Prevalence of underlying diseases in died cases of COVID-19: A systematic review and meta-analysis

The association between potential predictors and death of patients during the COVID-19 pandemic in Shiraz: a hierarchical multiple regression analysis

INTRODUCTION

Identifying clinical factors that increase the risk of mortality in COVID-19 patients is crucial. This enables targeted screening, optimizing treatment, and prevention of severe complications, ultimately reducing death rates. This study aimed to develop prediction models for the death of patients (i.e., survival or death) during the COVID-19 pandemic in Shiraz, exploring the main influencing factors.

METHOD

We conducted a retrospective cohort study using hospital-based records of 1030 individuals diagnosed with COVID-19, who were hospitalized for treatment between March 21, 2021, and March 21, 2022, in Shiraz, Iran. Variables related to the final outcome were selected based on criteria and univariate logistic regression. Hierarchical multiple logistic regression and classification and regression tree (CART) models were utilized to explore the relationships between potential influencing factors and the final outcome. Additionally, methods were employed to identify the high-risk population for increased mortality rates during COVID-19. Finally, accuracy was evaluated the performance of the models, with the area under the receiver operator characteristic curve(AUC), sensitivity, and specificity metrics.

RESULTS

In this study, 558 (54.2%) individuals infected with COVID-19 died. The final model showed that the type of medicine antiviral (OR: 11.10, p = 0.038) than reference (antiviral and corticosteroid), and discharge oxygen saturation(O2) (OR: 1.10, p < 0.001) had a positive association with the chance of survival, but other variables were not considered as predictive variables. Predictive models for the final outcome(death) achieved accuracies ranging from 81 to 87% for hierarchical multiple logistic regression and from 87 to 94% for the CART model. Therefore, the CART model performed better than the hirerical multiple logistic regression model.

CONCLUSION

These findings firstly elucidate the incidence and associated factors of the outcome (death) among patients in Shiraz, Iran. Furthermore, we demonstrated that antiviral medication alone (without corticosteroids) and high O2 increase the survival chances of COVID patients.

Impact of COVID-19 on individual mental health and maternal health services in Ethiopia: systematic review and meta-analysis

Background

The COVID-19 pandemic has caused a major outbreak in the 21st century and has led to significant mental health hazards worldwide. To address this issue, a systematic review has been conducted to analyze existing literature on the impact of COVID-19 on the psychological well-being of the general population, as well as the associated risk factors.

Methods

A comprehensive search was carried out on PubMed, Embase, Medline, Web of Science, and Scopus databases, covering all available literature up until February 20, 2024. This search was conducted in accordance with the PRISMA guidelines, ensuring a systematic approach. The selection of articles was based on predetermined eligibility criteria, ensuring the inclusion of appropriate and suitable research. In the final analysis, a total of 15 articles focusing on depression and anxiety, 11 articles on stress, and 7 articles on psychological problems were included. These articles specifically examined the outcome variables within the context of English language and specific areas. For the meta-analysis on maternal health services, 11 articles were included for family planning, 25 articles for postnatal care services, 16 articles for institutional delivery, and 14 articles for safe abortion services. These articles were carefully selected for the final pooled analysis.

Result

According to a recent systematic review, anxiety, depression, stress, and psychological distress have been prevalent in Ethiopia during the COVID-19 pandemic, with rates of 40, 41, 23, and 41%, respectively. The review also identified various sociodemographic factors that have impacted the country's response to the pandemic, including female gender, age, marital status, incarceration, low income, and lack of social support. Furthermore, the review found that maternal health services have experienced significant reductions during the pandemic.

Conclusion

The COVID-19 pandemic has led to a significant increase in psychological distress, which in some cases, is severe enough to require clinical treatment. It is crucial to prioritize efforts to address the negative impact of COVID-19 on mental health as a global public health priority. Additionally, it is important to pay attention to maternal health services during COVID-19 mitigation programs.

Clinical Characteristics and Prognosis of Older Patients with Coronavirus Disease 2019 Requiring Mechanical Ventilation

An older age is associated with severe progression and poor prognosis in coronavirus disease 2019 (COVID-19), and mechanical ventilation is often required. The specific characteristics of older patients undergoing mechanical ventilation and their prognostic factors are largely unknown. We aimed to identify potential prognostic factors in this group to inform treatment decisions. This retrospective cohort study collected data from patients with COVID-19 at 22 medical centers. Univariate and multivariate Cox regression analyses were performed to assess factors that influence mortality. We allocated 434 patients in geriatric (≥80 years) and elderly (65-79 years) groups. The former group scored significantly higher than the elderly group in the clinical frailty scale and sequential organ failure assessment, indicating more severe organ dysfunction. Significantly lower administration rates of tocilizumab and extracorporeal membrane oxygenation and higher intensive care unit (ICU) and in-hospital mortality were noted in the geriatric group. The factors associated with ICU and in-hospital mortality included high creatinine levels, the use of continuous renal replacement therapy, prone positioning, and the administration of life-sustaining treatments. These results highlight significant age-related differences in the management and prognosis of critically ill older patients with COVID-19. Increased mortality rates and organ dysfunction in geriatric patients undergoing mechanical ventilation necessitate age-appropriate treatment strategies to improve their prognoses.

Lack of racial and ethnic disparities in mortality in minority patients hospitalised with COVID-19 in a mid-Atlantic healthcare system

INTRODUCTION

In the USA, minoritised communities (racial and ethnic) have suffered disproportionately from COVID-19 compared with non-Hispanic white communities. In a large cohort of patients hospitalised for COVID-19 in a healthcare system spanning five adult hospitals, we analysed outcomes of patients based on race and ethnicity.

METHODS

This was a retrospective cohort analysis of patients 18 years or older admitted to five hospitals in the mid-Atlantic area between 4 March 2020 and 27 May 2022 with confirmed COVID-19. Participants were divided into four groups based on their race/ethnicity: non-Hispanic black, non-Hispanic white, Latinx and other. Propensity score weighted generalised linear models were used to assess the association between race/ethnicity and the primary outcome of in-hospital mortality.

RESULTS

Of the 9651 participants in the cohort, more than half were aged 18-64 years old (56%) and 51% of the cohort were females. Non-Hispanic white patients had higher mortality (p<0.001) and longer hospital length-of-stay (p<0.001) than Latinx and non-Hispanic black patients.

DISCUSSION

In this large multihospital cohort of patients admitted with COVID-19, non-Hispanic black and Hispanic patients did not have worse outcomes than white patients. Such findings likely reflect how the complex range of factors that resulted in a life-threatening and disproportionate impact of incidence on certain vulnerable populations by COVID-19 in the community was offset through admission at well-resourced hospitals and healthcare systems. However, there continues to remain a need for efforts to address the significant pre-existing race and ethnicity inequities highlighted by the COVID-19 pandemic to be better prepared for future public health emergencies.

The Triglycerides and Glucose Index Is an Independent Risk Factor for Acute Respiratory Distress Syndrome in Patients with COVID-19

Introduction: Although it has been observed that the triglycerides and glucose (TyG) index, a biomarker of insulin resistance, is associated with severity and morbidity by COVID-19, evidence is still scarce. Therefore, the objective of this study was to determine whether the TyG index is associated with both the degree of severity and mortality by acute respiratory distress syndrome (ARDS) in patients with COVID-19. Methods: Men and women aged 20 years or more with diagnosis of COVID-19 were included in a case-control study. Exclusion criteria were pregnancy, cancer, autoimmune diseases, autoimmune treatment, and incomplete data. Patients with severe COVID-19 ARDS were allocated into the case group, and those with mild or moderate COVID-19 ARDS in the control group. COVID-19 was defined by a positive reverse transcriptase-polymerase chain reaction test for SARS-CoV-2, and ARDS was defined according to the Berlin criteria. Results: A total of 206 patients were included and allocated into the case (n = 103) and control (n = 103) groups. The logistic regression analysis adjusted by age, sex, and body mass index showed that the TyG index is significantly associated with moderate [odds ratio (OR) = 6.0; 95% confidence interval (CI): 1.1-30.6] and severe (OR = 9.5; 95% CI: 2.4-37.5) COVID-19 ARDS, and death (OR = 10.1; 95% CI: 2.2-46.5). Conclusion: The results of our study show a significant and independent association of the TyG index with ARDS and mortality in patients with COVID-19.

A mathematical model for the transmission of co-infection with COVID-19 and kidney disease

The world suffers from the acute respiratory syndrome COVID-19 pandemic, which will be scary if other co-existing illnesses exacerbate it. The co-occurrence of the COVID-19 virus with kidney disease has not been available in the literature. So, further research needs to be conducted to reveal the transmission dynamics of COVID-19 and kidney disease. This study aims to create mathematical models to understand how COVID-19 interacts with kidney diseases in specific populations. Therefore, the initial step was to formulate a deterministic Susceptible-Infected-Recovered (SIR) mathematical model to depict the co-infection dynamics of COVID-19 and kidney disease. A mathematical model with seven compartments has been developed using nonlinear ordinary differential equations. This model incorporates the invariant region, disease-free and endemic equilibrium, along with the positivity solution. The basic reproduction number, calculated via the next-generation matrix, allows us to assess the stability of the equilibrium. Sensitivity analysis is also utilised to understand the influence of each parameter on disease spread or containment. The results show that a surge in COVID-19 infection rates and the existence of kidney disease significantly enhances the co-infection risks. Numerical simulations further clarify the potential outcomes of treating COVID-19 alone, kidney disease alone, and co-infected cases. The study of the potential model can be utilised to maximise the benefits of simulation to minimise the global health complexity of COVID-19 and kidney disease.

Assessment of the predictive value of plasma calprotectin in the evolution of SARS-Cov-2 primo-infection

BACKGROUND

The COVID-19 epidemic still calls for anticipation aimed at preventing the overloading of critical care services. With this in mind, the predictive value of easily accessible biomarkers is to be assessed.

OBJECTIVE

Secretion of calprotectin is stimulated during an inflammatory process, especially in the cytokine storm. We tried to determine whether early plasma concentration of calprotectin in patients with primary SARS-CoV-2 infection could predict an adverse outcome in cases of COVID-19.

METHODS

We included 308 patients with a primary diagnosis of SARS-CoV-2 confirmed by PCR. Heparinized tube samples, collected within the first 24 h of hospitalization, were used for biomarker assays, in which plasma calprotectin was included. Data from the patients' medical records and severity groups established subsequent to diagnosis at the end of hospitalization were collected.

RESULTS

Early plasma calprotectin concentration is significantly associated with progression to a severe form of COVID-19 in patients with primary infection (Relative Risk: 2.2 [1.6-2.7]). In multivariate analysis, however, it does not appear to provide additional information compared to other parameters (age, GFR, CRP…).

CONCLUSION

Our study shows that while an early single blood test for calprotectin could help to predict the progression of a primary SARS-CoV-2 infection, it is not superior to the other parameters currently used in emergency medicine. However, it paves the way for future considerations, such as the interest of this biomarker for high-risk infected patients (immunocompromised individuals…). Finally, the usefulness of early serial measurements of plasma calprotectin to assess progression towards severity of COVID-19 requires further assessment.

Evaluation of the efficacy of N-acetylcysteine and bromhexine compared with standard care in preventing hospitalization of outpatients with COVID-19: a double blind randomized clinical trial

INTRODUCTION AND AIM

Since its emergence in December 2019, the coronavirus disease caused by the severe acute respiratory syndrome coronavirus 2 has become a global emergency, spreading rapidly worldwide. In response to the early referral of these patients to outpatient health centers, we decided to seek more effective treatments in the early stages of their referral. This study aims to prevent both the progression and deterioration of the physical conditions of COVID-19 patients, reduce the rate of referrals, and mitigate the risks of hospitalization and death.

MATERIAL AND METHODS

Conducted at Dibaj Therapeutic Center, Hamadan City, Iran, a double-blind randomized controlled trial encompassed 225 COVID-19 patients from April to September 2022. Ethical approval was obtained from Hamadan University of Medical Sciences (Approval No.: IR.UMSHA.REC.1400.957), with the protocol registered in the Iranian Registry of Clinical Trials (Registration No. : IRCT20220302054167N1). In this study, we included patients who tested positive for COVID-19- PCR and were symptomatic, excluding those who were pregnant or had received a COVID-19 vaccine. Patients with oxygen saturation above 92% were allocated to three groups: Group A received N-acetylcysteine, Group B received Bromhexine, and Group C received standard care. Follow-ups on oxygen levels, symptoms, and hospitalization needs were conducted on days 7 and 14, with hospitalized patients monitored for one month post-hospitalization.

RESULTS

The study found that both N-acetylcysteine and Bromhexine can effectively reduce hospitalization rates and mortality and shorten the duration of hospitalization. The third visit of patients who received N-acetylcysteine showed an increase of 1.33% in oxygen saturation compared to their first visit, and in patients who received Bromhexine, this increase was 1.19%. The mortality rate was 9.33% in the control group and zero in both groups of patients who received medication.

CONCLUSION

In conclusion, the results of this study indicate that NAC and bromhexine may be effective in the treatment of patients with positive COVID-19, with a lower hospitalization rate, shorter hospitalization, faster recovery time, and reduced mortality compared to the control group.

Vitamin D Supplementation and Prior Oral Poliovirus Vaccination Decrease Odds of COVID-19 Outcomes among Adults Recently Inoculated with Inactivated Poliovirus Vaccine

BACKGROUND

Structural and functional commonalities between poliovirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggest that poliovirus inoculation may induce antibodies that mitigate the coronavirus disease (COVID-19). No known studies have evaluated COVID-19 risk factors in adults recently vaccinated against poliovirus.

STUDY OBJECTIVE

Among adults with no history of COVID-19 infection or vaccination, who recently received an inactivated poliovirus vaccine (IPV), we sought to determine which biological factors and social determinants of health (SDOH) may be associated with (1) testing positive for SARS-CoV-2, (2) experiencing COVID-19 symptoms, and (3) a longer duration of COVID-19 symptoms.

METHODS

The influence of biological factors and SDOH on SARS-CoV-2 infection and COVID-19 symptoms were evaluated among 282 adults recently inoculated with IPV. Participant-reported surveys were analyzed over 12 months post-enrollment. Bivariate and multivariate linear and logistic regression models identified associations between variables and COVID-19 outcomes.

RESULTS

Adjusting for COVID-19 vaccinations, variants, and other SDOH, secondary analyses revealed that underlying conditions, employment, vitamin D, education, and the oral poliovirus vaccination (OPV) were associated with COVID-19 outcomes. The odds of testing positive for SARS-CoV-2 and experiencing symptoms were significantly reduced among participants who took vitamin D (OR 0.12 and OR 0.09, respectively). Unemployed or part-time working participants were 72% less likely to test positive compared with full-time workers. No prior dose of OPV was one of the strongest predictors of SARS-CoV-2 infection (OR 4.36) and COVID-19 symptoms (OR 6.95).

CONCLUSIONS

Findings suggest that prophylactic measures and mucosal immunity may mitigate the risk and severity of COVID-19 outcomes. Larger-scale studies may inform future policies.

A comprehensive profiling of renin-angiotensin system in mouse and human plasma by a rapid quantitative analysis of 14 angiotensin peptides using ultrahigh-performance liquid chromatography with tandem mass spectrometry

BACKGROUND

The renin-angiotensin system produces a series of biologically active angiotensin (Ang) peptides. These Ang peptides are the major regulators of blood pressure and Na homeostasis, and play a critical role in maintaining cardiovascular and fluid homeostasis. The concentration of Ang peptides in the body is at trace levels, making their detection and quantification a challenge. In this study, a rapid and sensitive analytical method using mass spectrometry coupled with ultrahigh-performance liquid chromatography (UHPLC/MS) was developed to simultaneously quantify 14 Ang peptides.

METHODS

UHPLC/MS was employed to quantify 14 Ang peptides in mouse and human plasma. An HSS T3 column (2.1 × 100 mm, 1.8 μm) with an HSS T3 precolumn and triple-quadrupole mass spectrometer combined with an electrospray ionization source were utilized. Sample pretreatment involved a one-step protein precipitation using methanol. The total analysis time was within 7.5 min and the target peptides were detected in positive ion mode and quantified by selected reaction monitoring mode.

RESULTS

The method was validated for linearity, detection and quantification limits, precision, stability, recovery and matrix effect. The limits of detection of Ang II, Ang III, Ang-(1-7), Ang-(2-7), Ang-(3-7), Ang-(1-9), bradykinin, Asn1 and Val5 -Ang II are all less than 1 pg mL-1 , indicating high sensitivity. The intra-day and inter-day precision was within 15%, and the accuracy was between 85% and 115%. Meanwhile, the sample and reference solution were stable within 48 h, and the recovery and matrix effect met the quantitative requirements.

CONCLUSIONS

The method is currently reported to allow the largest number of Ang peptide species to be detected at one time. In addition, the proposed method offers a fast and reliable approach for comprehensive analysis of Ang metabolism in biological samples, facilitating research on the physiological and pathological states of cardiovascular, kidney and respiratory diseases.

Direct impact of 2 years of COVID-19 on chronic disease patients: a population-based study in a large hard-hit Italian region

OBJECTIVES

We aimed to provide a region-wide comprehensive account of the direct effects of COVID-19 on chronic disease patients, in terms of disease incidence, severity and mortality, over a 2-year pandemic period (2020-2021).

DESIGN

Population-based retrospective study.

SETTING/PARTICIPANTS

Adult patients, affected by at least 1 of 32 prevalent chronic conditions, residing in the Emilia-Romagna Region in Italy, during the years 2020 (N=1 791 189, 47.7% of the overall adult regional population) and 2021 (N=1 801 071, 47.8%).

RESULTS

COVID-19 incidence among chronic disease patients was 4.1% (74 067 cases) in 2020 and 7.3% (126 556 cases) in 2021, varying across pathologies, with obesity and dementia showing the highest incidence. Hospitalisation rate for pneumonia or acute respiratory distress syndrome among SARS-CoV-2-positive patients was 15.4%. COVID-19-related excess mortality, that is, deaths from COVID-19 as either main or contributing (1.5% of the total) cause of death, was observed during the three pandemic waves, with observed/expected death ratios ranging from +38% (March 2020) to +11% (December 2021). Increased risks of both COVID-19-related hospitalisation and death were associated with male gender, elderly age and many pre-existing pathologies, including cardiovascular, cerebrovascular and respiratory diseases, neurological and psychiatric disorders, and metabolic dysfunctions. The higher the number of concomitant pathologies, the greater the risk of COVID-19-related adverse outcomes: the likelihood of hospitalisation and death more than doubled for people with more than two comorbidities, compared with those with one underlying condition.

CONCLUSIONS

This study presents a thorough and up-to-date quantification of the direct impact of COVID-19 on chronic disease patients. The results obtained are particularly relevant considering that people with pre-existing chronic conditions accounted for almost all cases of COVID-19-related hospitalisation (82.6%) and death (91.5%) in a vast region of Italy, among the hardest hit by the pandemic.

Chest computed tomography severity score is a reliable predictor of mortality in patients with chronic obstructive pulmonary disease co-infected with COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic is considered a global health crisis. The data related to chronic obstructive pulmonary disease (COPD) patients with COVID-19 are incomplete, especially the findings of the chest computed tomography (CT). The aim of the current study was to investigate the severity of the disease of COVID-19 in patients with COPD based on CT severity score and to evaluate its predictive power in the mortality of patients.

METHODS

In a retrospective study, demographic, clinical, and CT scan findings of COPD patients with COVID-19 were extracted from March 2020 to February 2022. CT severity score was determined based on the extent and nature of involvement of lungs in CT scan findings. By performing receiver operating characteristics (ROC) and Kaplan-Meier survival analysis were determined the disease severity and survival probability.

RESULTS

The most frequent radiological findings in chest CT scan included ground glass opacities (89.3%), consolidations (51.8%), crazy-paving pattern (46.4%), and septal thickening (35.7%). The mean CT severity score of deceased patients (34.61 ± 18.73) was significantly higher than recovered patients (16.71 ± 14.01, p < 0.001). Based on the ROC and Kaplan-Meier survival curves, it was revealed that CT severity score was a valuable criteria in the diagnosis of mortality in COPD patients with COVID-19.

CONCLUSION

The findings of this study revealed that the CT severity scoring in COPD patients with COVID-19 was valuable in identifying poor prognosis, although further studies are needed.

Mental Health of People with Intellectual Disabilities Living in Residential Care before, during, and after Lockdown

BACKGROUND

The impact of the COVID-19 on the well-being of people with intellectual disabilities (PID) has been little studied.

METHODS

We analyzed its impact with a cohort study quantitatively analyzing anxiety, depression, organic symptoms, quality of life, and support needs in 24 PID, aged 19-74 years (x¯ 40, σ = 13.09), living in a residential center, before, during, and after the pandemic.

RESULTS

Their mental health improved unexpectedly at the onset of the lockdown although there was an increase in organic symptoms. But, with the progress of the lockdown, their mental health deteriorated drastically. On the contrary, as expected, their quality of life and support needs worsened from the beginning of the lockdown until the country returned to normality, a time when there was a general recovery, without reaching pre-pandemic levels. These results show that the mental health of PID was affected differently to that of people without intellectual disabilities.

Development and validation of a hybrid deep learning-machine learning approach for severity assessment of COVID-19 and other pneumonias

The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase. Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory diseases (IRDs) can emerge unpredictably. Therefore, we aimed to develop and validate a severity assessment model for IRDs, including COVID-19, influenza, and novel influenza, using CT images on a multi-centre data set. Of the 805 COVID-19 patients collected from a single centre, 649 were used for training and 156 were used for internal validation (D1). Additionally, three external validation sets were obtained from 7 cohorts: 1138 patients with COVID-19 (D2), and 233 patients with influenza and novel influenza (D3). A hybrid model, referred to as Hybrid-DDM, was constructed by combining two deep learning models and a machine learning model. Across datasets D1, D2, and D3, the Hybrid-DDM exhibited significantly improved performance compared to the baseline model. The areas under the receiver operating curves (AUCs) were 0.830 versus 0.767 (p = 0.036) in D1, 0.801 versus 0.753 (p < 0.001) in D2, and 0.774 versus 0.668 (p < 0.001) in D3. This study indicates that the Hybrid-DDM model, trained using COVID-19 patient data, is effective and can also be applicable to patients with other types of viral pneumonia.

Staying Home, Tweeting Hope: Mixed Methods Study of Twitter Sentiment Geographical Index During US Stay-At-Home Orders

BACKGROUND

Stay-at-home orders were one of the controversial interventions to curb the spread of COVID-19 in the United States. The stay-at-home orders, implemented in 51 states and territories between March 7 and June 30, 2020, impacted the lives of individuals and communities and accelerated the heavy usage of web-based social networking sites. Twitter sentiment analysis can provide valuable insight into public health emergency response measures and allow for better formulation and timing of future public health measures to be released in response to future public health emergencies.

OBJECTIVE

This study evaluated how stay-at-home orders affect Twitter sentiment in the United States. Furthermore, this study aimed to understand the feedback on stay-at-home orders from groups with different circumstances and backgrounds. In addition, we particularly focused on vulnerable groups, including older people groups with underlying medical conditions, small and medium enterprises, and low-income groups.

METHODS

We constructed a multiperiod difference-in-differences regression model based on the Twitter sentiment geographical index quantified from 7.4 billion geo-tagged tweets data to analyze the dynamics of sentiment feedback on stay-at-home orders across the United States. In addition, we used moderated effects analysis to assess differential feedback from vulnerable groups.

RESULTS

We combed through the implementation of stay-at-home orders, Twitter sentiment geographical index, and the number of confirmed cases and deaths in 51 US states and territories. We identified trend changes in public sentiment before and after the stay-at-home orders. Regression results showed that stay-at-home orders generated a positive response, contributing to a recovery in Twitter sentiment. However, vulnerable groups faced greater shocks and hardships during the COVID-19 pandemic. In addition, economic and demographic characteristics had a significant moderating effect.

CONCLUSIONS

This study showed a clear positive shift in public opinion about COVID-19, with this positive impact occurring primarily after stay-at-home orders. However, this positive sentiment is time-limited, with 14 days later allowing people to be more influenced by the status quo and trends, so feedback on the stay-at-home orders is no longer positively significant. In particular, negative sentiment is more likely to be generated in states with a large proportion of vulnerable groups, and the policy plays a limited role. The pandemic hit older people, those with underlying diseases, and small and medium enterprises directly but hurt states with cross-cutting economic situations and more complex demographics over time. Based on large-scale Twitter data, this sociological perspective allows us to monitor the evolution of public opinion more directly, assess the impact of social events on public opinion, and understand the heterogeneity in the face of pandemic shocks.

Associations between underlying diseases with COVID-19 and its symptoms among adults: a cross-sectional study

Background

Specific underlying diseases were reported to be associated with severe COVID-19 outcomes, but little is known about their combined associations. The study was aimed to assess the relations of number of and specific underlying diseases to COVID-19, severe symptoms, loss of smell, and loss of taste.

Methods

A total of 28,204 adult participants in the National Health Interview Survey 2021 were included. Underlying diseases (including cardiovascular diseases, cancer, endocrine diseases, respiratory diseases, neuropsychiatric diseases, liver and kidney diseases, fatigue syndrome, and sensory impairments), the history of COVID-19, and its symptoms were self-reported by structured questionnaires. Multivariable logistic regression models were used to assess the combined relation of total number of underlying diseases to COVID-19 and its symptoms, while mutually adjusted logistic models were used to examine their independent associations.

Results

Among the 28,204 participants (mean ± standard deviation: 48.2 ± 18.5 years), each additional underlying disease was related to 33, 20, 37, and 39% higher odds of COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.29-1.37), severe symptoms (OR: 1.20, 95% CI: 1.12-1.29), loss of smell (OR: 1.37, 95% CI: 1.29-1.46), and loss of taste (OR: 1.39, 95% CI: 1.31-1.49). In addition, independent associations of sensory impairments with COVID-19 (OR: 3.73, 95% CI: 3.44-4.05), severe symptoms (OR: 1.37, 95% CI: 1.13-1.67), loss of smell (OR: 8.17, 95% CI: 6.86-9.76), and loss of taste (OR: 6.13, 95% CI: 5.19-7.25), cardiovascular diseases with COVID-19 (OR: 1.13, 95% CI: 1.03-1.24), neuropsychiatric diseases with severe symptoms (OR: 1.41, 95% CI: 1.15-1.74), and endocrine diseases with loss of taste (OR: 1.28, 95% CI: 1.05-1.56) were observed.

Conclusion

A larger number of underlying diseases were related to higher odds of COVID-19, severe symptoms, loss of smell, and loss of taste in a dose-response manner. Specific underlying diseases might be individually associated with COVID-19 and its symptoms.

Diabetes and deaths of COVID-19 patients: Systematic review of meta-analyses

Background

COVID-19 is affecting all kinds of patients including diabetics. This article provides an overview of conducted meta-analyses regarding the effect of diabetes on the deaths of COVID-19 patients.

Methodology

The study was conducted as per preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement.

Data sources

The relevant meta-analyses were searched on PubMed till April 2021 and data was extracted from 24 relevant meta-analyses. The overall estimate was calculated in terms of odds ratio or relative risk with a 95% confidence interval.

Results

A total of 09 meta-analyses showed the association of diabetes with the death of COVID-19 patients and 15 meta-analyses have reported the association of diabetes with other comorbidities in the death of COVID-19 patients. The pooled odds ratio or relative risk has shown a significant association of diabetes alone or its associated comorbidities with deaths of COVID-19 patients.

Conclusion

Patients with diabetes and its associated comorbidities need more monitoring if get SARS-Cov-2 infection to reduce deaths.

A Bayesian belief network-based analytics methodology for early-stage risk detection of novel diseases

During a pandemic, medical specialists have substantial challenges in discovering and validating new disease risk factors and designing effective treatment strategies. Traditionally, this approach entails several clinical studies and trials that might last several years, during which strict preventive measures are enforced to manage the outbreak and limit the death toll. Advanced data analytics technologies, on the other hand, could be utilized to monitor and expedite the procedure. This research integrates evolutionary search algorithms, Bayesian belief networks, and innovative interpretation techniques to provide a comprehensive exploratory-descriptive-explanatory machine learning methodology to assist clinical decision-makers in responding promptly to pandemic scenarios. The proposed approach is illustrated through a case study in which the survival of COVID-19 patients is determined using inpatient and emergency department (ED) encounters from a real-world electronic health record database. Following an exploratory phase in which genetic algorithms are used to identify a set of the most critical chronic risk factors and their validation using descriptive tools based on the concept of Bayesian Belief Nets, the framework develops and trains a probabilistic graphical model to explain and predict patient survival (with an AUC of 0.92). Finally, a publicly available online, probabilistic decision support inference simulator was constructed to facilitate what-if analysis and aid general users and healthcare professionals in interpreting model findings. The results widely corroborate intensive and expensive clinical trial research assessments.

Socioeconomic disparities associated with mortality in patients hospitalized for COVID-19 in Colombia

Socioeconomic disparities play an important role in the development of severe clinical outcomes including deaths from COVID-19. However, the current scientific evidence in regard the association between measures of poverty and COVID-19 mortality in hospitalized patients is scant. The objective of this study was to investigate whether there is an association between the Colombian Multidimensional Poverty Index (CMPI) and mortality from COVID-19 in hospitalized patients in Colombia from May 1, 2020 to August 15, 2021. This was an ecological study using individual data on hospitalized patients from the National Institute of Health of Colombia (INS), and municipal level data from the High-Cost Account and the National Administrative Department of Statistics. The main outcome variable was mortality due to COVID-19. The main exposure variable was the CMPI that ranges from 0 to 100% and was categorized into five levels: (i) level I (0%−20%), (ii) level II (20%−40%), (iii) level III (40%−60%), (iv) level IV (60%−80%); and (v) level V (80%−100%). The higher the level, the higher the level of multidimensional poverty. A Bayesian multilevel logistic regression model was applied to estimate Odds Ratio (OR) and their corresponding 95% credible intervals (CI). In addition, a subgroup analysis was performed according to the epidemiological COVID-19 waves using the same model. The odds for dying from COVID-19 was 1.46 (95% CI 1.4–1.53) for level II, 1.41 (95% CI 1.33–1.49) for level III and 1.70 (95% CI 1.54–1.89) for level IV hospitalized COVID-19 patients compared with the least poor patients (CMPI level I). In addition, age and male sex also increased mortality in COVID-19 hospitalized patients. Patients between 26 and 50 years-of-age had 4.17-fold increased odds (95% CI 4.07–4.3) of death compared with younger than 26-years-old patients. The corresponding for 51–75 years-old patients and those above the age of 75 years were 9.17 (95% CI 8.93–9.41) and 17.1 (95% CI 16.63–17.56), respectively. Finally, the odds of death from COVID-19 in hospitalized patients gradually decreased as the pandemic evolved. In conclusion, socioeconomic disparities were a major risk factor for mortality in patients hospitalized for COVID-19 in Colombia.

Risk of Underlying Diseases and Effectiveness of Drugs on COVID-19 Inpatients Assessed Using Medical Claims in Japan: Retrospective Observational Study

Background

Results of earlier studies have demonstrated underlying diseases such as cancer, diabetes mellitus, immunodeficiency, hypertension and heart failure to be risk factors for severe outcomes and mortality. Furthermore, clinical trials have shown that drugs such as antiviral drugs, antibody cocktails, steroids and anti-inflammatory drugs can be expected to prevent severe COVID-19 outcomes and death.

Methods

This study, using inpatient records from the Medical Information Analysis Databank covering national hospital organizations in Japan, was conducted to evaluate the effects of underlying diseases and/or administered drugs on mortality. Subjects were all inpatients receiving oxygen administration and inpatients using respiratory ventilators, categorized by three age classes: all ages, patients 65 years old or older, and patients younger than 65 years old. We used logistic regression to analyze outcomes for underlying diseases, administered drugs, age, sex, the proportion of the mutated strains, and vaccine coverage.

Results

Patients with hypertension, except for younger inpatients, have a lower risk of mortality (estimated coefficient 0.67 among all inpatients (p < 0.01): 0.77 among inpatients with oxygen therapy (p = 0.02) and 0.57 among inpatients with respiratory ventilation w (p = 0.01)). Except for younger inpatients, antibody cocktail (casirivimab/imdevimab or sotrovimab) administration was associated with a higher probability of survival (estimated coefficient 0.27 among all inpatients (p < 0.01)). It raised the survival probability consistently, although other drugs might have reduced the probability of survival.

Conclusion

These findings suggest that antiviral drugs (remdesivir, estimated coefficient 1.44 (p < 0.01)), steroids (dexamethasone, estimated coefficient 1.85 (p < 0.01)), and anti-inflammatory drugs (baricitinib, estimated coefficient 1.62 (p < 0.01), and tocilizumab, estimated coefficient 2.73 (p < 0.01)) might not contribute to survival. These results have not been reported from earlier studies. More sophisticated estimation procedures, such as treatment effect models, are necessary to obtain conclusive results.

The United States public health services failure to control the coronavirus epidemic

The unprecedented COVID-19 epidemic in the United States (US) and worldwide, caused by a new type of coronavirus (SARS-CoV-2), occurred mostly because of higher-than-expected transmission speed and degree of virulence compared with previous respiratory virus outbreaks, especially earlier Coronaviruses with person-to-person transmission (e.g., MERS, SARS). The epidemic's size and duration, however, are mostly a function of failure of public health systems to prevent/control the epidemic. In the US, this failure was due to historical disinvestment in public health services, key players equivocating on decisions, and political interference in public health actions. In this communication, we present a summary of these failures, discuss root causes, and make recommendations for improvement with focus on public health decisions.

The effect of education of patients with type 2 diabetes at risk of covid-19 on symptoms and some metabolic outcomes: A randomized controlled study

OBJECTIVE

Type 2 diabetes is one of the most common chronic diseases worldwide. It also has a high risk of morbidity and mortality in the covid 19 pandemic. Due to pandemic measures, disruptions have emerged in the care treatments of patients with type 2 diabetes. The present study aimed to determine the effects of telehealth monitoring and patient training on the symptoms and metabolic outcomes in the patients with type 2 diabetes who are at risk of COVID-19.

METHODOLOGY

The current study is in the design of a single-blind randomized controlled trial. Patients were randomized into intervention group (n=41) and control group (n = 44). The patients in the intervention group received diabetes training once a week for the first 4 weeks and every other week for weeks 5-12. No training was given to the control group. The data was collected using the socio-demographic information form, the questionnaire of diabetes treatment, the form of metabolic control variables, and the Diabetes Symptoms Checklist. The data was analyzed with Chi-square, independent samples t-test, and paired sample t-test.

RESULTS

The mean age of the patients in the control group was 56.86 ± 9.40, and the mean age of those in the intervention group was 54.12 ± 8.32. After the training, a statistically significant difference was found between the checklist averages of the groups in the subscale of hyperglycemia. However, a statistically significant difference was found between the subscales of neurology, cardiology, cognition, hyperglycemia, and the total checklist averages in the intervention group before and after the training (p < 0.05). In the control group, there was a statistically significant difference between the subscale of hyperglycemia and the total checklist averages at the beginning and 3 months later (p < 0.05).

CONCLUSION

It has been determined that the disease training given to the patients with diabetes via telehealth monitoring during the COVID-19 process has a positive effect on the diabetes control of the patients. Health education through telehealth methods can be an effective and cost-effective strategy to support patients with diabetes.

Evaluation of the Effect of Underlying Diseases on Mortality of COVID-19 Patients: A Study of 19,985 Cases

Background: The outbreak of a new coronavirus in China in 2019 (COVID-19) caused a global health crisis. Objectives: This study was performed to investigate the effect of different underlying diseases on mortality in patients with COVID-19. Methods: This retrospective cohort study was performed on COVID-19 patients admitted to the Shahid Rahimi and Sohada-ye Ashayer teaching hospitals in Khorramabad, Iran, from 2019 to 2021. Data on disease severity, clinical manifestations, mortality, and underlying disorders were collected and analyzed using the SPSS software version 22 at a 95% confidence interval and 0.05 significance level. Results: The study included 9653 men (48%) and 10332 women (52%). Patients with chronic kidney diseases, cancer, chronic obstructive pulmonary disease, hypertension, cardiovascular disease, and diabetes were at higher mortality risk than those without these underlying diseases, respectively. However, there was no significant relationship between asthma and mortality. Also, age > 50 years, male gender, oxygen saturation < 93 on admission, and symptoms lasting ≤ 5 days were associated with increased mortality. Conclusions: Since patients with underlying diseases are at higher mortality risk, they should precisely follow the advice provided by health authorities and receive a complete COVID-19 vaccination series.

Systematic Literature Review of the Prevalence, Pattern, and Determinant of Multimorbidity Among Older Adults in Nigeria

Introduction

Multimorbidity is a rising health issue globally and it is likely to become challenging in developing countries like Nigeria as they experience economic, demographic, and epidemiological transition. Yet, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. This study aims to systematically review studies of the prevalence, patterns, and determinants of multimorbidity in Nigeria.

Methods

Studies were identified by searching 5 electronic databases (PubMed, Web of Science, CINAHL, PsycINFO, Africa Index Medicus/Global Index Medicus). Multimorbidity as well as other versions of it was used to search. The prevalence and determinants were also searched. According to preestablished inclusion criteria, and using different search strategies, 6 articles were included. The quality and risk of bias were assessed using Joanna Briggs Institute appraisal tool for prevalence studies. Two researchers assessed the eligibility of studies for inclusion. The protocol was registered on PROSPERO Ref no. CRD42021273222. The overall prevalence, pattern, and determinants were analyzed.

Results

We identified 6 eligible publications describing studies that included a total of 3332 (men 47.5%, women 52.5%) patients from 4 states plus the federal capital territory Abuja. The multimorbidity prevalence ranges from 27% to 74% among elderly Nigerians. Cardiovascular together with metabolic and/or musculoskeletal conditions were the frequent patterns of multimorbidity. A positive association was observed between age and multimorbidity in most studies. Other factors associated with multimorbidity were female gender, low education status, poor monthly income/unemployment, hospitalization, medical visits, and emergency services.

Conclusion

There has been a growing need for more applied health services research to understand better and manage multimorbidity in developed countries. The scarcity of studies in our review reveals that multimorbidity is not a priority area of research in Nigeria, and this will continue to hinder policy development in that area.

Clinical outcomes among hospitalized US adults with asthma or chronic obstructive pulmonary disease, with or without COVID-19

OBJECTIVE

This study assesses the risk of severe clinical outcomes during hospitalizations of adults with asthma and/or COPD plus COVID-19 and compares those risks with those during hospitalizations of adults with asthma and/or COPD without COVID-19.

METHODS

We used data from 877 U.S. hospitals from the Premier Healthcare Database during March 2020-March 2021. Hospitalizations (n = 311,215) among patients aged ≥18 years with an ICD-10-CM diagnosis involving asthma or COPD were classified into three groups: adults with asthma (but not COPD), adults with COPD (but not asthma), and adults with both asthma and COPD. We used multivariable Poisson regression to assess associations of severe clinical outcomes [intensive care unit (ICU) admission, use of invasive mechanical ventilation (IMV), and death] and COVID-19 status.

RESULTS

The percentage of hospitalizations among patients with asthma and COVID-19 resulting in ICU admission, IMV, and death were 46.9%, 14.0%, and 8.0%, respectively. These risks were higher than those among patients with asthma without COVID-19 (adjusted risk ratio [aRR], 1.17 [95% confidence interval (CI), 1.14-1.21], 1.61 [95% CI, 1.50-1.73], and 5.56 [95% CI, 4.89-6.32]), respectively. Risks of ICU admission, IMV, and death were also high among patients with COPD and COVID-19 and exceeded the corresponding risks among patients with COPD without COVID-19.

CONCLUSION

Hospitalizations among patients with asthma and/or COPD with COVID-19 had a more severe clinical course than hospitalizations for asthma and/or COPD exacerbations without COVID-19.

Supplemental data for this article is available online at at www.tandfonline.com/ijas .

Prognostic comparison of COVID-19 outpatients and inpatients treated with Remdesivr: A retrospective cohort study

Introduction

Since the late COVID-19, many countries have faced various surges and peaks within the number of infected. Iran was one of the countries that faced many surges and peaks within these years and faced many inadequacies and shortages of resources and hospital beds. Hence the healthcare system started using in-hospital medication such as Remdesivir in outpatients to reduce the load of patients admitted to the hospital. This study aimed to evaluate and compare the reported signs, symptoms, and outcomes of COVID-infected hospitalized and out-patients receiving Remdesivir.

Methods

In this retrospective cohort study, 214 patients (121 outpatient and 93 hospitalized) with moderate levels of Covid infection between October 2021 and February 2022 were studied. Both groups were treated with 200mg of Remdesivir, followed by 100 mg daily intravenous injections for five days; signs and symptoms, such as pain, shortness of breath, cough, fever and etc., of patients at the initiation and the end of treatment were recorded. Moreover, the patients’ blood oxygen saturation was assessed two to three times a day, and the mean of the recorded measures was considered as the daily oxygen saturation. The outpatient group had to visit the hospital daily for treatment and assessment. At the treatment’s end, mortality rates, disease signs, and symptoms alleviations were compared between the groups.

Results

The outpatient and hospitalized group’s mean age was 40.30 ± 12.25 and 37.70 ± 12.00 years, and 51.2% and 55.9% were males, respectively. There was no statistical difference between baseline and clinical characteristics in the outpatients and hospitalized groups. After adjusting for oxygen saturation at baseline and gender in the multivariable Cox regression analysis, the risk of death did not statistically differ between the hospitalized and outpatient group (hazard ratio: 0.99, 95% confidence interval: 0.39–2.50)) at the end of the study.

Conclusion

Based on the results of this study, the outcome, signs, and symptoms of inpatient and outpatient Remdesivir treatment groups did not differ significantly. Hence in COVID-19 surges where we have limitations in admitting patients, outpatient Remdesivir treatment for those without any underlying diseases can be a proper management method.

An explanatory analytics framework for early detection of chronic risk factors in pandemics

Timely decision-making in national and global health emergencies such as pandemics is critically important from various aspects. Especially, early identification of risk factors of contagious viral diseases can lead to efficient management of limited healthcare resources and saving lives by prioritizing at-risk patients. In this study, we propose a hybrid artificial intelligence (AI) framework to identify major chronic risk factors of novel, contagious diseases as early as possible at the time of pandemics. The proposed framework combines evolutionary search algorithms with machine learning and the novel explanatory AI (XAI) methods to detect the most critical risk factors, use them to predict patients at high risk of mortality, and analyze the risk factors at the individual level for each high-risk patient. The proposed framework was validated using data from a repository of electronic health records of early COVID-19 patients in the US. A chronological analysis of the chronic risk factors identified using our proposed approach revealed that those factors could have been identified months before they were determined by clinical studies and/or announced by the United States health officials.

Length of hospital stay and survival of hospitalized COVID-19 patients during the second wave of the pandemic: A single centre retrospective study from Slovenia

Background

As of writing, there are no publications pertaining to the prediction of COVID-19-related outcomes and length of stay in patients from Slovene hospitals.

Objectives

To evaluate the length of regular ward and ICU stays and assess the survival of COVID-19 patients to develop better prediction models to forecast hospital capacity and staffing demands in possible further pandemic peaks.

Methods

In this retrospective, single-site study we analysed the length of stay and survival of all patients, hospitalized due to the novel coronavirus (COVID-19) at the peak of the second wave, between November 18th 2020 and January 27th 2021 at the University Clinic Golnik, Slovenia.

Results

Out of 407 included patients, 59% were male. The median length of stay on regular wards was 7.5 (IQR 5–13) days, and the median ICU length of stay was 6 (IQR 4–11) days. Age, male sex, and ICU stay were significantly associated with a higher risk of death. The probability of dying in 21 days at the regular ward was 14.4% (95% CI [10.9–18%]) and at the ICU it was 43.6% (95% CI [19.3-51.8%]).

Conclusion

The survival of COVID-19 is strongly affected by age, sex, and the fact that a patient had to be admitted to ICU, while the length of hospital bed occupancy is very similar across different demographic groups. Knowing the length of stay and admission rate to ICU is important for proper planning of resources during an epidemic.

Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data

Background

Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.

Methods

This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.

Results

This analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.

Conclusions

A strong antiviral immune response is essential in reducing severity of COVID-19.

Are lipid ratios and triglyceride-glucose index associated with critical care outcomes in COVID-19 patients?

Lipid ratios and the triglyceride and glucose index (TyG) could be a simple biochemical marker of insulin resistance (IR). The current study was carried out to examine the correlation between triglyceride to high-density lipoprotein-cholesterol (TG/HDL-C), total cholesterol to HDL-C (TC/HDL-C), low-density lipoprotein-cholesterol to HDL-C ratio (LDL-C/HDL-C), as well as TyG index with the severity and mortality of severe coronavirus disease 2019 (COVID-19). A total of 1228 confirmed COVID-19 patients were included in the current research. Regression models were performed to evaluate the correlation between the lipid index and severity and mortality of COVID-19. The TyG index and TG/HDL-C levels were significantly higher in the severe patients (P<0.05). TG/HDL-C, LDL-C/HDL-C, TC/HDL-C ratios, and TyG index were significantly lower in survivor cases (P<0.05). Multivariate logistic regression analysis demonstrated that predictors of the severity adjusted for age, sex and BMI were TyG index, TG/HDL-C ratio (OR = 1.42 CI:1.10–1.82, OR = 1.06 CI: 1.02–1.11, respectively). This analysis showed that TG/HDL-C, TC/HDL-C, LDL-C/HDL-C ratios, and TyG index statistically are correlated with COVID-19 mortality (OR = 1.12 CI:1.06–1.18, OR = 1.24 CI:1.05–1.48, OR = 1.47 CI:1.19–1.80, OR = 1.52 CI:1.01–2.31, respectively). In summary, the TyG index and lipid ratios such as TC/HDL-C, TG/HDL-C, LDL-C/HDL-C could be used as an early indicator of COVID-19 mortality. Furthermore, the study revealed that TyG index and TG/HDL-C indices are biochemical markers of COVID-19 severe prognosis.

Lipid profile of patients with arterial hypertension who underwent COVID-19: possibilities of drug therapy/ LEADER

Aim. To study the dynamics of the lipid profile of hypertensive patients with dyslipidemia who underwent COVID-19.

Material and methods. Hypertensive patients with dyslipidemia who underwent COVID-19 [n=126; 58 men and 68 women; median age 60 (56.0; 65.5) years] examined. Patients were included into two groups: group 1 (n=64) received a single pill combination of lisinopril + amlodipine + rosuvastatin; 2 groups (n=62) continued the previous drug treatment. Clinical, demographic, office blood pressure (BP), total cholesterol (TC), low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol, triglycerides, C-reactive protein (CRP) levels were assessed in all patients in 3 visits within 24 weeks.

Results. The groups did not differ in prior antihypertensive therapy (except for more frequent use of angiotensin II receptor blockers in group 2, p<0.05), lipid profile and blood pressure parameters at study entry. A decrease in systolic (by 9.5%) and diastolic blood pressure (by 12.1%) after 24 weeks was found in group 1 compared with 4.29% and 5.56%, respectively, in group 2 (p<0.05). A decrease in the level of total cholesterol by 14.5% and LDL-c by 31.4% after 24 weeks was found in group 1 compared with 11.2% and 9.7%, respectively, in group 2 (p<0.05). The level of CRP during the observation period decreased by 53.7% in group 1 versus 43.4% in patients of group 2 (p<0.05).

Conclusion. The single pill combination of lisinopril/amlodipine/rosuvastatin in hypertensive patients with dyslipidemia who underwent COVID-19 led to an improvement in lipid profile and blood pressure control.

The influence of physical activity level on the length of stay in hospital in older men survivors of COVID-19

The purpose of this study was to verify the influence of physical activity level on the length of hospital stay in older men recovered from COVID-19. In total, 126 older men diagnosed with COVID-19 were admitted to the hospital between September and December 2020. Among them, 70 survived, of which 39 older men were included in the study. Within 30 days after discharge, patients answered the International Physical Activity Questionnaire to measure their physical activity level through phone contact, with questions corresponding to the week before symptom onset. Clinical and laboratorial data from admission, days between onset of symptoms and admission, length of stay, computed tomography abnormalities, and the need for the intensive care unit were collected. The groups (active × sedentary) were compared using the Student t test or Mann-Whitney test for quantitative data and chi-square test was used for categorical data. There is no difference between the groups in characteristics of admission (p > 0.05), except by potassium level. Active older men had a shorter length of stay (6.50 ± 3.46 vs 11.48 ± 7.63 days; p = 0.03), disease duration (15.71 ± 4.84 vs 21.09 ± 7.69 days; p = 0.02), and lower frequency of lung damage when compared to their sedentary counterparts. In conclusion, being physically active prior to infection can attenuate length of hospital stay in older men with COVID-19.

HIV and COVID-19 co-infection: A mathematical model and optimal control

A new mathematical model for COVID-19 and HIV/AIDS is considered to assess the impact of COVID-19 on HIV dynamics and vice-versa. Investigating the epidemiologic synergy between COVID-19 and HIV is important. The dynamics of the full model is driven by that of its sub-models; therefore, basic analysis of the two sub-models; HIV-only and COVID-19 only is carried out. The basic reproduction number is computed and used to prove local and global asymptotic stability of the sub-models' disease-free and endemic equilibria. Using the fmincon function in the Optimization Toolbox of MATLAB, the model is fitted to real COVID-19 data set from South Africa. The impact of intervention measures, namely, COVID-19 and HIV prevention interventions and COVID-19 treatment are incorporated into the model using time-dependent controls. It is observed that HIV prevention measures can significantly reduce the burden of co-infections with COVID-19, while effective treatment of COVID-19 could reduce co-infections with opportunistic infections such as HIV/AIDS. In particular, the COVID-19 only prevention strategy averted about 10,500 new co-infection cases, with similar number also averted by the HIV-only prevention control.

Immunogenicity of COVID-19 Vaccines in Patients with Diverse Health Conditions: a Comprehensive Systematic Review

It remains unclear how effective COVID-19 vaccinations will be in patients with weakened immunity due to diseases, transplantation, and dialysis. We conducted a systematic review comparing the efficacy of COVID-19 vaccination in patients with solid tumor, hematologic malignancy, autoimmune disease, inflammatory bowel disease, and patients who received transplantation or dialysis. A literature search was conducted twice using the Medline/PubMed database. As a result, 21 papers were included in the review, and seropositivity rate was summarized by specific type of disease, transplantation, and dialysis. When different papers studied the same type of patient group, a study with a higher number of participants was selected. Most of the solid tumor patients showed a seropositivity rate of more than 80% after the second inoculation, but a low seropositivity was found in certain tumors such as breast cancer. Research in patients with certain types of hematological malignancy and autoimmune diseases has also reported low seropositivity, and this may have been affected by the immunosuppressive treatment these patients receive. Research in patients receiving dialysis or transplantation has reported lower seropositivity rates than the general population, while all patients with inflammatory bowel disease have converted to be seropositive. Meta-analysis validating these results will be needed, and studies will also be needed on methods to protect patients with reduced immunity from COVID-19. This article is protected by copyright. All rights reserved.

COVID-19-Related Burden and Risk Perception in Individuals with Chronic Inflammatory Demyelinating Polyneuropathy and Multifocal Motor Neuropathy: A Cross-Sectional Study

Introduction

This study investigated the mental health burden of patients with chronic inflammatory demyelinating polyneuropathy (CIDP) or multifocal motor neuropathy (MMN) during the COVID-19 pandemic in comparison to matched healthy controls.

Methods

The cross-sectional study included 59 patients with a diagnosis of either CIDP or MMN and 59 propensity score matched healthy controls. All participants completed a survey including demographics, distress (distress thermometer), depressive symptoms (PHQ-2), generalized anxiety (GAD-7), COVID-19-related fear, and risk perception. Additionally, patients with CIDP or MMN were asked about the frequency and type of infections since treatment initiation.

Results

Patients with either CIDP or MMN reported experiencing reduced frequency or no differences in infection frequency since immune medication was initiated. Regarding COVID-19, patients with CIDP or MMN rated their risk of infection similar to healthy controls, while they expected a higher probability of the occurrence of symptoms, severe course, and dying of COVID-19. They reported increased depressive symptoms, generalized anxiety, and COVID-19-related fear in comparison to healthy controls.

Conclusion

Despite their personal experience of reduced frequency of infection since immune medication was initiated, patients with CIDP or MMN reported increased risk perception and prevalence of depressive symptoms, generalized anxiety, and COVID-19-related fear in comparison to healthy controls. This highlights the need for evidence-driven strategies to protect the mental health of this vulnerable group.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00359-3.

Association between chronic physical conditions and depressive symptoms among hospital workers in a national medical institution designated for COVID-19 in Japan

Objective

This study aimed to investigate the cross-sectional association between the presence of chronic physical conditions and depressive symptoms among hospital workers at a national medical institution designated for COVID-19 treatment in Tokyo, Japan. We also accounted for the combined association of chronic physical conditions and SARS-CoV-2 infection risk at work in relation to depressive symptoms, given that occupational infection risk might put additional psychological burden among those with chronic physical conditions with risk of severe COVID-19 outcome.

Methods

The study sample consisted of 2,440 staff members who participated in a health survey conducted at the national medical institution during period between October 2020 and December 2020. Participants who reported at least one chronic physical condition that were deemed risk factors of severe COVID-19 outcome were regarded as having chronic physical conditions. Depressive symptoms were assessed using the patient health questionnaire-9 (PHQ-9). We performed logistic regression analysis to assess the association between chronic physical conditions and depressive symptoms.

Results

Our results showed that the presence of chronic physical conditions was significantly associated with depressive symptoms (odds ratio (OR) = 1.49, 95% confidence interval (CI) = 1.10–2.02). In addition, the prevalence of depressive symptoms was significantly higher among healthcare workers with chronic physical conditions who were at a higher occupational infection risk (OR = 1.81, 95% CI = 1.04–3.16).

Conclusion

Our findings suggest the importance of providing more assistance to those with chronic physical conditions regarding the prevention and control of mental health issues, particularly among frontline healthcare workers engaging in COVID-19-related work.

Polycystic ovary syndrome and risks for COVID-19 infection: A comprehensive review : PCOS and COVID-19 relationship

This comprehensive review aimed to evaluate the relationship between SARS-CoV-2 infection (the cause of coronavirus disease 2019, or COVID-19) and the metabolic and endocrine characteristics frequently found in women with polycystic ovary syndrome (PCOS). In the general population, COVID-19 is more severe in subjects with dyslipidemia, obesity, diabetes mellitus, and arterial hypertension. Because these conditions are comorbidities commonly associated with PCOS, it was hypothesized that women with PCOS would be at higher risk for acquiring COVID-19 and developing more severe clinical presentations. This hypothesis was confirmed in several epidemiological studies. The present review shows that women with PCOS are at 28%-50% higher risk of being infected with the SARS-CoV-2 virus at all ages and that, in these women, COVID-19 is associated with increased rates of hospitalization, morbidity, and mortality. We summarize the mechanisms of the higher risk of COVID-19 infection in women with PCOS, particularly in those with carbohydrate and lipid abnormal metabolism, hyperandrogenism, and central obesity.

The importance of association of comorbidities on COVID-19 outcomes: a machine learning approach

BACKGROUND

The individual influence of a variety of comorbidities on COVID-19 patient outcomes has already been analyzed in previous works in an isolated way. We aim to determine if different associations of diseases influence the outcomes of inpatients with COVID-19.

METHODS

Retrospective cohort multicenter study based on clinical practice. Data were taken from the SEMI-COVID-19 Registry, which includes most consecutive patients with confirmed COVID-19 hospitalized and discharged in Spain. Two machine learning algorithms were applied in order to classify comorbidities and patients (Random Forest -RF algorithm, and Gaussian mixed model by clustering -GMM-). The primary endpoint was a composite of either, all-cause death or intensive care unit admission during the period of hospitalization. The sample was randomly divided into training and test sets to determine the most important comorbidities related to the primary endpoint, grow several clusters with these comorbidities based on discriminant analysis and GMM, and compare these clusters.

RESULTS

A total of 16,455 inpatients (57.4% women and 42.6% men) were analyzed. According to the RF algorithm, the most important comorbidities were heart failure/atrial fibrillation (HF/AF), vascular diseases, and neurodegenerative diseases. There were six clusters: three included patients who met the primary endpoint (clusters 4, 5, and 6) and three included patients who did not (clusters 1, 2, and 3). Patients with HF/AF, vascular diseases, and neurodegenerative diseases were distributed among clusters 3, 4 and 5. Patients in cluster 5 also had kidney, liver, and acid peptic diseases as well as a chronic obstructive pulmonary disease; it was the cluster with the worst prognosis.

CONCLUSION

The interplay of several comorbidities may affect the outcome and complications of inpatients with COVID-19.

Approximation to the Consumption of Healthcare Resources and the Economic Cost of SARS-CoV-2 Patient Management: A Retrospective Study

Spain has become one of the countries most affected by coronavirus disease 2019 (COVID-19), with the highest testing rates, and one of the worst-performing countries in the fight against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. There are no studies related to the consumption of health resources and the economic cost of the SARS-CoV-2 virus. We present a retrospective analysis of 9,811 (Primary Care and Hospital) patients which aimed to estimate public health expenditure by the consumption of health resources due to COVID-19. According to the results, the gender distribution of patients has a similar rate in both groups, with slightly higher rates in women. Similarly, age is the same in both groups, with a median of 62 years in the case of hospitalizations and 61 years in the case of primary care; using a weighted average of these rates and costs, we can estimate that the average cost of care per patient infected with the SARS-CoV-2 virus, regardless of the course is €2373.24. We conclude that a patient with COVID-19 without hospitalization costs €729.79, while the expenses of a hospitalized patient are between €4294.36 and €14440.68, if there is ICU admission.

Mechanistic Insights Into the Immune Pathophysiology of COVID-19; An In-Depth Review

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which causes coronavirus-19 (COVID-19), has caused significant morbidity and mortality globally. In addition to the respiratory manifestations seen in severe cases, multi-organ pathologies also occur, making management a much-debated issue. In addition, the emergence of new variants can potentially render vaccines with a relatively limited utility. Many investigators have attempted to elucidate the precise pathophysiological mechanisms causing COVID-19 respiratory and systemic disease. Spillover of lung-derived cytokines causing a cytokine storm is considered the cause of systemic disease. However, recent studies have provided contradictory evidence, whereby the extent of cytokine storm is insufficient to cause severe illness. These issues are highly relevant, as management approaches considering COVID-19 a classic form of acute respiratory distress syndrome with a cytokine storm could translate to unfounded clinical decisions, detrimental to patient trajectory. Additionally, the precise immune cell signatures that characterize disease of varying severity remain contentious. We provide an up-to-date review on the immune dysregulation caused by COVID-19 and highlight pertinent discussions in the scientific community. The response from the scientific community has been unprecedented regarding the development of highly effective vaccines and cutting-edge research on novel therapies. We hope that this review furthers the conversations held by scientists and informs the aims of future research projects, which will potentially further our understanding of COVID-19 and its immune pathogenesis.

Worldwide Prevalence of Hypertension in Patients with COVID-19: A Meta-analysis and Systematic Review

Background: This systematic review and meta-analysis aimed to assess the ratio of patients with hypertension for whom coronavirus disease 2019 (COVID-19) has been diagnosed in the world. In addition, the effect of COVID-19 on the outcomes of hypertension was evaluated. Methods: To find articles published by July 2020, a comprehensive systematic search was carried out in five electronic databases, including PubMed, Scopus, Embase, and Web of Science. The meta-analysis entailed all relevant articles on the clinical and epidemiological features of patients with COVID-19. Two researchers independently reviewed the eligible post-selection studies, and finally, the discrepancies between the opinions of the two researchers were resolved by a third arbitrator. Two researchers independently examined the risk of bias using the Newcastle-Ottawa Scale. Results: The pooled prevalence of high blood pressure in patients hospitalized with COVID-19 worldwide was obtained as 31% (95% CI: 23 - 38%). The changes for hypertension prevalence in different studies included in the meta-analysis varied from 2 to 64%. Moreover, the results of subgroups analysis based on different countries demonstrated that the prevalence of hypertension in patients with COVID-19 in China and other countries was 29% (95% CI: 24 - 34%) and 32% (95% CI: 19 - 46%), respectively. Conclusions: The evidence revealed that a health condition that commonly accompanies and affects the outcomes of COVID-19 is hypertension. Therefore, COVID-19 patients with hypertension should be given priority and benefit from a preventive, therapeutic approach. Furthermore, essential training should be provided by health policymakers.

Outcome, Severity, and Risk of Mortality in Patients with COVID-19 and Chronic Underlying Diseases: A Prospective Study

Background: The novel coronavirus pandemic, severe acute respiratory syndrome CoV-2 (SARS COV-2), has become a global threat and rapidly spread worldwide. The COVID-19 pandemic has posed a number of challenges, the most notable of which is the management of patients with chronic underlying diseases. Objectives: The present study aimed to evaluate the risk of COVID-19 severity and mortality in patients with chronic underlying diseases. Methods: In this retrospective cohort study, the data on the disease severity and morality of confirmed COVID-19 patients admitted to Baharloo Hospital, Tehran, Iran, from February 2020 to March 2020 were analyzed and reported. Patients’ characteristics, including age, gender, and underlying diseases, were also considered. Results: The study encompassed 1244 patients with the mean age of 53.29 years, among whom there were 573 patients with at least one co-existing chronic disease. Hypertension, diabetes mellitus (DM), and ischemic heart disease (IHD) were the most common co-existing chronic diseases. The findings revealed that underlying diseases were significantly associated with disease mortality and severity. Conclusions: The findings showed that patients with comorbidities were significantly at higher risk of death and severe forms of COVID-19. In this regard, patients with underlying diseases should be of concern.

Systematic review of host genetic association with Covid-19 prognosis and susceptibility: What have we learned in 2020?

Biomarker identification may provide strategic opportunities to understand disease pathophysiology, predict outcomes, improve human health, and reduce healthcare costs. The highly heterogeneous Covid-19 clinical manifestation suggests a complex interaction of several different human, viral and environmental factors. Here, we systematically reviewed genetic association studies evaluating Covid-19 severity or susceptibility to SARS-CoV-2 infection following PRISMA recommendations. Our research comprised papers published until December 31st , 2020, in PubMed and BioRXiv databases focusing on genetic association studies with Covid-19 prognosis or susceptibility. We found 20 eligible genetic association studies, of which 11 assessed Covid-19 outcome and 14 evaluated infection susceptibility (five analyzed both effects). Q-genie assessment indicated moderate quality. Five large-scale association studies (GWAS, whole-genome, or exome sequencing) were reported with no consistent replication to date. Promising hits were found on the 3p21.31 region and ABO locus. Candidate gene studies examined ACE1, ACE2, TMPRSS2, IFITM3, APOE, Furin, IFNL3, IFNL4, HLA, TNF-ɑ genes, and ABO system. The most evaluated single locus was the ABO, and the most sampled region was the HLA with three and five candidate gene studies, respectively. Meta-analysis could not be performed. Available data showed the need for further reports to replicate claimed associations.

Emergency Department Management of Hypertension in the Context of COVID-19

PURPOSE OF REVIEW

This review describes the relationship between COVID-19 and hypertension (HTN), and considerations for emergency medicine providers in the management of hypertensive patients during the COVID-19 pandemic.

RECENT FINDINGS

Hypertensive patients with COVID-19 have a higher risk of severe disease/complications, hospitalizations, intensive care unit (ICU) admissions, and mortality than non-hypertensive patients. Studies have also shown the importance of consideration of various demographic factors (such as older age) and socioeconomic factors that may confound these relationships. Despite concerns at the start of the pandemic that RAAS inhibiting antihypertension medications may contribute to worsened outcomes in COVID-19 patients, subsequent research has shown that use of ACEi/ARBs is associated with neutral or even improved COVID-19 outcomes. Socioeconomic factors must also be considered including patients' potential delay of health care due to fear of contracting COVID-19, loss of health insurance, and barriers to accessing primary care appointments for post-ED follow-up care. While there is mixed evidence on biological considerations for HTN care during the COVID-19 pandemic, the pandemic has undoubtedly been a major stressor and barrier to effective chronic disease management. Emergency medicine and other providers should consider this when evaluating acute care patients with a history of HTN or newly elevated blood pressure.

An alternative approach to determination of Covid-19 personal risk index by using fuzzy logic

COVID-19 disease is an outbreak that seriously affected the whole world, occurred in December 2019, and thus was declared a global epidemic by WHO (World Health Organization). To reduce the impact of the epidemic on humans, it is important to detect the symptoms of the disease in a timely and accurate manner. Recently, several new variants of COVID-19 have been identified in the United Kingdom (UK), South Africa, Brazil and India, and preliminary findings have been suggested that these mutations increase the transmissibility of the virus. Therefore, the aim of this study is to construct a support system based on fuzzy logic for experts to help detect of COVID-19 infection risk in a timely and accurate manner and to get a numerical output on symptoms of the virus from every person. The decision support system consists of three different sub and one main Mamdani type fuzzy inference systems (FIS). Subsystems are Common- Serious symptoms (First), Rare Symptoms (Second) and Personal Information (Third). The first FIS has five inputs, fever-time, cough-time, fatigue-time, shortness of breath and chest pain/dysfunction; the second FIS has four inputs, Loss of Taste/Smell, Body Aches, Conjuctivitis, and Nausea/Vomiting/Diarrhea; and the third FIS has three inputs, Age, Smoke, and Comorbidities. Then, we obtain personal risk index of individual by combining the outputs of these subsystems in a final FIS. The results can be used by health professionals and epidemiologists to make inferences about public health. Numerical output can also be useful for self-control of an individual.

Trypsin enhances SARS-CoV-2 infection by facilitating viral entry

Coronaviruses infect cells by cytoplasmic or endosomal membrane fusion, driven by the spike (S) protein, which must be primed by proteolytic cleavage at the S1/S2 furin cleavage site (FCS) and the S2′ site by cellular proteases. Exogenous trypsin as a medium additive facilitates isolation and propagation of several coronaviruses in vitro. Here, we show that trypsin enhances severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in cultured cells and that SARS-CoV-2 enters cells via either a non-endosomal or an endosomal fusion pathway, depending on the presence of trypsin. Interestingly, trypsin enabled viral entry at the cell surface and led to more efficient infection than trypsin-independent endosomal entry, suggesting that trypsin production in the target organs may trigger a high level of replication of SARS-CoV-2 and cause severe tissue injury. Extensive syncytium formation and enhanced growth kinetics were observed only in the presence of exogenous trypsin when cell-adapted SARS-CoV-2 strains were tested. During 50 serial passages without the addition of trypsin, a specific R685S mutation occurred in the S1/S2 FCS (⁶⁸¹PRRAR⁶⁸⁵) that was completely conserved but accompanied by several mutations in the S2 fusion subunit in the presence of trypsin. These findings demonstrate that the S1/S2 FCS is essential for proteolytic priming of the S protein and fusion activity for SARS-CoV-2 entry but not for viral replication. Our data can potentially contribute to the improvement of SARS-CoV-2 production for the development of vaccines or antivirals and motivate further investigations into the explicit functions of cell-adaptation-related genetic drift in SARS-CoV-2 pathogenesis.

Not Only High Number and Specific Comorbidities but Also Age Are Closely Related to Progression and Poor Prognosis in Patients With COVID-19

Background: Some patients with comorbidities and rapid disease progression have a poor prognosis.

Aim: We aimed to investigate the characteristics of comorbidities and their relationship with disease progression and outcomes of COVID-19 patients.

Methods: A total of 718 COVID-19 patients were divided into five clinical type groups and eight age-interval groups. The characteristics of comorbidities were compared between the different clinical type groups and between the different age-interval groups, and their relationships with disease progression and outcomes of COVID-19 patients were assessed.

Results: Approximately 91.23% (655/718) of COVID-19 patients were younger than 60 years old. Approximately 64.76% (465/718) had one or more comorbidities, and common comorbidities included non-alcoholic fatty liver disease (NAFLD), hyperlipidaemia, hypertension, diabetes mellitus (DM), chronic hepatitis B (CHB), hyperuricaemia, and gout. COVID-19 patients with comorbidities were older, especially those with chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD). Hypertension, DM, COPD, chronic kidney disease (CKD) and CVD were mainly found in severe COVID-19 patients. According to spearman correlation analysis the number of comorbidities was correlated positively with disease severity, the number of comorbidities and NAFLD were correlated positively with virus negative conversion time, hypertension, CKD and CVD were primarily associated with those who died, and the above-mentioned correlation existed independently of age. Risk factors included age, the number of comorbidities and hyperlipidaemia for disease severity, the number of comorbidities, hyperlipidaemia, NAFLD and COPD for the virus negative conversion time, and the number of comorbidities and CKD for prognosis. Number of comorbidities and age played a predictive role in disease progression and outcomes.

Conclusion: Not only high number and specific comorbidities but also age are closely related to progression and poor prognosis in patients with COVID-19. These findings provide a reference for clinicians to focus on not only the number and specific comorbidities but also age in COVID-19 patients to predict disease progression and prognosis.

Clinical Trial Registry: Chinese Clinical Trial Register ChiCTR2000034563.

COVID-19 Pandemic: What Considerations Should Be Taken during the Assessment and Management of COPD Exacerbation?

The on-going coronavirus disease 2019 (COVID-19) pandemic could contribute to higher mortality in population with underlying respiratory diseases, including chronic obstructive pulmonary disease (COPD). The aim of this review was to inform readers pertaining to the correlation of COPD exacerbation and severe acute respiratory syndrome-2 (SARS-CoV-2) infection along with considerations that could be taken in the clinical diagnosis and management. The literature search was conducted on Google Scholar, Scopus, and PubMed databases using related terms (such as, but not limited to, “COVID-19,” “SARS-CoV-2,” “COPD management,” “N-acetylcysteine,” and “corticosteroids”) on November 1–9, 2021. Recent studies suggest that COVID-19 and COPD are correlated through three pathways, namely, angiotensin-converting enzyme 2 expression, dysregulation of biological parameters, and occurrence of pneumonia. Early detection of COVID-19 in patients with underlying COPD is difficult because they share similar symptoms, attributed to advanced progression of the infection and subsequently deteriorates lung function. During COPD management, clinicians are expected to take consideration on the effect of systemic corticosteroids if patients develop COVID-19. In conclusion, COVID-19 and COPD and its management are potentially correlated, contributing to the worsening of the disease. There is a need of immediate research to reveal the true correlation between COVID-19 and COPD to improve the management.

Evaluation of the clinical and biochemical parameters of hospitalized COVID-19 patients: A retrospective, single-center study from Bosnia and Herzegovina

Background/Aim. For the first time, we evaluated and presented the socio-demographic characteristics, clinical manifestations and laboratory findings of hospitalized coronavirus disease 2019 (COVID-19) patients from Canton Sarajevo, Bosnia and Herzegovina. Methods. This retrospective, single-centre study included 159 RT-PCR verified COVID-19 patients (92 mild/moderate; 67 severe/critical) consecutively hospitalized at the General Hospital "Prim. dr Abdulah Nakaš" in Sarajevo, Bosnia and Herzegovina. Socio-demographic, clinical, and laboratory data on admission were retrospectively obtained from each patient's electronic medical record and patient files by two experienced physicians. Results. 43.4% of the patients belonged to the age range of 46-65 years; 71.1% were men, and 68.6% had comorbidities; hypertension was the most prevalent comorbidity (100%), followed by diabetes (91.7%) and ischemic heart disease (35.8%). The leading clinical symptoms were fever (87.44%), tiredness (77.8%), and body/muscle aches (70.3%). There was significant reduction of blood oxygen saturation (p = 0.005), and significant elevation of D-dimer (p = 0.003), CRP (p = 0.044), and fasting plasma glucose (p = 0.047) in the severe/critical patients group compared to mild/moderate group. Conclusion. Older age, the male gender, confirmed comorbidities, decreased blood oxygen saturation, increased levels of CRP, D-dimer, and fasting plasma glucose, together with symptoms of chest pain/shortness of breath and/or diarrhea occurred more frequently in severe/critical than mild/moderate COVID-19 patients.