cluster model also differed significantly by age, sex, and new-onset diabetes mellitus.

Discussion and Conclusion

This work identified distinct longitudinal blood glucose changes associated with subclinical glucose dysfunction in the low-complexity model and increased new-onset diabetes incidence in the high-complexity model. Together, these findings highlight the utility of data-driven techniques to elucidate longitudinal glycemic dysfunction in patients with COVID-19 and provide clinical evidence for further evaluation of the role of COVID-19 in diabetes pathogenesis.

Diabetes and COVID-19: The past, the present, and the future

Diabetes, one of the most prevalent chronic diseases in the world, is strongly associated with a poor prognosis in COVID-19. Scrupulous blood sugar management is crucial, since the worse outcomes are closely associated with higher blood sugar levels in COVID-19 infection. Although recent observational studies showed that insulin was associated with mortality, it should not deter insulin use in hospitalized patients requiring tight glucose control. Back and forth dilemma in the past with regards to continue/discontinue certain medications used in diabetes have been mostly resolved. The initial fears of consequences related to continuing certain medications have been largely dispelled. COVID-19 also necessitates the transformation in diabetes care through the integration of technologies. Recent advances in health-related technologies, notably telemedicine and remote continuous glucose monitoring, have become essential in the management of diabetes during the pandemic. Today, these technologies have changed the landscape of medicine and become more important than ever. Being a high-risk population, patients with type 1 or type 2 diabetes, should be prioritized for vaccination. In the future, as the pandemic fades, the prevalence of non-communicable diseases is expected to rise due to lifestyle changes and medical issues/dilemma encountered during the pandemic.

Both high and low pre-infection glucose levels associated with increased risk for severe COVID-19: New insights from a population-based study

Importance

Patients with diabetes are known to be at increased risk for infections including severe coronavirus disease 2019 (COVID-19) but the relationship between COVID-19 severity and specific pre-infection glucose levels is not known.

Objective

To assess the differential effects of pre-infection glucose levels on the risk for severe COVID-19 amongst patients with and without diabetes.

Design

Population based historical cohort study.

Setting

National state-mandated HMO.

Patients

All adult patients with a positive SARS-COV2 test between March-October 2020.

Exposure

Recent fasting blood glucose (FBG) and glycated hemoglobin (HBA1C), age, gender, body mass index (BMI) and diagnoses of diabetes, hypertension, ischemic heart disease.

Outcome

Risk for severe COVID-19, defined as resulting in ≥10 hospitalization days, ICU admission or death.

Results

37,121 patients with a positive SARS-COV2 test were identified; 707 defined as severe (1.9%). Unadjusted risk factors for severe disease were age (OR = 1.1 for every year increase; 95% CI 1.09–1.11, p < 0.001), male gender (OR = 1.34, 95% CI 1.06–1.68, p = 0.012); BMI (OR = 1.02 for 1 kg/m² increase, 95% CI 1.00–1.04, p = 0.025). Controlling for these factors, we found an association between pre-infection FBG and the risk of severe COVID-19, with a differential effect in patients with and without a diagnosis of diabetes. For patients without diabetes, elevated FBG in the pre-diabetes range (106–125 mg/dl) was associated with severe COVID-19 (OR 1.55 95% CI 1.04–2.26 p = 0.027). For patients with a diagnosis of diabetes, we found a J-shaped association between pre-infection glucose control and the risk for severe COVID-19 where the lowest risk for was for patients with FBG 106–125 mg/dl; the risk increased with higher pre-infection glucose levels but strikingly also for patients with a low pre-infection FBG (<100mg/dl) or HbA1C (<5.7%).

Conclusions and relevance

Elevated pre-infection blood glucose is a risk factor for severe COVID-19 even in non-diabetics. For patients with a diagnosis of diabetes both high as well as low pre-infection glucose levels are risk factors for severe COVID-19. Further research is required to assess whether these associations are causal, but we believe these findings can already have clinical implications for COVID-19 risk assessment and stratification.

Hyperglycemia is Associated With Increased Mortality in Critically Ill Patients With COVID-19

Objective

To explore the relationship between hyperglycemia in the presence and absence of diabetes mellitus (DM) and adverse outcomes in critically ill patients with coronavirus disease 2019 (COVID-19).

Methods

The study included 133 patients with COVID-19 admitted to an intensive care unit (ICU) at an urban academic quaternary-care center between March 10 and April 8, 2020. Patients were categorized based on the presence or absence of DM and early-onset hyperglycemia (EHG), defined as a blood glucose >180 mg/dL during the first 2 days after ICU admission. The primary outcome was 14-day all-cause in-hospital mortality; also examined were 60-day all-cause in-hospital mortality and the levels of C-reactive protein, interleukin 6, procalcitonin, and lactate.

Results

Compared to non-DM patients without EHG, non-DM patients with EHG exhibited higher adjusted hazard ratios (HRs) for mortality at 14 days (HR 7.51, CI 1.70-33.24) and 60 days (HR 6.97, CI 1.86-26.13). Non-DM patients with EHG also featured higher levels of median C-reactive protein (306.3 mg/L, P = .036), procalcitonin (1.26 ng/mL, P = .028), and lactate (2.2 mmol/L, P = .023).

Conclusion

Among critically ill COVID-19 patients, those without DM with EHG were at greatest risk of 14-day and 60-day in-hospital mortality. Our study was limited by its retrospective design and relatively small cohort. However, our results suggest the combination of elevated glucose and lactate may identify a specific cohort of individuals at high risk for mortality from COVID-19. Glucose testing and control are important in individuals with COVID-19, even those without preexisting diabetes.

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.

Admission Hyperglycemia in Non-diabetics Predicts Mortality and Disease Severity in COVID-19: a Pooled Analysis and Meta-summary of Literature

In the latter part of 2019, a cluster of unexplained pneumonia cases were reported in Wuhan, China. In less than a year, SARS-CoV-2 has infected over 27 million people and claimed more than 800,000 deaths worldwide. Diabetes is a highly prevalent chronic metabolic disease, and recent reports have suggested a possible existence of COVID-19 related new-onset diabetes. Hyperglycemia induces an inflammatory state in the body, which coupled with coronavirus associated immune response is a possible explanation for clinical worsening of patients. We present a summary and pooled analysis of available evidence to ascertain the relationship between hyperglycemia in undiagnosed diabetics and outcomes of COVID-19 disease. Our results showed that hyperglycemia in non-diabetics was associated with higher risk of severe/critical illness (OR 1.837 (95% CI 1.368–2.465, P < 0.001) and mortality (2.822, 95% CI 1.587–5.019, P < 0.001) compared with those with normal values of blood glucose. The management of hyperglycemia in COVID-19 poses significant challenges in clinical practice, and the need to develop strategies for optimal glucose control in these patients cannot be overlooked.