Factors Behind the Higher COVID-19 Risk in Diabetes: A Critical Review

Effects of COVID-19 Status on Hip Fracture Surgical Outcomes: An ACS NSQIP Study

BACKGROUND

Studies have indicated that patients infected with the SARS-CoV-2 virus fare worse clinically after a traumatic injury, especially those who are older and have other comorbidities.

OBJECTIVE

This study aims to understand the effects of Corona Virus Disease 19 (COVID-19) diagnosis on patients undergoing surgery for hip fractures.

METHODS

This is a retrospective review of the 2021 American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) Targeted Hip Fracture database for patients who underwent surgery. Two cohorts were formed based on patients' preoperative COVID-19 status, as tested within 14 days prior to the operation. Several clinical factors were compared.

RESULTS

The COVID-positive cohort consisted of 184 patients, all of whom had a laboratory-confirmed or clinically suspected SARS-CoV-2 infection, while the COVID-negative cohort consisted of 12,211 patients with no infection. A lower proportion of COVID-positive patients had an emergent operation compared to the COVID-negative cohort (58.70% vs. 73.09%, p < .001). Preoperatively, the COVID-positive cohort showed higher rates of coagulopathy/bleeding disorders (22.83% vs. 14.12%), congestive heart failure (16.30% vs. 9.84%), diabetes mellitus (28.26% vs. 19.24%), and dementia (42.39% vs. 28.07%), with p ≤ .005 for all. Postoperatively, a higher proportion of COVID-positive patients died (9.78% vs. 5.40%) or had pneumonia (8.70% vs. 3.65%), hospital readmission within 30 days (10.87% vs. 6.76%), and pressure sores (8.15% vs. 4.55%), with p ≤ .033 for all.

CONCLUSION

The diagnosis of COVID-19 in hip fracture patients was associated with higher rates of postoperative complications, including mortality, when compared to COVID-negative patients, indicating the severity of the viral infection.

Comparative Analysis of COVID-19 Outcomes in Type 1 and Type 2 Diabetes: A Three-Year Retrospective Study

Background and Objectives: This comprehensive retrospective study assesses COVID-19 outcomes in type 1 (T1D) and type 2 diabetes (T2D) patients across three years, focusing on how these outcomes varied with the evolving pandemic and changes in diabetes management. The study aims to determine if COVID-19 outcomes, including severity, intensive care unit (ICU) admission rates, duration of hospitalization, and mortality, are significantly different between these diabetes subtypes. Materials and Methods: The study analyzed data from patients admitted to the Victor Babes Hospital for Infectious Diseases and Pulmonology with confirmed COVID-19 and pre-existing diabetes, from the years 2020, 2021, and 2022. Results: Among 486 patients (200 without diabetes, 62 with T1D, 224 with T2D), T2D patients showed notably higher severity, with 33.5% experiencing severe cases, compared to 25.8% in T1D. Mortality rates were 11.6% in T2D and 8.1% in T1D. T2D patients had longer hospital stays (11.6 ± 7.0 days) compared to T1D (9.1 ± 5.8 days) and were more likely to require ICU admission (OR: 2.24) and mechanical ventilation (OR: 2.46). Hyperglycemia at admission was significantly higher in the diabetes groups, particularly in T2D (178.3 ± 34.7 mg/dL) compared to T1D (164.8 ± 39.6 mg/dL). Conclusions: The study reveals a discernible difference in COVID-19 outcomes between T1D and T2D, with T2D patients having longer hospital admissions, mechanical ventilation necessities, and mortality risks.

Risk factors for SARS-CoV-2 infection: a test-negative case-control study with additional population controls in Norway

OBJECTIVES

This study aims to assess risk factors for SARS-CoV-2 infection by combined design; first comparing positive cases to negative controls as determined by PCR testing and then comparing these two groups to an additional prepandemic population control group.

DESIGN AND SETTING

Test-negative design (TND), multicentre case-control study with additional population controls in South-Eastern Norway.

PARTICIPANTS

Adults who underwent SARS-CoV-2 PCR testing between February and December 2020. PCR-positive cases, PCR-negative controls and additional age-matched population controls.

PRIMARY OUTCOME MEASURES

The associations between various risk factors based on self- reported questionnaire and SARS-CoV-2 infection comparing PCR-positive cases and PCR-negative controls. Using subgroup analysis, the risk factors for both PCR-positive and PCR-negative participants were compared with a population control group.

RESULTS

In total, 400 PCR-positive cases, 719 PCR-negative controls and 14 509 population controls were included. Male sex was associated with the risk of SARS-CoV-2 infection only in the TND study (OR 1.9, 95% CI 1.4 to 2.6), but not when PCR-positive cases were compared with population controls (OR 1.2, 95% CI 0.9. to 1.5). Some factors were positively (asthma, wood heating) or negatively (hypertension) associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but lacked convincing association in the TND study. Smoking was negatively associated with the risk of SARS-CoV-2 infection in both analyses (OR 0.5, 95% CI 0.3 to 0.8 and OR 0.6, 95% CI 0.4 to 0.8).

CONCLUSIONS

Male sex was a possible risk factor for SARS-CoV-2 infection only in the TND study, whereas smoking was negatively associated with SARS-CoV-2 infection in both the TND study and when using population controls. Several factors were associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but not in the TND study, highlighting the strength of combining case-control study designs during the pandemic.

Diabetic individuals with COVID-19 exhibit reduced efficacy of gliptins in inhibiting dipeptidyl peptidase 4 (DPP4). A suggested explanation for increased COVID-19 susceptibility in patients with type 2 diabetes mellitus (T2DM)

AIMS

Dipeptidyl peptidase 4 (DPP4) has been proposed as a coreceptor for SARS-CoV-2 cellular entry. Considering that type 2 diabetes mellitus (T2DM) has been identified as the most important risk factor for SARS-CoV-2, and that gliptins (DPP4 inhibitors) are a prescribed diabetic treatment, this study aims to unravel the impact of DPP4 in the intersection of T2DM/COVID-19.

MATERIALS AND METHODS

We analyzed 189 serum human samples, divided into six clinical groups (controls, T2DM, T2DM + gliptins, COVID-19, COVID-19 + T2DM, and COVID-19 + T2DM + gliptins), measuring DPP4 protein concentration and activity by Western blot, ELISA, and commercial activity kits. The obtained results were verified in Huh-7 cellular models.

KEY FINDINGS

Both DPP4 concentration and activity were decreased in COVID-19 patients, and as in T2DM patients, compared to controls. Despite these lower levels, the ratio of DPP4 activity/concentration in COVID-19 sera was the highest (0.782 ± 0.289 μU/ng vs. 0.547 ± 0.050 μU/ng in controls, p < 0.0001), suggesting a compensating mechanism in these patients. Supernatants of Huh-7 cells incubated with COVID-19 serum showed a consistent and significantly lower DPP4 concentration and activity. Furthermore, COVID-19 + T2DM + gliptins patients showed a higher serum DPP4 concentration and activity than T2DM + gliptin subjects (p < 0.05), indicating that sera from COVID-19 convalescents interfere with gliptins.

SIGNIFICANCE

Either SARS-CoV-2 or some metabolites present in the sera of COVID-19-convalescent patients interact with soluble DPP4 or even gliptins themselves since the inhibitory effect of gliptins on DPP4 activity is being prevented. The interactions between DPP4, gliptins, and SARS-CoV-2 should be further elucidated to reveal the mechanism of action for these interesting observations.

Increased risk of poor clinical outcome in COVID-19 patients with diabetes mellitus and in-hospital mortality predictors: A retrospective cohort from a tertiary hospital in Indonesia

AIM

To determine association between diabetes in confirmed cases of COVID-19 and intensive care admission and in-hospital mortality, evaluate several laboratory parameters as mortality predictor and develop predictors of in-hospital mortality among diabetics with COVID-19.

METHODS

This retrospective cohort recruited all cases of COVID-19 hospitalized in Fatmawati General Hospital from March to October 2020. Inclusion criterion was RT-PCR confirmed cases of COVID-19 who aged 18 years and older while exclusion criteria were incomplete medical record or cannot be found and pregnant women.

RESULTS

We enrolled 506 participants to this study with median age of 51 years (IQR:22), female (56.32%), and diabetes (28.46%). Diabetes increased intensive care admission (adjusted OR: 2.57; 95% CI: 3.52-10.43) and in-hospital mortality (adjusted OR: 2.50; 95% CI: 1.61-3.89). In predicting in-hospital mortality, ferritin and lactate dehydrogenase offered an acceptable discrimination, AUC: 0.71 (95% CI: 0.62-0.79) and AUC: 0.70 (95% CI: 0.61-0.78), respectively. The optimal cut-off of predicting mortality for ferritin was 786 g/mL and for LDH was 514.94 u/L. Factors include age above 70 years old, RBGs level on admission above 250 mg/dL or below 140 mg/dL, ferritin level above 786 ng/mL and presence of ARDS increased the odds of mortality among individuals with diabetes.

CONCLUSIONS

Diabetes increases risk intensive care admission and in hospital mortality in COVID-19. Multivariate analysis showed that older age, RBG on admission, high ferritin level, presence of ARDS increased the odds of mortality among individuals with diabetes.

Diabetes related phenotypes and their influence on outcomes of patients with corona virus disease 2019 (COVID-19)

INTRODUCTION

Diabetes mellitus (DM) is associated with severe forms of COVID-19 but little is known about the diabetes-related phenotype considering pre-admission, on-admission and data covering the entire hospitalization period.

METHODS

We analyzed COVID-19 inpatients (n = 3327) aged 61.2(48.2-71.4) years attended from March to September 2020 in a public hospital.

RESULTS

DM group (n = 1218) differed from Non-DM group (n = 2109) by higher age, body mass index (BMI), systolic blood pressure and lower O2 saturation on admission. Gender, ethnicity and COVID-19-related symptoms were similar. Glucose and several markers of inflammation, tissue injury and organ dysfunction were higher among patients with diabetes: troponin, lactate dehydrogenase, creatine phosphokinase (CPK), C-reactive protein (CRP), lactate, brain natriuretic peptide, urea, creatinine, sodium, potassium but lower albumin levels. Hospital (12 × 11 days) and intensive care unit permanence (10 × 9 days) were similar but DM group needed more vasoactive, anticoagulant and anti-platelet drugs, oxygen therapy, endotracheal intubation and dialysis. Lethality was higher in patients with diabetes (39.3% × 30.7%) and increased with glucose levels and age, in male sex and with BMI < 30 kg/m2 in both groups (obesity paradox). It was lower with previous treatment with ACEi/BRA in both groups. Ethnicity and education level did not result in different outcomes between groups. Higher frequency of comorbidities (hypertension, cardiovascular/renal disease, stroke), of inflammatory (higher leucocyte number, RCP, LDH, troponin) and renal markers (urea, creatinine, potassium levels and lower sodium, magnesium) differentiated lethality risk between patients with and without diabetes.

CONCLUSIONS

Comorbidities, inflammatory markers and renal disfunction but not Covid-19-related symptoms, obesity, ethnicity and education level differentiated lethality risk between patients with and without diabetes.

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes

BACKGROUND

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort.

METHODS

We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups.

RESULTS

We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease.

CONCLUSIONS

These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations.

TRIAL REGISTRATION

NCT04357366.

COVID-19 associated Mucormycosis among ICU patients: risk factors, control, and challenges

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic is still difficult to be controlled. The spread of this virus and the emergence of new variants are considered a great challenge worldwide. Disturbance in infection control guidelines implementation, use of steroids, antibiotics, hospital crowdedness, and repeated use of oxygen masks during the management of critically ill COVID-19 patients lead to an increase in the rate of opportunistic infections. So, patients need to fight both the virus with its different variants and opportunistic pathogens including bacteria and fungi especially patients with diabetes mellitus, malignancy, or those who undergo hemodialysis and receive deferoxamine. During the pandemic, many cases of Mucormycosis associated with COVID-19 infection were observed in many countries. In this review, we discuss risk factors that increase the chance of infection by opportunistic pathogens, especially fungal pathogens, recent challenges, and control measures.

Predictors of mortality in critically ill patients with COVID-19 and diabetes

The COVID-19 pandemic has challenged the entire world, and patients with diabetes mellitus (DM) have been particularly affected. We aimed to evaluate predictors of mortality during the first 30 days of hospitalization in critically ill patients with COVID-19 and comorbid DM. This prospective study included 110 critically ill patients admitted with COVID-19 infection. Thirty-two (29%) patients had a previous diagnosis of DM. Clinical variables, laboratory tests, and vascular biomarkers, such as VCAM-1, syndecan-1, ICAM-1, angiopoietin-1, and angiopoeitin-2, were evaluated after intensive care unit (ICU) admission. A comparison was made between patients with and without DM. No difference in mortality was observed between the groups (48.7 vs 46.9%, P=0.861). In the multivariate Cox regression analysis, VCAM-1 levels at ICU admission (HR: 1 [1-1.001], P<0.006) were associated with death in patients with DM. Among patients with DM, advanced age (HR 1.063 [1.031-1.096], P<0.001), increased Ang-2/Ang-1 ratio (HR: 4.515 [1.803-11.308] P=0.001), and need for dialysis (HR: 3.489 [1.409-8.642], P=0.007) were independent predictors of death. Higher levels of VCAM-1 in patients with DM was better at predicting death of patients with severe COVID-19 and comorbid DM, and their cut-off values were useful for stratifying patients with a worse prognosis. Vascular biomarkers VCAM-1 and Ang-2/Ang-1 ratio were predictors of death in patients with severe COVID-19 and comorbid DM and those without DM. Additionally, kidney injury was associated with an increased risk of death.

Diagnosis and Treatment of Coagulopathy Caused by the New Coronavirus: A Systematic Review and Meta-Analysis Protocol

Background

The new coronavirus is an agent of respiratory infections associated with thrombosis in vital organs. This study aimed to propose a better diagnosis and treatment of coagulation disorders caused by the new coronavirus (Covid-19).

Materials and Methods

Search in Cochrane central, Web of Science, PubMed, Scopus, and Ovid will be done. Also, according to the inclusion criteria, cross-sectional studies, cohort, clinical trial, and case-control will be included without gender and language restriction. Participants will also be Covid-19 patients with coagulation disorders. Any disagreement in the stages of screening, selection, and extraction of data between the two reviewers will be resolved by discussion, then if not resolved, the opinion of expert reviewers will be used. The risk of bias will be assessed using the NOS (Newcastle-Ottawa scale) tool for cross-sectional study, cohort and case-control, and the Cochrane checklist for clinical trials study. Metaanalysis of included studies that are similar based on the methodology will be done. Also, a fixed or random-effect model will be used for this it. Heterogeneity indices (I2), odds ratio (OR), risk ratio (RR), mean difference, and %95 confidence interval will also be calculated by Stata V.13.0 (Corporation, College Station TX).

Results

Treatment with anticoagulants will reduce the severity of thrombosis and lung disease in patients. D-dimer measurement will also be a diagnosis indicator of thrombosis.

Conclusions

Simultaneous study of coagulation disorders and thrombosis in patients and development of a Godliness based on it will play a treatment role in the follow-up of the coronavirus disease.

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79–0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81–0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. Hierarchical cluster analysis showed that inflammatory laboratory markers grouped together in three distinct clusters including positive correlations: WBC with NEU, NEU with neutrophil-to-lymphocyte ratio (NLR), NEU with systemic immune-inflammation index (SII), NLR with SII and platelet-to-lymphocyte ratio (PLR) with SII. When analyzing the routine laboratory parameters in the subgroups of comorbidities, the risk of death was associated with a common set of laboratory markers of systemic inflammation. Our results have shown that a panel of several routine laboratory parameters recorded on admission could be helpful for early evaluation of the risk of disease severity and mortality in COVID-19 patients. Inflammatory markers for mortality risk were similar in the subgroups of comorbidities, suggesting the limited effect of confounding factors in predicting COVID-19 mortality at admission.

Prevalence and Predictors of Persistent Symptoms After Clearance of SARS-CoV-2 Infection: A Multicenter Study from Egypt

Background and Aim

Little is known about the persistence of symptoms after clearance of SARS-CoV-2 infection. Our study aimed to assess persistent symptoms in COVID-19 patients after clearance of SARS-CoV-2 infection.

Methodology

A multi-center survey was conducted on first wave COVID-19 patients with confirmed SARS-CoV-2 infection. Sociodemographic and clinical characteristics, including presenting symptoms and persistent symptoms after viral clearance and possible factors contributing to persistence of such symptoms, were collected using an online multicomponent questionnaire. Descriptive and inferential statistical analysis was performed to detect the most persisting symptoms and factors contributing to their persistence.

Results

Overall, 538 patients were enrolled. Mean age was 41.17 (±SD 14.84), 54.1% were males, and 18.6% were smokers. Hypertension and diabetes were the most reported co-morbidities. Mild symptoms were reported in 61.3% of patients, 51.3% were admitted to hospital and 6.5% were admitted to the intensive care unit. Our study identified 49 types of persisting symptoms. Fatigue (59.1%), sense of fever (46.5%), anorexia (24.3%) and diarrhea (24.3%) were the most commonly reported persisting symptoms followed by loss of taste and smell (22.3%), headache (21.4%), cough (20.8) and dyspnea (21%). The use of hydroxychloroquine, azithromycin and multivitamins were significantly associated with persistence of symptoms (OR = 8.03, 8.89 and 10.12, respectively).

Conclusion

Our study revealed that in COVID-19 recovered patients, many patients reported persistence of at least one symptom, particularly fatigue and sense of fever. Follow-up of patients after discharge from hospital is recommended until complete resolution of symptoms.

Challenges and Opportunities in Using Telehealth for Diabetes Care

The ongoing coronavirus pandemic led to a rapid and dramatic increase in the use of telehealth for diabetes care. In the wake of this transition, we examine new opportunities and ongoing challenges for using telehealth within diabetes management, based on data and experiences from the pre-pandemic and pandemic time frames.

Effectiveness of COVID-19 Vaccines in Patients Under Maintenance Hemodialysis

BACKGROUND

Several published data on the dialysis population showed that antibody levels decreased after COVID-19 vaccinations in comparison to the overall population. We aimed to illustrate the persistence of humoral response after receiving second dose of the Pfizer or AstraZeneca vaccines in patients under maintenance hemodialysis (HD).

METHODS

A total of 119 adult patients on HD who were recruited from a single hemodialysis center in Madinah, Saudi Arabia. An enzyme-linked immunosorbent assay (ELISA) was utilized to measure the specific antibody response to the spike protein in the serum samples.

RESULTS

Mean age of patients was 48.5 ± 13.5 years, while mean time since starting the renal dialysis was 5.09 ± 5.29 years. Blood samples were collected after 89.2 ± 25.7 days of receiving the second dose of the vaccines. A very high positive correlation between anti-S IgG antibodies in pre- and post-dialysis was found (rs= 0.93, p < 0.001). Additionally, there was a high positive correlation between anti-S IgG antibody collected at baseline and follow-up blood samples (30 days apart) (rs= 0.82, p < 0.001). Moreover, patients who received Pfizer had significantly higher mean change in anti-S IgG antibodies compared to patients who received AstraZeneca (0.41 ± 0.94 vs 0.03 ± 0.30, respectively, p = 0.026).

CONCLUSION

The majority of the patients included in this study were able to yield an immune response to the vaccine after receiving the two doses. Persistence of IgG antibodies in the majority of the patients on HD in response to COVID-19 vaccines is encouraging in terms of continuing to vaccinate this category of patients in addition to monitoring them.

Mortality and Clinical Outcomes among Patients with COVID-19 and Diabetes

Background Diabetes mellitus (DM) is a decisive risk factor for severe illness in coronavirus disease 2019 (COVID-19). India is home to a large number of people with DM, and many of them were infected with COVID-19. It is critical to understand the impact of DM on mortality and other clinical outcomes of COVID-19 infection from this region. Aims The primary objective of our study was to analyze the mortality rate in people with DM infected with COVID-19. The secondary objectives were to assess the effect of various comorbidities on mortality and study the impact of DM on other clinical outcomes. Methods This is a retrospective study of COVID-19 infected patients admitted to a tertiary care hospital in north India in the early phase of the pandemic. Results Of the 1211 cases admitted, 19 were excluded because of incomplete data, and 1192 cases were finally considered for analysis. DM constituted 26.8% of total patients. The overall mortality rate was 6.1%, and the rate was 10.7% in the presence of diabetes (p < 0.01, OR 2.55). In univariate analysis, increased age, chronic kidney disease (CKD), coronary artery disease (CAD), stroke, and cancer were associated with mortality. On multiple logistic regression, the independent predictors of mortality were CAD, CKD, and cancer. Breathlessness and low SpO₂ at presentation, extensive involvement in CXR, and elevated ANC/ALC ratio were also significantly associated with mortality. Conclusions The presence of comorbidities such as DM, hypertension, CAD, CKD, and cancer strongly predict the risk of mortality in COVID-19 infection. Early triaging and aggressive therapy of patients with these comorbidities can optimize clinical outcomes.

d-Galactose treatment increases ACE2, TMPRSS2, and FURIN and reduces SERPINA1 mRNA expression in A549 human lung epithelial cells

Several comorbidities including diabetes, immune deficiency, and chronic respiratory disorders increase the risk of severe Covid-19 and fatalities among SARS-CoV-2 infected individuals. Severe Covid-19 risk among diabetes patients may reflect reduced immune response to viral infections. SARS-CoV-2 initially infects respiratory tract epithelial cells by binding to the host cell membrane ACE2, followed by proteolytic priming for cell entry by the host cell membrane serine protease TMPRSS2. Additionally, the protease FURIN facilitates cell exit of mature SARS-CoV-2 virions. Alpha-1 antitrypsin (AAT), the major plasma serine protease inhibitor, encoded by SERPINA1, is known to promote immune response to viral infections. AAT inhibits neutrophil elastase, a key inflammatory serine protease implicated in alveolar cell damage during respiratory infections, and AAT deficiency is associated with susceptibility to lung infections. AAT is implicated in Covid-19 as it inhibits TMPRSS2, a protease essential for SARS-CoV-2 cell entry. Here we show that treatment of A549 human lung epithelial cells for 7 days with 25 mM d-galactose, an inducer of diabetic-like and oxidative stress cellular phenotypes, leads to increased mRNA levels of ACE2, TMPRSS2, and FURIN, along with reduced SERPINA1 mRNA. Together, the dysregulated transcription of these genes following d-galactose treatment suggests that chronic diabetic-like conditions may facilitate SARS-CoV-2 infection of lung epithelial cells. Our findings may in part explain the higher severe Covid-19 risk in diabetes, and highlight the need to develop special treatment protocols for diabetic patients.