To verify the effect of 12 weeks of Combined Training (CT) in patients suffering from COVID-19 of mild to moderate intensity.

69 participants diagnosed with mild to moderate COVID-19 were evaluated, with shortness of breath as the main symptom. All of them were sent by the Centro de Atendimento ao Funcionário do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (CEAC-HCFMUSP). The sample was divided into three groups: Group 1 (G1) - 26 patients diagnosed with COVID-19 evaluated before and after combined training together with nutritional guidance. Group 2 (G2) - 21 patients diagnosed with COVID-19 were evaluated before and after 12 weeks. Patients in G2 (control) did not participate in the protocol but were instructed to train outside the hospital and did not receive nutritional guidance. Group 3 (G3) - 22 patients diagnosed with COVID-19 were evaluated before and after combined training along with nutritional monitoring and post-workout whey protein supplementation throughout the duration of the protocol.

The three groups did not have significant statistical differences when compared to each other, but there was significant intragroup improvement in the analyzed variables. There was an improvement in cardiorespiratory, metabolic, and muscular fitness. Furthermore, late symptoms of the disease were reduced at the end of the program.

The results of the dependent variables analyzed were significant within groups, CT was an efficient training model in improving the patient's general condition (fatigue and dyspnea) when training was controlled with supervision.

Diabetes mellitus (DM) is recognized and classified as a group of conditions marked by persistent high blood glucose levels. It is also an inflammatory condition that may influence concurrent disease states, including Coronavirus Disease 2019 (COVID-19). Currently, no effective drug has been found to treat COVID-19, especially in DM patients. Many herbal medicines, such as the well-known Andrographis paniculata, have been explored as drugs and complementary therapies due to their antidiabetic, antibacterial, antiviral, anti-inflammatory, and immunomodulatory effects. This study aimed to examine the potential of herbal medicines as complementary therapy in DM patients with COVID-19 complications, drawing from in-vitro and in-vivo investigations. This study analyzed articles published within the last 15 years using keywords including "herbal medicines", "COVID-19", "Diabetes Mellitus", "antidiabetics", "antiviral", and "anti-inflammatory". The results showed that several herbal medicines could serve as complementary therapy for DM patients with COVID-19 complications. These include Andrographis paniculata, Ageratum conyzoides, Artocarpus altilis, Centella asiatica, Momordica charantia, Persea gratissima, Phyllanthus urinaria, Physalis angulata, Tinospora cordifolia, and Zingiber zerumbet. Herbal medicines may serve as a complementary therapy for DM patients with COVID-19, but these claims need experimental validation in infection models and among affected patients.

Several epidemiological studies have appreciated the impact of "duration" and "level" of hyperglycemia on the initiation and development of chronic complications of diabetes. However, glycemic profiles could not fully explain the presence/absence and severity of diabetic complications. Genetic issues and concepts of "hyperglycemic memory" have been introduced as additional influential factors involved in the pathobiology of late complications of diabetes. In the extended phase of significant diabetes randomized, controlled clinical trials, including DCCT/EDIC and UKPDS, studies have concluded that the quality of glycemic or metabolic control at the early time around the diabetes onset could maintain its protective or detrimental impact throughout the following diabetes course. There is no reliable indication of the mechanism by which the transient exposure to a given glucose concentration level could evoke a consistent cellular response at target tissues at the molecular levels. Some biological phenomena, such as the production and the concentration of advanced glycation end products (AGEs), reactive oxygen species (ROS) and protein kinase C (PKC) pathway activations, epigenetic changes, and finally, the miRNAs-mediated pathways, may be accountable for the development of hyperglycemic memory. This work summarizes evidence from previous experiments that may substantiate the hyperglycemic memory soundness by its justification in molecular terms.

The coronavirus disease (COVID-19) is an infectious disease caused by the newly discovered SARS-CoV-2 virus. Patients diagnosed with COVID-19 experience several complications including hypertension or elevated blood pressure which is a serious medical condition that significantly increases the risks of heart, brain, and kidney diseases.

To assess the prevalence and control of hypertension in COVID-19 patients.

Cross-sectional descriptive hospital-based study conducted in an isolation center at Atbara Teaching Hospital in 2021. The data were collected by interviewing patients through a close-ended questionnaire and analyzed using a statistical computerized program (SPSS version 21).

The main results of the study revealed that the prevalence of blood pressure amongst patients diagnosed with COVID-19 was mild 45%, moderate 17.7%, and severe 10%; of the cases, 25.7% were newly discovered hypertension cases, of the cases 26.7% were diabetic patients; and 70.7% of the study group full recovered form COVID-19 at discharge.

The study concluded that most of the study group had hypertension with COVID-19, some of them were newly discovered cases of hypertension and also had diabetes mellitus which indicates that COVID-19 may cause the onset of hypertension.

Evidence shows that diabetes raises the probability of contracting COVID-19 and associated complications. We hypothesize that metformin, being pleiotropic, may improve COVID-19 in diabetics.

A retrospective cohort study was conducted with 421 COVID-19 patients with diabetes, hospitalized between 1st April 2020 and 31st March 2022 in a tertiary-care hospital. Patients with metformin or its combination constituted the study cohort (SC; n = 221), while other antidiabetics constituted the reference cohort (RC; n = 200).

SC and RC were matched for mean age ± SD (SC: 53.3 ± 5.7 vs. RC: 54.3 ± 8.2 years). The mean length of hospitalization (days) was significantly shorter in SC (9.0 ± 5.7) than in RC (12.7 ± 6) (p < 0.02). Metformin use was associated with reduction in mortality risk (OR: 0.106, 95% CI = 0.039-0.287; p < 0.001). Moreover, SC also improved levels of LDH (OR: 0.243, 95% CI = 0.104-0.566; p < 0.001), CRP (OR: 0.281, 95% CI = 0.120-0.659; p < 0.004), and D-dimer (OR: 0.220, 95% CI = 0.089-0.539; p < 0.001) than RC. The calculated number needed to treat for metformin was 3.1.

Metformin users have a decrease in hospital stay and mortality rates and improvement in LDH, CRP, and D-dimer levels. Therefore, metformin might protect against mortality in COVID-19 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.

SARS-CoV-2 first appeared in Wuhan, China, in December 2019. Looking at the prevalence data in the world and in Indonesia, the highest mortality rate due to COVID-19 involves age, gender and comorbidities such as diabetes mellitus. Severity of the condition also refers to coagulation abnormalities, such as abnormal prothrombin time values.

This systematic review study and meta-analysis used online literature sourced from PubMed, Science Direct, EBSCO, Cochrane and Google Scholar. The literature used here is literature that has data on age, sex and prothrombin time of COVID-19 patients with diabetes mellitus whose quality is assessed by the NOS (Newcastle-Ottawa Scale) criteria and processing data using Review Manager 5.4.

Out of 8711 literatures that were traced from various search sources, there were 45 literatures that were included in this study. The results of the analysis on age showed the Standardized Mean Difference (SMD) value of 0.45 and P <0.0001 (95% CI: 0.23-0.68), the gender analysis showed an Odds Ratio (OR) value of 3.28 and P = 0.01 (95% CI: 1.26-8.52) and the prothrombin time analysis showed SMD values of 0.41 and P = 0.07 (95%CI = -0.03-0.85).

Patients with COVID-19 who have DM have a higher risk compared to those without DM. Among COVID-19 patients with DM admitted to hospitals, they were older compared to those without DM and prothrombin time values similar but slightly higher in COVID-19 patients with DM.

Diabetes, a chronic disease worldwide, may be associated with a poorer prognosis in patients with coronavirus disease 2019 (COVID-19). While some antihyperglycemic medications may be beneficial, others may increase the risk of adverse clinical outcomes of COVID-19. We aimed to analyze the effect of antihyperglycemic medications on COVID-19.

We searched the Web of Science, Cochrane Library, EMBASE, PubMed, and Scopus databases from December 2019 to June 2022 to identify literature related to patients with COVID-19 and type 2 diabetes mellitus (T2DM) treated with antihyperglycemic medications.

56 studies were included in the analysis. Metformin (OR 0.66; 95% CI 0.58-0.74; p < 0.05), Glucagon-like peptide-1 receptor agonist (GLP-1ra) (OR 0.73; 95% CI 0.59-0.91; p < 0.05), and sodium-dependent glucose transporters 2 inhibitor (SGLT 2i) (OR 0.77; 95% CI 0.69-0.87; p < 0.05) were associated with lower mortality risk, while insulin was associated with increased mortality risk (OR 1.40; 95% CI 1.26-1.55; p < 0.05). Meanwhile, metformin (OR 0.65; 95% CI 0.50-0.85; p < 0.05) and GLP-1ra (OR 0.84; 95% CI 0.76-0.94; p < 0.05) were significantly associated with decreased severe manifestation risk. What's more, metformin (OR 0.77; 95% CI 0.62-0.96; p < 0.05), GLP-1ra (OR 0.86; 95% CI 0.81-0.92; p < 0.05), and SGLT 2i (OR 0.87; 95% CI 0.79-0.97; p < 0.05) were also associated with a decreased risk of hospitalization, but insulin were associated with an increased risk of hospitalization (OR 1.31; 95% CI 1.12-1.52; p < 0.05). Nevertheless, the results of the subgroup analyses showed that the effects of different glucose-lowering agents on COVID-19 may be related to in-hospital use or out-hospital use, elderly or non-elderly patients use, and different geography.

Metformin, GLP-1ra, and SGLT 2i have shown a positive effect on clinical outcomes in COVID-19, particularly in non-elderly individuals. However, insulin use may pose a higher risk, especially in elderly patients, so need with caution. Meanwhile, DPP-4i, TZD, α-GLUi, and sulfonylureas appeared to have a neutral effect. These results need to be validated in future clinical studies.

It has been reported that diabetes and hypertension increase the adverse outcomes of coronavirus disease 2019 (COVID-19). Aside from the inherent factors of diabetes and hypertension, it remains unclear whether antidiabetic or antihypertensive medications contribute to the increased adverse outcomes of COVID-19. The effect of commonly used antidiabetic and antihypertensive medications on COVID-19 outcomes has been inconsistently concluded in existing observational studies. Conducting a systematic study on the causal relationship between these medications and COVID-19 would be beneficial in guiding their use during the COVID-19 pandemic.

We employed the 2-sample Mendelian randomization approach to assess the causal relationship between 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and 3 commonly used antihypertensive medications (calcium channel blockers [CCB], ACE inhibitors, β-receptor blockers [BB]), and COVID-19 susceptibility, hospitalization, and severe outcomes. The genetic variations in the drug targets of the 5 antidiabetic medications and 3 antihypertensive medications were utilized as instrumental variables. European population-specific genome-wide association analysis (GWAS) data on COVID-19 from the Host Genetics Initiative meta-analyses were obtained, including COVID-19 susceptibility (n = 2597,856), COVID-19 hospitalization (n = 2095,324), and COVID-19 severity (n = 1086,211). The random-effects inverse variance-weighted estimation method was employed as the primary assessment technique, with various sensitivity analyses conducted to evaluate heterogeneity and pleiotropy.

There were no potential associations between the genetic variations in the drug targets of the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity (all P > .016).

The findings from this comprehensive Mendelian randomization analysis suggest that there may be no causal relationship between the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity.

The SARS-CoV-2 virus first emerged in China in December 2019 and quickly spread worldwide. Despite the absence of a vaccination or authorized drug specifically developed to combat this infection, certain medications recommended for other diseases have shown potential effectiveness in treating COVID-19, although without definitive confirmation. This review aims to evaluate the existing literature on the efficacy of these medications against COVID-19. The review encompasses various potential treatments, including antiviral medications, anti-malaria and anti-rheumatic drugs, vaccines, corticosteroids, non-steroidal anti-inflammatory drugs (NSAIDs), antipyretic and analgesic medicines, antiparasitic drugs, and statins. The analysis also addresses the potential benefits and drawbacks of these medications, as well as their effects on hypertension and diabetes. Although these therapies hold promise against COVID-19, further research, including suitable product production or clinical testing, is needed to establish their therapeutic efficacy.

Intracellularly, membrane-less organelles are formed by spontaneous fusion and fission of macro-molecules in a process called phase separation, which plays an essential role in cellular activities. In certain disease states, such as cancers and neurodegenerative diseases, aberrant phase separations take place and participate in disease progression. Chromatin structure-related proteins, based on their characteristics and upon external stimuli, phase separate to exert functions like genome assembly, transcription regulation, and signal transduction. Moreover, many chromatin structure-related proteins, such as histones, histone-modifying enzymes, DNA-modifying enzymes, and DNA methylation binding proteins, are involved in epigenetic regulations through phase separation. This review introduces phase separation and how phase separation affects epigenetics with a focus on chromatin structure-related molecules.

The COVID-19 lockdown influenced the glycemic control and other metabolic parameters in people with type 1 and 2 diabetes mellitus.

To study the effects of COVID-19 lockdown on glycemic control in people with type 2 diabetes mellitus (T2DM).

Our study group included 120 Romanian people with T2DM from both urban and rural areas. We employed a structured questionnaire with multiple-choice to collect data about DM management during lockdown, the interaction with their diabetologist, the access to treatment, and what other factors influenced their DM management during the lockdown.

We did not observe an increase of numbers of hyper or hypoglycemia during the restriction period in people with T2DM. The number of glycemic imbalances was higher in people treated with insulin than those with oral antidiabetics (OAD) (p=0.003, X2=8.91). Regarding the causes of imbalances, we did not obtain a significant difference during the restriction period, neither between patients following treatment with insulin nor with OAD. On the contrary, we observed that only 26.7% of people with T2DM managed to maintain their weight or lost weight vs 73.3% patients who gained several extra kg (p<0.001, X2=52.26).

The findings of this study have demonstrated that in people with T2DM, the COVID-19 lockdown determines better glycemic control among patients treated with OAD compared to those treated with insulin therapy. Anxiety, stress, and emotions were the main reasons that led to the increase in glycemic values of these patients. Also, most patients have gained weight either due to lack of physical activity or due to stress.

An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes patients. Diabetes and heart patients need real-time and remote monitoring and recommendation-based medical assistance. Such human-centered smart healthcare systems can not only provide continuous medical assistance to diabetes patients but can also reduce overall medical expenses. In the last decade, machine learning has been successfully implemented to design more accurate and precise medical applications. In this paper, a smart sensing technologies-based architecture is proposed that uses AI and the Internet of Things (IoT) for continuous monitoring and health assistance for diabetes patients. The designed system senses various health parameters, such as blood pressure, blood oxygen, blood glucose (non-invasively), body temperature, and pulse rate, using a wrist band. We also designed a non-invasive blood sugar sensor using a near-infrared (NIR) sensor. The proposed system can predict the patient's health condition, which is evaluated by a set of machine learning algorithms with the support of a fuzzy logic decision-making system. The designed system was validated on a large data set of 50 diabetes patients. The results of the simulation manifest that the random forest classifier gives the highest accuracy in comparison to other machine learning algorithms. The system predicts the patient's condition accurately and sends it to the doctor's portal.

Aim: Conditions linked to metabolic syndrome, such as obesity, hypertension, insulin resistance, and dyslipidemia, are common in patients with severe coronavirus disease 2019 (COVID-19). These conditions can act synergistically to contribute to negative outcomes. We describe and analyze the relationship between metabolic syndrome and COVID-19 severity in terms of risk of hospitalization. Methods: We designed a retrospective, cross-sectional study, including patients with confirmed COVID-19 diagnosis. Clinical and laboratory parameters regarding metabolic syndrome were collected. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was used to assess insulin resistance. The outcome was needed for hospitalization. Logistic regression was used to calculate odds ratios, and to determine the association between variables and risk of hospitalization. Advanced approaches using machine learning were also used to identify and interpret the effects of predictors on the proposed outcome. Results: We included 2716 COVID-19 patients with a mean age of 61.8 years. Of these, 48.9% were women, 28.9% had diabetes, and 50.6% were diagnosed with metabolic syndrome. Overall, 212 patients required hospitalization. Patients with metabolic syndrome had a 58% greater chance of hospitalization if they were men, 32% if they had metabolic syndrome, and 23% if they were obese. Machine learning methods identified body mass index, metabolic syndrome, systolic blood pressure, and HOMA-IR as the most relevant features for our predictive model. Conclusion: Metabolic syndrome and its related biomarkers increase the odds for a severe clinical course of COVID-19 and the need for hospitalization. Machine learning methods can aid understanding of the effects of single features when assessing risks for a given outcome.

The effects of diabetes medications on COVID-19 hospitalization outcomes have not been consistent. We sought to determine the effect of metformin, dipeptidyl peptidase-4 inhibitors (DPP-4i), and insulin on admission to the intensive care unit (ICU), need for assisted ventilation, development of renal insufficiency, and mortality in patients admitted with COVID-19 infection after controlling for clinical variables and other relevant diabetes-related medications in patients with type 2 diabetes mellitus (DM).

This was a retrospective study of patients hospitalized with COVID-19 from a single hospital system. Univariate and multivariate analyses were performed that included demographic data, glycated hemoglobin, kidney function, smoking status, insurance, Charlson comorbidity index, number of diabetes medications, and use of angiotensin-converting enzyme inhibitors and statin prior to admission and glucocorticoids during admission.

A total of 529 patients with type 2 DM were included in our final analysis. Neither metformin nor DPP4i prescription was associated with ICU admission, need for assisted ventilation, or mortality. Insulin prescription was associated with increased ICU admission but not with need for assisted ventilation or mortality. There was no association of any of these medications with development of renal insufficiency.

In this population, limited to type 2 DM and controlled for multiple variables that have not been consistently studied (such as a measure of general health, glycated hemoglobin, and insurance status), insulin prescription was associated with increased ICU admission. Metformin and DPP4i prescriptions did not have an association with the outcomes.

This study aims to describe the clinical characteristics, laboratory data and complications of hospitalized COVID-19 patients with type 2 diabetes mellitus (T2DM) since epidemic prevention and control optimization was adjusted in December 2022 in China.

This retrospective multicenter study included 298 patients with confirmed type 2 diabetes mellitus with or without COVID-19. We collected data from the first wave of the pandemic in The Fifth Affiliated Hospital of Guangzhou Medical University, Loudi Central Hospital and The First People's Hospital of Xiangtan from December 1, 2022 to February 1, 2023. We extracted baseline data, clinical symptoms, acute complications, laboratory findings, treatment and outcome data of each patient from electronic medical records.

For among 298 hospitalized patients with type 2 diabetes, 136 (45.6%) were COVID-19 uninfected, and 162 (54.4%) were COVID-19 infected. We found that the incidence of cough, fatigue, fever, muscle soreness, sore throat, shortness of breath, hyposmia, hypogeusia and polyphagia (all p<0.01) were significantly higher in the exposure group. They showed higher levels of ketone (p=0.04), creatinine (p<0.01), blood potassium (p=0.01) and more diabetic ketoacidosis (p<0.01). Patients with COVID-19 less use of metformin (p<0.01), thiazolidinediones (p<0.01) and SGLT2 (p<0.01) compared with patients without COVID-19.

COVID-19 patients with diabetes showed more severe respiratory and constitutional symptoms and an increased proportion of hyposmia and hypogeusia. Moreover, COVID-19 patients with diabetes have a higher incidence of acute complications, are more prone to worsening renal function, and are more cautious about the use of antidiabetic drugs.

To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death.

This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach.

A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out.

Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease.

PROSPERO registration no. CRD42020193692.

This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD).

The re-emergence of Zika virus (ZIKV) remains a major public health threat that has raised worldwide attention. Accumulating evidence suggests that ZIKV can cause serious pathological changes to the human nervous system, including microcephaly in newborns. Recent studies suggest that metformin, an established treatment for diabetes may play a role in viral infection; however, little is known about the interactions between ZIKV infection and metformin administration. Using fluorescent ZIKV by flow cytometry and immunofluorescence imaging, we found that ZIKV can infect microglia in a dose-dependent manner. Metformin diminished ZIKV replication without the alteration of viral entry and phagocytosis. Our study demonstrated that metformin downregulated ZIKV-induced inflammatory response in microglia in a time- and dose-dependent manner. Our RNA-Seq and qRT-PCR analysis found that type I and III interferons (IFN), such as IFNα2, IFNβ1 and IFNλ3 were upregulated in ZIKV-infected cells by metformin treatment, accompanied with the downregulation of GBP4, OAS1, MX1 and ISG15. Together, our results suggest that metformin-mediated modulation in multiple pathways may attribute to restraining ZIKV infection in microglia, which may provide a potential tool to consider for use in unique clinical circumstances.

Globally, COVID-19 affected radiopharmaceutical laboratories. This study sought to determine the economic, service, and research impacts of COVID-19 on radiopharmacy. This online survey was conducted with the participation of employees from nuclear medicine and radiopharmaceutical companies. The socioeconomic status of the individuals was collected. The study was participated by 145 medical professionals from 25 different countries. From this work, it is evident that 2-deoxy-2-[18F]fluoro-D-glucose (2-[18F]FDG), and 99mTc-labeled macro aggregated albumin 99mTc-MAA were necessary radiopharmaceuticals used by 57% (83/145and 34% (49/145;) respondents, respectively for determining how COVID infections affect a patient's body. The normal scheduling procedure for the radiopharmacy laboratory was reduced by more than half (65%; 94/145). In COVID-19, 70% (102/145) of respondents followed the regulations established by the local departments. Throughout the pandemic, there was a 97% (141/145) decrease in all staffing recruitment efforts. The field of nuclear medicine research, as well as the radiopharmaceutical industry, were both adversely affected by COVID-19.

The coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2 infection has become a global pandemic due to the high viral transmissibility and pathogenesis, bringing enormous burden to our society. Most patients infected by SARS-CoV-2 are asymptomatic or have mild symptoms. Although only a small proportion of patients progressed to severe COVID-19 with symptoms including acute respiratory distress syndrome (ARDS), disseminated coagulopathy, and cardiovascular disorders, severe COVID-19 is accompanied by high mortality rates with near 7 million deaths. Nowadays, effective therapeutic patterns for severe COVID-19 are still lacking. It has been extensively reported that host metabolism plays essential roles in various physiological processes during virus infection. Many viruses manipulate host metabolism to avoid immunity, facilitate their own replication, or to initiate pathological response. Targeting the interaction between SARS-CoV-2 and host metabolism holds promise for developing therapeutic strategies. In this review, we summarize and discuss recent studies dedicated to uncovering the role of host metabolism during the life cycle of SARS-CoV-2 in aspects of entry, replication, assembly, and pathogenesis with an emphasis on glucose metabolism and lipid metabolism. Microbiota and long COVID-19 are also discussed. Ultimately, we recapitulate metabolism-modulating drugs repurposed for COVID-19 including statins, ASM inhibitors, NSAIDs, Montelukast, omega-3 fatty acids, 2-DG, and metformin.

The past two decades have witnessed telemedicine becoming a crucial part of health care as a method to facilitate doctor-patient interaction. Due to technological developments and the incremental acquisition of experience in its use, telemedicine's advantages and cost-effectiveness has led to it being recognised as specifically relevant to diabetology. However, the pandemic created new challenges for healthcare systems and the rate of development of digital services started to grow exponentially. It was soon discovered that COVID-19-infected patients with diabetes had an increased risk of both mortality and debilitating sequelae. In addition, it was observed that this higher risk could be attenuated primarily by maintaining optimal control of the patient's glucose metabolism. As opportunities for actual physical doctor-patient visits became restricted, telemedicine provided the most convenient opportunity to communicate with patients and maintain delivery of care. The wide range of experiences of health care provision during the pandemic has led to the development of several excellent strategies regarding the applicability of telemedicine across the whole spectrum of diabetes care. The continuation of these strategies is likely to benefit clinical practice even after the pandemic crisis is over.

To characterize COVID-19 patients in Indiana, United States, and to evaluate their demographics and comorbidities as risk factors to COVID-19 severity.

EHR data of 776 936 COVID-19 cases and 1 362 545 controls were collected from the COVID-19 Research Data Commons (CoRDaCo) in Indiana. Data regarding county population and per capita income were obtained from the US Census Bureau. Statistical analysis was conducted to determine the association of demographic and clinical variables with COVID-19 severity. Predictive analysis was conducted to evaluate the predictive power of CoRDaCo EHR data in determining COVID-19 severity.

Chronic obstructive pulmonary disease, cardiovascular disease, and type 2 diabetes were found in 3.49%, 2.59%, and 4.76% of the COVID-19 patients, respectively. Such COVID-19 patients have significantly higher ICU admission rates of 10.23%, 14.33%, and 11.11%, respectively, compared to the entire COVID-19 patient population (1.94%). Furthermore, patients with these comorbidities have significantly higher mortality rates compared to the entire COVID-19 patient population. Health disparity analysis suggests potential health disparities among counties in Indiana. Predictive analysis achieved F1-scores of 0.8011 and 0.7072 for classifying COVID-19 cases versus controls and ICU versus non-ICU cases, respectively.

Black population in Indiana was more adversely affected by COVID-19 than the White population. This is consistent to findings from existing studies. Our findings also indicate other health disparities in terms of demographic and economic factors.

This study characterizes the relationship between comorbidities and COVID-19 outcomes with respect to ICU admission across a large COVID-19 patient population in Indiana.

Attempts were made to review the literature on diabetic patients who experience complications when they contract COVID-19, and to determine whether ethnicity and other risk factors play an important role in the development of symptoms and their severity, as well as responding to medications. A literature search was performed using five keywords, namely COVID-19, diabetes, ethnicity, medications, and risk factors between January 2019 and December 2020 using electronic databases such as PubMed, Science Direct, Google Scholar, Springer Link, and Scopus. Forty studies were included. The review indicated that diabetes was a significant risk factor for poorer outcomes and increased mortality associated with COVID-19. There were several risk factors for diabetic patients that increased their likelihood of poorer outcomes associated with COVID-19. These included black and Asian ethnicity, male sex with high BMI. In conclusion, patients with diabetes of black or Asian origin with high BMI, male sex, and older age had an increased risk of poorer outcomes associated with COVID-19. This highlights the importance of considering the history of the patient in prioritising care and treatment.

Diabetes mellitus (DM) and the 2019 coronavirus (COVID-19) appear to interact in both directions. There is mounting proof that patients with DM have a worse COVID-19 prognosis than those without it. Pharmacotherapy is also known to affect in view of the possible interplay between drugs and the pathophysiology of the above conditions in a given patient.

In this review, we discuss the pathogenesis of COVID-19 and its connections with diabetes mellitus. We also analyze the treatment modalities for COVID-19 and diabetes patients. The possible mechanisms of the different medications and their management limitations are also systematically reviewed.

COVID-19 management as well as its knowledge base is changing constantly. The Pharmacotherapy and the choice of drugs also need to be specifically considered in view of the concomitant presence of these conditions in a patient. Anti-diabetic agents must be carefully evaluated in diabetic patients in view of the disease's severity, blood glucose level, appropriate treatment, and other components that could aggravate adverse events. A methodical technique is anticipated to enable the safe and rational use of drug therapy in COVID-19-positive diabetic patients to take.

Diabetic patients are at particular risk of severe COVID-19. Human dipeptidyl peptidase-4 (DPP-4) is a membrane-bound aminopeptidase that regulates insulin release by inactivating incretin. DPP-4 inhibitors (DPP-4is) are therefore used as oral anti-diabetic drugs to restore normal insulin levels. These molecules also have anti-inflammatory and anti-hypertension effects. Recent studies on the interactions of SARS-CoV-2 spike glycoprotein and DPP-4 predict a possible entry route for SARS-CoV-2. Therefore, DPP-4is could be effective at reducing the virus-induced 'cytokine storm', thereby ceasing inflammatory injury to vital organs. Moreover, DPP-4is may interfere with viral entry into host cells. Herein, we have reviewed the efficacy of DPP-4is as potential repurposed drugs to reduce the severity of SARS-CoV-2 infection in patients with diabetes.

Coronavirus disease 2019 (COVID-19) is a new pandemic that the entire world is facing since December of 2019. Increasing evidence has shown that metformin is linked to favorable outcomes in patients with COVID-19. The aim of this study was to address whether outpatient or inpatient metformin therapy for type 2 diabetes mellitus is associated with low in-hospital mortality in patients hospitalized for COVID-19.

We searched studies published in PubMed, Embase, Google Scholar and Cochrane Library up to November 1, 2022. Raw event data extracted from individual study were pooled using the Mantel-Haenszel approach. Odds ratio (OR) or hazard ratio (HR) adjusted for covariates that potentially confound the association using multivariable regression or propensity score matching was pooled by the inverse-variance method. Random effect models were applied for meta-analysis due to variance among studies.

Twenty-two retrospective observational studies were selected. The pooled unadjusted OR for outpatient metformin therapy and in-hospital mortality was 0.48 (95% CI, 0.37-0.62) and the pooled OR adjusted with multivariable regression or propensity score matching was 0.71 (95% CI, 0.50-0.99). The pooled unadjusted OR for inpatient metformin therapy and in-hospital mortality was 0.18 (95% CI, 0.10-0.31), whereas the pooled adjusted HR was 1.10 (95% CI, 0.38-3.15).

Our results suggest that there is a significant association between the reduction of in-hospital mortality and outpatient metformin therapy for type 2 diabetes mellitus in patients hospitalized for COVID-19.

Type 2 diabetes mellitus (T2DM) requires a continues bulk of cares. It is very probable COVID-19 pandemic is affected its healthcare coverage.

The interrupted time series analysis is used to model the trend of diabetes healthcare indices, such as the health worker visits, physician visits, body mass index (MBI), fasting blood sugar (FBS), and hemoglobin A1c (HbA1c), before and after the start of COVID-19 pandemic. The reference of data was the totals of all T2DM patients living in Fars Province, Southern Iran, areas covered by Shiraz University of Medical Science (SUMS), from 2019 to 2020.

A significant decrease for visits by the health workers, and physicians was observed by starting COVID-19 pandemic (β2 = -0.808, P < 0.001, β2 = -0.560, P < 0.001); Nevertheless, the coverage of these services statistically increased by next months (β3 = 0.112, P < 0.001, β3 = 0.053, P < 0.001). A same pattern was observed for the number of BMI, FBS and HbA1c assessments, and number of refer to hospital emergency wards (β3 = 0.105, P < 0.001; β3 = 0.076, P < 0.001; β3 = 0.022, P < 0.001; β3 = 0.106, P < 0.001). The proportion of T2DM patients with HbA1C < 7%, and controlled hypertension during study period was statistically unchanged.

When the COVID-19 pandemic was announced, T2DM healthcare coverage drastically decreased, but it quickly began to rebound. The health monitoring system could not have any noticeable effects on diabetes outcomes.

Recent evidence relating to the impact of COVID-19 on people with diabetes is limited but continues to emerge. COVID-19 pneumonia is a newly identified illness spreading rapidly throughout the world and causes many disabilities and fatal deaths. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery have become prominent, along with the lingering effects of the virus on those directly infected. Diabetes is a commonly identified risk factor that contributes not only to the severity and mortality of COVID-19 patients, but also to the associated complications, including acute respiratory distress syndrome (ARDS) and multi-organ failure. Diabetic patients are highly affected due to increased viral entry into the cells and decreased immunity. Several hypotheses to explain the increased incidence and severity of COVID-19 infection in people with diabetes have been proposed and explained in detail recently. On the other hand, 20-50% of COVID-19 patients reported new-onset hyperglycemia without diabetes and new-onset diabetes, suggesting the two-way interactions between COVID-19 and diabetes. A systematic review is required to confirm diabetes as a complication in those patients diagnosed with COVID-19. Diabetes and diabetes-related complications in COVID-19 patients are primarily due to the acute illness caused during the SARS-CoV-2 infection followed by the release of glucocorticoids, catecholamines, and pro-inflammatory cytokines, which have been shown to drive hyperglycemia positively. This review provides brief insights into the potential mechanisms linking COVID-19 and diabetes, and presents clinical management recommendations for better handling of the disease.

Coronavirus disease (COVID-19) is closely associated with hyperglycemia and a worse prognosis in patients with a previous diagnosis of type 2 diabetes mellitus. A few studies investigated the effects of diabetes treatment regimens in these patients during hospitalization. Here, we evaluate the impact of insulin and non-insulin therapy on glucose control in patients with type 2 diabetes admitted with COVID-19. This is a retrospective study including 359 COVID-19 patients with type 2 diabetes. Patients were divided into 2 groups according to diabetes treatment during hospitalization. The first group included patients treated with insulin only, and the second group patients treated with other antidiabetic agents with or without insulin. Average blood glucose was higher in the insulin-only treatment group (201 ± 66 mg/dL vs 180 ± 71 mg/dL, P = .004), even after excluding mechanically ventilated patients (192 ± 69 vs 169 ± 59 mg/dL, P = .003). In patients with moderate severity of COVID-19, average blood glucose was also significantly higher in the insulin-only treated group (197 ± 76 vs 168 ± 51 mg/dL, P = .001). Most patients (80%) in the combination treatment group received metformin. Moderately affected COVID-19 patients with type 2 diabetes could safely be treated with antihyperglycemic medications with or without insulin.

SARS-CoV-2 invades human cells and leads to COVID-19 by direct associating with angiotensin converting enzyme 2 (ACE2) receptors, the level of which may be increased by treatment with angiotensin-converting enzyme inhibitors (ACEIs) and/or angiotensin receptor blockers (ARBs). This meta-analysis aimed to explore the impact of ACEI/ARB treatment on the clinical outcomes of patients with COVID-19 infections among population in the East-Asia region.

We collected clinical data published from January 2000 to May 2022 in the English databases including PubMed, Embase, and the Cochrane Library. Two reviewers independently screened and identified studies that met the prespecified criteria. Review Manager 5.3 software was used to perform the meta-analysis.

A total of 28 articles were included in this analysis. The results showed that patients who were prescribed with ACEI/ARB had a shorter duration of hospital stay [MD = -2.37, 95%CI (-3.59, -1.14), P = 0.000 2] and a lower mortality rate [OR = 0.61, 95% CI (0.52, 0.70), P<0.000 01] than patients who were not on ACEI/ARB. Furthermore, there was no statistically significant difference in disease severity [OR = 0.99, 95% CI (0.83, 1.17), P = 0.90] between individuals receiving ACEI/ARB or not.

This meta-analysis suggested that the use of ACEI/ARB was not associated with adverse clinical outcomes in East-Asian Covid-19 patients and a reduced mortality and shorter duration of hospital stay among East-Asian population (especially for female subjects) was found. Thus, ACEI/ARB should be continued in patients infected by Covid-19.

To provide a detailled analysis of the microvascular burden in patients with diabetes hopitalized for COVD-19.

We analysed data from the French CORONADO initiative and the UK Association of British Clinical Diabetologists (ABCD) COVID-19 audit, two nationwide multicentre studies, and the AMERICADO, a multicentre study conducted in New York area. We assessed the association between risk of all-cause death during hospital stay and the following microvascular complications in patients with diabetes hospitalized for COVID-19: diabetic retinopathy and/or diabetic kidney disease and/or history of diabetic foot ulcer.

Among 2951 CORONADO, 3387 ABCD COVID-19 audit and 9327 AMERICADO participants, microvascular diabetic complications status was ascertained for 1314 (44.5%), 1809 (53.4%) and 7367 (79.0%) patients, respectively: 1010, 1059 and 1800, respectively, had ≥1 severe microvascular complication(s) and 304, 750 and 5567, respectively, were free of any complications. The patients with isolated diabetic kidney disease had an increased risk of all-cause death during hospital stay: odds ratio [OR] 2.53 (95% confidence interval [CI] 1.66-3.83), OR 1.24 (95% CI 1.00-1.56) and OR 1.66 (95% CI 1.40-1.95) in the CORONADO, the ABCD COVID-19 national audit and the AMERICADO studies, respectively. After adjustment for age, sex, hypertension and cardiovascular disease (CVD), compared to those without microvascular complications, patients with microvascular complications had an increased risk of all-cause death during hospital stay in the CORONADO, the ABCD COVID-19 diabetes national audit and the AMERICADO studies: adjusted OR (_adj OR) 2.57 (95% CI 1.69-3.92), _adj OR 1.22 (95% CI 1.00-1.52) and _adj OR 1.33 (95% CI 1.15-1.53), respectively. In meta-analysis of the three studies, compared to patients free of complications, those with microvascular complications had an unadjusted OR for all-cause death during hospital stay of 2.05 (95% CI 1.42-2.97), which decreased to 1.62 (95% CI 1.19-2.119) after adjustment for age and sex, and to 1.50 (1.12-2.02) after hypertension and CVD were further added to the model.

Microvascular burden is associated with an increased risk of death in patients hospitalized for COVID-19.

Since the outbreak of coronavirus disease (COVID-19) in Wuhan, China, triggered by severe acute respiratory coronavirus 2 (SARS-CoV-2) in late November 2019, spreading to more than 200 countries of the world, the ensuing pandemic to an enormous loss of lives, mainly the older population with comorbidities, like diabetes, cardiovascular disease, chronic obstructive pulmonary disease, obesity, and hypertension. Amongst these immune-debilitating diseases, SARS-CoV-2 infection is the most common in patients with diabetes due to the absence of a normal active immune system to fight the COVID-19. Recovery of patients having a history of diabetes from COVID-19 encounters several complications, and their management becomes cumbersome. For control of coronavirus, antiviral medications, glucose-lowering agents, and steroids have been carefully evaluated. In the present review, we discuss the crosstalk between SARS-CoV-2 infection and patients with a history of diabetes. We mainly emphasize the molecular factors that are involved in diabetic individuals recently infected by SARS-CoV-2 and developed COVID-19 disease. Lastly, we examine the medications available for the long-term management of diabetic patients with SARS-CoV-2 infection.

Patients with COVID-19 have a high prevalence of diabetes, and diabetes and blood glucose control are determinants of intensive care unit admission and mortality.

To evaluate the association between COVID-19-related adverse outcomes and 8 antihyperglycemic drugs in patients with diabetes who were subsequently diagnosed and hospitalized with COVID-19.

Data were retrieved and collected in PubMed, Embase, Cochrane Central Register, Web of Science, and ClinicalTrials.gov from database inception to September 5, 2022.

For this systematic review and network meta-analysis, randomized clinical trials and observational studies conducted among patients with diabetes while receiving glucose-lowering therapies for at least 14 days before the confirmation of COVID-19 infection were included after blinded review by 2 independent reviewers and consultations of disagreement by a third independent reviewer. Of 1802 studies initially identified, 31 observational studies met the criteria for further analysis.

This study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Bayesian network meta-analyses were performed with random effects.

A composite adverse outcome, including the need for intensive care unit admission, invasive and noninvasive mechanical ventilation, or in-hospital death.

Thirty-one distinct observational studies (3 689 010 patients with diabetes hospitalized for COVID-19) were included. The sodium-glucose cotransporter-2 inhibitors (SGLT-2is) were associated with relatively lower risks of adverse outcomes compared with insulin (log of odds ratio [logOR], 0.91; 95% credible interval [CrI], 0.57-1.26), dipeptidyl peptidase-4 inhibitors (logOR, 0.61; 95% CrI, 0.28-0.93), secretagogues (logOR, 0.37; 95% CrI, 0.02-0.72), and glucosidase inhibitors (logOR, 0.50; 95% CrI, 0.00-1.01). Based on the surface under the cumulative ranking curves value, SGLT-2is were associated with the lowest probability for adverse outcomes (6%), followed by glucagon-like peptide-1 receptor agonists (25%) and metformin (28%). A sensitivity analysis revealed that the study was reliable.

These findings suggest that the use of an SGLT-2i before COVID-19 infection is associated with lower COVID-19-related adverse outcomes. In addition to SGLT-2is, glucagon-like peptide-1 receptor agonists and metformin were also associated with relatively low risk of adverse outcomes.

To analyse if antidiabetic treatment was associated with better COVID-19 outcomes in type 2 diabetic patients, measured by hospital admission and mortality rates as severe outcomes.

Cohort study including COVID-19 patients registered in the Primary Care electronic records, in March-June 2020, comparing exposed to metformin in monotherapy with exposed to any other antidiabetic.

SIDIAP (Information System for Research in Primary Care), which captures clinical information of 5,8 million people from Catalonia, Spain.

We included 31,006 diabetic patients infected with COVID-19, 43.7% previously exposed to metformin, 45.5% of them in monotherapy. 16.4% were admitted to hospital and 15.1% died. Users of insulin in monotherapy (OR 1.29, 95% CI 1.11-1.50), combined with metformin (OR 1.38, 1.13-1.69) or IDPP4 alone (OR 1.29, 1.03-1.63) had higher risk of severe outcomes than those in metformin monotherapy. Users of any insulin (OR 1.61, 1.32-1.97) or combined with metformin (OR 1.69, 1.30-2.20) had a higher risk of mortality.

Patients receiving metformin monotherapy in our study showed a lower risk of hospitalization and death in comparison to those treated with other frequent antidiabetic agents. We cannot distinguish if better outcomes are related with the antidiabetic therapy or with other factors, such as metabolic control or interventions applied during the hospital admission.

Coronavirus disease 2019 (COVID-19) is associated with a high risk of mortality and complications in patients with diabetes mellitus. Achieving good glycemic control is very important in diabetic patients to reduce complications and mortality due to COVID-19. Recent studies have shown the mortality benefit and anti-inflammatory effects of Dipeptidyl-peptidase-4 inhibitors (DPP-4i) in diabetic patients with COVID-19. DPP-4i may have a beneficial role in halting the severity of infection primarily by three routes, namely viral entry inhibition, anti-inflammatory and anti-fibrotic effects and glycemic control. This has raised the pro-mising hypothesis that DPP-4i might be an optimal strategy for treating COVID-19 in patients with diabetes. This review aims to summarise the possible therapeutic non-glycemic effects of DPP-4i in diabetic patients diagnosed with COVID-19 in the light of available evidence.