Prevalence and impact of diabetes in hospitalized COVID-19 patients: A systematic review and meta-analysis

Type 2 diabetes mellitus as a predictor of severe outcomes in COVID-19 - a systematic review and meta-analyses

BACKGROUND

The COVID-19 pandemic has posed significant challenges to global health, with type 2 diabetes mellitus (T2DM) emerging as a key risk factor for adverse outcomes. This study systematically reviews and quantifies the association between T2DM and COVID-19 outcomes, including mortality, severity, and need for mechanical ventilation.

METHODS

A systematic review and meta-analysis were conducted that adhered to PRISMA guidelines. We searched PubMed, Scopus, Web of Science and Embase for studies published from december 2019 to march 2024. Eligible studies reported on the impact of T2DM on COVID-19 outcomes in the adult population. Data were extracted and analyzed using a random-effects model, and heterogeneity was assessed using the I2 statistic. Publication bias was assessed using Egger regression, Kendall's Tau, and the Fail-safe N calculation.

RESULTS

Eighteen studies were included in the meta-analysis for mortality, six for severity and five for mechanical ventilation. T2DM was significantly associated with higher mortality (OR = 3.66, 95% CI: 2.20-5.11, p < 0.001), higher severity (OR = 1.97, 95% CI: 1.02-2.92, p < 0.001), and higher need for mechanical ventilation (OR = 2.34, 95% CI: 1.18-3.49, p < 0.001). Heterogeneity was high for mortality (I2 = 83.83%) but low for severity and mechanical ventilation (I2 = 0%). No significant publication bias was found.

CONCLUSIONS

T2DM is associated with significantly worse outcomes in COVID-19 patients, including higher mortality, higher severity and a greater likelihood of needing mechanical ventilation. These findings emphasize the need for targeted interventions and management strategies for individuals with T2DM during the ongoing pandemic. Future research should focus on understanding the underlying mechanisms and exploring strategies to mitigate these risks.

Longitudinal Evaluation of Metabolic Benefits of Inactivated COVID-19 Vaccination in Diabetic Patients in Tianjin, China

BACKGROUND Diabetes significantly heightens risks of COVID-19 infection, and vaccine hesitancy remains high due to safety concerns. MATERIAL AND METHODS This study assessed the effects of inactivated COVID-19 vaccine in 548 diabetic patients from Tianjin, China, categorized by vaccination status: unvaccinated (n=94), primary immunization (n=117), and booster immunization (n=337). A total of 22 clinical values were assessed prior to vaccination, 3 months after vaccination, and 12 months after vaccination. Variables with a normal distribution were compared across groups using one-way ANOVA, while non-normally distributed variables were compared using the Kruskal-Wallis test and chi-square tests for categorical data. Linear mixed-effects models were used to evaluate the effects of time and vaccine type on these clinical values, with random intercepts to account for within-subject variability and interaction terms for detailed group comparisons over time. RESULTS Baseline results showed no major differences across groups, including fasting glucose, HbA1c, granulocytes, hemoglobin, platelets, renal function markers such as uric acid, creatinine, and eGFR. Booster vaccination significantly reduced FPG (Estimate=-0.123, p<0.001) and HbA1c (Estimate=-0.049, p<0.01), with primary vaccination also reducing FPG (Estimate=-0.118, p<0.001) and HbA1c (Estimate=-0.040, p<0.05). However, creatinine decreased and bilirubin levels rose in vaccinated groups but remained within the normal physiological range. Other indicators showed no significant changes. CONCLUSIONS In conclusion, COVID-19 inactivated vaccine can provide metabolic benefits for diabetic patients.

COVID-19 Vaccine Effectiveness and Risk Factors of Booster Failure in 480,000 Patients with Diabetes Mellitus: A Population-Based Cohort Study

To investigate the real-world effectiveness of COVID-19 vaccines in a large cohort of patients with diabetes mellitus (DM), we analyzed all >18-year-old patients with COVID-19 registered in a Brazilian nationwide surveillance database between February 2020 and February 2023. The primary outcome of interest was vaccine effectiveness against death, evaluated using multivariate logistic regression models. Among the 2,131,089 patients registered in the SIVEP-Gripe, 482,677 (22.6%) had DM. After adjusting for covariates, patients with DM had a higher risk of death than those without comorbidities (adjusted odds ratio [aOR] = 1.43, 95% CI, 1.39-1.47). For patients without comorbidities (72.7%, 95% CI, 70.5-74.7) and those with DM (73.4%, 95% CI, 68.2-76.7), vaccine effectiveness was similar after the booster dose. However, it was reduced in patients with DM associated with other comorbidities (60.5%; 95% CI, 57.5-63.2). The strongest factor associated with booster failure was the omicron variant (aOR = 27.8, 95% CI, 19.9-40.1). Our study revealed that COVID-19 vaccines provided robust protection against death in individuals with DM. However, our findings underscore the need to update vaccines and develop tailored strategies for individuals with diabetes, especially those with additional underlying conditions.

Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury

Background

Acute respiratory distress syndrome (ARDS), a severe form of respiratory failure, can be precipitated by acute kidney injury (AKI), leading to a significant increase in mortality among affected patients. This study aimed to identify the risk factors for ARDS and construct a predictive nomogram.

Methods

We conducted a retrospective analysis of 1,241 AKI patients admitted to the Second Hospital of Shanxi Medical University from August 25, 2016, to December 31, 2023. The patients were divided into a study cohort (1,012 cases, including 108 with ARDS) and a validation cohort (229 cases, including 23 with ARDS). Logistic regression analysis was employed to identify the risk factors for ARDS, which were subsequently incorporated into the development of a nomogram. The predictive performance of the nomogram was assessed by AUC, calibration plots, and decision curve analyses, with external validation also performed.

Results

Six risk factors were identified and included in the nomogram: older age (OR = 1.020; 95%CI = 1.005-1.036), smoking history (OR = 1.416; 95%CI = 1.213-1.811), history of diabetes mellitus (OR = 1.449; 95%CI = 1.202-1.797), mean arterial pressure (MAP; OR = 1.165; 95%CI = 1.132-1.199), higher serum uric acid levels (OR = 1.002; 95%CI = 1.001-1.004), and higher AKI stage [(stage 1: reference), (stage 2: OR = 11.863; 95%CI = 4.850-29.014), (stage 3: OR = 41.398; 95%CI = 30.840-52.731)]. The AUC values were 0.951 in the study cohort and 0.959 in the validation cohort. Calibration and decision curve analyses confirmed the accuracy and clinical utility of the nomogram.

Conclusion

The nomogram, which integrates age, smoking history, diabetes mellitus history, MAP, and AKI stage, predicts the risk of ARDS in patients with AKI. This tool may aid in early detection and facilitate clinical decision-making.

Disparities in Access to Reperfusion Therapy for Acute Ischemic Stroke (DARTS): A Comprehensive Meta-Analysis of Ethnicity, Socioeconomic Status, and Geographical Factors

BACKGROUND

Reperfusion therapies, such as intravenous thrombolysis (IVT) and endovascular thrombectomy (EVT), are crucial for improving outcomes in patients with acute ischemic stroke (AIS). However, access to these treatments can vary significantly due to ethnicity, socioeconomic status (SES), and geographical location, impacting patient outcomes.

OBJECTIVES

The Disparities in Access to Reperfusion Therapy for Acute Ischemic Stroke (DARTS) study aims to systematically assess disparities in access to IVT and EVT on the basis of ethnicity, SES, and geographical location.

METHODS

A comprehensive meta-analysis was conducted, incorporating data from 38 studies involving 5,256,531 patients with AIS. The analysis evaluated IVT and EVT utilization rates across ethnic groups, SES levels, and geographical locations.

RESULTS

The findings reveal substantial disparities in access to reperfusion therapies. IVT and EVT utilization rates varied significantly by ethnicity (9% ethnic, 11% non-ethnic for IVT; 7% ethnic, 6% non-ethnic for EVT), SES (13% low SES, 16% high SES for IVT; 7% low SES, 10% high SES for EVT), and geography (9% rural, 12% urban for IVT; 1% rural, 4% urban for EVT). Black patients had significantly lower odds of receiving IVT (OR 0.69, p = 0.001) and EVT (OR 0.87, p = 0.005) compared with white patients. Similarly, patients with low SES and those from rural areas faced reduced odds of receiving IVT (OR 0.74, p < 0.001; OR 0.72, p = 0.002) and EVT (OR 0.74, p < 0.001; OR 0.39, p < 0.001). Rural patients also had significantly lower odds of timely hospital arrival (p < 0.001), posing a barrier to accessing reperfusion therapies.

CONCLUSIONS

The DARTS study (and this meta-analysis) reveals significant access disparities in AIS treatment related to ethnicity, geography, and SES, particularly affecting Black communities, low SES individuals, and rural populations. Despite advances in reperfusion therapies, suboptimal implementation rates persist. To address these issues, we recommend the EQUITY framework: Educate, Ensure Quality, provide Universal Access, Implement Inclusive Policy Reforms, Enhance Timely Data Collection, and Yield Culturally Sensitive Care Practices. Adopting these recommendations will improve access, reduce disparities, and enhance stroke management and outcomes globally. Equitable access is essential for all eligible patients to fully benefit from reperfusion treatments.

Classification of the ICU Admission for COVID-19 Patients with Transfer Learning Models Using Chest X-Ray Images

Objectives: Predicting intensive care unit (ICU) admissions during pandemic outbreaks such as COVID-19 can assist clinicians in early intervention and the better allocation of medical resources. Artificial intelligence (AI) tools are promising for this task, but their development can be hindered by the limited availability of training data. This study aims to explore model development strategies in data-limited scenarios, specifically in detecting the need for ICU admission using chest X-rays of COVID-19 patients by leveraging transfer learning and data extension to improve model performance. Methods: We explored convolutional neural networks (CNNs) pre-trained on either natural images or chest X-rays, fine-tuning them on a relatively limited dataset (COVID-19-NY-SBU, n = 899) of lung-segmented X-ray images for ICU admission classification. To further address data scarcity, we introduced a dataset extension strategy that integrates an additional dataset (MIDRC-RICORD-1c, n = 417) with different but clinically relevant labels. Results: The TorchX-SBU-RSNA and ELIXR-SBU-RSNA models, leveraging X-ray-pre-trained models with our training data extension approach, enhanced ICU admission classification performance from a baseline AUC of 0.66 (56% sensitivity and 68% specificity) to AUCs of 0.77-0.78 (58-62% sensitivity and 78-80% specificity). The gradient-weighted class activation mapping (Grad-CAM) analysis demonstrated that the TorchX-SBU-RSNA model focused more precisely on the relevant lung regions and reduced the distractions from non-relevant areas compared to the natural image-pre-trained model without data expansion. Conclusions: This study demonstrates the benefits of medical image-specific pre-training and strategic dataset expansion in enhancing the model performance of imaging AI models. Moreover, this approach demonstrates the potential of using diverse but limited data sources to alleviate the limitations of model development for medical imaging AI. The developed AI models and training strategies may facilitate more effective and efficient patient management and resource allocation in future outbreaks of infectious respiratory diseases.

Prevalence and Prognostic Impact of Diabetes Mellitus in Hospitalized COVID-19 Patients: A Monocentric Study From India

Background COVID-19 has been a fatal pandemic in modern history, with diabetes mellitus (DM) as a common comorbidity. However, data on the effect of DM on Indian COVID-19 patients are still scarce. We aimed to evaluate the prevalence and prognostic impact of DM in COVID-19 patients hospitalized at Index Medical College Hospital and Research Center (IMCHRC), Indore, Madhya Pradesh. Methods This is a retrospective monocentric observational study including all consecutive adult COVID-19 patients admitted to our center from July 2021 to March 2022. Data including demographics, clinical features, DM history, laboratory investigations, comorbidities, disease severity, intensive care unit (ICU) admission, invasive fungal infections, multi-organ dysfunction, and death were retrieved from the medical records of the patients and analyzed. Results A total of 357 COVID-19 patients (236 males) with a mean age of 52+9.7 years were evaluated. The overall prevalence of DM in the patients was 32% (115/357), comprising of 23% (83/357) cases of pre-existing DM and 9% (32/357) cases of new onset of DM. Vascular comorbidities consisting of hypertension (62% vs 27%; p=0.002), cardiovascular disease (39% vs 21%; p=0.016), and kidney disease (42% vs 27%; p=0.019) were significantly associated with DM. Diabetic versus non-diabetic COVID-19 patients had a higher rate of ICU admission (23% vs 10%; p=0.042), severe disease (43% [49/115] vs 5% [13/242]; p=0.002), acute respiratory distress syndrome (25% vs 7%), secondary infections (30% vs 11%; p=0.033), multi-organ dysfunction (16% vs 9%; p=0.045), and in-hospital mortality (21% [24/115] vs 6% [15/242]; p=0.011). Conclusions Our study shows a high prevalence of DM in COVID-19 patients and an adverse effect of DM on the prognosis of COVID-19 patients including increased disease severity and in-hospital mortality.

Factors Associated with Length of Hospitalization in Patients with Diabetes and Mild COVID-19: Experiences from a Tertiary University Center in Serbia

Background and Objectives: During the COVID-19 pandemic, there was an increased number of hospitalized COVID-19-positive patients suffering from type 2 diabetes mellitus (T2DM). The objective of this research study was to explore factors associated with the length of hospitalization of patients with T2DM and the mild form of COVID-19. Material and Methods: This retrospective cohort study involved all patients who tested positive for COVID-19 and those who were treated in the dedicated COVID-19 department of the University Clinical Center (UCC) in Nis between 10 September 2021 and 31 December 2021. Upon admission, patients underwent blood tests for biochemical analysis, including blood count, kidney and liver function parameters (C-reactive protein (CRP), creatinine kinase, and D-dimer), and glycemia and HbA1c assessments. Additionally, all patients underwent lung radiography. Univariate and multivariate regression analyses were employed to assess the impact of specific factors on the length of hospitalization among patients with T2DM. Results: Out of a total of 549 treated COVID-19-positive patients, 124 (21.0%) had T2DM, while 470 (79.0%) did not have diabetes. Among patients with T2DM, men were significantly younger than women (60.6 ± 16.8 vs. 64.2 ± 15.3, p < 0.01). The average hospitalization length of patients with diabetes was 20.2 ± 9.6 (5 to 54 days), and it was significantly longer than for patients without diabetes, at 15.0 ± 3.4, which ranged from 3 days to 39 (t-test ≈ 5.86, p < 0.05). According to the results of the univariate regression analysis, each year of age is associated with an increase in the length of hospital stay of 0.06 days (95% CI: 0.024 to 0.128, p = 0.004). Patients who received oxygen therapy were treated for 2.8 days longer than those who did not receive oxygen treatment (95% CI: 0.687 to 4988, p = 0.010), and each one-unit increase in CRP level was associated with a 0.02-day reduction in the length of hospitalization (95% CI: 0.004 to 0.029, p = 0.008). Based on the results of the multivariate regression analysis, each year of age is associated with an increase in the length of hospitalization by 0.07 days (95% CI: 0.022 to 0.110, p = 0.003). Patients who received oxygen therapy were treated for 3.2 days longer than those who did not receive oxygen therapy (95% CI: 0.653 to 5726, p = 0.014), and each unit increase in CRP level was associated with a 0.02-day reduction in the length of hospitalization (95% CI: 0.005 to 0.028, p = 0.004). Conclusions: Based on the presented results, COVID-19-positive patients with diabetes had, on average, longer hospitalizations than COVID-19 patients without diabetes. The hospital treatment of patients with T2DM and a milder form of COVID-19 was associated with older age, the use of oxygen therapy, and elevated CRP values. Patients who received oxygen therapy were treated approximately 3 days longer than those who did not receive this therapy.

Research Progress on the Weak Immune Response to the COVID-19 Vaccine in Patients with Type 2 Diabetes

Coronavirus Disease 2019 (COVID-19) is generally susceptible to the population, highly infectious, rapidly transmitted, and highly fatal. There is a lack of specific drugs against the virus at present and vaccination is the most effective strategy to prevent infection. However, studies have found that some groups, particularly patients with diabetes, show varying degrees of weak immune reactivity to various COVID-19 vaccines, resulting in poor preventive efficacy against the novel coronavirus in patients with diabetes. Therefore, in this study, patients with type 2 diabetes mellitus (T2DM) who had weak immune response to the COVID-19 vaccine in recent years were analyzed. This article reviews the phenomenon, preliminary mechanism, and related factors affecting weak vaccine response in patients with T2DM, which is expected to help in the development of new vaccines for high-risk groups for COVID-19.

Impact of COVID-19 on diabetes care: mixed methods study in an Indigenous area of Guatemala

INTRODUCTION

SARS-CoV-2 has impacted globally the care of chronic diseases. However, direct evidence from certain vulnerable communities, such as Indigenous communities in Latin America, is missing. We use observational data from a health district that primarily serves people of Maya K'iche' ethnicity to examine the care of type 2 diabetes in Guatemala during the pandemic.

METHODS

We used a parallel convergent mixed methods design. Quantitative data (n=142 individuals with diabetes) included glycated haemoglobin (HbA1c), blood pressure, body mass index and questionnaires on diabetes knowledge, self-care and diabetes distress. Quantitative data was collected at two points, at baseline and after COVID restrictions were lifted. For quantitative outcomes, we constructed multilevel mixed effects models with multiple imputation for missing data. Qualitative data included interviews with providers, supervisors and individuals living with diabetes (n=20). We conducted thematic framework analysis using an inductive approach.

RESULTS

Quantitative data was collected between June 2019 and February 2021, with a median of 487 days between data collection points. HbA1c worsened +0.54% (95% CI, 0.14 to 0.94) and knowledge about diabetes decreased -3.54 points (95% CI, -4.56 to -2.51). Qualitatively, the most important impact of the pandemic was interruption of the regular timing of home visits and peer group meetings which were the standard of care.

CONCLUSIONS

The deterioration of diabetes care was primarily attributed to the loss of regular contact with healthcare workers. The results emphasize the vulnerability of rural and Indigenous populations in Latin America to the suspension of chronic disease care.

Role of inflammation in determining the severity of COVID-19 infection in patients with diabetes: A comparative study

There is a need to consider the geographical origins when studying the association between COVID-19 and the comorbid conditions. To examine the role of inflammation in determining the severity of COVID-19 among hospitalized patients with diabetes and compare these roles with those who does not have diabetes. A cross sectional comparative design was used with a convenience sample of 352 patients. Samples were collected from hospitalized patients with COVID-19 who were divided into 2 groups (diabetes and non-diabetes). Data regarding results of selected inflammatory markers and sociodemographic were collected. The severity of COVID-19 differed significantly between the diabetes and non-diabetes groups (Chi square = 25.58 P < .05). There was significant difference in the mean scores of neutrophil counts, monocyte count, Basophil count, erythrocyte sedimentation rate, partial thromboplastin time, C-creative protein, platelets, white blood cells, and mean cellular hemoglobin center between those with and those without diabetes. The diabetes were shown more increased in the predictors and severity of the COVID-19 disease. However, neutrophil to lymphocyte ratio, neutrophil count, and age were the significant predictors of the severity level of COVID-19 among patients with diabetes. In conclusion, our study addressed the influence of having diabetes among hospitalized patients with moderate and severe COVID-19 infection. The results showed that severity of COVID-19 infection was affected by diabetes where those with diabetes had more tendency to suffer from the severe form of the disease rather that the moderate level.

Diabetes mellitus and functional limitations among older adults: Evidence from a large, representative Ghanaian aging study

OBJECTIVES

Literature linking diabetes mellitus (DM) to functional status is limited in low- and middle-income countries. Importantly, factors influencing this association are even less understood. This study aims to examine the association of DM with functional limitations (FL) in older adults and to identify potential factors influencing this association.

METHODS

In a cross-sectional analysis, we examined the association between DM and basic and instrumental activities of daily living-related FL in 1201 adults aged ≥50 years from the Aging, Health, Psychological Well-being, and Health-seeking Behavior Study. DM was defined as a self-report of physician diagnosis. The associations were assessed using hierarchical regression estimates and bootstrapping technique via the Hayes PROCESS macro program.

RESULTS

The prevalence of DM and FL was 10.1% and 36.1%, respectively, with OR = 2.50 (95%CI = 1.59-3.92) after accounting for sociodemographic factors, smoking, alcohol use, self-rated health, loneliness, and sleep quality. After full adjustment, polytomous regressions showed that the association of DM with FL increased with the number of FL (i.e., OR = 1.60 for 1-2, OR = 1.88 for 3-5, and OR = 2.0o for >5 FL compared with no FL). However, this association was attenuated after controlling for physical activity (OR = 2.06, 95%CI = 1.28-3.31), hypertension (OR = 1.87, 95%CI = 1.14-2.99), stroke (OR = 1.82, 95%CI = 1.20-2.93), and pain facets (OR = 1.80, 95%CI = 1.04-3.02). PA thus mediated 40.39% of the DM-FL association.

CONCLUSIONS

In this representative study, older adults with DM showed higher odds for FL, and this association was partially explained by physical activity and health variables. Investing in a holistic management approach might be helpful for public health planning efforts to address DM-induced FL in old age.

Antidiabetic Drug Efficacy in Reduction of Mortality during the COVID-19 Pandemic

Background and Objectives: The COVID-19 pandemic caused by the Coronavirus SARS-CoV-2 is a complex challenge for the existing scientific and medical landscape. It is an ongoing public health crisis, with over 245,373,039 confirmed cases globally, including 4,979,421 deaths as of 29 October 2021. Exploring molecular mechanisms correlated with the disease's severity has demonstrated significant factors of immune compromise, noted in diabetic patients with SARS-CoV-2 infections. Among diabetics, the altered function of the immune system allows for better penetration of the virus into epithelial cells, increased viral binding affinity due to hyperglycemia, reduced T cell function, decreased viral clearance, high risks of cytokine storm, and hyper-inflammatory responses, altogether increasing the susceptibility of these patients to an extreme COVID-19 disease course. Materials and Methods: This research involved a systematic literature search among various databases comprising PubMed and Google Scholar in determining credible studies about the effects of antidiabetic drugs on the high mortality rates among diabetic patients infected with COVID-19. The primary search found 103 results. Duplicated results, non-pertinent articles, and the unavailability of full text were excluded. Finally, we included 74 articles in our review. The inclusion criteria included articles published during 2020-2023, studies that reported a low risk of bias, and articles published in English. Exclusion criteria included studies published in non-peer-reviewed sources, such as conference abstracts, thesis papers, or non-academic publications. Results: Among the studied anti-diabetic drugs, Metformin, the Glucagon-like peptide 1 receptor agonist (GLP-1RA), and Sodium-glucose co-transporter 2 inhibitors (SGLT-2i) have demonstrated decreased mortality rates among diabetic patients infected with COVID-19. Insulin and Dipeptidyl peptidase 4 inhibitors (DPP-4i) have demonstrated increased mortality rates, while Sulfonylureas, Thiazolidinedione (TZD), and Alpha-glucosidase inhibitors (AGI) have demonstrated mortality-neutral results.

Endothelium dysfunction and thrombosis in COVID-19 with type 2 diabetes

SARS-CoV-2 can directly or indirectly damage endothelial cells. Endothelial injury, especially phosphatidylserine (PS) exposure on the outer membrane of cells, can more easily promote thrombosis. Type 2 diabetes(T2D) patients were more susceptible to COVID-19, they had more severe symptoms, higher risk of thrombotic complications, and longer duration of post-COVID-19 sequelae. This review provided a detailed overview of the mechanisms underlying endothelial dysfunction in T2D patients with COVID-19 (including long COVID), which may be influenced by hyperglycemia, hypoxia, and pro-inflammatory environments. The mechanisms of thrombosis in T2D patients with COVID-19 are also explored, particularly the effects of increased numbers of PS-exposing particles, blood cells, and endothelial cells on hypercoagulability. Given the high risk of thrombosis in T2D patients with COVID-19, early antithrombotic therapy can both minimize the impact of the disease on patients and maximize the chances of improvement, thereby alleviating patient suffering. We provided detailed guidance on antithrombotic drugs and dosages for mild, moderate, and severe patients, emphasizing that the optimal timing of thromboprophylaxis is a critical factor in influencing prognosis. Considering the potential interactions between antidiabetic, anticoagulant, and antiviral drugs, we proposed practical and comprehensive management recommendations to supplement the incomplete efficacy of vaccines in the diabetic population, reduce the incidence of post-COVID-19 sequelae, and improve patient quality of life.

Diabetes Mellitus after SARS-CoV-2 Infection: An Epidemiological Review

Diabetes mellitus (DM) is among the major global public health issues. According to recent projections, a continued rise in DM prevalence is expected in the following decades. The research has shown that DM is associated with poorer outcomes of coronavirus disease 2019 (COVID-19). However, there is growing evidence suggesting that COVID-19 is associated with new-onset DM type 1 and type 2. This review aims to summarize the current knowledge about the new onset of DM following COVID-19. All identified studies were longitudinal, and they have predominantly shown a significantly increased risk for new-onset DM (both type 1 and type 2) following a SARS-CoV-2 infection. Increased risk of poorer COVID-19 outcomes (mechanical ventilation, death) was noted in persons with new-onset DM following SARS-CoV-2 infection. Studies investigating risk factors for new-onset DM in COVID-19 patients showed that severe disease, age, ethnicity, ventilation, and smoking habits were associated with DM occurrence. The information summarized in this review presents a valuable source of evidence for healthcare policymakers and healthcare workers in the effort of planning prevention measures for new-onset DM after SARS-CoV-2 infection and the timely identification and appropriate treatment of patients with COVID-19 who could be at greater risk for new-onset DM.

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis

BACKGROUND

COVID-19 and diabetes both contribute to large global disease burdens.

PURPOSE

To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality.

DATA SOURCES

Systematic review identified 729 studies with 29,874,938 COVID-19 patients.

STUDY SELECTION

Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity.

DATA EXTRACTION

Study information, COVID-19 disease stages, and diabetes prevalence were extracted.

DATA SYNTHESIS

The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death.

LIMITATIONS

Most studies had a high risk of bias.

CONCLUSIONS

The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.

Associations of body mass index with severe outcomes of COVID-19 among critically ill elderly patients: A prospective study

Background and Aim

Few studies assessed the associations of overweight and obesity with severe outcomes of coronavirus disease 2019 (COVID-19) among elderly patients. This study was conducted to assess overweight and obesity in relation to risk of mortality, delirium, invasive mechanical ventilation (IMV) requirement during treatment, re-hospitalization, prolonged hospitalization, and ICU admission among elderly patients with COVID-19.

Methods

This was a single-center prospective study that was done on 310 elderly patients with COVID-19 hospitalized in the intensive care unit (ICU). We collected data on demographic characteristics, laboratory parameters, nutritional status, blood pressure, comorbidities, medications, and types of mechanical ventilation at baseline. Patients were followed up during ICU admission and until 45 days after the first visit, and data on delirium incidence, mortality, need for a form of mechanical ventilation, discharge day from ICU and hospital, and re-hospitalization were recorded for each patient.

Results

During the follow-up period, we recorded 190 deaths, 217 cases of delirium, and 35 patients who required IMV during treatment. After controlling for potential confounders, a significant association was found between obesity and delirium such that obese patients with COVID-19 had a 62% higher risk of delirium compared with normal-weight patients (HR: 1.62, 95% CI: 1.02-2.57). This association was not observed for overweight. In terms of other outcomes including ICU/45-day mortality, IMV therapy during treatment, re-hospitalization, prolonged hospitalization, and ICU admission, we found no significant association with overweight and obesity either before or after controlling for potential confounders.

Conclusion

We found that obesity may be a risk factor for delirium among critically ill elderly patients with COVID-19.

The effects of sustained COVID-19 emergency and restrictions on the mental health of subjects with serious mental illness: A prospective study

Few longitudinal studies have so far investigated the impact of sustained COVID-19 among people with pre-existing psychiatric disorders. We conducted a prospective study involving people with serious mental illness (n = 114) and healthy controls (n = 41) to assess changes in the Perceived Stress Scale, Generalized Anxiety Disorder Scale, Patient Health Questionnaire, and Specific Psychotic Experiences Questionnaire scores 18 months after the COVID-19 pandemic outset. Subjects underwent interviews with a mental health professional in April 2020 and at the end of the local third wave (October 2021). A significant increase in perceived stress was found in healthy controls, especially females. Psychiatric patients showed a significant worsening of anxiety symptoms compared to baseline records (t = -2.3, p = 0.036). Patients who rejected vaccination had significantly higher paranoia scores compared to those willing to get vaccinated (U = 649.5, z = -2.02, p = 0.04). These findings indicate that COVID-19's sustained emergency may cause enduring consequences on mental health, soliciting further investigations.

Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms in the COVID-19 Community Research Partnership

OBJECTIVE

Obesity and diabetes are established risk factors for severe SARS-CoV-2 outcomes, but less is known about their impact on susceptibility to COVID-19 infection and general symptom severity. We hypothesized that those with obesity or diabetes would be more likely to self-report a positive SARS-CoV-2 test, and among those with a positive test, have greater symptom severity and duration.

METHODS

Among 44,430 COVID-19 Community Research Partnership participants, we evaluated the association of self-reported and electronic health record obesity and diabetes with a self-reported positive COVID-19 test at any time. Among the 2,663 participants with a self-reported positive COVID-19 test during the study, we evaluated the association of obesity and diabetes with self-report of symptom severity, duration, and hospitalization. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status.

RESULTS

We found a positive graded association between Body Mass Index (BMI) category and positive COVID-19 test (Overweight OR = 1.14 [1.05-1.25]; Obesity I OR = 1.29 [1.17-2.42]; Obesity II OR = 1.34 [1.19-1.50]; Obesity III OR = 1.53 [1.35-1.73]), and a similar but weaker association with COVID-19 symptoms and severity among those with a positive test. Diabetes was associated with COVID-19 infection but not symptoms after adjustment, with some evidence of an interaction between obesity and diabetes.

CONCLUSIONS

While the limitations of this health system convenience sample include generalizability and selection around test-seeking, the strong graded association of BMI and diabetes with self-reported COVID-19 infection suggests that obesity and diabetes may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic factors.

Risk factors and survival in patients with COVID-19 in northeastern Brazil

BACKGROUND

Knowledge about the epidemiology and risk factors surrounding COVID-19 contributes to developing better health strategies to combat the disease.

OBJECTIVE

This study aimed to establish a survival analysis and identify the risk factors for patients with COVID-19 in an upper middle-income city in Brazil.

METHODS

A retrospective cohort study was conducted with 280 hospitalized patients with COVID-19. The eCOVID platform provided data to monitor COVID-19 cases and help the communication between professionals.

RESULTS

Age ≥ 65 years was associated with decreased survival (54.8%), and females had a lower survival rate than males (p = 0.01). Regarding risk factors, urea concentration (p<0.001), hospital length of stay (p = 0.002), oxygen concentration (p = 0.005), and age (p = 0.02) were associated with death.

CONCLUSION

Age, hospital length of stay, high blood urea concentration, and low oxygen concentration were associated with death by COVID-19 in the studied population. These findings corroborate with studies conducted in research centers worldwide.

Venous Thromboembolism in Cancer Patients Undergoing Chemotherapy: A Systematic Review and Meta-Analysis

Objective: Venous thromboembolism (VTE) is a life-threatening complication that may exacerbate cancer prognosis. Whilst some studies indicate an increased risk of VTE in cancer patients undergoing chemotherapy, the prevalence estimates on the pooled prevalence of VTE in cancer patients undergoing chemotherapy are not known. This study aims to calculate the pooled prevalence of VTE in chemotherapy-treated cancer patients. Methods: Studies on VTE occurrence in cancer patients undergoing chemotherapy were retrieved after database search. The terms used included “cancer”, “chemotherapy”, and “venous thromboembolism”. A random-effects meta-analysis was conducted to obtain a pooled estimate of VTE prevalence in cancer patients undergoing chemotherapy. Results: A total of 102 eligible studies involving 30,671 patients (1773 with VTE, 28,898 without) were included in the meta-analysis. The pooled estimate of VTE prevalence was found to be 6%, ranging from 6% to 7% (ES 6%; 95% CI 6−7%; z = 18.53; p < 0.001). Conclusions: The estimated pooled prevalence rate of VTEs was 6% in cancer patients undergoing CRT, which was higher than the overall crude prevalence rate (5.78%). Comprehensive cancer care should consider stratified VTE risk assessment based on cancer phenotype, given that certain phenotypes of cancer such as bladder, gastric and ovarian posing particularly high risks of VTE.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Utilization Patterns and Outcomes of People With Diabetes and COVID-19: Evidence From United States Medicare Beneficiaries in 2020

Objective

Determine differences in utilization patterns, disease severity, and outcomes between patients with and without diabetes mellitus diagnosed with COVID-19 in 2020

Research Design and Methods

We used an observational cohort comprised of Medicare fee-for-service beneficiaries with a medical claim indicating a COVID-19 diagnosis. We performed inverse probability weighting between beneficiaries with and without diabetes to account for differences in socio-demographic characteristics and comorbidities.

Results

In the unweighted comparison of beneficiaries, all characteristics were significantly different (P&lt;0.001). Beneficiaries with diabetes were younger, more likely to be black, had more comorbidities, higher rates of Medicare-Medicaid dual-eligibility, and were less likely to be female. In the weighted sample, hospitalization rates for COVID-19 among beneficiaries with diabetes was higher (20.5% vs 17.1%; p &lt; 0.001). Outcomes of hospitalizations were similarly worse among beneficiaries with diabetes: admissions to ICU during hospitalizations (7.78% vs. 6.11%; p &lt; 0.001); in-hospital mortality (3.85% vs 2.93%; p &lt; 0.001); and ICU mortality (2.41% vs 1.77%). Beneficiaries with diabetes had more ambulatory care visits (8.9 vs. 7.8, p &lt; 0.001) and higher overall mortality (17.3% vs. 14.9%, p &lt; 0.001) following COVID-19 diagnosis.

Conclusion

Beneficiaries with diabetes and COVID-19 had higher rates of hospitalization, ICU use and overall mortality. While the mechanism of how diabetes impacts the severity of COVID-19 may not be fully understood, there are important clinical implications for persons with diabetes. A diagnosis of COVID-19 leads to greater financial and clinical burden than for their counterparts, persons without diabetes, including perhaps most significantly, higher death rates.

The Effect of Diabetes Mellitus on Outcomes of Patients Admitted with COVID-19: A Single - Center Experience from a Tertiary Hospital in India

BACKGROUND AND OBJECTIVES

Diabetes mellitus is associated with poor clinical outcomes in patients with coronavirus disease 2019 (COVID-19). This study aimed to explore the clinical characteristics of patients with type 2 diabetes with COVID-19, and to determine the impact of type 2 diabetes on clinical outcome of patients with COVID-19.

MATERIAL AND METHODS

This single-center, retrospective, observational study enrolled patients admitted from March 2020 to June 2021 with COVID-19. The clinical and biochemical characteristics of patients with known type 2 diabetes, newly diagnosed diabetes, type 2 diabetes with comorbidities and those who succumbed to illness were analyzed.

RESULTS

Of 4,559 patients with COVID-19, 2,090 (45.8%) had type 2 diabetes. Patients with COVID-19 with diabetes were older, more likely to receive mechanical ventilation, had higher odds of mortality from COVID-19 as compared with patients without diabetes. In addition, patients with diabetes had significantly higher levels of serum creatinine, C-reactive protein, ferritin, lactate dehydrogenase, and D-dimer. Compared with previously diagnosed patients with diabetes, newly diagnosed patients had higher mortality (33% vs. 27%, P = 0.049). Among patients with COVID-19 and diabetes, nonsurvivors had significantly higher levels of inflammatory markers and had severe impairment of cardiac, renal, and coagulation parameters as opposed to survivors.

CONCLUSION

Patients with COVID-19 with diabetes were more likely to have severe disease and had higher mortality. Presence of chronic kidney disease and coronary artery disease in patients with diabetes with COVID-19 was associated with adverse outcome. Patients with newly diagnosed diabetes had higher odds of severe disease at presentation and had higher mortality.

The association between immunosuppressant and the outcome of COVID-19

We read with great interest the study investigating the association between immunosuppressant and the outcome of patients withs SARS-CoV-2 infection [1]. They found that the prior use of immunosuppressant would be associated with a significantly increased risk of death (adjusted relative risk [RR], 1.56; 95% CI, 1.10–2.22) which was mainly driven by exposure to systemic glucocorticoids (aRR, 2.38; 95% CI 1.72–3.30). Overall, it is a well-designed study; however, we have three concerns about the findings of this study.

Effect of diabetes on short-term mortality and incidence of first hospitalizations for cardiovascular events after recovery from SARS-CoV-2 infection

AIM

To evaluate the impact of diabetes and COVID-19 on all-cause-mortality and first hospitalizations for cardiovascular events (CVE): myocardial infarction or stroke, within six months after being tested positive and having recovered from SARS-CoV-2 infection.

METHODS

Resident population in Tuscany, Italy of age 45-94 yr without prior hospitalization for CVE, tested positive for SARS-CoV-2 by March 1st, 2020 and afterwards recovering from COVID-19 was compared with age, gender and diabetes matched controls without infection, for incidence rate ratio (IRR) of all-cause-deaths or first CVE at six months follow up.

RESULTS

46,152 subjects of whom 4,597 with diabetes, tested positive and recovered from SARS-CoV-2 were compared with 1:1 age, gender and diabetes matched controls without infection. COVID-19 was associated with higher all-cause-mortality: IRR:1.92(95 %CI:1.63-2.25) while diabetes with increased risk of first CVE hospitalizations: IRR:2.24(2.18-4.25). Co-presence of COVID-19 and diabetes didn't add any additional excess risk. Being women and statins' use significantly reduced death risk.

CONCLUSIONS

After recovery from COVID-19, independently of diabetes, all-cause-mortality risk at six months was twofold increased, while risk of first CVE hospitalization remained unmodified. Diabetes, independently of prior COVID-19, resulted in higher six-months risk of first CVE not of death. Female gender and statins' use reduced both excess risks.