SARS-CoV-2 poses significant challenges to people living with diabetes (PLWD). This systematic review aimed to explore the impact of COVID-19 on mortality, complications associated with diabetes and haematological parameters among PLWD.

Systematic review and meta-analysis using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials and LILACS were searched between 1 December 2019 and 14 January 2025.

Eligible studies included case-control and cohort studies involving PLWD categorised into two groups: those with confirmed SARS-CoV-2 infection and those without.

Meta-analyses estimated the odds ratios (ORs) and mean differences (MDs) of outcomes including mortality, intensive care unit (ICU) admission, diabetic ketoacidosis (DKA), acute kidney injury, hospitalisation length and haematological parameters. We pooled results using random-effects models and assessed study quality with the Newcastle-Ottawa Scale. A funnel plot was used to detect potential publication bias. The overall certainty of evidence was assessed using GRADE.

25 of 7266 unique studies were eligible, including 1 154674 PLWD (561 558 with COVID-19 and 593 116 without COVID-19). SARS-CoV-2 infection in PLWD was associated with significantly increased mortality (OR 2.52, 95% CI 1.45 to 4.36, I2=99%), acute kidney injury (3.69, 95% CI 2.75 to 4.94, I2=0%), random plasma glucose in subjects with type 1 diabetes (MD 20.38 mg/dL, 95% CI 7.39 to 33.36, I2=0%), haemoglobin A1C in subjects with type 2 diabetes (0.21%, 95% CI 0.05 to 0.38, I2=13%), creatinine (0.12 mg/dL, 95% CI 0.04 to 0.19, I2=0%), C reactive protein (38.30 mg/L, 95% CI 4.79 to 71.82, I2=82%) and D-dimer (1.52 µg/mL, 95% CI 0.73 to 2.31, I2=0%). No significant differences were observed in the incidence of ICU admission and DKA, hospitalisation length, haemoglobin, leucocyte, lymphocyte, neutrophil to lymphocyte ratio, platelet, blood urea nitrogen, estimated glomerular filtration rate, procalcitonin, albumin, ferritin and bilirubin among PLWD with and without SARS-CoV-2 infection.

SARS-CoV-2 infection is associated with elevated risks of mortality and acute kidney injury and poor glycaemic control in PLWD, alongside increased levels of inflammatory and coagulation biomarkers. These findings underscore the urgent need for tailored clinical management strategies for PLWD with COVID-19.

CRD42023418039.

This study investigated the correlation between epidemiological and clinical characteristics of patients infected with omicron variants and the cycle threshold (Ct value) for RT-PCR detection. The study population consisted of 115 patients with Omicron infection and the most common symptoms included fever (43.5 %), cough (38.3 %) and sore throat (29.6 %). Laboratory abnormalities were mainly lymphopenia, elevated globulins and elevated blood glucose. Univariate analysis found that older age (P < 0.001) and unvaccinated (P = 0.003) were associated with low Ct values (high viral load). Multivariate analysis showed that an elevated monocyte count (OR: 3.556; 95 % CI: 1.330-9.503) was associated with low Ct values, whereas being vaccinated (OR: 0.209; 95 % CI: 0.051-0.854) and lower serum sodium (OR: 0.137; 95 % CI: 0.051-0.367) were negatively associated with low Ct values. Studies have shown that factors such as monocyte count, vaccination status and serum sodium correlate with Ct values, suggesting the potential of Ct values as a clinical predictor, which could also provide a valuable reference for clinical decision-making.

Coronavirus infection (COVID-19), designated a global health emergency by the World Health Organization in 2020, continues to spur the search for effective therapeutics. The causative agent, SARS-CoV-2, depends on viral proteins and host metabolic reprogramming for replication. This study explores the potential of glycolytic inhibitors as dual-action agents against SARS-CoV-2, explicitly targeting the main protease and the spike protein due to their critical roles in viral replication and cellular entry. These inhibitors disrupt the activity of viral proteins and host cell glycolysis, thereby preventing viral propagation. Through a combination of virtual screening, molecular docking, and molecular dynamics simulations, fluoro-deoxy-glucose folate (FDGF) and N-(2-fluoro-3-(6-O-glucosylpropyl-azomycin)) were identified as potent candidates. The docking results showed strong binding affinities, with scores of -8.6 and -7.1 kcal/mol for main protease and -9.9 and - 7.5 kcal/mol for spike receptor-binding domain bound to ACE2. Further molecular dynamic simulations confirmed the stability of the FDGF complexes, with RMSD fluctuations consistently remained within 1.6-2.9 Å over a 100 ns trajectory. Additionally, MM-GBSA binding free energy calculations revealed favorable binding energies, underscoring the stability and potential efficacy of these compounds. Overall, the findings suggest that FDGF and N-(2-fluoro-3-(6-O-glucosylpropyl-azomycin)) show promise as SARS-CoV-2 therapeutics, warranting further in vitro and in vivo validation to confirm their antiviral potential.

The online version contains supplementary material available at 10.1007/s40203-025-00336-2.

A better understanding of the mechanisms underlying an elevated infection risk in individuals with type 2 diabetes is needed to guide risk stratification and prevention. We investigated the risk of infection in subgroups of individuals with type 2 diabetes according to indices of insulin sensitivity and beta cell function.

We classified 7265 individuals with recently diagnosed type 2 diabetes (median duration 1.4 years, IQR 0.5-2.9 years) into hyperinsulinaemic (high beta cell function [HOMA 2-beta-cell function, HOMA2-B], low insulin sensitivity [HOMA 2-insulin sensitivity, HOMA2-S]), classical (low HOMA2-B, low HOMA2-S) and insulinopenic (low HOMA2-B, high HOMA2-S) type 2 diabetes. Individuals were followed until first hospital-treated infection or first prescription for an anti-infective agent (community-treated infection). We used Cox regression analysis to estimate HRs adjusted for age, sex, index year, diabetes duration and treatment, lifestyle behaviours and comorbidities.

Among study participants, 28% had hyperinsulinaemic, 63% had classical and 9% had insulinopenic type 2 diabetes. The 10 year risks of hospital-treated infections were 42.3%, 36.8% and 31.0% in the three subgroups, respectively. Compared with the insulinopenic subgroup, adjusted HRs for hospital-treated infections were elevated for hyperinsulinaemic (1.38 [95% CI 1.16, 1.65]) and classical type 2 diabetes (1.20 [95% CI 1.02, 1.42]). The 10 year risks of community-treated infections were high in all three subgroups at 91.6%, 90.1% and 88.3%, respectively, corresponding to adjusted HRs of 1.20 (95% CI 1.08, 1.33) for the hyperinsulinaemic and 1.10 (95% CI 1.00, 1.21) for the classical subgroup. Infection risk in the hyperinsulinaemic subgroup decreased substantially when further adjusted for abdominal obesity, metabolic derangements and low-grade inflammation.

The risk of severe infections is clearly elevated in individuals with type 2 diabetes characterised by a higher degree of insulin resistance/hyperinsulinaemia.

The objective of the study was to analyse possible changes in antibiotic policy with ceftazidime-avibactam during the SARS-CoV-2 pandemic in an Intensive Care Unit (ICU) to determine patient mortality 28 days after initiation of antimicrobial therapy and to describe the microorganisms that most frequently colonise critically ill patients.

Observational, single-centre, cohort study that included patients on treatment with ceftazidime-avibactam in ICU between March 2020 and September 2021. Demographic (age, sex), microbiological (colonisation, microorganisms isolated in blood cultures), pharmacotherapeutic (duration of treatment with ceftazidime-avibactam, antimicrobials used in synergy with ceftazidime-avibactam) and clinical (mortality, length of hospital stay and comorbidities) variables were collected. As associated comorbidities, we identified how many of the patients included in the study had diabetes mellitus (DM), chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD) or obesity.

Eighty-nine patients were included, 85.39% of whom were male. Forty-nine patients were infected with Sars-CoV-2. Median ICU stay was 46 days (RIQ = 58-27) in SARS-CoV-2 infected and 34 days (RIQ = 51-24) in non-infected patients. Patients were on ceftazidime-avibactam treatment for a median of 8 days (RIQ = 13-4), being 7 days (RIQ = 11-2) in COVID-19 positive patients and 11 days (RIQ = 14-6) in COVID-19 negative patients (p > 0.05). Empirical treatment with ceftazidime-avibactam was started empirically in 41.57% (n = 37) of the patients. The percentage of empiric initiations in SARS-CoV-2 infected patients was 43% and in non-infected patients 40%, with no statistically significant difference between empiric initiation according to SARS-CoV-2 diagnostic status (p > 0.05). A total of 43.8% (n = 39) of the patients were colonised by a multidrug-resistant (MDR) bacterium. Regarding on the microorganisms that colonised patients had, the most frequent was Klebsiella pneumoniae, present in 66.6% of patients (n = 26 patients). Overall mortality was 41.6%, with no statistically significant differences between SARS-CoV-2 infected and non-infected patients (42.9% and 40%, respectively; p > 0.05).

The SARS-CoV-2 pandemic did not lead to a change in the criteria for the use of ceftazidime-avibactam in the critically ill patient.

The role of diabetes mellitus (DM) in hospitalized COVID-19 patients and of HbA1c in hospitalized COVID-19 patients with DM were not studied adequately in the past.

It was a retrospective cohort study. In this study, data from 305 hospitalized COVID-19 patients was analyzed. The study objective was to determine the association of DM with in-hospital mortality in COVID-19 patients. Another study objective was to determine the association of HbA1c with mortality in COVID-19 patients with DM.

In this retrospective study, DM was present in 41.3% (126/305) of the study population. The multivariate Cox regression analysis showed a significant association between DM and mortality (adjusted hazard ratio (aHR): 2.116, 95% CI: 1.088-4.116, p = 0.027). The median HbA1c in diabetic patients was 8.9% (7.5-11.0). HbA1c was found to be associated with mortality in diabetic patients in the multivariate cox-regression analysis (aHR:1.272, 95% CI: 1.028-1.574, p = 0.027). The multivariate Cox regression analysis also showed the association of HbA1c (10.5%≤HbA1c > 10.5%) as a dichotomous variable with in-hospital mortality (aHR: 2.53, 95% CI: 2.606-194.81, p = 0.005) in diabetic patients.

DM was independently associated with mortality in hospitalized COVID-19 patients in the multivariate analysis. In COVID-19 patients with DM, HbA1c was associated with mortality as a continuous and dichotomous variable in the multivariate analysis.

Long-term adverse consequences of SARS-CoV-2 infection, termed "long COVID" or post-acute sequelae of COVID (PASC), are a major component of overall COVID-19 disease burden. Prior obesity and metabolic disease increase the severity of acute disease, but SARS-CoV-2 infection also contributes to the development of new-onset metabolic disease. Since the COVID pandemic occurred in the context of the global obesity epidemic, an important question is the extent to which pre-existing obesity modifies long-term responses to SARS-CoV-2 infection. We utilized a nonhuman primate model to compare the effects of infection with the SARS-CoV-2 delta variant in lean and obese/insulin-resistant adult male rhesus macaques over a 6-month time course. While some longitudinal responses to SARS-CoV-2 infection, including overall viral dynamics, SARS-CoV-2-specific IgG induction, cytokine profiles, and tissue persistence of viral RNA, did not appreciably differ between lean and obese animals, other responses, including neutralizing Ab dynamics, lung pathology, body weight, degree of insulin sensitivity, adipocytokine profiles, body temperature, and nighttime activity levels were significantly different in lean versus obese animals. Furthermore, several parameters in lean animals were altered following SARS-CoV-2 infection to resemble those in obese animals. Notably, persistent changes in multiple parameters were present in most animals, suggesting that PASC may be more prevalent than estimated from self-reported symptoms in human studies.

The world is currently grappling with the potentially life-threatening coronavirus disease 2019 (COVID-19), marking it as the most severe health crisis in the modern era. COVID-19 has led to a pandemic, with the World Health Organization (WHO) predicting that individuals with diabetes are at a higher risk of contracting the virus compared to the general population. This review aims to provide a practical summary of the long-term impacts of COVID-19 on patients with diabetes. Specifically, it focuses on the effects of SARS-CoV-2 on different types of diabetic patients, the associated mortality rate, the underlying mechanisms, related complications, and the role of vitamin D and zinc in therapeutic and preventive approaches.

Relevant literature was identified through searches on PubMed, Web of Science, and Science Direct in English, up to April 2023.

COVID-19 can lead to distressing symptoms and pose a significant challenge for individuals living with diabetes. Older individuals and those with pre-existing conditions such as diabetes, coronary illness, and asthma are more susceptible to COVID-19 infection. Managing COVID-19 in individuals with diabetes presents challenges, as it not only complicates the fight against the infection but also potentially prolongs the recovery time. Moreover, the virus may thrive in individuals with high blood glucose levels. Various therapeutic approaches, including antidiabetic drugs, are available to help prevent COVID-19 in diabetic patients.

Diabetes increases the morbidity and mortality risk for patients with COVID-19. Efforts are globally underway to explore therapeutic interventions aimed at reducing the impact of diabetes on COVID-19.

The gut microbiome affects the occurrence and development of metabolic diseases, with a significant amount of research focused on intestinal bacteria. As an important part of the gut microbiome, gut viruses were studied recently, particularly through fecal virome transplantation (FVT), revealing manipulating the gut virus could reverse overweight and glucose intolerance in mice. And human cohort studies found gut virome changed significantly in patients with metabolic disease. By summarizing those studies, we compared the research and analytical methods, as well as the similarities and differences in their results, and analyzed the reasons for these discrepancies. FVT provided potential value to improve metabolic diseases, but the mechanisms involved and the effect of FVT on humans should be investigated further. The potential methods of regulating intestinal virome composition and the possible mechanisms of intestinal virome changes affecting metabolic diseases were also discussed.

Recent studies have found that a link between people with type 1 diabetes mellitus (T1DM) are at higher risk of morbidity as well as mortality from COVID-19 infection, indicating a need for vaccination. T1DM appears to impair innate and adaptive immunity. The overabundance of pro-inflammatory cytokines produced in COVID-19 illness that is severe and potentially fatal is known as a "cytokine storm." Numerous cohorts have revealed chronic inflammation as a key risk factor for unfavorable COVID-19 outcomes. TNF-α, interleukin (IL)-1a, IL-1, IL-2, IL-6, and other cytokines were found in higher concentrations in patients with T1DM. Even more importantly, oxidative stress contributes significantly to the severity and course of COVID- 19's significant role in the progression and severity of COVID-19 diseases. Severe glucose excursions, a defining characteristic of type 1 diabetes, are widely recognized for their potent role as mediating agents of oxidative stress via several routes, such as heightened production of advanced glycation end products (AGEs) and activation of protein kinase C (PKC). Furthermore, persistent endothelial dysfunction and hypercoagulation found in T1DM may impair microcirculation and endothelium, which could result in the development of various organ failure and acute breathing syndrome.

To overview the recent literature regarding the relationship between COVID-19 vaccines and glycemic control.

Data were extracted from text and tables of all available articles published up to September 2023 in PubMed Database describing glucose homeostasis data in subjects exposed to COVID-19 vaccines, focusing on patients with diabetes mellitus (DM).

It is debated if the immune system impairment observed in diabetic patients makes them susceptible to lower efficacy of vaccines, but evidence suggests a possible improvement in immune response in those with good glycemic control. Despite their proven protective role lowering infection rates and disease severity, COVID-19 vaccines can result in diabetic ketoacidosis, new-onset diabetes, or episodes of hyper- or hypoglycemia.

Evidence with COVID-19 vaccines highlights the strong relationship existing between DM and immune system function. Clinicians should strive to achieve optimal glucose control before vaccination and promptly manage possible glucose homeostasis derangement following vaccine exposure.

In clinical terms, chronic pain is the most prevalent sequela resulting from COVID-19, which is induced by the novel coronavirus (SARS-CoV-2), while type 2 diabetes mellitus (T2D) is the most common comorbidity. This triangular relationship can be attributed to the dysfunction of the insulin receptor signaling system (IRSS) in both central and peripheral systems. Patients with T2D are essentially more susceptible to SARS-CoV-2 infection due to the widespread expression of angiotensin converting enzyme 2 (ACE2) in their pancreatic beta cells, which serves as the cellular port for the SARS-CoV-2 to infect and enter the cell. This infection can exacerbate chronic pain and insulin resistance for various reasons. Peripherally, once infected, the virus can cause damage to peripheral nerves and pancreatic β-cells, further exacerbating pain and glucose metabolism conditions. Additionally, in the central nervous system, dysfunctional IRSS is closely linked to chronic pain. Over the past few years of the COVID-19 pandemic, an increasing body of evidence suggests that insulin and other medications currently used in clinical practice for hyperglycemia control may not be safe for treating these patients. Therefore, we need a proper approach for the treatment of chronic pain in long COVID patients, especially patients with T2D. This review presents evidence that transcutaneous auricular vagal nerve stimulation (taVNS) may provide a viable treatment option for chronic pain and metabolic dysfunction by improving the function of IRSS in both the central nervous system and peripheral tissues.

Defining the protective thresholds against the severe-acute-respiratory-syndrome-related corona virus-2 pandemic is a crucial challenge. To reduce the risks of severe disease, hospitalization, and death, various COVID-19 vaccines have been rapidly developed.

This study aimed to assess the impact of three common COVID-19 vaccine types; two mRNA COVID-19 vaccines: (Pfizer/BioNTech's BNT162b2 and Moderna's mRNA-1273), one adenoviral vector vaccine: Oxford/AstraZeneca's ChAdOx1, and one inactivated vaccine (Sinovac Biotech/China's Sinovac) on the level of neutralizing antibodies, considering factors such as vaccine type, demographic characteristics, and hybrid immunity. We conducted a direct comparative analysis involving 300 healthcare workers, both with and without prior SARS-CoV-2 infection (B.1, C.36.3, and AY.32 (Delta) variants). Neutralizing antibodies levels were measured at baseline (before vaccination), before the second dose, and six months after the second dose.

The results showed a significant increase in neutralizing antibodies levels after complete vaccination with all vaccine types. Among healthcare workers, those vaccinated with mRNA vaccines (Moderna or Pfizer) exhibited the highest neutralizing antibodies titers, followed by AstraZeneca, and finally Sinovac with the lowest titer. On studying the effect of previous COVID-19 infection after vaccination, no significant difference in neutralizing antibodies levels was observed between healthcare workers vaccinated with mRNA or AstraZeneca vaccines, both with prior COVID-19 infection, following the first and six months after the second dose.

These findings suggest that individuals with prior COVID-19 may only require a single dose of mRNA or AstraZeneca vaccines to achieve a similar level of immunization as those without prior COVID-19 who completed the vaccination program.

There is a significant increase in neutralizing antibodies levels after complete vaccination against COVID-19 Vaccination with mRNA vaccines exhibits the highest neutralizing antibodies titers. Vaccination with Sinovac exhibits the lowest neutralizing antibodies titers.

The COVID-19 pandemic has added to the pre-existing challenges of diabetes management in many countries. It has accelerated the wider use of digital health solutions which have tremendous potential to improve health outcomes for people with diabetes. However, little is known about the attributes and the implementation of these solutions.

To identify and describe digital health solutions for community-based diabetes management and to highlight their key implementation outcomes.

We searched Ovid Medline, CINAHL, Embase, PsycINFO, and Web of Science for relevant articles. A purposive search was also used to identify grey literature. Articles that described digital health solutions that aimed to improve community-based diabetes management were included in this review. We applied a thematic synthesis of evidence to describe the characteristics of digital health solutions, and to summarize their key implementation outcomes.

We included 15 articles that reported digital health solutions that primarily focused on community-based diabetes management. Nine of the 15 innovations involved were mobile applications and/or web-based platforms, and five were based on social media platforms. The majority of the digital health solutions were used for diabetes education and support. High engagement, utilization, and satisfaction rates with digital health solutions were observed. The use of digital health solutions was also associated with improvement in self-management, taking medication, and reduction in glycated hemoglobin (HbA1c) levels.

COVID-19 triggered digital health solutions have tremendous potential to improve health outcomes for people with diabetes. Further studies are needed to evaluate the sustainability and scale-up of these solutions.

To assess the association between cardiorespiratory fitness (CRF) and COVID-19-related health outcomes including mortality, hospitalization, and mechanical ventilation.

In a retrospective analysis of 750,302 patients included in the Exercise Testing and Health Outcomes Study, we identified 23,140 who had a positive result on COVID-19 testing between March 2020 and September 2021 and underwent a maximal exercise test in the Veterans Affairs Health Care System between October 1, 1999 to September 3, 2020. The association between CRF and risk for severe COVID-19 outcomes, including mortality, hospitalization due to COVID-19, and need for intubation was assessed after adjustment for 15 covariates. Patients were stratified into 5 age-specific CRF categories (Least-Fit, Low-Fit, Moderate-Fit, Fit, and High-Fit), based on peak metabolic equivalents achieved.

During a median of follow-up of 100 days, 1643 of the 23,140 patients (7.1%) died, 4995 (21.6%) were hospitalized, and 927 (4.0%) required intubation for COVID-19-related reasons. When compared with the Least-Fit patients (referent), the Low-Fit, Moderate-Fit, Fit, and High-Fit patients had hazard ratios for mortality of 0.82 (95% CI, 0.72 to 0.93), 0.73 (95% CI, 0.63 to 0.86), 0.61 (95% CI, 0.53 to 0.72), and 0.54 (95% CI, 0.45 to 0.65), respectively. Patients who were more fit also had substantially lower need for hospital admissions and intubation. Similar patterns were observed for elderly patients and subgroups with comorbidities including hypertension, diabetes, cardiovascular disease, and chronic kidney disease; for each of these conditions, those in the High-Fit category had mortality rates that were roughly half those in the Low-Fit category.

Among patients positive for COVID-19, higher CRF had a favorable impact on survival, need for hospitalization, and need for intubation regardless of age, body mass index, or the presence of comorbidities.

Type 2 diabetes mellitus (T2DM), a disease that threatens public health worldwide and can cause a series of irreversible complications, has been a major concern. Although the treatment based on hypoglycemic drugs is effective, its side effects should not be ignored, which has led to an urgent need for developing new hypoglycemic drugs. Bioactive peptides with antidiabetic effects obtained from food proteins have become a research hotspot as they are safer and with higher specificity than traditional hypoglycemic drugs. Here, we reviewed antidiabetic peptides that have the ability to inhibit key enzymes (α-glucosidase, α-amylase, and DPP-IV) in T2DM, the hypoglycemic mechanisms and structure-activity relationships were summarized, some antidiabetic peptides that improve insulin resistance and reverse gut microbiota and their metabolites were overviewed, the bitterness of antidiabetic peptides was predicted in silico, proposed solutions to the current challenges encountered in the development of antidiabetic peptide drugs, and provided an outlook on the future focus of commercial production. It provides a reference for the application of food-derived antidiabetic peptides.

Considering the diverse symptomatology of COVID-19-ranging from mild to severe cases-multi-professional interventions are crucial for enhancing physical recovery, nutritional status, and mental health outcomes in affected patients. Thus, this study aimed to investigate the effects of such an intervention on health-related physical fitness and biomarkers in overweight COVID-19 survivors with varying degrees of symptom severity after 8 weeks and 16 weeks.

This non-randomized clinical trial included 59 overweight COVID-19 survivors (32 males and 27 females) divided into three groups: mild (n = 31), moderate (n = 13), and severe/critical (n = 15). The participants underwent a multi-professional program and were assessed for anthropometric and body composition (primary outcome), as well as physical fitness and biochemical markers (secondary outcome) 8 and 16 weeks before the intervention.

After 8 weeks, time effects were observed for the maximum isometric handgrip strength (p < 0.001), maximum isometric lumbar-traction strength (p = 0.01), flexibility (p < 0.001), abdominal strength-endurance (p < 0.001), the sit-and-stand test (p < 0.001), maximum oxygen consumption (p < 0.001), and distance covered in the 6 min walk test (p < 0.001). Additionally, time effects were also observed for fat mass (p = 0.03), body fat percentage (p = 0.02), abdominal circumference (p = 0.01), total cholesterol (p < 0.001), low-density lipoproteins (p < 0.001), and glycated hemoglobin (p < 0.001), with lower values after multi-professional interventions. After 16 weeks, the systolic and diastolic blood pressure showed significant reductions independently of the intervention group (p < 0.001).

These findings suggest that multi-professional interventions can provide substantial benefits for post-COVID-19 patients, regardless of the severity of their initial symptoms.

SUMMARYSeveral examples of high-impact cross-species transmission of newly emerging or re-emerging bat-borne viruses, such as Sudan virus, Nipah virus, and severe acute respiratory syndrome coronavirus 2, have occurred in the past decades. Recent advancements in next-generation sequencing have strengthened ongoing efforts to catalog the global virome, in particular from the multitude of different bat species. However, functional characterization of these novel viruses and virus sequences is typically limited with regard to assessment of their cross-species potential. Our understanding of the intricate interplay between virus and host underlying successful cross-species transmission has focused on the basic mechanisms of entry and replication, as well as the importance of host innate immune responses. In this review, we discuss the various roles of the respective molecular mechanisms underlying cross-species transmission using different recent bat-borne viruses as examples. To delineate the crucial cellular and molecular steps underlying cross-species transmission, we propose a framework of overall characterization to improve our capacity to characterize viruses as benign, of interest, or of concern.

The prevalence of diabetes has been increasing globally, necessitating innovative approaches beyond conventional blood sugar monitoring and insulin control. Diabetes is associated with complex health complications, including cardiovascular diseases. Continuous Glucose Monitoring (CGM) devices, though automated, have limitations such as irreversibility and interference with bodily fluids. Hydrogel technologies provide non-invasive alternatives to traditional methods, addressing the limitations of current approaches. This review explores hydrogels as macromolecular biopolymeric materials capable of absorbing and retaining a substantial amount of water within their structure. Due to their high-water absorption properties, these macromolecules are utilized as coating materials for wound care and diabetes management. The study emphasizes the need for early diagnosis and monitoring, especially during the COVID-19 pandemic, where heightened attention to diabetic patients is crucial. Additionally, the article examines the role of the Internet of Things (IoT) and machine learning-based systems in enhancing diabetes management effectiveness. By leveraging these technologies, there is potential to revolutionize diabetes care, providing more personalized and proactive solutions. This review explores cutting-edge hydrogel-based systems as a promising avenue for diabetes diagnosis, management, and treatment, highlighting key biopolymers and technological integrations.

Studies of new-onset diabetes as a post-acute sequela of SARS-CoV-2 infection are difficult to generalize to all socio-demographic subgroups.

To study the risk of new-onset diabetes after SARS-CoV-2 infection in a socio-demographically diverse sample.

Retrospective cohort study of electronic health record (EHR) data available from the OneFlorida + clinical research network within the National Patient-Centered Clinical Research Network (PCORnet).

Persons aged 18 or older were included as part of an Exposed cohort (positive SARS-CoV-2 test or COVID-19 diagnosis between 1 March 2020 and 29 January 2022; n = 43,906), a contemporary unexposed cohort (negative SARS-CoV-2 test; n = 162,683), or an age-sex matched historical control cohort (index visits between 2 Mar 2018 and 30 Jan 2020; n = 40,957).

The primary outcome was new-onset type 2 diabetes ≥ 30 days after index visit. Hazard ratios and cases per 1000 person-years of new-onset diabetes were studied using target trial approaches for observational data. Associations were reported by sex, race/ethnicity, age, and hospitalization status subgroups.

The sample was 62% female, 21.4% non-Hispanic Black, and 21.4% Hispanic; mean age was 51.8 (SD, 18.9) years. Relative to historical controls (cases, 28.2 [26.0-30.5]), the unexposed (HR, 1.28 [95% CI, 1.18-1.39]; excess cases, [5.1-10.3]), and exposed cohorts (HR, 1.64 [95% CI, 1.50-1.80]; excess cases, 17.3 [13.7-20.8]) had higher risk of new-onset T2DM. Relative to the unexposed cohort, the exposed cohort had a higher risk (HR, 1.28 [1.19-1.37]); excess cases, 9.5 [6.4-12.7]). Findings were similar across subgroups.

The pandemic period was associated with increased T2DM cases across all socio-demographic subgroups; the greatest risk was observed among individuals exposed to SARS-CoV-2.

Obesity and type 2 diabetes (DM) are risk factors for severe coronavirus disease 2019 (COVID-19) outcomes, which disproportionately affect South Asian populations. This study aims to investigate the humoral and cellular immune responses to SARS-CoV-2 in adult COVID-19 survivors with overweight/obesity (Ov/Ob, BMI ≥ 23 kg/m2) and DM in Bangladesh.

In this cross-sectional study, SARS-CoV-2-specific antibody and T-cell responses were investigated in 63 healthy and 75 PCR-confirmed COVID-19 recovered individuals in Bangladesh, during the pre-vaccination first wave of the COVID-19 pandemic in 2020.

In COVID-19 survivors, SARS-CoV-2 infection induced robust antibody and T-cell responses, which correlated with disease severity. After adjusting for age, sex, DM status, disease severity, and time since onset of symptoms, Ov/Ob was associated with decreased neutralizing antibody titers, and increased SARS-CoV-2 spike-specific IFN-γ response along with increased proliferation and IL-2 production by CD8 + T cells. In contrast, DM was not associated with SARS-CoV-2-specific antibody and T-cell responses after adjustment for obesity and other confounders.

Ov/Ob is associated with lower neutralizing antibody levels and higher T-cell responses to SARS-CoV-2 post-COVID-19 recovery, while antibody or T-cell responses remain unaltered in DM.

An increased risk of diabetes mellitus (DM) after COVID-19 has been reported in the United States, Europe, and Asia. The burden of COVID-related DM has yet to be described in Africa, where the overall risk of DM has been increasing rapidly. Our objective was to compare the prevalence of pre-DM and DM in Nigerian individuals with a history of COVID-19 to individuals without known COVID-19 infection.

We undertook a retrospective cohort study with 256 individuals with a past medical history of COVID-19 with no history of pre-DM or DM and 256 individuals without a history of COVID-19 or pre-DM/DM. Participants were categorized as pre-DM (fasting capillary glucose 100-125 mg/dL) or DM (fasting capillary glucose ≥ 126 mg/dL). We employed univariate and multivariable logistic regression to identify key predictors and adjust for confounders related to hyperglycaemia risk factors. Additionally, we used multinomial logistic regression to analyze the relationship between COVID-19 history and diabetes status, distinguishing between normal, pre-diabetic, and diabetic glucose levels. All models were adjusted for age, gender, hypertension, physical activity, central adiposity, and family history of DM.

Compared to the control group, those with a history of COVID-19 had a similar median age (38 vs. 40 years, p = 0.84), had a higher proportion of men (63% vs. 49%), and had a lower prevalence of central adiposity (waist: hip ratio ≥ 0.90 for males and WHR ≥ 0.85 for females) (48% vs. 56.3%, p = 0.06). Of the 256 with a history of COVID-19, 44 (17%) required in-patient care. The median (interquartile range) time interval between COVID-19 diagnosis and the glycaemic assessment was 19 (IQR: 14, 24) months. Pre-DM prevalence was 27% in the post-COVID-19 group and 4% in the control group, whereas the prevalence of DM was 7% in the post-COVID-19 group and 2% in the control group. After multivariable adjustment, the odds of pre-DM were 8.12 (95% confidence interval (CI): 3.98, 16.58; p < 0.001) higher, and the odds of DM were 3.97 (95% CI: 1.16, 13.63) higher in those with a history of COVID-19 compared to controls. In the adjusted multinomial logistic regression analysis, individuals with a history of COVID-19 exhibited significantly elevated risks for pre-diabetes (RRR = 7.55, 95% CI: 3.76-15.17) and diabetes (RRR = 3.44, 95% CI: 1.01-11.71) compared to those without COVID-19.

Previous COVID-19 was found to be a risk factor for prevalent pre-diabetes and diabetes mellitus in Nigeria. More intensive screening for DM in those with a history of COVID-19 should be considered.

To determine the frequency of new-onset diabetes mellitus (NODM) in patients with COVID-19 in a tertiary care hospital.

It was a retrospective descriptive study carried out in Lady Reading Hospital Peshawar, Khyber Pakhtunkhwa province of Pakistan from November 2021 to April 2022. All patients having new onset Diabetes Mellitus (NODM) were identified among a total of 300 patients admitted to the hospital with COVID-19 infection. Patients' data including relevant investigations were accessed through the hospital management information system (HMIS). SPSS version-23 was used for data entry and statistical analysis.

Out of 300 COVID-19 patients included in the study, 163 (54.3%) were female and 137(45.7%) were male. The mean age of the patients was 56.80±13.72 (IQR 15) years. Frequency of the new onset diabetes was 44(14.7%); 19 (6.33%) male and 25(8.33%) female. Among the 44 NODM patients, the majority (57%) were female (p=0.720). Most (64%) of the patients with new-onset DM were in the middle age (p=0.018).

A significant number of patients with COVID-19 infection are prone to develop new-onset diabetes during their admission to the hospital.

Background Effective management of both acute and post-acute sequelae of SARS-CoV-2 is essential, particularly for type 2 diabetes mellitus (T2DM) patients, who are at increased risk of severe pro-inflammatory responses and complications. Persistent symptoms and residual lung and cardiovascular damage in post-coronavirus disease (COVID-19) individuals highlight the need for comprehensive long-term treatment strategies. Conventional treatments, including Remdesivir and glucocorticoids, have limitations, suggesting that further investigation into Ayurvedic therapies could be beneficial, though controlled trials are currently limited. Objectives Evaluate the effectiveness and safety of Ayurveda with the standard of care (SOC) versus SOC in improving symptoms, moderating immune responses (interleukin-6 (IL-6), C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and radiological outcomes in oxygen-dependent, high-risk, non-vaccinated type 2 diabetes COVID-19 patients over 60 days, and thus addressing their heightened vulnerability to severe infections. Methods A controlled trial with 50 diabetic COVID-19 patients, aged 18-80, with an NLR of >= 4, primarily on Remdesivir, was assigned to Group 1 (Add-on Ayurveda+SOC, n=30) or Group 2 (SOC, n=20) based on their voluntary choice with follow-up on days 14, 28, and 60. Parametric outcomes in group analysis were assessed with robust regression and non-parametric outcomes with Cochran-Mantel-Haenszel, log-rank test, and chi-square tests at 95% confidence interval (CI). Results Group 1 exhibited statistically significant improvements in fever, cough, diarrhea, as well as NLR, IL-6, and CRP by 14 days, and in anosmia, loss of taste, shortness of breath, general weakness, and headache by 60 days. Though the sample size is small, notable improvements can be seen in troponin levels in Group 1 at 28 and 60 days. High-resolution computer tomography COVID-19 reporting and data system (HRCT CO-RADS) scores improved more slowly in Group 2 than in Group 1. Survival rates were 96.4% for Group 1 and 90% for Group 2. Numbers were too small for reliable comparisons at 60 days.  Conclusion The add-on Ayurveda group showed a better symptomatic response, and faster normalization in inflammatory markers, including IL-6 and NLR by 14 days, and cardiac markers by 28 days. Minimal clinical and no laboratory adverse events were observed. This study supports the need for a randomized, double-blind trial.

Telemedicine has aided patients with diabetes during the COVID-19 pandemic in receiving better healthcare services. However, despite its numerous benefits, the use of this technology has faced several challenges. This study aimed to identify the challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic.

This scoping review was conducted in 2024. Relevant articles published between 2020 and 2023 were searched in databases including PubMed, Scopus, Web of Science, ProQuest, and the Cochrane Library. Initially, 822 articles were retrieved, and after screening 21 articles were selected.

The challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic were categorized into the clinical, individual, organizational, and technical challenges. The clinical challenges included the lack of physical examinations and unavailability of patients' medical history. The individual challenges contained difficulties in using smart phones by patients and their low level of literacy. The organizational challenges were related to insufficient laws about obtaining patient consent and limited reimbursement for telemedicine services, and the technical challenges included limited access to the high-speed Internet services and inadequate technical infrastructure for telemedicine services. Most studies highlighted the role of individual and organizational challenges in using this technology.

Considering the numerous challenges experienced in using telemedicine for patients with diabetes during the COVID-19 pandemic, it seems that more attention should be paid to address each of these challenges to improve the actual usage, service quality, and user acceptance of telemedicine technology. This, in turn, can lead to saving costs and improving the health status and quality of life of patients with diabetes.

The aim of the study was to determine the association between coronavirus disease 2019 (COVID-19) infection and diabetes management indices in patients with type 2 diabetes mellitus.

A single-center, retrospective, observational study of patients with type 2 diabetes mellitus at Kenwakai Hospital (Nagano, Japan) was conducted. Data of 95 patients (mean age, 72 ± 12 years; men, 67.4%) who visited between March 1, 2019 and February 28, 2022 were obtained from the hospital's electronic information system. COVID-19 was diagnosed by a chemiluminescent enzyme immunoassay (CLEIA).

There was no association between COVID-19 infection and age, sex, hemodialysis treatment status, or the Charlson Comorbidity Index. After adjustment for possible confounding factors, the incidence of COVID-19 infection was significantly correlated with HbA1c ≥7.0% (odds ratio [OR], 5.51; 95% confidence interval [CI], 1.30-23.26).

The results suggest an association between high HbA1c levels and COVID-19 infection in patients with type 2 diabetes mellitus. Appropriate management of diabetes mellitus, focusing on HbA1c levels, may help prevent COVID-19 infection and severe disease after infection.

Background: The COVID-19 pandemic has caused severe health issues worldwide and contributed to huge financial losses. Key comorbidities linked to an increased risk of severe COVID-19 and higher mortality rates include cardio-metabolic disorders such as type 1 and type 2 diabetes mellitus (T1DM and T2DM), atherosclerotic cardiovascular disease, chronic kidney disease, hypertension, heart failure, and obesity. The persistence of symptoms even after the acute phase is over is termed long COVID-19 syndrome. This study aimed to evaluate the relationship between long COVID-19 syndrome and the development of insulin resistance in previously non-diabetic patients. Methods: A prospective observational study was performed on 143 non-diabetic patients who had tested positive for SARS-CoV-2 infection by a PCR test and were hospitalized in our hospital between January 2020 and December 2022. The clinical and para-clinical data at 0, 4, and 12 months of hospital admission for post-COVID-19 infection follow-up was collected and labeled as t0, t4, and t12. Blood glucose, insulin, and C-peptide levels were measured at the beginning and further at 2, 5, 10, and 30 min after the intravenous arginine stimulation test. Similarly, BMI was calculated, and hs-CRP and ESR levels were noted. The results obtained were statistically analyzed. Results: More than one-third (30.7%) of the included patients developed long COVID-19 syndrome. It was found that 75% of patients with long COVID-19 hospitalized in our clinic developed diabetes within a year of acute infection with COVID-19; therefore, it can be said that the presence of long COVID-19 is a major risk for an altered metabolic status, which can cause diabetes. When comparing the glycemia levels (106 mg/dL) with the BMI at t0, t4, and t12 time intervals, the p-values were found to be 0.214, 0.042, and 0.058, respectively. Almost 62% of the patients having BMI > 30 kg/m2 were found to have an increase in blood glucose levels at 1 year. Similarly, insulin resistance was noted during this interval. A negative correlation of 0.40 for hsCRP and 0.38 for ESR was noted when compared with acute infection with COVID-19. Conclusions: The association between long COVID-19 and insulin resistance highlights the varied and widespread impacts of SARS-CoV-2 infection. Addressing the complexities of long COVID-19 requires a holistic strategy that encompasses both respiratory and metabolic considerations, which is crucial for enhancing the well-being of those enduring this persistent condition.

Our study aimed to describe the group of severe COVID-19 patients at an institutional level, and determine factors associated with different outcomes.

A retrospective chart review of patients admitted with severe acute hypoxic respiratory failure due to COVID-19 infection. Based on outcomes, we categorized 3 groups of severe COVID-19: (1) Favorable outcome: progressive care unit admission and discharge (2) Intermediate outcome: ICU care (3) Poor outcome: in-hospital mortality.

Eighty-nine patients met our inclusion criteria; 42.7% were female. The average age was 59.7 (standard deviation (SD):13.7). Most of the population were Caucasian (95.5%) and non-Hispanic (91.0%). Age, sex, race, and ethnicity were similar between outcome groups. Medicare and Medicaid patients accounted for 62.9%. The average BMI was 33.5 (SD:8.2). Moderate comorbidity was observed, with an average Charlson Comorbidity index (CCI) of 3.8 (SD:2.6). There were no differences in the average CCI between groups(p = 0.291). Many patients (67.4%) had hypertension, diabetes (42.7%) and chronic lung disease (32.6%). A statistical difference was found when chronic lung disease was evaluated; p = 0.002. The prevalence of chronic lung disease was 19.6%, 27.8%, and 40% in the favorable, intermediate, and poor outcome groups, respectively. Smoking history was associated with poor outcomes (p = 0.04). Only 7.9% were fully vaccinated. Almost half (46.1%) were intubated and mechanically ventilated. Patients spent an average of 12.1 days ventilated (SD:8.5), with an average of 6.0 days from admission to ventilation (SD:5.1). The intermediate group had a shorter average interval from admission to ventilator (77.2 hours, SD:67.6), than the poor group (212.8 hours, SD:126.8); (p = 0.001). The presence of bacterial pneumonia was greatest in the intermediate group (72.2%), compared to the favorable group (17.4%), and the poor group (56%); this was significant (p<0.0001). In-hospital mortality was seen in 28.1%.

Most patients were male, obese, had moderate-level comorbidity, a history of tobacco abuse, and government-funded insurance. Nearly 50% required mechanical ventilation, and about 28% died during hospitalization. Bacterial pneumonia was most prevalent in intubated groups. Patients who were intubated with a good outcome were intubated earlier during their hospital course, with an average difference of 135.6 hours. A history of cigarette smoking and chronic lung disease were associated with poor outcomes.

COVID-19 has generated a global impact due to its contagiousness and high lethality rates, with a large number of deaths occurring in intensive care units (ICUs). This study aimed to verify the occurrence of and understand the factors related to mortality in adult patients with COVID-19 admitted to the ICU in a tertiary hospital. This is a retrospective cohort study, which included COVID-19 patients admitted between March 2020 and December 2021. A total of 588 patients were included, of whom the majority (55.27%) did not survive. Invasive mechanical ventilation was the strongest predictor of the risk of death in the ICU with OR = 97.85 (95% CI = 39.10-244.86; p < 0.001), along with age and Simplified Acute Physiology Score 3 (SAPS3). The length of the ICU stay was protective. Evaluating patients on invasive mechanical ventilation in isolation, using an adjusted model, we found the following risk factors: use of vasopressin, renal replacement therapy, red cell distribution width > 15, use of hydrocortisone, and age in years. Protective factors included the days of mechanical ventilation use, being admitted from another service, and being of female sex. Identifying early predictors of mortality in patients with COVID-19 who require hospitalization is essential in the search for actions to prevent and manage complications, which can increase the survival of these patients and reduce the impact on health services.

Post-COVID-19 conditions (long COVID) has impacted many individuals, yet risk factors for this condition are poorly understood. This retrospective analysis of 88,943 COVID-19 patients at a multi-state US health system compares phenotypes, laboratory tests, medication orders, and outcomes for 1,086 long-COVID patients and their matched controls. We found that history of chronic pulmonary disease (CPD) (odds ratio: 1.9, 95% CI: [1.5, 2.6]), migraine (OR: 2.2, [1.6, 3.1]), and fibromyalgia (OR: 2.3, [1.3, 3.8]) were more common for long-COVID patients. During the acute infection phase long COVID patients exhibited high triglycerides, low HDL cholesterol, and a high neutrophil-lymphocyte ratio; and were more likely hospitalized (5% vs. 1%). Our findings suggest severity of acute infection and history of CPD, migraine, chronic fatigue syndrome (CFS), or fibromyalgia as risk factors for long COVID. These results suggest that suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug-target network and dynamic network-based drug-repurposing analysis, ubiquitin-carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.

The field of nanophotonics has advanced and can be utilized as a method to detect different infectious diseases. The introduction of multiplex nanophotonic diagnostics has enabled the speedy and simultaneous detection of viral infections and specific biomarkers. The quick reaction times, high sensitivity, and specificity of multiplex nanophotonic diagnostics enable real-time identification of viruses without the need for nucleic acid amplification. This review presents an overview of nanophotonic tools used to identify diseases and particular biomarkers. The paper also examines possible research areas for the development of unique, cutting-edge multiplex nanophotonic diagnostics capable of concurrently detecting various diseases or biomarkers/biomolecules. Furthermore, it discusses barriers to further advancement and offers insight into anticipated trends.

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.

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.

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.

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.

After fully lifting coronavirus disease 2019 (COVID-19) pandemic control measures in mainland China in 12/2022, the incidence of COVID-19 has increased markedly, making it difficult to meet the general time-in-range (TIR) requirement. We investigated a more clinically practical TIR threshold and examined its association with the prognosis of COVID-19 patients with type 2 diabetes(T2D).

63 T2D patients complicated with COVID-19 were evaluated. Patients were divided into favorable outcome group and adverse outcome group according to whether achieving composite endpoint (a >20-day length of stay, intensive care unit admission, mechanical ventilation use, or death). TIR, the time-below-range (TBR) and the time-above-range (TAR) were calculated from intermittently scanned continuous glucose monitoring. Logistic regression analysis and other statistical methods were used to analyze the correlation between glucose variability and prognosis to establish the appropriate reference range of TIR.

TIR with thresholds of 80 to 190 mg/dL was significantly associated with favorable outcomes. An increase of 1% in TIR is connected with a reduction of 3.70% in the risk of adverse outcomes. The Youden index was highest when the TIR was 54.73%, and the sensitivity and specificity were 58.30% and 77.80%, respectively. After accounting for confounding variables, our analysis revealed that threshold target ranges (TARs) ranging from 200 mg/dL to 230 mg/dL significantly augmented the likelihood of adverse outcomes.

The TIR threshold of 80 to 190 mg/dL has a comparatively high predictive value of the prognosis of COVID-19. TIR >54.73% was associated with a decreased risk of adverse outcomes. These findings provide clinically critical insights into possible avenues to improve outcomes for COVID-19 patients with T2D.