Severe COVID-19 in people with type 1 and type 2 diabetes in Sweden: A nationwide retrospective cohort study

Antidiabetic Medicines Utilisation During Pre-Pandemic, Pandemic and Post-Pandemic Period of COVID-19-Data for Bulgarian Population

BACKGROUND

Type 2 diabetes is a chronic disease with high global prevalence and significant social and economic burden. The pandemic affected patients' diagnostics and medicines dispensing. Diabetes was among the most-affected conditions during lockdown due to the limited resources and unaffordable medicines. The impact of the pandemic on utilisation and cost has not been thoroughly studied, which inspired us to conduct the current study.

OBJECTIVES

The study explored cost dynamics, changes in antidiabetic medicines utilisation, and public expenditure of pharmacotherapy in three periods: pre-pandemic (2018-2019), during the pandemic (2020-2021), and post-pandemic (2022-2023).

METHODS

It is a retrospective, observational, macroeconomic analysis. Reimbursed cost and utilisation were analysed as a crude sum and as indexes of the average value.

RESULTS

The result shows that five new INNs have been included in the Positive Medicines List (PML), two of these being fixed dose combinations (FDCs). During the pandemic, a slow tendency of increase of the crude sum of public expenditure was observed, followed by a sharp increase in the post-pandemic period. The public spending increased more than twice, and we found a 30,018,982 Euro growth. The highest public spending is found for dapagliflozine in post-pandemic vs. pandemic period (index = 1.67), as well as empagliflozin/metformin and dapagliflozine in pandemic vs. pre-pandemic period (index = 0.21). Total utilisation increases from 58.16 to 71.78 DDD/1000 inh/day during 2018-2023. The most significant rise of utilisation is found for canagliflozin (index = 0.68) pandemic vs. pre-pandemic and dapagliflozin (index = 3.66) post-pandemic vs. pandemic.

CONCLUSIONS

Analysis of the antidiabetic medicines market reveals the rising of reimbursed cost and utilisation in pre-, post-, and during the pandemic. In conclusion, organisation of the supply and financing of antidiabetic medicines was not affected during the pandemic.

Association of Polypharmacy and Burden of Comorbidities on COVID-19 Adverse Outcomes in People with Type 1 or Type 2 Diabetes

INTRODUCTION

It is widely accepted that the higher the number of medications prescribed and taken by an individual, the higher the risk of poor health outcomes. We have investigated whether polypharmacy and comorbidities conveyed more risk of adverse health outcomes following COVID-19 infection (as a paradigm of serious viral infections in general) in people with type 1 diabetes (T1DM) or type 2 diabetes (T2DM).

METHODS

The Greater Manchester Care Record (GMCR) is an integrated database of electronic health records containing data collected from 433 general practices in Greater Manchester. Baseline demographic information (age, body mass index [BMI], gender, ethnicity, smoking status, deprivation index), hospital admission or death within 28 days of infection were extracted for adults (18+) diagnosed with either T1DM or T2DM.

RESULTS

The study cohort included individuals diagnosed as T1DM and T2DM separately. Across the Greater Manchester Region, a total of 145,907 individuals were diagnosed with T2DM and 9705 were diagnosed with T1DM. For the T2DM individuals, 45.2% were women and for the T1DM individuals, 42.7% were women. For T2DM, 16-20 medications (p = 0.005; odds ratio [OR] [95% confidence interval (CI) 2.375 [1.306-4.319]) and > 20 medications (p < 0.001; OR [95% CI] 3.141 [1.755-5.621]) were associated with increased risk of death following COVID-19 infection. Increased risk of hospital admissions in T2DM individuals was associated with 11 to 15 medications (p = 0.013; OR = 1.341 (95% CI) [1.063-1.692]). This was independent of comorbidities, metabolic and demographic factors. For T1DM, there was no association of polypharmacy with hospital admission. Additionally, respiratory, cardiovascular/cerebrovascular and gastrointestinal conditions were associated with increased risk of hospital admissions and deaths in T2DM (p < 0.001). Many comorbidities were common across both T1DM and T2DM.

CONCLUSIONS

We have shown in T2DM an independent association of multiple medications taken from 11 upwards with adverse health consequences following COVID-19 infection. We also found that individuals with diabetes develop comorbidities that were common across both T1DM and T2DM. This study has laid the foundation for future investigations into the way that complex pharmacological interactions may influence clinical outcomes in people with T2DM.

Mathematical model for understanding the relationship between diabetes and novel coronavirus

A new model is proposed to explore interactions between diabetes and novel coronavirus. The model accounted for both the omicron variant and variants varying from omicron. The model investigated compartments such as hospitalization, diabetes, co-infection, omicron variant, and quarantine. Additionally, the impact of different vaccination doses is assessed. Sensitivity analysis is carried out to determine disease prevalence and control options, emphasizing the significance of knowing epidemics and their characteristics. The model is validated using actual data from Japan. The parameters are fitted with the help of "Least Square Curve Fitting" method to describe the dynamic behavior of the proposed model. Simulation results and theoretical findings demonstrate the dynamic behavior of novel coronavirus and diabetes mellitus (DM). Biological illustrations that illustrate impact of model parameters are evaluated. Furthermore, effect of vaccine efficacy and vaccination rates for the vaccine's first, second, and booster doses is conducted. The impact of various preventive measures, such as hospitalization rate, quarantine or self-isolation rate, vaccine dose-1, dose-2, and booster dose, is considered for diabetic individuals in contact with symptomatic or asymptomatic COVID-19 infectious people in the proposed model. The findings demonstrate the significance of vaccine doses on people with diabetes and individuals infectious with omicron variant. The proposed work helps with subsequent prevention efforts and the design of a vaccination policy to mitigate the effect of the novel coronavirus.

Risk factors associated with 30-day mortality following COVID-19 infection in patients receiving kidney replacement therapy in Australian and New Zealand

BACKGROUND AND AIMS

The COVID-19 pandemic impacted greatest among patients with pre-existing chronic health conditions, including chronic kidney disease. This retrospective cohort study aimed to investigate the 30-day mortality of patients receiving kidney replacement therapy (KRT) after infection with COVID-19, living in Australia and New Zealand between 2020 and 2022, including patients on haemodialysis (HD), peritoneal dialysis (PD) and renal transplant (KT) recipients.

METHODS

This is a retrospective cohort study using data from the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA). Patients were included if they tested positive for COVID-19 infection while receiving KRT between the first reported infection in January 2020 and the end of November 2022. Multivariable logistic regression was used to assess the relationship between KRT modality and 30-day mortality following COVID-19 infection, with all potential confounders included.

RESULTS

A total of 9828 patients requiring KRT tested positive for COVID-19 within Australia and New Zealand between 2020 and 2022. The crude mortality rate by KRT modality was 3.0% for HD, 3.8% for PD and 2.4% for KT. In the adjusted model, there was a significant increase in the odds of mortality for increasing age, diabetes, peripheral vascular disease, having ever smoked and having received dialysis for ≥5 years. Relative to HD, KT recipients had increased odds of death in 2021 and 2022 but not 2020.

CONCLUSIONS

The 30-day mortality rate following COVID-19 infection in patients requiring KRT was significantly higher than the general population, with several risk factors identified associated with increased mortality rates.

Clinico-demographic factors affecting mortality in COVID-19 patients at a health care facility, Western Uttar Pradesh

Background

Coronavirus disease 2019 (COVID-19) a global problem, has affected all aspects of health, that is, physical, social, and mental. Our study aimed to describe various social-demographic factors and existing comorbidities that affected mortality in COVID-19 admitted patients.

Materials and Methods

This was a hospital-based retrospective study. The study included medical records of COVID-19 patients admitted from April 2021 to August 2021. Data was entered in Microsoft Excel 2013 and analyzed in STATA version 18.0. The Chi-square test, unpaired t-test, and Cox proportional hazard model were employed for analysis.

Results

Of the total 1156 admitted patients, 103 hospitalized patients progressed to death (8.91%). Factors found to be significant with non-survivorship were age, residence, admission status, and coexisting comorbidities. In hazard analysis, geriatric patients had 4.358 times more hazard of death. Patients with diabetes and hypertension had two times higher hazard of death than patients without these comorbidities.

Conclusion

Mortality of patients was substantially higher in patients' ages above 60 years and patients with comorbidities. Therefore, close monitoring and priority treatment should be provided to elderly patients and patients with comorbidities.

Women Suffered More Than Men Both During and After the COVID-19 Pandemic-A Cross-Sectional Study Among 29,079 Patients With Type 2 Diabetes

OBJECTIVE

To investigate the gender differences and the disparities between infected and noninfected patients with type 2 diabetes (T2D) regarding patient-reported experiences during the COVID-19 pandemic in Norway.

METHOD

Register study using questionnaires sent electronically to patients with T2D, June 2022. The questionnaire included 82 questions covering COVID-19 disease, symptoms, medications, comorbidities, hospital care, possibility of working from home and information received from health authorities. Clinical and demographic data were collected from the Norwegian diabetes registry for adults.

RESULTS

A total of 29,079 T2D patients participated, of whom 38.1% were women. Patients infected with COVID-19 were younger, had shorter diabetes duration and less comorbidities than noninfected (p < 0.01). Women reported significantly more anxiety, depression and fear of not getting their diabetes medication than men did. Most patients were vaccinated against COVID-19 (98.3%), whereas approximately 60% had received seasonal flu vaccine, and only 27.2% the pneumococcal vaccine. Women described more vaccine adverse effects and long Covid symptoms. Overall, 14% experienced vaccine complications and 27.3% of infected individuals reported long Covid symptoms. 2.4% of the infected patients needed hospital admission. Patients were satisfied with the follow-up of their diabetes, and with information from the government during the pandemic.

CONCLUSION

Female patients were more likely to experience a prolonged Covid course, and higher degree of adverse effects from the COVID-19 vaccine than male patients. Also, long Covid symptoms were significantly more often reported among female patients, while men were more prone to be hospitalised when infected. Hospitalised patients, both men and women, had significantly higher HbA1C than those who were not hospitalised. T2D patients had a surprisingly low pneumococcal vaccination coverage, despite recommendations in national guidelines.

Comorbid burden at ICU admission in COVID-19 compared to sepsis and acute respiratory distress syndrome

BACKGROUND

Comorbidities are similarly associated with short-term mortality for COVID-19, acute respiratory distress syndrome (ARDS) and sepsis in intensive care unit (ICU) patients, but their adjusted frequencies at admission are unknown. Thus, we aimed to evaluate the adjusted distribution, reported as odds ratios, of known risk factors (i.e., age, sex and comorbidities) for ICU admission between COVID-19, sepsis and ARDS patients in this nationwide registry-based study.

METHODS

In this cohort study, we included adult patients admitted to Swedish ICUs with COVID-19 (n = 7382) during the pandemic and compared them to patients admitted to ICU with sepsis (n = 22,354) or ARDS (n = 2776) during a pre-COVID-19 period. The main outcomes were the adjusted odds for comorbidities, sex, and age in multivariable logistic regression on diagnostic categories in patients admitted to ICU, COVID-19 or sepsis and COVID-19 or ARDS.

RESULTS

We found that most comorbidities, as well as age, had a stronger association with sepsis admission than COVID-19 admission with the exception of male sex, type 2 diabetes mellitus, and asthma that were more strongly associated with COVID-19 admission, while no difference was seen for chronic renal failure and obesity. For COVID-19 and ARDS admission most risk factors were more strongly associated with ARDS admission except for male sex, type 2 diabetes mellitus, chronic renal failure, and obesity which were more strongly associated with COVID-19 admission, whereas hypertension, chronic obstructive pulmonary disease and asthma were not different.

CONCLUSIONS

Patients admitted to ICU with sepsis or ARDS carry a heavier burden of comorbidity and high age than patients admitted with COVID-19. This is likely caused by a combination of: (1) respiratory failure in COVID-19 being less dependent on comorbidities than in other forms of ARDS, and the cause of critical illness in other infections causing sepsis and (2) COVID-19 patients being deferred admission in situations where patients with the other syndromes were admitted.

Mortality and Years of Life Lost from Diabetes Mellitus in Poland: A Register-Based Study (2000-2022)

BACKGROUND

The aim of the study was to assess mortality and years of life lost from diabetes mellitus in Poland between 2000 and 2022.

METHODS

The database was created from death cards made available for the purposes of this study by Statistics Poland. The study used data on deaths caused by type 1 diabetes mellitus, T1DM (N = 33,328), and type 2 diabetes mellitus, T2DM (N = 113,706). Standardized death rates (SDRs) and standard expected years of life lost per person (SEYLLp) and per death (SEYLLd) were calculated. A time trend analysis was performed using joinpoint models. The annual percentage change (APC) and the average annual percentage change (AAPC) were estimated.

RESULTS

Between 2000 and 2022, 33,328 people died from T1DM in Poland. The SDR rate increased from 6.0 to 8.8 per 100,000 population in the analyzed period. The APC was 1.3% (p < 0.05). SEYLLp rates per 100,000 population were 79.3 in 2000 and 109.2 in 2022. SEYLLd rates were 22.9 and 17.9 years, respectively (APC = -1.0%, p < 0.05). The mean age of those who died from T1DM increased from 66.1 in 2000 to 72.5 in 2022. Between 2000 and 2022, 113,706 people died from T2DM. The SDR increased from 12.5 to 37.7 per 100,00 (APC = 5.5%, p < 0.05). SEYLLp rates were 88.8 and 296.0 per 100,000 population (APC = 6.4%, p < 0.05). SEYLLd rates decreased from 16.9 in 2000 to 13.4 in 2022 (AAPC = -1.0%, p < 0.05). The mean age of those who died from T2DM increased from 73.1 to 78.1 years.

CONCLUSIONS

The study showed a growing problem of diabetes as a cause of death and years of life lost.

Glycemic Management in Patients with COVID-19 Admitted to the Intensive Care Unit: Evaluation of Glycemic Control and Drug Therapy

Background

Emerging evidence describes the high incidence and strong impact of hyperglycemia on the outcomes of critically ill patients with a diagnosis of COVID-19. Given resource limitations during the COVID-19 pandemic, clinicians moved away from using continuous IV infusions of insulin to manage hyperglycemia.

Objective

To evaluate glycemic control in critically ill patients receiving various medication regimens to manage their hyperglycemia.

Methods

This retrospective cohort study involved 120 mechanically ventilated adult patients (> 18 years) with COVID-19 who were admitted to the intensive care unit (ICU) between February 2020 and December 2021. The following data were collected for the first 14 days of the ICU admission: blood glucose values (up to 4 times daily), hypoglycemia events, and antihyperglycemic medication regimens.

Results

The use of IV insulin infusions maintained glucose measurements within the target range of 4 to 10 mmol/L more often than any other medication regimen, with 60% of measured values falling within the target range. The use of a sliding-scale insulin regimen maintained 52% of glucose measurements within the target range. Oral hypoglycemic agents performed relatively poorly, with only 12% to 29% of glucose measurements within range. The coadministration of corticosteroids led to worse glycemic control across all medication regimens.

Conclusions

This study confirmed that ICUs should continue using the standard protocol of IV insulin infusion to achieve recommended blood glucose targets in critically ill patients with COVID-19, particularly those receiving corticosteroids.

Are we Ready for Real-Time Continuous Glucose Monitoring in the Hospital Setting? Benefits, Challenges, and Practical Approaches for Implementation : Case Vignette: Remote Real-Time Continuous Glucose Monitoring for Hospitalized Care in Quincy Koala

PURPOSE OF REVIEW

While preliminary evidence for use of real-time continuous glucose monitoring (rtCGM) in the hospital setting is encouraging, challenges with currently available devices and technology will need to be overcome as part of real-world integration. This paper reviews the current evidence and guidelines regarding use of rtCGM in the hospital and suggests a practical approach to implementation.

RECENT FINDINGS

There is now a considerable body of real-world evidence on the benefits of reducing dysglycemia in the hospital using both traditional point-of-care (POC) glucose testing and rtCGM. Benefits of rtCGM include decreased frequency of hypo- and hyperglycemia with reduced need of frequent POC checks and it is both feasible and well-accepted by nursing staff and providers. If expansion to additional sites is to be considered, practical solutions will need to be offered. Recommendations for an operational workflow and tools are described to guide implementation in the non-ICU setting. Further testing in randomized controlled trials and real-world dissemination and implementation designs is needed, together with industry and technology collaborations, to further streamline the integration into health systems.

DNAm scores for serum GDF15 and NT-proBNP levels associate with a range of traits affecting the body and brain

BACKGROUND

Plasma growth differentiation factor 15 (GDF15) and N-terminal proB-type natriuretic peptide (NT-proBNP) are cardiovascular biomarkers that associate with a range of diseases. Epigenetic scores (EpiScores) for GDF15 and NT-proBNP may provide new routes for risk stratification.

RESULTS

In the Generation Scotland cohort (N ≥ 16,963), GDF15 levels were associated with incident dementia, ischaemic stroke and type 2 diabetes, whereas NT-proBNP levels were associated with incident ischaemic heart disease, ischaemic stroke and type 2 diabetes (all PFDR < 0.05). Bayesian epigenome-wide association studies (EWAS) identified 12 and 4 DNA methylation (DNAm) CpG sites associated (Posterior Inclusion Probability [PIP] > 95%) with levels of GDF15 and NT-proBNP, respectively. EpiScores for GDF15 and NT-proBNP were trained in a subset of the population. The GDF15 EpiScore replicated protein associations with incident dementia, type 2 diabetes and ischaemic stroke in the Generation Scotland test set (hazard ratios (HR) range 1.36-1.41, PFDR < 0.05). The EpiScore for NT-proBNP replicated the protein association with type 2 diabetes, but failed to replicate an association with ischaemic stroke. EpiScores explained comparable variance in protein levels across both the Generation Scotland test set and the external LBC1936 test cohort (R2 range of 5.7-12.2%). In LBC1936, both EpiScores were associated with indicators of poorer brain health. Neither EpiScore was associated with incident dementia in the LBC1936 population.

CONCLUSIONS

EpiScores for serum levels of GDF15 and Nt-proBNP associate with body and brain health traits. These EpiScores are provided as potential tools for disease risk stratification.

Trends in diabetic ketoacidosis- and hyperosmolar hyperglycemic state-related mortality during the COVID-19 pandemic in the United States: A population-based study

BACKGROUND

During the pandemic, a notable increase in diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS), conditions that warrant emergent management, was reported. We aimed to investigate the trend of DKA- and HHS-related mortality and excess deaths during the pandemic.

METHODS

Annual age-standardized mortality rates related to DKA and HHS between 2006 and 2021 were estimated using a nationwide database. Forecast analyses based on prepandemic data were conducted to predict the mortality rates during the pandemic. Excess mortality rates were calculated by comparing the observed versus predicted mortality rates. Subgroup analyses of demographic factors were performed.

RESULTS

There were 71 575 DKA-related deaths and 8618 HHS-related deaths documented during 2006-2021. DKA, which showed a steady increase before the pandemic, demonstrated a pronounced excess mortality during the pandemic (36.91% in 2020 and 46.58% in 2021) with an annual percentage change (APC) of 29.4% (95% CI: 16.0%-44.0%). Although HHS incurred a downward trend during 2006-2019, the excess deaths in 2020 (40.60%) and 2021 (56.64%) were profound. Pediatric decedents exhibited the highest excess mortality. More than half of the excess deaths due to DKA were coronavirus disease 2019 (COVID-19) related (51.3% in 2020 and 63.4% in 2021), whereas only less than a quarter of excess deaths due to HHS were COVID-19 related. A widened racial/ethnic disparity was observed, and females exhibited higher excess mortality than males.

CONCLUSIONS

The DKA- and HHS-related excess mortality during the pandemic and relevant disparities emphasize the urgent need for targeted strategies to mitigate the escalated risk in these populations during public health crises.

Diabetes Mellitus and Pneumococcal Pneumonia

Currently, there are more than 500 million people suffering from diabetes around the world. People aged 65 years or older are the most affected by this disease, and it is estimated that approximately 96% of diabetes cases worldwide are type 2 diabetes. People with diabetes mellitus are at an increased risk of infections such as pneumonia, due to a series of factors that may contribute to immune dysfunction, including hyperglycemia, inhibition of neutrophil chemotaxis, impaired cytokine production, phagocytic cell dysfunction, altered T cell-mediated immune responses and the co-existence of chronic comorbidities. Rates of infection, hospitalization and mortality in diabetic patients are reported to be higher than in the general population. Research into the risk of infectious diseases such as pneumonia in these patients is very important because it will help improve their management and treatment.

COVID-19 Vaccination Reactions and Risk of Breakthrough Infections Among People With Diabetes: Cohort Study Derived From Community Reporters

BACKGROUND

This exploratory study compares self-reported COVID-19 vaccine side effects and breakthrough infections in people who described themselves as having diabetes with those who did not identify as having diabetes.

OBJECTIVE

The study uses person-reported data to evaluate differences in the perception of COVID-19 vaccine side effects between adults with diabetes and those who did not report having diabetes.

METHODS

This is a retrospective cohort study conducted using data provided online by adults aged 18 years and older residing in the United States. The participants who voluntarily self-enrolled between March 19, 2021, and July 16, 2022, in the IQVIA COVID-19 Active Research Experience project reported clinical and demographic information, COVID-19 vaccination, whether they had experienced any side effects, test-confirmed infections, and consented to linkage with prescription claims. No distinction was made for this study to differentiate prediabetes or type 1 and type 2 diabetes nor to verify reports of positive COVID-19 tests. Person-reported medication use was validated using pharmacy claims and a subset of the linked data was used for a sensitivity analysis of medication effects. Multivariate logistic regression was used to estimate the adjusted odds ratios of vaccine side effects or breakthrough infections by diabetic status, adjusting for age, gender, education, race, ethnicity (Hispanic or Latino), BMI, smoker, receipt of an influenza vaccine, vaccine manufacturer, and all medical conditions. Evaluations of diabetes medication-specific vaccine side effects are illustrated graphically to support the examination of the magnitude of side effect differences for various medications and combinations of medications used to manage diabetes.

RESULTS

People with diabetes (n=724) reported experiencing fewer side effects within 2 weeks of vaccination for COVID-19 than those without diabetes (n=6417; mean 2.7, SD 2.0 vs mean 3.1, SD 2.0). The adjusted risk of having a specific side effect or any side effect was lower among those with diabetes, with significant reductions in fatigue and headache but no differences in breakthrough infections over participants' maximum follow-up time. Diabetes medication use did not consistently affect the risk of specific side effects, either using self-reported medication use or using only diabetes medications that were confirmed by pharmacy health insurance claims for people who also reported having diabetes.

CONCLUSIONS

People with diabetes reported fewer vaccine side effects than participants not reporting having diabetes, with a similar risk of breakthrough infection.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04368065; https://clinicaltrials.gov/study/NCT04368065.

SARS-CoV-2 immunity in animal models

The COVID-19 pandemic, which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a worldwide health crisis due to its transmissibility. SARS-CoV-2 infection results in severe respiratory illness and can lead to significant complications in affected individuals. These complications encompass symptoms such as coughing, respiratory distress, fever, infectious shock, acute respiratory distress syndrome (ARDS), and even multiple-organ failure. Animal models serve as crucial tools for investigating pathogenic mechanisms, immune responses, immune escape mechanisms, antiviral drug development, and vaccines against SARS-CoV-2. Currently, various animal models for SARS-CoV-2 infection, such as nonhuman primates (NHPs), ferrets, hamsters, and many different mouse models, have been developed. Each model possesses distinctive features and applications. In this review, we elucidate the immune response elicited by SARS-CoV-2 infection in patients and provide an overview of the characteristics of various animal models mainly used for SARS-CoV-2 infection, as well as the corresponding immune responses and applications of these models. A comparative analysis of transcriptomic alterations in the lungs from different animal models revealed that the K18-hACE2 and mouse-adapted virus mouse models exhibited the highest similarity with the deceased COVID-19 patients. Finally, we highlighted the current gaps in related research between animal model studies and clinical investigations, underscoring lingering scientific questions that demand further clarification.

Estimating the potential impact and diagnostic requirements for SARS-CoV-2 test-and-treat programs

Oral antivirals have the potential to reduce the public health burden of COVID-19. However, now that we have exited the emergency-phase of the COVID-19 pandemic, declining SARS-CoV-2 clinical testing rates (average testing rates = [Formula: see text]10 tests/100,000 people/day in low-and-middle income countries; <100 tests/100,000 people/day in high-income countries; September 2023) make the development of effective test-and-treat programs challenging. We used an agent-based model to investigate how testing rates and strategies affect the use and effectiveness of oral antiviral test-to-treat programs in four country archetypes of different income levels and demographies. We find that in the post-emergency-phase of the pandemic, in countries where low testing rates are driven by limited testing capacity, significant population-level impact of test-and-treat programs can only be achieved by both increasing testing rates and prioritizing individuals with greater risk of severe disease. However, for all countries, significant reductions in severe cases with antivirals are only possible if testing rates were substantially increased with high willingness of people to seek testing. Comparing the potential population-level reductions in severe disease outcomes of test-to-treat programs and vaccination shows that test-and-treat strategies are likely substantially more resource intensive requiring very high levels of testing (≫100 tests/100,000 people/day) and antiviral use suggesting that vaccination should be a higher priority.

Diet-induced obesity and diabetes enhance mortality and reduce vaccine efficacy for SARS-CoV-2

IMPORTANCE

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a wide spectrum of diseases in the human population, from asymptomatic infections to death. It is important to study the host differences that may alter the pathogenesis of this virus. One clinical finding in coronavirus disease 2019 (COVID-19) patients is that people with obesity or diabetes are at increased risk of severe illness from SARS-CoV-2 infection. We used a high-fat diet model in mice to study the effects of obesity and type 2 diabetes on SARS-CoV-2 infection as well as how these comorbidities alter the response to vaccination. We find that diabetic/obese mice have increased disease after SARS-CoV-2 infection and they have slower clearance of the virus. We find that the lungs of these mice have increased neutrophils and that removing these neutrophils protects diabetic/obese mice from disease. This demonstrates why these diseases have increased risk of severe disease and suggests specific interventions upon infection.

Demographic, Clinical, and Quality of Life Profiles of Older People With Diabetes During the COVID-19 Pandemic: Cross-Sectional Study

BACKGROUND

Diabetes mellitus, one of the main diseases that affects the Brazilian population older than 60 years, is defined as a divergent group of metabolic disorders that present a high level of glycemia (hyperglycemia), causing damage to various organs and systems of the body, including the heart, kidneys, eyes, and nervous system. It is believed that in 2025, in Brazil alone, there will be more than 18.5 million individuals diagnosed with diabetes mellitus. Therefore, it is important to know the individuals' quality of life in the context of life and culture.

OBJECTIVE

This study aimed to assess the demographic, clinical, and quality of life profiles of older adults with diabetes during the COVID-19 pandemic in a university hospital complex in the northern Amazon region.

METHODS

We conducted a cross-sectional, exploratory, noninterventional, descriptive, and analytical study using a nonrandom sample of 54 older people diagnosed with diabetes mellitus at the geriatrics outpatient clinic of the medium and high complexity university hospital in the western Brazilian Amazon between 2020 and 2022. We used 3 instruments, namely, a sociodemographic questionnaire, a clinical conditions questionnaire, and Diabetes-39. Qualitative data were described using absolute and relative frequencies. The Kolmogorov-Smirnov normality test was applied, and the z test was used for inferential analysis. SPSS software (version 27) was used for data analysis, and the significance level was 5%.

RESULTS

Of the 54 interviewees, the majority were women, married, retired, and had a good quality of life. Of these, 48.1% (n=26) were infected by COVID-19, 61.5% (n=16) of whom progressed to long COVID, presenting with fatigue or muscle weakness. As for the quality of life, the "social overload" (P<.001) and "sexual functioning" (P<.001) dimensions had with low scores compared to the "energy and mobility" (P=.005), "diabetes control" (P<.001), and "anxiety and worry" (P<.001) dimensions. Quality of life was negatively impacted in the "anxiety and worry" dimension. Among those affected by COVID-19, most progressed to long COVID; however, there was a lack of data on this theme in the population of older people with diabetes.

CONCLUSIONS

The majority of interviewees progressed to long COVID, with their quality of life negatively impacted in the "anxiety and worry" dimension, reflecting that health actions prioritizing mental health should be implemented by health professionals.

Anti-SARS-CoV-2 antibody levels predict outcome in COVID-19 patients with type 2 diabetes: a prospective cohort study

Patients with type 2 diabetes (T2D) constitute one of the most vulnerable subgroups in COVID-19. Despite high vaccination rates, a correlate of protection to advise vaccination strategies for novel SARS-CoV-2 variants of concern and lower mortality in this high-risk group is still missing. It is further unclear what antibody levels provide protection and whether pre-existing organ damage affects this threshold. To address these gaps, we conducted a prospective multicenter cohort study on 1152 patients with COVID-19 from five hospitals. Patients were classified by diabetes and vaccination status. Anti-SARS-CoV-2-spike-antibodies, creatinine and NTproBNP were measured on hospital admission. Pre-specified endpoints were all-cause in-hospital-mortality, ICU admission, endotracheal intubation, and oxygen administration. Propensity score matching was applied to increase comparability. We observed significantly lower anti-SARS-CoV-2-spike-antibodies in diabetic non-survivors compared to survivors (mean, 95% CI 351BAU/ml, 106-595 vs. 1123, 968-1279, p < 0.001). Mortality risk increased two-fold with each standard deviation-decrease of antibody levels (aHR 1.988, 95% CI 1.229-3.215, p = 0.005). T2D patients requiring oxygen administration, endotracheal intubation and ICU admission had significantly lower antibody levels than those who did not (p < 0.001, p = 0.046, p = 0.011). While T2D patients had significantly worse outcomes than non-diabetic patients, the differences were less pronounced compared to propensity-score-matched non-diabetic patients. Anti-SARS-CoV-2 spike antibodies on hospital admission are inversely associated with oxygen administration, endotracheal intubation, intensive care and in-hospital mortality in diabetic COVID-19 patients. Pre-existing comorbidities may have a greater impact on outcome than diabetes status alone.

Estimating the potential impact and diagnostic requirements for SARS-CoV-2 test-and-treat programs

Oral antivirals have the potential to reduce the public health burden of COVID-19. However, now that we have exited the emergency phase of the COVID-19 pandemic, declining SARS-CoV-2 clinical testing rates (average testing rates = ≪10 tests/100,000 people/day in low- and-middle income countries; <100 tests/100,000 people/day in high-income countries; September 2023) make the development of effective test-and-treat programs challenging. We used an agent-based model to investigate how testing rates and strategies affect the use and effectiveness of oral antiviral test-to-treat programs in four country archetypes of different income levels and demographies. We find that in the post-emergency phase of the pandemic, in countries where low testing rates are driven by limited testing capacity, significant population-level impact of test-and-treat programs can only be achieved by both increasing testing rates and prioritizing individuals with greater risk of severe disease. However, for all countries, significant reductions in severe cases with antivirals are only possible if testing rates were substantially increased with high willingness of people to seek testing. Comparing the potential population-level reductions in severe disease outcomes of test-to-treat programs and vaccination shows that test-and-treat strategies are likely substantially more resource intensive requiring very high levels of testing (>>100 tests/100,000 people/day) and antiviral use suggesting that vaccination should be a higher priority.

The published trend of studies on COVID-19 and diabetes: bibliometric analysis

Background

Since the COVID-19 pandemic outbreak, diabetes mellitus (DM) has been at the core of the confirmed risk factors for fatal or critical care unit-treated COVID-19 and COVID-19 related complications. Although relevant studies on DM have developed rapidly during the COVID-19 pandemic. However, the aforementioned research results have not been systematically quantified by means of bibliometric analysis.

Purpose

The purpose of this study is to provide a comprehensive analysis of the current status and trends of publications related to DM research during the COVID19 epidemic.

Methods

A bibliometric analysis was performed using the Web of Science database. In this study, we used citespace, R software and R-Bibliometrix to analyze keywords, most-cited authors, most-cited countries, most-cited global documents, and co-occurrence and co-citation networks.

Results

A total of 1688 publications was included in this study. Investigators from the United States contributed the most publications. The United States, China and Europe have the most collaboration with the other countries/regions. A total of 3355 institutions made contributions to this study. Of the top 10 institutions with the most publications, N8 Research Partnership showed the most centrality. Among the top 10 journals, Diabetes Research and Clinical Practice published the most articles. Among authors included, Khunti Kamlesh is rated first with 27 papers and has the highest centrality. The most frequently co-cited article is entitled "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study". The most popular keywords included diabetes, mortality, diabetes, outcome, occurrences, risk, and type 1 diabetes.

Conclusion

This bibliometric study provides an overall picture of DM research and research trends during the COVID-19 pandemic and provides a basis for researchers to develop their next research strategies.

Risk and predictors of severity and mortality in patients with type 2 diabetes and COVID-19 in Dubai

BACKGROUND

Globally, patients with diabetes suffer from increased disease severity and mortality due to coronavirus disease 2019 (COVID-19). Old age, high body mass index (BMI), comorbidities, and complications of diabetes are recognized as major risk factors for infection severity and mortality.

AIM

To investigate the risk and predictors of higher severity and mortality among in-hospital patients with COVID-19 and type 2 diabetes (T2D) during the first wave of the pandemic in Dubai (March-September 2020).

METHODS

In this cross-sectional nested case-control study, a total of 1083 patients with COVID-19 were recruited. This study included 890 men and 193 women. Of these, 427 had T2D and 656 were non-diabetic. The clinical, radiographic, and laboratory data of the patients with and without T2D were compared. Independent predictors of mortality in COVID-19 non-survivors were identified in patients with and without T2D.

RESULTS

T2D patients with COVID-19 were older and had higher BMI than those without T2D. They had higher rates of comorbidities such as hypertension, ischemic heart disease, heart failure, and more life-threatening complications. All laboratory parameters of disease severity were significantly higher than in those without T2D. Therefore, these patients had a longer hospital stay and a significantly higher mortality rate. They died from COVID-19 at a rate three times higher than patients without. Most laboratory and radiographic severity indices in non-survivors were high in patients with and without T2D. In the univariate analysis of the predictors of mortality among all COVID-19 non-survivors, significant associations were identified with old age, increased white blood cell count, lym-phopenia, and elevated serum troponin levels. In multivariate analysis, only lymphopenia was identified as an independent predictor of mortality among T2D non-survivors.

CONCLUSION

Patients with COVID-19 and T2D were older with higher BMI, more comorbidities, higher disease severity indices, more severe proinflammatory state with cardiac involvement, and died from COVID-19 at three times the rate of patients without T2D. The identified mortality predictors will help healthcare workers prioritize the management of patients with COVID-19.

Diabetes, COVID-19, and questions unsolved

Recent evidence suggests a role for Diabetes Mellitus in adverse outcomes from COVID-19 infection; yet the underlying mechanisms are not clear. Moreover, attention has turned to prophylactic vaccination to protect the population from COVID-19-related illness and mortality. We performed a comprehensive peer-reviewed literature search on an array of key terms concerning diabetes and COVID-19 seeking to address the following questions: 1. What role does diabetes play as an accelerator for adverse outcomes in COVID-19?; 2. What mechanisms underlie the differences in outcomes seen in people with diabetes?; 3. Are vaccines against COVID-19 efficacious in people with diabetes? The current literature demonstrates that diabetes is associated with an increased risk of adverse outcomes from COVID-19 infection, and post-COVID sequelae. Potential mechanisms include dysregulation of Angiotensin Converting Enzyme 2, Furin, CD147, and impaired immune cell responses. Hyperglycaemia is a key exacerbator of these mechanisms. Limited studies are available on COVID-19 vaccination in people with diabetes; however, the current literature suggests that vaccination is protective against adverse outcomes for this population. In summary, people with diabetes are a high-risk group that should be prioritised in vaccination efforts. Glycaemic optimisation is paramount to protecting this group from COVID-19-associated risk. Unsolved questions remain as to the molecular mechanisms underlying the adverse outcomes seen in people with diabetes; the functional impact of post-COVID symptoms on people with diabetes, their persistence, and management; how long-term vaccine efficacy is affected by diabetes, and the antibody levels that confer protection from adverse outcomes in COVID-19.

Diet Induced Obesity and Diabetes Enhance Mortality and Reduces Vaccine Efficacy for SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of Coronavirus disease 2019 (COVID-19), emerged in Wuhan, China, in December 2019. As of October 2022, there have been over 625 million confirmed cases of COVID-19, including over 6.5 million deaths. Epidemiological studies have indicated that comorbidities of obesity and diabetes mellitus are associated with increased morbidity and mortality following SARS-CoV-2 infection. We determined how the comorbidities of obesity and diabetes affect morbidity and mortality following SARS-CoV-2 infection in unvaccinated and adjuvanted spike nanoparticle (NVX-CoV2373) vaccinated mice. We find that obese/diabetic mice infected with SARS-CoV-2 have increased morbidity and mortality compared to age matched normal mice. Mice fed a high-fat diet (HFD) then vaccinated with NVX-CoV2373 produce equivalent neutralizing antibody titers to those fed a normal diet (ND). However, the HFD mice have reduced viral clearance early in infection. Analysis of the inflammatory immune response in HFD mice demonstrates a recruitment of neutrophils that was correlated with increased mortality and reduced clearance of the virus. Depletion of neutrophils in diabetic/obese vaccinated mice reduced disease severity and protected mice from lethality. This model recapitulates the increased disease severity associated with obesity and diabetes in humans with COVID-19 and is an important comorbidity to study with increasing obesity and diabetes across the world.

Diabetes as a risk factor of death in hospitalized COVID-19 patients - an analysis of a National Hospitalization Database from Poland, 2020

Introduction

Diabetes is one of the comorbidities associated with poor prognosis in hospitalized COVID-19 patients. In this nationwide retrospective study, we evaluated the risk of in-hospital death attributed to diabetes.

Methods

We analyzed data from discharge reports of patients hospitalized with COVID-19 in 2020 as submitted to the Polish National Health Fund. Several multivariate logistic regression models were used. In each model, in-hospital death was estimated with explanatory variables. Models were built either on the whole cohorts or cohorts matched with propensity score matching (PSM). The models examined either the main effects of diabetes itself or the interaction of diabetes with other variables.

Results

We included 174,621 patients with COVID-19 who were hospitalized in the year 2020. Among them, there were 40,168 diabetic patients (DPs), and the proportion of DPs in this group was higher than in the general population (23.0% vs. 9.5%, p<0.001). In this group of COVID-19 hospitalizations, 17,438 in-hospital deaths were recorded, and the mortality was higher among DPs than non-diabetics (16.3% vs. 8.1%, p<0.001). Multivariate logistic regressions showed that diabetes was a risk factor of death, regardless of sex and age. In the main effect analysis, odds of in-hospital death were higher by 28.3% for DPs than for non-diabetic patients. Similarly, PSM analysis including 101,578 patients, of whom 19,050 had diabetes, showed that the risk of death was higher in DPs regardless of sex with odds higher by 34.9%. The impact of diabetes differed among age groups and was the highest for patients aged 60-69.

Conclusions

This nationwide study confirmed that diabetes was an independent risk factor of in-hospital death in the course of COVID-19 infection. However, the relative risk differed across the age groups.

History of heart failure and chronic kidney disease and risk of all-cause death after COVID-19 during the first three waves of the pandemic in comparison with influenza outbreaks in Sweden: a registry-based, retrospective, case-control study

OBJECTIVES

To explore how cardiorenal disease (CRD; heart failure and/or chronic kidney disease) impacted mortality in men and women hospitalised for COVID-19 during the first three waves of the pandemic in Sweden in comparison to previous influenza outbreaks.

DESIGN

A registry-based, retrospective, case-control study.

SETTING

Hospital care in Sweden.

PARTICIPANTS

All patients in Sweden with a main hospital diagnosis of COVID-19 (January 2020-September 2021) or influenza (January 2015-December 2019) with previous CRD were identified in registries and compared with a reference group free from CRD but with COVID-19 or influenza.

PRIMARY OUTCOME MEASURE

Associated risk of all-cause death during the first year was analysed using adjusted Cox proportional hazards models.

RESULTS

In COVID-19 patients with and without prior history of CRD (n=44 866), mean age was 79.8 years (SD 11.8) and 43% were women. In influenza patients (n=8897), mean age was 80.6 years (SD 11.5) and 45% were women. COVID-19 versus influenza was associated with higher mortality risk during the first two COVID-19 waves (HR 1.53; 95% CI 1.45 to 1.62, p<0.001 and HR 1.52; 95% CI 1.44 to 1.61, p<0.001), but not in the third wave (HR 1.07; 95% CI 0.99 to 1.14, p=0.072). CRD was an independent risk factor for all-cause death after COVID-19 in men and women (men: 1.37; 95% CI 1.31 to 1.44, p<0.001; women: 1.46; 95% CI 1.38 to 1.54, p<0.001). At ages <70 years, women with CRD had a similar mortality rate to men with CRD, while at ages ≥70 years, the mortality rate was higher in men.

CONCLUSIONS

Outcome after COVID-19 is worse if CRD is present. In women at ages <70 years, the presence of CRD attenuates the protective effect of female sex. COVID-19 was associated with higher mortality risk than influenza during the first two pandemic waves.

Risk factors for severe COVID-19 in the young-before and after ICU admission

BACKGROUND

Factors associated with severe COVID-19 and death among young adults are not fully understood, including differences between the sexes. The aim of this study was to identify factors associated with severe COVID-19 requiring intensive care and 90-day mortality among women and men below 50 years of age.

METHODS

A register-based study using data from mandatory national registers, where patients with severe COVID-19 admitted to the ICU with need for mechanical ventilation (cases) between March 2020 and June 2021 were matched regarding age, sex, and district of residence with 10 population-based controls. Both the study population and the controls were divided into groups based on age (< 50 years, 50-64, and ≥ 65 years) and sex. Multivariate logistic regression models including socioeconomic factors were used to calculate odds ratios (OR) with 95% confidence intervals (CIs) for associations between severe COVID-19 in the population to compare the magnitude of the risk associations for co-morbidities in the different age categories, and subsequently factors associated with 90-day mortality among patients admitted to ICU.

RESULTS

In total, 4921 cases and 49,210 controls (median age 63 years, 71% men) were included. The co-morbidities with the strongest associations with severe COVID-19 for the young population compared to older patients were chronic kidney disease (OR 6.80 [3.61-12.83]), type 2 diabetes (OR 6.31 [4.48-8.88]), hypertension (OR 5.09 [3.79-6.84]), rheumatoid arthritis (OR 4.76 [2.29-9.89]), obesity (OR 3.76 [2.88-4.92]), heart failure (OR 3.06 [1.36-6.89]), and asthma (OR 3.04 [2.22-4.16]). When comparing women vs. men < 50 years of age, stronger associations were seen for women regarding type 2 diabetes (OR 11.25 [6.00-21.08] vs OR 4.97 [3.25-7.60]) and hypertension (OR 8.76 [5.10-15.01] vs OR 4.09 [2.86-5.86]). The factors associated with 90-day mortality in the young were previous venous thromboembolism (OR 5.50 [2.13-14.22]), chronic kidney disease (OR 4.40 [1.64-11.78]) and type 2 diabetes (OR 2.71 [1.39-5.29]). These associations with 90-day mortality were foremost driven by the female population.

CONCLUSION

Chronic kidney failure, type 2 diabetes, hypertension, rheumatoid arthritis, obesity, heart failure, and asthma were the strongest risk factors associated with severe COVID-19 requiring ICU-care in individuals < 50 years compared to the older population. However, after ICU admission, previous thromboembolism, chronic kidney failure, and type 2 diabetes were associated with increased 90-day mortality. The risk associations for co-morbidities were generally stronger among younger individuals compared to older and in women compared to men.

Cohort profile: a longitudinal regional cohort study to assess COVID-19 seroprevalence in blood donors - baseline characteristics of the SeMaCo study participants

PURPOSE

The SeMaCo study (Serologische Untersuchungen bei Blutspendern des Großraums Magdeburg auf Antikörper gegen SARS-CoV-2), a prospective, longitudinal cohort study with four survey phases spanning 3-5 months each over a period of 22 months, extends the spectrum of seroepidemiological studies in Germany. We present here a careful characterisation of the initial survey phase of the cohort to provide baseline data on infection incidence and obtained from questionnaires, focussing in particular on the attitude towards COVID-19 vaccinations, the vaccination success and the vaccination acceptance.

PARTICIPANTS

A total of 2195 individual blood donors from the donor pool of the blood donation service of the University Hospital Magdeburg were enrolled in the initial survey phase from 20 January 2021 to 30 April 2021. 2138 participants gave sociodemographic/contact data (51.7% male, mean age 44 years) and 2082 participants answered the vaccination questionnaire.

FINDINGS TO DATE

Out of 2195 participants with antibody results, 1909 (87.0%) were antibody negative. The remaining 286 subjects (13.0%) were either antibody-positive and vaccinated (160/286; 55.9%) or antibody-positive without vaccination information (17/286; 5.9%) or antibody-positive and unvaccinated (109/286; 38.1%). The latter result reflects the rate of true or highly probable SARS-CoV-2 infections in our initial study cohort.

FUTURE PLANS

The study primarily aims to measure the prevalence and long-term kinetics of IgG-antibodies against SARS-CoV-2. Including the baseline, the study foresees four survey periods of 3-4 months each. At each visit, we will assess the blood donors' attitude towards vaccination, the antibody response following vaccination and/or infection, as well as undesired vaccination effects. We aim to test the same participants during the survey periods by repeated invitations for blood donation to ensure a long-term (follow-up) in as many study participants as possible. After the four survey phases, a longitudinal data set will be created that reflects the course of the antibody levels/frequencies as well as the infection and vaccination incidence.

TRIAL REGISTRATION NUMBER

DRKS00023263.

Severe COVID-19 Infection in Type 1 and Type 2 Diabetes During the First Three Waves in Sweden

OBJECTIVE

Type 2 diabetes is an established risk factor for hospitalization and death in COVID-19 infection, while findings with respect to type 1 diabetes have been diverging.

RESEARCH DESIGN AND METHODS

Using nationwide health registries, we identified all patients aged ≥18 years with type 1 and type 2 diabetes in Sweden. Odds ratios (ORs) describe the general and age-specific risk of being hospitalized, need for intensive care, or dying, adjusted for age, socioeconomic factors, and coexisting conditions, compared with individuals without diabetes. Machine learning models were used to find predictors of outcomes among individuals with diabetes positive for COVID-19.

RESULTS

Until 30 June 2021, we identified 365 (0.71%) and 11,684 (2.31%) hospitalizations in 51,402 and 504,337 patients with type 1 and 2 diabetes, respectively, with 67 (0.13%) and 2,848 (0.56%) requiring intensive care unit (ICU) care and 68 (0.13%) and 4,020 (0.80%) dying (vs 7,824,181 individuals without diabetes [41,810 hospitalizations (0.53%), 8,753 (0.11%) needing ICU care, and 10,160 (0.13%) deaths). Although those with type 1 diabetes had moderately raised odds of being hospitalized (multiple-adjusted OR 1.38 [95% CI 1.24-1.53]), there was no independent effect on ICU care or death (OR of 1.21 [95% CI 0.94-1.52] and 1.13 [95% CI 0.88-1.48], respectively). Age and socioeconomic factors were the dominating features for predicting hospitalization and death in both types of diabetes.

CONCLUSIONS

Type 2 diabetes was associated with increased odds for all outcomes, whereas patients with type 1 diabetes had moderately increased odds of hospitalization but not ICU care and death.

Clinical determinants of oxygen saturation and length of hospitalisation of COVID-19 patients: A cross-sectional study in Indonesia

Aims

Indonesia was one of the countries with the highest COVID-19 positive cases. Understanding the length of hospitalisation is critical for anticipating bed demand and resource allocation, such as oxygen. This study aims to examine the determinants of oxygen saturation and the length of hospitalisation in Hermina Mekarsari Hospital, West Java, Indonesia.

Methods

This cross-sectional study uses medical records from June to August 2021. The inclusion criteria were: COVID-19 patients aged between18 and 65, fully conscious, and not using mechanical ventilation. Participants who passed away during hospital stay were excluded. We used demographic information, laboratory data, and the clinician's assessments of the patients admitted to the hospital. Linear regression was performed for oxygen saturation on day seven, while logistic regression analysis was conducted to predict the length of hospital stay.

Results

In total, 371 participants with an average age of 47.2 (standard deviation 15.8) years were included. Most participants were female (57.7%) and smoking (78.4%). The results indicated that decreasing oxygen saturation was reported in vomiting patients (β = 1.63, p-value = .001), hypertensive patients (β 1.18 with, p-value = .034), and patients with the increased respiratory rate (β = 0.28, p-value = .000). In the logistic regression, we found that respondents who experienced dyspnoea, headache, fever, an increasing number of D-Dimer and blood glucose, and those with diabetes mellitus were more likely to stay more than 14 days.

Conclusions

Oxygen saturation was influenced by vomiting, hypertension, and increasing respiratory rate. Length of hospitalisation of more than 14 days was influenced by dyspnoea, headache, fever, increased number of D-Dimer, blood glucose, and diabetes mellitus. Identifying the determinants of oxygen saturation and length of stay can inform health professionals in designing a suitable intervention to reduce mortality and length of stay among COVID-19 patients in Indonesia.

Severity Status of COVID-19 and Its Associated Factors at the Nyarugenge Treatment Center in Rwanda

Background The COVID-19 pandemic has continued to be a public health emergency currently; on March 11, 2020, the World Health Organization (WHO) declared it a global pandemic. Despite the Rwanda National Health Measures that have been put in place to protect the public including lockdowns, curfew, face mask mandate, handwashing sensitization, etc., severe morbidity and mortality cases of COVID-19 are continued to be seen. Some studies have linked COVID-19 complications to its direct chain of mechanism; however, other studies have linked comorbidity or underlying disease conditions to its poor prognosis. Studies have not yet been conducted in Rwanda on the severe status of COVID-19 and its associated factors among patients. Therefore, this study aimed to assess the severe status of COVID-19 and its associated factors at the Nyarugenge Treatment Center. Methods A descriptive cross-sectional study was done. All patients admitted to the Nyarugenge Treatment Center from January 8, 2021, when the hospital opened, until the end of May 2021 were recruited in the study. The eligible participants were all patients who were admitted and tested positive for COVID-19 by RT-PCR method according to the Rwanda Ministry of Health criteria. Results All data were analyzed using the Statistical Package for the Social Sciences (SPSS) software, version 25 (IBM Corp., Armonk, NY). The number of patients admitted during the study period was 648, with a median age of 53; 45.2% of them were females, and 54.2% were males. Of these, 81.2% (526) were discharged from the hospital, while 18.8% (122) died. The proportion of severe status of COVID-19 was 42.1%. The factors that showed a risk of severe COVID-19 status were age and the number of comorbidities. Patients aged above 60 years (OR = 11.7, 95% CI: 5.35-25.67, p-value < 0.001) and those between the age of 51 and 60 (OR = 6.86, 95% CI: 2.96-15.93, p-value < 0.001) were 12 and seven times more likely to have severe COVID-19 status compared to those aged below 30 years. Having two comorbidities had twice the risk of developing a severe COVID-19 status compared to those with no comorbidity (OR = 2.13, 95% CI: 1.20-3.77, p-value < 0.001). Conclusion Elderly people and those with comorbidities are encouraged to obtain all standard operating procedures and comply with the vaccination program.

Antidiabetic Treatment before Hospitalization and Admission Parameters in Patients with Type 2 Diabetes, Obesity, and SARS-CoV-2 Viral Infection

BACKGROUND

SARS-CoV-2 viral infection is a current and important topic for patients with comorbidities of type 2 diabetes and obesity, associated with increased risk of mortality and morbidity. This study aims to analyze, compare and describe admission parameters in patients with type 2 diabetes, obesity, and SARS-CoV-2 infection based on whether they received insulin therapy before hospital admission.

METHODS

Our study enrolled patients diagnosed with type 2 diabetes, obesity, and SARS-CoV-2 viral infection, 81 patients without insulin treatment before hospital admission, and 81 patients with insulin at "Gavril Curteanu" Municipal Clinical Hospital of Oradea, Romania, between August 2020 and March 2022. RT-PCR/rapid antigen tests were used for detecting SARS-CoV-2 viral infection.

RESULTS

The severe form of COVID-19 was found in 66% of all patients (65% in the group without insulin and 67% in the group with insulin). Oxygen saturation at the time of hospital admission was greater or equal to 90% in 62% of all patients. The most associated comorbidities we founded in this study were: hypertension in 75% of all patients (grade two hypertension 63% in the group without insulin and 64% in the group with insulin), ischemic heart disease in 35% of patients (25% in the group without insulin and 44% in the group with insulin, n = 0.008), heart failure in 9.3% of all patients (8.6% in the group without insulin and 10% in the group with insulin). CRP and procalcitonin are increased in both groups at hospital admission, with a slightly higher trend in the group with insulin therapy before hospital admission. We found that 56% of patients in the group with insulin treatment were with uncontrolled diabetes on admission. Only 10% of patients required a change in antidiabetic treatment with insulin therapy at discharge. In our study, 89% of all patients did not require short-term home oxygen therapy at discharge.

CONCLUSIONS

Antidiabetic therapy taken before hospital admission did not protect patients against cytokine storm in COVID-19, but is very important in the pathophysiological stage of comorbidities. Paraclinical parameters at hospitalization showed differences in correlation with oral antidiabetic treatment like metformin or insulin therapy. Changing the antidiabetic treatment for a small percentage of patients in the group who had not been receiving insulin therapy before discharge was necessary. It is necessary for future studies to see all changes involved in antidiabetic treatment in patients with diabetes type 2 and obesity after SARS-CoV2 viral infection and its long-term evolution.

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.

Diabetes and the COVID-19 pandemic

Almost immediately after the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus emerged, it was evident that people with chronic diseases, including diabetes, were disproportionately affected, with an increased risk of hospitalisation and mortality. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery in the short term have become prominent, along with the lingering effects of the virus in those directly infected. In the wake of the pandemic and without any evidence from high quality studies, a number of national and international consensus recommendations were published, which were subsequently rapidly updated based on observational studies. There have been unprecedented disruptions from both direct and indirect impacts of coronavirus disease-2019 (COVID-19) in people with diabetes. In this review, we summarise the impact of acute COVID-19 in people with diabetes, discuss how the presentation and epidemiology during the pandemic, including presentation of diabetic ketoacidosis and new-onset diabetes, has changed, and we consider the wider impact of the pandemic on patients and healthcare service delivery, including some of the areas of uncertainty. Finally, we make recommendations on prioritising patients as we move into the recovery phase and also how we protect people with diabetes for the future, as COVID-19 is likely to become endemic.

Comorbidities, multimorbidity and COVID-19

The influence of comorbidities on COVID-19 outcomes has been recognized since the earliest days of the pandemic. But establishing causality and determining underlying mechanisms and clinical implications has been challenging-owing to the multitude of confounding factors and patient variability. Several distinct pathological mechanisms, not active in every patient, determine health outcomes in the three different phases of COVID-19-from the initial viral replication phase to inflammatory lung injury and post-acute sequelae. Specific comorbidities (and overall multimorbidity) can either exacerbate these pathological mechanisms or reduce the patient's tolerance to organ injury. In this Review, we consider the impact of specific comorbidities, and overall multimorbidity, on the three mechanistically distinct phases of COVID-19, and we discuss the utility of host genetics as a route to causal inference by eliminating many sources of confounding. Continued research into the mechanisms of disease-state interactions will be crucial to inform stratification of therapeutic approaches and improve outcomes for patients.

Patients with type 1 and type 2 diabetes hospitalized with COVID-19 in comparison with influenza: mortality and cardiorenal complications assessed by nationwide Swedish registry data

BACKGROUND

The risk of severe coronavirus disease 2019 (COVID-19) is increased in people with diabetes, but effects of diabetes type and other risk factors remain incompletely characterized. We studied this in a Swedish cohort of hospitalized patients with type 1 and type 2 diabetes (T1D and T2D), also including comparisons with influenza epidemics of recent years.

METHODS

Nationwide healthcare registries were used to identify patients. A total of 11,005 adult patients with diabetes (T1D, n = 373; T2D, n = 10,632) were hospitalized due to COVID-19 from January 1, 2020 to September 1, 2021. Moreover, 5111 patients with diabetes (304 T1D, 4807 T2D) were hospitalized due to influenza from January 1, 2015 to December 31, 2019. Main outcomes were death within 28 days after admission and new hospitalizations for heart failure (HF), chronic kidney disease (CKD), cardiorenal disease (CRD; composite of HF and CKD), myocardial infarction (MI) and stroke during 1 year of follow-up.

RESULTS

Number of deaths and CRD events were 2025 and 442 with COVID-19 and 259 and 525 with influenza, respectively. Age- and sex-adjusted Cox regression models in COVID-19 showed higher risk of death and HF in T1D vs. T2D, hazard ratio (HR) 1.77 (95% confidence interval 1.41-2.22) and 2.57 (1.31-5.05). With influenza, T1D was associated with higher risk of death compared with T2D, HR 1.80 (1.26-2.57). Older age and previous CRD were associated with higher risks of death and hospitalization for CRD. After adjustment for prior comorbidities, mortality differences were still significant, but there were no significant differences in cardiovascular and renal outcomes. COVID-19 relative to influenza was associated with higher risk of death in both T1D and T2D, HR 2.44 (1.60-3.72) and 2.81 (2.59-3.06), respectively.

CONCLUSIONS

In Sweden, patients with T1D as compared to T2D had a higher age- and sex-adjusted risk of death within 28 days and HF within one year after COVID-19 hospitalization, whereas the risks of other non-fatal cardiovascular and renal disease events were similar. Patients with T1D as well as T2D have a greater mortality rate when hospitalized due to COVID-19 compared to influenza, underscoring the importance of vaccination and other preventive measures against COVID-19 for diabetes patients.

Analysis of risk factors for COVID-19-related fatal outcome in 337991 patients with type 1 and type 2 diabetes mellitus in 2020–2022 years: Russian nationwide retrospective study

BACKGROUND: The coronavirus pandemic has had an extremely negative impact on the patients with diabetes mellitus (DM both in terms of a more severe course of COVID -19 and an increased risk of death.

AIM: Analysis of risk factors for death due to COVID -19 in patients with DM type 1 and type 2 (DM1 and DM2).

MATERIALS AND METHODS: Retrospective analysis of the database of the national diabetes register (NDR), which included DM patients with COVID-19 and reported virus infection outcome (recovery/or death) in 15 712 DM1 and 322 279 DM2 patients during a 2-year follow-up period (01/02/2020 to 03/04/2022) (discharge date)).

RESULTS: Case fatality rate in patients with DM, who underwent COVID -19 was 17.1% (DM1–8.8%; DM2–17.5%). As a result of multivariate regression analysis of seven significant factors in DM1 and thirteen in DM2 (evaluated by univariate anlisys), a number of the most important predictors of risk for fatal outcome were identified: in DM1 these were age ≥65 years (OR =4.01, 95% CI: 1.42–11.36), presence of arterial hypertension (AH) (OR =2.72, 95% CI: 1.03 -7.16) and diabetic foot syndrome (DFS) (OR = 7.22, 95% CI: 1.98–26.29); for T2DM: age ≥ 65 years (OR =2.53, 95% CI: 1.96–3.27), male (OR =1.51, 95% CI: 1.23–1.84), duration DM ≥10 years (OR =2.01, 95% CI: 1.61–2.51), BMI ≥ 30 kg/m2 (OR =1.26, 95% CI: 1.02–1.55), ASCVD/CKD (OR =1.49, 95% CI: 1.01–2.04), history of diabetic coma (OR =12.97, 95% CI: 1.89–88.99) and presence of disability ( OR =1.40, 95% CI: 1.14–1.73). In T2DM, the type of antidiabetic therapy (ADT) prior to COVID -19 (last visit before the development of infection) had a significant impact: Insulin therapy (OR = 1.64, 95% CI: 1.30–2.07), sulfonylureas (SU) (OR =1.51, 95% CI: 1.23–1.84)); dipeptidyl peptidase-4 inhibitor (iDPP-4) therapy (OR =0.57, 95% CI: 0.39–0.83) and sodium-glucose cotransporter-2 inhibitor (iSGLT2) therapy (OR =0.64, 95% CI: 0.46–0.88). Vaccination was the most important protective factor in both types of DM: DM1 OR =0.19, 95% CI: 0.06–0.59; SD2 OR =0.20, 95% CI: 0.16–0.26.

CONCLUSION: The common risk factor for fatal outcome in both DM1 and DM2 was age ≥65 years; in DM1 — history of hypertension and DFS, in DM2 — male sex, diabetes duration ≥10 years, BMI ≥30 kg/m2, history of ASCVD/CKD and diabetic coma, disability. In T2DM, significant differences in risk were observed depending on the type of ADT: insulin and SU therapy were factors that increased the risk of death, whereas therapy with iDPP-4 and iSGLT2 reduced the risk of death. Vaccination reduced the risk of death in DM1 and DM2 by 5.2 and 5-fold, respectively.

Cardiometabolic Risk after SARS-CoV-2 Virus Infection: A Retrospective Exploratory Analysis

OBJECTIVE

The aim of this study is to characterize the cardiometabolic risk of individuals who were infected with the SARS-CoV-2 virus and subsequently admitted to a hospital in a major city in mainland Portugal.

METHODS

This is a retrospective exploratory study using a sample of 102 patients, with data analysis including descriptive statistics, nonparametric measures of association between variables based on Spearman's rank-order correlation, a logistic regression model for predicting the likelihood that an individual might eventually pass away, and a multiple linear regression model to predict a likely increase in the number of days an infected patient remained in the hospital.

RESULTS

About 62.7% of the individuals required intensive care on the second day of hospitalization, remaining 14.2 days in the intensive care unit (ICU) on average. The likelihood that an individual might eventually pass away due to SARS-CoV-2 virus infection increases for the older than younger ones and increases even more if he/she suffers from cardiometabolic disorders such as obesity, especially cardiovascular disease. Older individuals and those with obesity and hypertension remained more days in the ICU.

CONCLUSIONS

A later age and the prevalence of cardiometabolic disorders severely affect the care pathway of individuals infected with the SARS-CoV-2 virus.

Obesity and metabolic dysfunction drive sex-associated differential disease profiles in hACE2-mice challenged with SARS-CoV-2

Severe outcomes from SARS-CoV-2 infection are highly associated with preexisting comorbid conditions like hypertension, diabetes, and obesity. We utilized the diet-induced obesity (DIO) model of metabolic dysfunction in K18-hACE2 transgenic mice to model obesity as a COVID-19 comorbidity. Female DIO, but not male DIO mice challenged with SARS-CoV-2 were observed to have shortened time to morbidity compared to controls. Increased susceptibility to SARS-CoV-2 in female DIO was associated with increased viral RNA burden and interferon production compared to males. Transcriptomic analysis of the lungs from all mouse cohorts revealed sex- and DIO-associated differential gene expression profiles. Male DIO mice after challenge had decreased expression of antibody-related genes compared to controls, suggesting antibody producing cell localization in the lung. Collectively, this study establishes a preclinical comorbidity model of COVID-19 in mice where we observed sex- and diet-specific responses that begin explaining the effects of obesity and metabolic disease on COVID-19 pathology.

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Transcriptomic analysis of infected lungs revealed unique sex-dependent differences

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Obese female mice have high viral RNA burden and interferon production in the lung

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Male mice have altered antibody and T cell response gene profiles after viral challenge

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Metabolic dysfunction comorbidity can be studied in the hACE2 mouse model of COVID-19

Diabetes and COVID-19 testing, positivity, and mortality: A population-wide study in Northern Italy

AIMS

To assess if patients with type 2 diabetes mellitus (DM2) are: a) at excess risk of undergoing testing, contracting, and dying from SARS-CoV-2 infection compared to the general population; b) whether cardiovascular diseases (CAVDs) contribute to COVID-19-related death; and c) what is the effect of DM2 duration and control on COVID-19-related death.

METHODS

This population-based study involved all 449,440 adult residents of the Reggio Emilia province, Italy. DM2 patients were divided in groups by COVID testing, presence of CAVDs and COVID death. Several mediation analyses were performed.

RESULTS

Patients with DM2 had an increased likelihood of being tested (Odds ratio, OR 1.27 95 %CI 1.23-1.30), testing positive (OR 1.21 95 %CI 1.16-1.26) and dying from COVID-19 (OR 1.75 95 %CI 1.54-2.00). COVID-19-related death was almost three times higher among obese vs non-obese patients with DM2 (OR 4.3 vs 1.6, respectively). For COVID-19 death, CAVDs mediated a) just 5.1 % of the total effect of DM2, b) 40 % of the effect of DM2 duration, and c) did not mediate the effect of glycemic control.

CONCLUSIONS

For COVID-19-related deaths in DM2 patients, the effect is mostly direct, obesity amplifies it, DM2 control and duration are important predictors, while CAVDs only slightly mediates it.

The burden and risks of emerging complications of diabetes mellitus

The traditional complications of diabetes mellitus are well known and continue to pose a considerable burden on millions of people living with diabetes mellitus. However, advances in the management of diabetes mellitus and, consequently, longer life expectancies, have resulted in the emergence of evidence of the existence of a different set of lesser-acknowledged diabetes mellitus complications. With declining mortality from vascular disease, which once accounted for more than 50% of deaths amongst people with diabetes mellitus, cancer and dementia now comprise the leading causes of death in people with diabetes mellitus in some countries or regions. Additionally, studies have demonstrated notable links between diabetes mellitus and a broad range of comorbidities, including cognitive decline, functional disability, affective disorders, obstructive sleep apnoea and liver disease, and have refined our understanding of the association between diabetes mellitus and infection. However, no published review currently synthesizes this evidence to provide an in-depth discussion of the burden and risks of these emerging complications. This Review summarizes information from systematic reviews and major cohort studies regarding emerging complications of type 1 and type 2 diabetes mellitus to identify and quantify associations, highlight gaps and discrepancies in the evidence, and consider implications for the future management of diabetes mellitus.

Prognosis of COVID-19 in the middle eastern population, knowns and unknowns

Since its emergence in China in 2019, the SARS-CoV-2 virus has affected all countries worldwide. The virus is easily transmitted from one person to another via infected aerosols or contaminated surfaces. Unlike its counterparts, the prognosis of COVID-19 ranges from asymptomatic to critical disease or death. Several factors play a role in determining the severity of the disease in infected patients. Among others, is the pre-existence of an underlying medical condition such as diabetes, cancer, and others. Furthermore, although children are less prone to the severe form of the COVID-19 disease, they require attention due to the report of many atypical presentations of the infection, post-asymptomatic exposure. In the Middle East, little is known about the prognosis of the SARS-CoV-2 infection in high-risk categories, notably patients with diabetes, cancer, and pregnant women. The aim of this review is to summarize the current knowledge about this group of population in the middle eastern region as well as to highlight the gap in the literature. We have found that the majority of the papers were from the Gulf countries. Although, few studies were conducted; high-risk patients appear to have an increased risk of morbidity and mortality from COVID-19 compared to their counterparts. Higher levels of inflammatory markers, C-reactive protein, erythrocyte sedimentation rate, D-dimer, and ferritin levels were also observed. Children are often asymptomatic or present with atypical presentations. More studies should be conducted to determine the clinical biomarkers of COVID-19 in high-risk categories to help in patient risk stratification and management in the middle eastern population.

Recent Progress in the Diagnosis and Management of Type 2 Diabetes Mellitus in the Era of COVID-19 and Single Cell Multi-Omics Technologies

Type 2 diabetes mellitus (T2DM) is one of the world's leading causes of death and life-threatening conditions. Therefore, we review the complex vicious circle of causes responsible for T2DM and risk factors such as the western diet, obesity, genetic predisposition, environmental factors, and SARS-CoV-2 infection. The prevalence and economic burden of T2DM on societal and healthcare systems are dissected. Recent progress on the diagnosis and clinical management of T2DM, including both non-pharmacological and latest pharmacological treatment regimens, are summarized. The treatment of T2DM is becoming more complex as new medications are approved. This review is focused on the non-insulin treatments of T2DM to reach optimal therapy beyond glycemic management. We review experimental and clinical findings of SARS-CoV-2 risks that are attributable to T2DM patients. Finally, we shed light on the recent single-cell-based technologies and multi-omics approaches that have reached breakthroughs in the understanding of the pathomechanism of T2DM.

A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients

Introduction

Identifying COVID-19 patients that are most likely to progress to a severe infection is crucial for optimizing care management and increasing the likelihood of survival. This study presents a machine learning model that predicts severe cases of COVID-19, defined as the presence of Acute Respiratory Distress Syndrome (ARDS) and highlights the different risk factors that play a significant role in disease progression.

Methods

A cohort composed of 289,351 patients diagnosed with COVID-19 in April 2020 was created using US administrative claims data from Oct 2015 to Jul 2020. For each patient, information about 817 diagnoses, were collected from the medical history ahead of COVID-19 infection. The primary outcome of the study was the presence of ARDS in the 4 months following COVID-19 infection. The study cohort was randomly split into training set used for model development, test set for model evaluation and validation set for real-world performance estimation.

Results

We analyzed three machine learning classifiers to predict the presence of ARDS. Among the algorithms considered, a Gradient Boosting Decision Tree had the highest performance with an AUC of 0.695 (95% CI, 0.679–0.709) and an AUPRC of 0.0730 (95% CI, 0.0676 – 0.0823), showing a 40% performance increase in performance against a baseline classifier. A panel of five clinicians was also used to compare the predictive ability of the model to that of clinical experts. The comparison indicated that our model is on par or outperforms predictions made by the clinicians, both in terms of precision and recall.

Conclusion

This study presents a machine learning model that uses patient claims history to predict ARDS. The risk factors used by the model to perform its predictions have been extensively linked to the severity of the COVID-19 in the specialized literature. The most contributing diagnosis can be easily retrieved in the patient clinical history and can be used for an early screening of infected patients. Overall, the proposed model could be a promising tool to deploy in a healthcare setting to facilitate and optimize the care of COVID-19 patients.

Challenges in hyperglycemia management in critically ill patients with COVID-19

Hyperglycemia is commonly associated with adverse outcomes especially in patients requiring intensive care unit stay. Data from the corona virus disease 2019 (COVID-19) pandemic indicates that individuals with diabetes appear to be at similar risk for COVID-19 infection to those without diabetes but are more likely to experience increased morbidity and mortality. The proposed hypothesis for hyperglycemia in COVID-19 include insulin resistance, critical illness hyperglycemia (stress- induced hyperglycemia) secondary to high levels of hormones like cortisol and catecholamines that counteract insulin action, acute cytokine storm and pancreatic cell dysfunction. Diabetic patients are more likely to have severe hyperglycemic complications including diabetic ketoacidosis and hyperosmolar hyperglycemic state. Management of hyperglycemia in COVID-19 is often complicated by use of steroids, prolonged total parenteral or enteral nutrition, frequent acute hyperglycemic events, and restrictions with fluid management due to acute respiratory distress syndrome. While managing hyperglycemia special attention should be paid to mode of insulin delivery, frequency of glucose monitoring based on patient and caregiver safety thereby minimizing exposure and conserving personal protective equipment. In this article we describe the pathophysiology of hyperglycemia, challenges encountered in managing hyperglycemia, and review some potential solutions to address them.