Clinical characteristics, laboratory outcome characteristics, comorbidities, and complications of related COVID-19 deceased: a systematic review and meta-analysis

COVID-19 Predictors of Morbidity and Mortality

Background and objectives There are multiple factors and comorbid conditions that can impact the outcomes of COVID-19. This study aimed to assess how patients with certain comorbidities and risk factors were affected by COVID-19. Methodology This retrospective study involved 578 inpatients who presented to the emergency room (ER) due to COVID-19 infection, diagnosed with COVID-19 between 2020 and 2021. This research takes note of COVID-19 severity, particularly in individuals with comorbidities such as chronic obstructive pulmonary disease (COPD), diabetes mellitus (DM), chronic kidney disease (CKD), coronary artery disease (CAD), and hypertension. Results A two-sample t-test found that age was a significant factor affecting hospital length of stay (LOS) and mortality. An ANOVA analysis of race, DM, and CAD showed a significant effect on LOS (p-values = 0.005, 0.01, and 0.01, respectively) but not on mortality and intubation. White patients had an increased LOS compared to other ethnicities. CKD and hypertension significantly affect mortality and LOS. However, COPD did significantly influence all three variables: mortality, intubation, and LOS (p-values = 0.005, 0.013, and 0.01, respectively). A multiple ANOVA test showed that COPD, hypertension, and CKD had a significant effect on mortality, intubation, and LOS (p-values = 0.014, 0.004, and 0.01, respectively). DM showed weaker significance on mortality, intubation, and LOS (p-value = 0.108). Conclusions Patients with all three comorbid conditions (COPD, hypertension, and CKD) had increased length of stay, intubation, and mortality; thus, appropriate measures including close observation and early intervention may be necessary to prevent mortality in these patients.

COVID-19 mortality and its associated factors in Nepal: A cross-sectional study

Objectives

Reports from other countries have indicated that severe forms and fatal cases of COVID-19 in older adults and people with underlying comorbidities. The aim of this study was to assess the risk factors associated with COVID-19 mortality in Nepal.

Methods

A cross-sectional study was conducted from April 12 to July 23, 2021 to identify the underlying factors associated with COVID-19 deaths. Our sample included all cases diagnosed and registered as COVID-19-related deaths at 30 hospitals of Nepal.

Results

A total of 1459 COVID-19 hospital-based death records were collected from 30 hospitals. Mean age at death was 60.2 (±15.6) years. One-third of cases were admitted with fever, cough, and shortness of breath. The computerized tomography Severity Score showed that 7.3% of the individuals who underwent high-resolution computerized tomography chest had a severe form of lung involvement, and 3.6% had mild to moderate involvement. The most common comorbidities were hypertension (43.7%) followed by diabetes mellitus (25.8%). Among the deceased, 37.7% were diagnosed as cases of COVID-19 pneumonia. The most common recorded causes of death were respiratory failure followed by cardio-pulmonary arrest.

Conclusions

Individuals with comorbidities including hypertension and diabetes mellitus were at greater risk of developing complications and had a higher rate of mortality.

Risk factors for clinical stages of COVID-19 amongst employees of the International Committee of the Red Cross (ICRC) worldwide over a period of 12 months

BACKGROUND

Essential workers carry a higher risk of SARS-CoV-2 infection and COVID-19 mortality than individuals working in non-essential activities. Scientific studies on COVID-19 risk factors and clinical courses for humanitarian aid workers (HAW) specifically are lacking. The nature of their work brings HAW in proximity to various populations, therefore potentially exposing them to the virus. The objective of this study is to assess severity degrees of COVID-19 in relation to multiple risk factors in a cohort of HAW.

METHODS

Retrospective cohort study of data collected by the Staff Health Unit of the International Committee of the Red Cross, over 12 months (February 2021 - January 2022). Prevalence of demographic and health risk factors and outcome events were calculated. Factors associated with disease severity were explored in univariable and multivariable logistic regression models. Resulting OR were reported with 95%CI and p-values from Wald Test. P-values < 0.05 were considered significant.

RESULTS

We included 2377 patients. The mean age was 39.5y.o. Two thirds of the patients were males, and 3/4 were national staff. Most cases (3/4) were reported by three regions (Africa, Asia and Middle East). Over 95% of patients were either asymptomatic or presented mild symptoms, 9 died (CFR 0.38%). Fifty-two patients were hospitalised and 7 needed a medical evacuation outside the country of assignment. A minority (14.76%) of patients had at least one risk factor for severe disease; the most recorded one was high blood pressure (4.6%). Over 55% of cases occurred during the predominance of Delta Variant of Concern. All pre-existing risk factors were significantly associated with a moderate or higher severity of the disease (except pregnancy and immunosuppression).

CONCLUSIONS

We found strong epidemiological evidence of associations between comorbidities, old age, and the severity of COVID-19. Increased occupational risks of moderate to severe forms of COVID-19 do not only depend on workplace safety but also on social contacts and context.

Risk of COVID-19 hospitalization in people living with HIV and HIV-negative individuals and the role of COVID-19 vaccination: A retrospective cohort study

OBJECTIVE

To examine the risk of hospitalization within 14 days of COVID-19 diagnosis among people living with HIV (PLWH) and HIV-negative individuals who had laboratory-confirmed SARS-CoV-2 infection.

METHODS

We used Cox proportional hazard models to compare the relative risk of hospitalization in PLWH and HIV-negative individuals. Then, we used propensity score weighting to examine the influence of sociodemographic factors and comorbid conditions on risk of hospitalization. These models were further stratified by vaccination status and pandemic period (pre-Omicron: December 15, 2020, to November 21, 2021; Omicron: November 22, 2021, to October 31, 2022).

RESULTS

The crude hazard ratio (HR) for risk of hospitalization in PLWH was 2.44 (95% confidence interval [CI]: 2.04-2.94). In propensity score-weighted models that included all covariates, the relative risk of hospitalization was substantially attenuated in the overall analyses (adjusted HR [aHR]: 1.03; 95% CI: 0.85-1.25), in vaccinated (aHR 1.00; 95% CI: 0.69-1.45), inadequately vaccinated (aHR: 1.04; 95% CI: 0.76-1.41) and unvaccinated individuals (aHR: 1.15; 95% CI: 0.84-1.56).

CONCLUSION

PLWH had about two times the risk of COVID-19 hospitalization than HIV-negative individuals in crude analyses which attenuated in propensity score-weighted models. This suggests that the risk differential can be explained by sociodemographic factors and history of comorbidity, underscoring the need to address social and comorbid vulnerabilities (e.g., injecting drugs) that were more prominent among PLWH.

Is Age the Most Important Risk Factor in COVID-19 Patients? The Relevance of Comorbidity Burden: A Retrospective Analysis of 10,551 Hospitalizations

Purpose

To assess the contribution of age and comorbidity to the risk of critical illness in hospitalized COVID-19 patients using increasingly exhaustive tools for measuring comorbidity burden.

Patients and Methods

We assessed the effect of age and comorbidity burden in a retrospective, multicenter cohort of patients hospitalized due to COVID-19 in Catalonia (North-East Spain) between March 1, 2020, and January 31, 2022. Vaccinated individuals and those admitted within the first of the six COVID-19 epidemic waves were excluded from the primary analysis but were included in secondary analyses. The primary outcome was critical illness, defined as the need for invasive mechanical ventilation, transfer to the intensive care unit (ICU), or in-hospital death. Explanatory variables included age, sex, and four summary measures of comorbidity burden on admission extracted from three indices: the Charlson index (17 diagnostic group codes), the Elixhauser index and count (31 diagnostic group codes), and the Queralt DxS index (3145 diagnostic group codes). All models were adjusted by wave and center. The proportion of the effect of age attributable to comorbidity burden was assessed using a causal mediation analysis.

Results

The primary analysis included 10,551 hospitalizations due to COVID-19; of them, 3632 (34.4%) experienced critical illness. The frequency of critical illness increased with age and comorbidity burden on admission, irrespective of the measure used. In multivariate analyses, the effect size of age decreased with the number of diagnoses considered to estimate comorbidity burden. When adjusting for the Queralt DxS index, age showed a minimal contribution to critical illness; according to the causal mediation analysis, comorbidity burden on admission explained the 98.2% (95% CI 84.1-117.1%) of the observed effect of age on critical illness.

Conclusion

Comorbidity burden (when measured exhaustively) explains better than chronological age the increased risk of critical illness observed in patients hospitalized with COVID-19.

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.

Clinical Characteristics and Outcomes among Vaccinated and Unvaccinated Patients with Cardiovascular Disease Who Were Hospitalized for COVID-19 in Brazil: Retrospective Cohort

INTRODUCTION

COVID-19 in Brazil has already caused, and it still causes, several impacts on health, economy, and education. The risk factors for death involved those with cardiovascular diseases (CVD), which were prioritized for the vaccination of COVID-19.

OBJECTIVE

To investigate the clinical characteristics and outcomes between vaccinated and unvaccinated patients with cardiovascular diseases hospitalized for COVID-19 in Brazil in the year 2022.

METHODS

A retrospective cohort was analyzed from the year 2022, with cases being hospitalized by COVID-19 being drawn from SIVEP-GRIPE surveillance. We compared clinical characteristics, comorbidities, and outcomes between CVD carriers and non-carriers, and we also compared vaccinated with two doses vs. those that are unvaccinated in CVD carriers. We performed chi-square, odds ratio, logistic regression, and survival analysis.

RESULTS

We included, in the cohort, 112,459 hospital inpatients. An amount of 71,661 (63.72%) of the hospitalized patients had CVD. Regarding deaths, 37,888 (33.69%) died. Regarding vaccination against COVID-19, 20,855 (18.54%) people were not vaccinated with any dose among those with CVD. Death p- < 0.001 (OR 1.307-CI 1.235-1.383) and fever p- < 0.001 (OR 1.156-CI 1.098-1.218) were associated with the unvaccinated CVD carriers, and diarrhea p-0.015 (OR 1.116-CI 1.022-1.218), dyspnea p-0.022 (OR 1.074-CI 1.011-1.142), and respiratory distress p-0.021 (OR 1.070-CI 1.011-1.134) were also recorded. Those patients who possessed predictors of death, including invasive ventilation (p- < 0.001 (OR 8.816-CI 8.313-9.350)), were admitted to the ICU p- < 0.001 (OR 1.754-CI 1.684-1.827), and some had respiratory distress p- < 0.001 (OR 1.367-CI 1.312-1.423), dyspnea p < 0.001 (OR 1.341-CI 1.284-1.400), O₂ saturation < 95% p- < 0. 001 (OR 1.307-CI 1.254-1.363), they were unvaccinated against COVID-19 p- < 0.001 (OR 1.258-CI 1.200-1.319), they were of male sex p- < 0.001 (OR 1.179-CI 1.138-1.221), they had diarrhea p-0.018 (OR 1.081-CI 1.013-1.154), and they may have been old p < 0.001 (OR 1.034-CI 1.033-1.035). Survival was shorter for the unvaccinated p-0.003, and p- <0.001.

CONCLUSIONS

We highlight the predictors of death for those unvaccinated against COVID-19 in this research, and we evidenced the benefits of the COVID-19 vaccine in reducing deaths in hospitalized CVD patients.

Temporal pattern of humoral immune response in mild cases of COVID-19

BACKGROUND

Understanding the humoral response pattern of coronavirus disease 2019 (COVID-19) is one of the essential factors to better characterize the immune memory of patients, which allows understanding the temporality of reinfection, provides answers about the efficacy and durability of protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and consequently helps in global public health and vaccination strategy. Among the patients who became infected with SARS-CoV-2, the majority who did not progress to death were those who developed the mild COVID-19, so understanding the pattern and temporality of the antibody response of these patients is certainly relevant.

AIM

To investigate the temporal pattern of humoral response of specific immunoglobulin G (IgG) in mild cases of COVID-19.

METHODS

Blood samples from 191 COVID-19 real-time reverse transcriptase-polymerase chain reaction (RT-qPCR)-positive volunteers from the municipality of Toledo/ Paraná/Brazil, underwent two distinct serological tests, enzyme-linked immunosorbent assay, and detection of anti-nucleocapsid IgG. Blood samples and clinicoepidemiological data of the volunteers were collected between November 2020 and February 2021. All assays were performed in duplicate and the manufacturers' recommendations were strictly followed. The data were statistically analyzed using multiple logistic regression; the variables were selected by applying the P < 0.05 criterion.

RESULTS

Serological tests to detect specific IgG were performed on serum samples from volunteers who were diagnosed as being positive by RT-qPCR for COVID-19 or had disease onset in the time interval from less than 1 mo to 7 mo. The time periods when the highest number of participants with detectable IgG was observed were 1, 2 and 3 mo. It was observed that 9.42% of participants no longer had detectable IgG antibodies 1 mo only after being infected with SARS-CoV-2 and 1.57% were also IgG negative at less than 1 mo. At 5 mo, 3.14% of volunteers were IgG negative, and at 6 or 7 mo, 1 volunteer (0.52%) had no detectable IgG. During the period between diagnosis by RT-qPCR/symptoms onset and the date of collection for the study, no statistical significance was observed for any association analyzed. Moreover, considering the age category between 31 and 59 years as the exposed group, the P value was 0.11 for the category 31 to 59 years and 0.32 for the category 60 years or older, showing that in both age categories there was no association between the pair of variables analyzed. Regarding chronic disease, the exposure group consisted of the participants without any comorbidity, so the P value of 0.07 for the category of those with at least one chronic disease showed no association between the two variables.

CONCLUSION

A temporal pattern of IgG response was not observed, but it is suggested that immunological memory is weak and there is no association between IgG production and age or chronic disease in mild COVID-19.

Counter-regulatory renin-angiotensin system in hypertension: Review and update in the era of COVID-19 pandemic

Cardiovascular disease is the major cause of mortality and disability, with hypertension being the most prevalent risk factor. Excessive activation of the renin-angiotensin system (RAS) under pathological conditions, leading to vascular remodeling and inflammation, is closely related to cardiovascular dysfunction. The counter-regulatory axis of the RAS consists of angiotensin-converting enzyme 2 (ACE2), angiotensin (1-7), angiotensin (1-9), alamandine, proto-oncogene Mas receptor, angiotensin II type-2 receptor and Mas-related G protein-coupled receptor member D. Each of these components has been shown to counteract the effects of the overactivated RAS. In this review, we summarize the latest insights into the complexity and interplay of the counter-regulatory RAS axis in hypertension, highlight the pathophysiological functions of ACE2, a multifunctional molecule linking hypertension and COVID-19, and discuss the function and therapeutic potential of targeting this counter-regulatory RAS axis to prevent and treat hypertension in the context of the current COVID-19 pandemic.

N, Gautam N, Sunny AK, Thakur N, Subeedee KC, Mandal SK, Bastola A. Audit of Clinical Care Received by COVID-19 Patients Treated at a Tertiary Care Hospital of Nepal in 2021

Like the world over, Nepal was also hard hit by the second wave of COVID-19. We audited the clinical care provided to COVID-19 patients admitted from April to June 2021 in a tertiary care hospital of Nepal. This was a cohort study using routinely collected hospital data. There were 620 patients, and most (458, 74%) had severe illness. The majority (600, 97%) of the patients were eligible for admission as per national guidelines. Laboratory tests helping to predict the outcome of COVID-19, such as D-dimer and C-reactive protein, were missing in about 25% of patients. Nearly all (>95%) patients with severe disease received corticosteroids, anticoagulants and oxygen. The use of remdesivir was low (22%). About 70% of the patients received antibiotics. Hospital exit outcomes of most (>95%) patients with mild and moderate illness were favorable (alive and discharged). Among patients with severe illness, about 25% died and 4% were critically ill, needing further referral. This is the first study from Nepal to audit and document COVID-19 clinical care provision in a tertiary care hospital, thus filling the evidence gap in this area from resource-limited settings. Adherence to admission guidelines was excellent. Laboratory testing, access to essential drugs and data management needs to be improved.

Prognostic Performance of Cystatin C in COVID-19: A Systematic Review and Meta-Analysis

Cystatin C is a specific biomarker of kidney function. We perform this meta-analysis to determine the association of Cystatin C with the COVID-19 severity. In this systematic review and meta-analysis, we searched PubMed, EMBASE, Cochrane library, and Web of Science for studies published until 2nd September 2022 that reported associations between Cystatin C levels and COVID-19 severity. The analysis was performed using a random-effects model to calculate pooled standard mean difference (SMD). Twenty-five studies were included in the meta-analysis. Pooled analysis showed statistically significant differences of Cystatin C levels among survive vs. decreased patients (0.998 ± 0.225 vs. 1.328 ± 0.475 mg/dL, respectively; SMD = -2.14; 95%CI: -3.28 to -1.01; p < 0.001). Cystatin C levels in COVID-19 severe vs. non-severe groups varied and amounted to 1.485 ± 1.191 vs. 1.014 ± 0.601 mg/dL, respectively (SMD = 1.81; 95%CI: 1.29 to 2.32; p < 0.001). Additionally, pooled analysis showed that Cystatin C levels in patients with acute kidney injury (AKI) was 1.562 ± 0.885 mg/dL, compared to 0.811 ± 0.108 mg/dL for patients without AKI (SMD = 4.56; 95%CI: 0.27 to 8.85; p = 0.04). Summing up, Cystatin C is a potentially very good marker to be used in the context of COVID-19 disease due to the prognosis of patients' serious condition, risk of AKI and mortality. In addition, Cystatin C could be used as a marker of renal complications in COVID-19 other than AKI due to the need to monitor patients even longer after leaving the hospital.

Assessing the Nationwide COVID-19 Risk in Mexico through the Lens of Comorbidity by an XGBoost-Based Logistic Regression Model

The outbreak of the new COVID-19 disease is a serious health problem that has affected a large part of the world population, especially older adults and people who suffer from a previous comorbidity. In this work, we proposed a classifier model that allows for deciding whether or not a patient might suffer from the COVID-19 disease, considering spatio-temporal variables, physical characteristics of the patients and the presence of previous diseases. We used XGBoost to maximize the likelihood function of the multivariate logistic regression model. The estimated and observed values of percentage occurrence of cases were very similar, and indicated that the proposed model was suitable to predict new cases (AUC = 0.75). The main results revealed that patients without comorbidities are less likely to be COVID-19 positive, unlike people with diabetes, obesity and pneumonia. The distribution function by age group showed that, during the first and second wave of COVID-19, young people aged ≤20 were the least affected by the pandemic, while the most affected were people between 20 and 40 years, followed by adults older than 40 years. In the case of the third and fourth wave, there was an increased risk for young individuals (under 20 years), while older adults over 40 years decreased their chances of infection. Estimates of positive COVID cases with both the XGBoost-LR model and the multivariate logistic regression model were used to create maps to visualize the spatial distribution of positive cases across the country. Spatial analysis was carried out to determine, through the data, the main geographical areas where a greater number of positive cases occurred. The results showed that the areas most affected by COVID-19 were in the central and northern regions of Mexico.

The complexity of examining laboratory-based biological markers associated with mortality in hospitalized patients during early phase of the COVID-19 pandemic: A systematic review and evidence map

Importance

The measurement of laboratory biomarkers plays a critical role in managing patients with COVID-19. However, to date most systematic reviews examining the association between laboratory biomarkers and mortality in hospitalized patients early in the pandemic focused on small sets of biomarkers, did not account for multiple studies including patients within the same institutions during overlapping timeframes, and did not include a significant number of studies conducted in countries other than China.

Objective

To provide a comprehensive summary and an evidence map examining the relationship between a wide range of laboratory biomarkers and mortality among patients hospitalized with COVID-19 during the early phase of the pandemic in multiple countries.

Evidence review

MEDLINE, EMBASE, and Web of Science were searched from Dec 2019 to March 9, 2021. A total of 14,049 studies were identified and screened independently by two raters; data was extracted by a single rater and verified by a second. Quality was assessed using the Joanna Briggs Institute (JBI) Case Series Critical Appraisal tool. To allow comparison across biomarkers, standardized mean differences (SMD) were used to quantify the relationship between laboratory biomarkers and hospital mortality. Meta-regression was conducted to account for clustering within institutions and countries.

Results

Our systematic review included 94 case-series studies from 30 countries. Across all biomarkers, the largest and most precise SMDs were observed for cardiac (troponin (1.03 (95% CI 0.86 to 1.21)), and BNP/NT-proBNP (0.93 (0.52 to 1.34)), inflammatory (IL-6 (0.97 (0.67 to 1.28) and Neutrophil-to-lymphocyte ratio (0.94 (0.59 to 1.29)), and renal biomarkers (blood urea nitrogen (1.01 (0.79 to 1.23)) and estimated glomerular filtration rate (-0.96 (-1.42 to -0.50)). There was heterogeneity for most biomarkers across countries with studies conducted in China generally having larger effect sizes.

Conclusions and relevance

The results of this study provide an early pandemic summary of the relationship between biomarkers and mortality in hospitalized patients. We found our estimated ESs were generally attenuated compared to previous systematic reviews which predominantly included studies conducted in China. Despite using sophisticated methodology to examine studies across countries, heterogeneity in reporting of case-series studies early in the pandemic limits clinical interpretability.

Influencing demographic characteristics, comorbidities disease, and radiologic finding on mortality due to Covid-19 in Iran

Introduction

Recognition of death risk factors is urgently needed, not only to identify the defining clinical and epidemiological characteristics with greater precision but also to facilitate the appropriate supportive care and prompt access to the intensive care unit (ICU) if necessary. This study aimed to investigate the influencing demographic characteristics, comorbidities disease, and radiologic finding on COVID-19 death.

Method

Descriptive cross-sectional study included adult patients with COVID-19 from Imam Hossein. Demographic characteristics, comorbidities disease, chest CT scan findings, and outcome (death/survive) data were extracted from information health system (HIS), by using a data collection check list. To explore the influencing factors on mortality, logistic regression method was used.

Result

Result demonstrated that most patients who died because of Covid-19 were men (63.4%), more than 60 years (86.4%), married (95.8%), and self-employed (37.1%) with a mean age of 72.1 ± 15.46 years ranging from 22 to 93 years. Having comorbidities disease such as cancer, cardiac disease, diabetes, age, and pathologic chest CT findings was associated with death. In contrast, gender, marital, job, cerebral vascular disease, and HTN were not correlated.

Conclusion

Identification of demographic characteristics, comorbidities disease, and radiographic finding correlated with death of COVID-19 can help clinicians in order to with rapid diagnose and triages of high-risk patients to have a better plan for the care of these patients.

Elevated Fasting Blood Glucose Levels Are Associated with Worse Clinical Outcomes in COVID-19 Patients Than in Pneumonia Patients with Bacterial Infections

Aims: We investigate how fasting blood glucose (FBG) levels affect the clinical severity in coronavirus disease 2019 (COVID-19) patients, pneumonia patients with sole bacterial infection, and pneumonia patients with concurrent bacterial and fungal infections. Methods: We enrolled 2761 COVID-19 patients, 1686 pneumonia patients with bacterial infections, and 2035 pneumonia patients with concurrent infections. We used multivariate logistic regression analysis to assess the associations between FBG levels and clinical severity. Results: FBG levels in COVID-19 patients were significantly higher than in other pneumonia patients during hospitalisation and at discharge (all p < 0.05). Among COVID-19 patients, the odds ratios of acute respiratory distress syndrome (ARDS), respiratory failure (RF), acute hepatitis/liver failure (AH/LF), length of stay, and intensive care unit (ICU) admission were 12.80 (95% CI, 4.80−37.96), 5.72 (2.95−11.06), 2.60 (1.20−5.32), 1.42 (1.26−1.59), and 5.16 (3.26−8.17) times higher in the FBG ≥7.0 mmol/L group than in FBG < 6.1 mmol/L group, respectively. The odds ratios of RF, AH/LF, length of stay, and ICU admission were increased to a lesser extent in pneumonia patients with sole bacterial infection (3.70 [2.21−6.29]; 1.56 [1.17−2.07]; 0.98 [0.88−1.11]; 2.06 [1.26−3.36], respectively). The odds ratios of ARDS, RF, AH/LF, length of stay, and ICU admission were increased to a lesser extent in pneumonia patients with concurrent infections (3.04 [0.36−6.41]; 2.31 [1.76−3.05]; 1.21 [0.97−1.52]; 1.02 [0.93−1.13]; 1.72 [1.19−2.50], respectively). Among COVID-19 patients, the incidence rate of ICU admission on day 21 in the FBG ≥ 7.0 mmol/L group was six times higher than in the FBG < 6.1 mmol/L group (12.30% vs. 2.21%, p < 0.001). Among other pneumonia patients, the incidence rate of ICU admission on day 21 was only two times higher. Conclusions: Elevated FBG levels at admission predict subsequent clinical severity in all pneumonia patients regardless of the underlying pathogens, but COVID-19 patients are more sensitive to FBG levels, and suffer more severe clinical complications than other pneumonia patients.

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study

BACKGROUND

A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients.

METHODS

All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality.

RESULTS

A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18-4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02-3.11), but not for the highest CFS category (5-9, frail) (OR 1.35, 95% 0.75-2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52-0.66), 0.54 (0.46-0.62) and 0.58 (0.51-0.65)).

CONCLUSION

Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.

Blockchain Assisted Disease Identification of COVID-19 Patients with the Help of IDA-DNN Classifier

Globally, millions of people were affected by the Corona-virus disease-2019 (COVID-19) causing loads of deaths. Most COVID-19 affected people recover in a few spans of weeks. However, certain people even those with a milder variant of the disease persist in experiencing symptoms subsequent to their initial recuperation. Here, a novel Block-Chain (BC)-assisted optimized deep learning algorithm, explicitly improved dragonfly algorithm based Deep Neural Network (IDA-DNN), is proposed for detecting the different diseases of the COVID-19 patients. Initially, the input data of the COVID-19 recovered patients are gathered centered on their post symptoms and their data is amassed as a BC for rendering security to the patient's data. After that, the disease identification of the patient's data is performed with the aid of system training. The training includes '4' disparate datasets for data collection, and then, performs preprocessing, Feature Extraction (FE), Feature Reduction (FR), along with classification utilizing ID-DNN on the gathered inputted data. The IDA-DNN classifies '2' classes (presence of disease and absence of disease) for every type of data. The proposed method's outcomes are examined as well as contrasted with the other prevailing techniques to corroborate that the proposed IDA-DNN detects the COVID-19 more efficiently.

Clinical characteristics and Co-morbidities among patients admitted with COVID-19

Background

During the Coronavirus Disease-2019 (COVID-19) pandemic, several characteristics of COVID-19 patients, based on demographics, clinical symptoms, and the presence of comorbidities, were found to be associated with the complications developed. COVID-19 symptoms vary greatly and are more prominent with comorbid diseases. Therefore, the aim of this study to find the clinical characteristics and its association with different comorbidities.

Methods

This is a retrospective study that was performed on the data obtained from medical records of 3999 patients in Riyadh. Demographic data, clinical symptoms and comorbidities were noted on the day of hospital admission. Complications developed during the COVID -19 infection were observed.

Results

The average age of patients were 49.55 years old. Fever was the most common symptom among the patients (85.85%), followed by cough (85.85%), and shortness of breath (83.25%). The most common comorbidities were diabetes mellitus (39.51%), hypertension (33.91%), and asthma (9.45%), with chronic rhinosinusitis being the least common (0.5%). Pneumonia affected 61.90% of the patients admitted to the hospital. Furthermore, 8.73% got acute respiratory distress syndrome (ARDS), and 7.25% acquired pneumonia and Acute ARDS simultaneously. Co-morbidities were significantly correlated with complications developed during COVID-19.

Conclusion

Hypertension and diabetes mellitus were two of the most common symptoms observed. Clinical symptoms, comorbidities, and complications are higher in female patients compared to male patients and most of the patients’ developed complications.

•

Longitudinal data of hospitalized COVID-19 patient is beneficial for future pandemics.

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Comorbidities is key factor in any kind of outbreaks, in our study, females were at more risk of developing complications.

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Comorbidities can differ regarding rates of hospitalization and infection.

Bacterial and fungal co-infections among ICU COVID-19 hospitalized patients in a Palestinian hospital: a retrospective cross-sectional study

Background: Diagnosis of co-infections with multiple pathogens among hospitalized coronavirus disease 2019 (COVID-19) patients can be jointly challenging and essential for appropriate treatment, shortening hospital stays and preventing antimicrobial resistance. This study proposes to investigate the burden of bacterial and fungal co-infections outcomes on COVID-19 patients. It is a single center cross-sectional study of hospitalized COVID-19 patients at Beit-Jala hospital in Palestine.

Methods: The study included 321 hospitalized patients admitted to the ICU between June 2020 and March 2021 aged ≥20 years, with a confirmed diagnosis of COVID-19 via reverse transcriptase-polymerase chain reaction assay conducted on a nasopharyngeal swab. The patient's information was gathered using graded data forms from electronic medical reports.

Results: The diagnosis of bacterial and fungal infection was proved through the patient’s clinical presentation and positive blood or sputum culture results. All cases had received empirical antimicrobial therapy before the intensive care unit (ICU) admission, and different regimens during the ICU stay. The rate of bacterial co-infection was 51.1%, mainly from gram-negative isolates ( Enterobacter species and K.pneumoniae). The rate of fungal co-infection caused by A.fumigatus was 48.9%, and the mortality rate was 8.1%. However, it is unclear if it had been attributed to SARS-CoV-2 or coincidental.

Conclusions: Bacterial and fungal co-infection is common among COVID-19 patients at the ICU in Palestine, but it is not obvious if these cases are attributed to SARS-CoV-2 or coincidental, because little data is available to compare it with the rates of secondary infection in local ICU departments before the pandemic. Comprehensively, those conclusions present data supporting a conservative antibiotic administration for severely unwell COVID-19 infected patients. Our examination regarding the impacts of employing antifungals to manage COVID-19 patients can work as a successful reference for future COVID-19 therapy.

Low Oxygen Saturation of COVID-19 in Patient Case Fatalities, Limpopo Province, South Africa

On 1 August 2020, South Africa’s Minister of Health announced that more than half of a million coronavirus cases were confirmed in the country. South Africa was by far the hardest-hit country in Africa, accounting for half of all infections reported across the continent. The prevalence of underlying conditions such as fever and blood oxygen saturation (SpO2) has been known known to be a significant determinant in the hospitalisation of COVID-19 patients. Low oxygen saturation on admission was reported as a strong predictor of in-hospital mortality in COVID-19 patients. The study sought to assess the association between body temperature and other clinical risk factors with low SpO2 among COVID-19 inpatient case fatalities. A quantitative retrospective study was carried out in Limpopo Province, employing secondary data from the Limpopo Department of Health (LDoH) on COVID-19 inpatients case fatalities across all districts in the province. The chi-square test and Pearson’s correlation coefficient were used to assess the relationship between body temperature and clinical risk factors with SpO2 levels. The findings of this paper indicated that age (older age), chills, sore throat, anosmia, dysgeusia, myalgia/body aches, diarrhoea and HIV/AIDS were associated with low SpO2 in-hospital mortality in COVID-19 patients. Nasal prongs and a face mask with a reservoir for respiratory support cannula were commonly used patient interfaces to provide supplemental oxygen, with the use of only a high-flow nasal cannula (HFNC) being minimal (7%). The majority of COVID-19 inpatient fatalities had normal body temperature (<38 °C) and SpO2, with no correlation between the two variables. Considering temperature screening as a possible strategy to combat the spread of COVID-19 or suspicious COVID-19 cases appeared, then, to be a pointless exercise. This study aimed to recommend new clinical criteria for detecting COVID-19 cases.

Prognostic value of copeptin and mid-regional proadrenomedullin in COVID-19-hospitalized patients

BACKGROUND

Biomarkers are used for diagnosis, risk stratification and medical decisions. Copeptin and mid-regional proadrenomedullin (MR-proADM) are markers of stress and endothelial function, respectively, which have been studied in pneumonia, sepsis and septic shock. This study aimed to assess whether copeptin and MR-proADM could predict coronavirus disease 2019 (COVID-19) in-hospital outcomes, that is multi-system complications, length of stay and mortality.

METHODS

Copeptin and MR-proADM were assessed at admission in 116 patients hospitalized with COVID-19. Data were retrospectively extracted from an online database. The primary endpoint was in-hospital mortality. The secondary endpoints were in-hospital complications, the composite outcome 'death, or admission to intensive care unit, or in-hospital complications', and length of stay. The predictive power was expressed as area under the receiver operator characteristic curve (AUROC).

RESULTS

Copeptin was increased in non-survivors (median 29.7 [interquartile range 13.0-106.2] pmol/L) compared to survivors (10.9 [5.9-25.3] pmol/L, p < 0.01). The AUROC for mortality was 0.71, with a hazard ratio of 3.67 (p < 0.01) for copeptin values > 25.3 pmol/L. MR-proADM differentiated survivors (0.8 [0.6-1.1] nmol/L) from non-survivors (1.5 [1.1-2.8] nmol/L, p < 0.001) and yielded a AUROC of 0.79 and a hazard ratio of 7.02 (p < 0.001) for MR-proADM values > 1.0 nmol/L. Copeptin and MR-proADM predicted sepsis (AUROC 0.95 and 0.96 respectively), acute kidney injury (0.87 and 0.90), the composite outcome (0.69 and 0.75) and length of stay (r = 0.42, p < 0.001, and r = 0.46, p < 0.001).

CONCLUSIONS

Admission MR-proADM and copeptin may be implemented for early risk stratification in COVID-19-hospitalized patients to help identify those eligible for closer monitoring and care intensification.

Mortality Predictive Value of APACHE II and SOFA Scores in COVID-19 Patients in the Intensive Care Unit

Background. COVID-19 pandemic has become a global dilemma since December 2019. Are the standard scores, such as acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA) score, accurate for predicting the mortality rate of COVID-19 or the need for new scores? We aimed to evaluate the mortality predictive value of APACHE II and SOFA scores in critically ill COVID-19 patients. Methods. In a cohort study, we enrolled 204 confirmed COVID-19 patients admitted to the intensive care units at the Imam Khomeini hospital complex. APACHE II on the first day and daily SOFA scoring were performed. The primary outcome was the mortality rate in the nonsurvived and survived groups, and the secondary outcome was organ dysfunction. Two groups of survived and nonsurvived patients were compared by the chi-square test for categorical variables and an independent sample t-test for continuous variables. We used logistic regression models to estimate the mortality risk of high APACHE II and SOFA scores. Result. Among 204 severe COVID-19 patients, 114 patients (55.9%) expired and 169 patients (82.8%) had at least one comorbidity that 103 (60.9%) of them did not survive ( $P=0.002$ ). Invasive mechanical ventilation and its duration were significantly different between survived and nonsurvived groups ( $P\le 0.001$ and $P=0.002$ , respectively). Mean APACHE II and mean SOFA scores were significantly higher in the nonsurvived than in the survived group (14.4 ± 5.7 vs. 9.5 ± 5.1, $P\le 0.001$ , 7.3 ± 3.1 vs. 3.1 ± 1.1, $P\le 0.001$ , respectively). The area under the curve was 89.5% for SOFA and 73% for the APACHE II score. Respiratory diseases and malignancy were risk factors for the mortality rate ( $P=0.004$ and $P=0.007$ , respectively) against diabetes and hypertension. Conclusion. The daily SOFA was a better mortality predictor than the APACHE II in critically ill COVID-19 patients. But they could not predict death with high accuracy. We need new scoring with consideration of the prognostic factors and daily evaluation of changes in clinical conditions.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18–60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%–60%) and the plasma concentrations increased (170%–400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.

Incidence and investigation of Covid-19 trend in Babol, northern Iran: A Joinpoint regression analysis

BACKGROUND

In December 2019, China released the first report of the coronavirus (COVID-19). On March 11, 2020 the World Health Organization (WHO) characterized the COVID-19 as "pandemic". The rapid occurrence of positive cases motivated this study to examine the trend of incidence cases.

METHODS

We used the data from the database of the Deputy of Health of Babol City and in Iran, the country report of definite cases of the disease that was reported to the World Health Organization had been used. This study was a cross-sectional study and the data from period of 56 weeks (from February 24, 2020 to March 20, 2021) were gathered. Descriptive analysis with SPSS20 and data classification with EXCEL2016 and Joinpoint regression with Joinpoint trend analysis software 4.9.0.0 identify the significant changes in the temporal trends of the outbreak.

RESULTS

In this study, 11341 patients with a mean age of 53.56 years, of whom 5865(51.5%) were males, were studied. Three waves of Covid19 were created. AWPC (average weekly percentage change) incidence rate with a slope of 2.7 was estimated for Babol and 6.2 for Iran. The incidence was higher in men in the first wave of 1887(55.6%) and so is the third 2373(50.1%), the average age in the third wave (50.92) was lower than the other waves as well.

CONCLUSION

The incidence of coronavirus in men was higher in three waves and also the incidence was increasing in younger age groups. Also, due to the observance of health protocols and quarantine during the peak in Iran and Babol, we witnessed a decrease in incidence.

COVID-19 Detection Using the NHS Lateral Flow Test Kit

Approximately one in three people infected with the SARS-CoV-2 virus have mild symptoms or are asymptomatic. However, these individuals can still spread the virus. Regular self-testing can help to detect these individuals and thereby slow the spread and protect the more vulnerable members of society. Here, we present a protocol for use of the COVID-19 rapid antigen test which was made freely available to residents of the United Kingdom in April of this year. This using the lateral flow technique for detection of antigens and is amenable to multiplexing.

COVID-19 and chronic kidney disease: an updated overview of reviews

BACKGROUND

Coronavirus disease (COVID-19) has resulted in the death of more than 3.5 million people worldwide. While COVID-19 mostly affects the lungs, different comorbidities can have an impact on its outcomes. We performed an overview of reviews to assess the effect of Chronic Kidney Disease (CKD) on contracting COVID-19, hospitalization, mortality, and disease severity.

METHODS

We searched published and preprint databases. We updated the reviews by searching for primary studies published after August 2020, and prioritized reviews that are most updated and of higher quality using the AMSTAR tool.

RESULTS

We included 69 systematic reviews and 66 primary studies. Twenty-eight reviews reported on the prevalence of CKD among patients with COVID-19, which ranged from 0.4 to 49.0%. One systematic review showed an increased risk of hospitalization in patients with CKD and COVID-19 (RR = 1.63, 95% CI 1.03-2.58) (Moderate certainty). Primary studies also showed a statistically significant increase of hospitalization in such patients. Thirty-seven systematic reviews assessed mortality risk in patients with CKD and COVID-19. The pooled estimates from primary studies for mortality in patients with CKD and COVID-19 showed a HR of 1.48 (95% CI 1.33-1.65) (Moderate certainty), an OR of 1.77 (95% CI 1.54-2.02) (Moderate certainty) and a RR of 1.6 (95% CI 0.88-2.92) (Low certainty).

CONCLUSIONS

Our review highlights the impact of CKD on the poor outcomes of COVID-19, underscoring the importance of identifying strategies to prevent COVID-19 infection among patients with CKD.

Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy

The outbreak of Coronavirus (COVID-19) has spread between people around the world at a rapid rate so that the number of infected people and deaths is increasing quickly every day. Accordingly, it is a vital process to detect positive cases at an early stage for treatment and controlling the disease from spreading. Several medical tests had been applied for COVID-19 detection in certain injuries, but with limited efficiency. In this study, a new COVID-19 diagnosis strategy called Feature Correlated Naïve Bayes (FCNB) has been introduced. The FCNB consists of four phases, which are; Feature Selection Phase (FSP), Feature Clustering Phase (FCP), Master Feature Weighting Phase (MFWP), and Feature Correlated Naïve Bayes Phase (FCNBP). The FSP selects only the most effective features among the extracted features from laboratory tests for both COVID-19 patients and non-COVID-19 people by using the Genetic Algorithm as a wrapper method. The FCP constructs many clusters of features based on the selected features from FSP by using a novel clustering technique. These clusters of features are called Master Features (MFs) in which each MF contains a set of dependent features. The MFWP assigns a weight value to each MF by using a new weight calculation method. The FCNBP is used to classify patients based on the weighted Naïve Bayes algorithm with many modifications as the correlation between features. The proposed FCNB strategy has been compared to recent competitive techniques. Experimental results have proven the effectiveness of the FCNB strategy in which it outperforms recent competitive techniques because it achieves the maximum (99%) detection accuracy.

The impact of casirivimab-imdevimab antibody cocktail in patients amidst and post COVID 19 treatment: A retro-prospective comparative study in India

Background

Monoclonal antibodies have gained attention in developing countries owing to its benefits portrayed by few clinical trials. However, no studies until now have been undergone in India.

Methods

A retro-prospective comparative observational study was conducted in symptomatic COVID19 patients to evaluate the impact of Casirivimab and Imdevimab antibody cocktail in the high-risk population. Through an extensive data retrieval for 6 months, 152 samples were documented and sorted into test (Casirivimab and Imdevimab treated patients, n = 79) and control (Non- Casirivimab and Imdevimab treated individuals, n = 73) subsets. The research had two phases; first, estimation of mechanical ventilation and high flow oxygen requirement and mortality in samples amidst the treatment, and second was the post COVID19 patients' feedback through validated (Cronbach's alpha coefficient = 0.7) questionnaire that evaluated their health and vaccination status, and treatment satisfaction.

Results

We noticed lesser requisite for mechanical ventilation (6.3%; p < 0.001), high flow oxygen (5.1%; p < 0.001) and no death during Casirivimab and Imdevimab therapy. Meanwhile, non-vaccinated test groups were not on mechanical ventilation and those fully immunized seldom entailed high flow oxygen (test, 6.3%; control, 41.9%, p < 0.01). On evaluating the post COVID19 status of each patient in the study, 90.1% of the test samples were healthy and 97.2% were satisfied with the treatment than those in control group.

Conclusions

Casirivimab and Imdevimab regimen was clinically beneficial for high risk COVID19 patients than those treated without the antibody cocktail.

Lung Ultrasound Findings Associated With COVID-19 ARDS, ICU Admission, and All-Cause Mortality

BACKGROUND

As lung ultrasound (LUS) has emerged as a diagnostic tool in patients with COVID-19, we sought to investigate the association between LUS findings and the composite in-hospital outcome of ARDS incidence, ICU admission, and all-cause mortality.

METHODS

In this prospective, multi-center, observational study, adults with laboratory-confirmed SARS-CoV-2 infection were enrolled from non-ICU in-patient units. Subjects underwent an LUS evaluating a total of 8 zones. Images were analyzed off-line, blinded to clinical variables and outcomes. A LUS score was developed to integrate LUS findings: ≥ 3 B-lines corresponded to a score of 1, confluent B-lines to a score of 2, and subpleural or lobar consolidation to a score of 3. The total LUS score ranged from 0-24 per subject.

RESULTS

Among 215 enrolled subjects, 168 with LUS data and no current signs of ARDS or ICU admission (mean age 59 y, 56% male) were included. One hundred thirty-six (81%) subjects had pathologic LUS findings in ≥ 1 zone (≥ 3 B-lines, confluent B-lines, or consolidations). Markers of disease severity at baseline were higher in subjects with the composite outcome (n = 31, 18%), including higher median C-reactive protein (90 mg/L vs 55, P < .001) and procalcitonin levels (0.35 μg/L vs 0.13, P = .033) and higher supplemental oxygen requirements (median 4 L/min vs 2, P = .001). However, LUS findings and score did not differ significantly between subjects with the composite outcome and those without, and were not associated with outcomes in unadjusted and adjusted logistic regression analyses.

CONCLUSIONS

Pathologic findings on LUS were common a median of 3 d after admission in this cohort of non-ICU hospitalized subjects with COVID-19 and did not differ among subjects who experienced the composite outcome of incident ARDS, ICU admission, and all-cause mortality compared to subjects who did not. These findings should be confirmed in future investigations. The study is registered at Clinicaltrials.gov (NCT04377035).

Incidence of cardiac complications following COVID-19 infection: An umbrella meta-analysis study

Background

COVID-19 causes fatal cardiac damages. Despite many overwhelming meta-analysis related to cardiac complications following COVID-19 disease, no umbrella meta-analysis study has been conducted.

Objectives

We aimed to report the summarized pooled incidences of cardiac complications in the overall, critically ill, and deceased patients, compare the cardiac complications between the severe/non-severe or deceased/non-deceased patients, and also compare poor outcomes between patients with/without acute myocardial injury (AMI).

Methods

PubMed, Scopus, web of science, Cochrane, ProQuest, Springer, Sage journals were searched before April 2021. After assessing the quality and duplicate data, data were run by the random/fixed-effect models, I2 heterogeneity index, Egger's test, and sensitivity analysis.

Results

After removing duplicate data, in the overall COVID-19 patients, the pooled incidence of AMI, heart failure, arrhythmia, cardiac arrest, and acute coronary syndrome (ACS) were 21%, 14%, 16%, 3.46%, and 1.3%, respectively. In the patients with severe disease, the pooled incidence of AMI and shock were 33 and 35%, respectively. Similarly, in the deceased COVID-19 patients, the pooled incidence rate of AMI and arrhythmia were 56% and 47.5%, respectively. The patients with severe disease were at higher risk of AMI (RR = 5.27) and shock (OR = 20.18) compared with the non-severe cases. Incidence of AMI was associated with transfer to the intensive care units (ICU) (RR = 2.92) and mortality (RR = 2.57, OR = 8.36), significantly.

Conclusion

Cardiac complications were found to be increased alarmingly in COVID-19 patients. Baseline and during hospitalization checking with electrocardiography, echocardiography, and measuring of cardiac biomarkers should be applied.

Clinical and laboratory factors associated with coronavirus disease 2019 (Covid-19): A systematic review and meta-analysis

SARS Coronavirus-2 is one of the most widespread viruses globally during the 21st century, whose severity and ability to cause severe pneumonia and death vary. We performed a comprehensive systematic review of all studies that met our standardised criteria and then extracted data on the age, symptoms, and different treatments of Covid-19 patients and the prognosis of this disease during follow-up. Cases in this study were divided according to severity and death status and meta-analysed separately using raw mean and single proportion methods. We included 171 complete studies including 62,909 confirmed cases of Covid-19, of which 148 studies were meta-analysed. Symptoms clearly emerged in an escalating manner from mild-moderate symptoms, pneumonia, severe-critical to the group of non-survivors. Hypertension (Pooled proportion (PP): 0.48 [95% Confident interval (CI): 0.35-0.61]), diabetes (PP: 0.23 [95% CI: 0.16-0.33]) and smoking (PP: 0.12 [95% CI: 0.03-0.38]) were highest regarding pre-infection comorbidities in the non-survivor group. While acute respiratory distress syndrome (PP: 0.49 [95% CI: 0.29-0.78]), (PP: 0.63 [95% CI: 0.34-0.97]) remained one of the most common complications in the severe and death group respectively. Bilateral ground-glass opacification (PP: 0.68 [95% CI: 0.59-0.75]) was the most visible radiological image. The mortality rates estimated (PP: 0.11 [95% CI: 0.06-0.19]), (PP: 0.03 [95% CI: 0.01-0.05]), and (PP: 0.01 [95% CI: 0-0.3]) in severe-critical, pneumonia and mild-moderate groups respectively. This study can serve as a high evidence guideline for different clinical presentations of Covid-19, graded from mild to severe, and for special forms like pneumonia and death groups.

Association Between the "COVID-19 Occupational Vulnerability Index" and COVID-19 Severity and Sequelae Among Hospital Employees

OBJECTIVES

In addition to personal and health related factors, healthcare workers have an increased risk due to their work. We assessed the association of the score of the Occupational Vulnerability Index with the risk of suffering a severe COVID-19 and sequelae.

METHODS

Retrospective observational study carried out in healthcare workers. Among 119 employees infected, the COVID-19 Occupational Vulnerability Index (composed of 29 items regarding personal health, working conditions, and ability to comply with preventive measures) was calculated and correlated with COVID-19 severity/sequelae.

RESULTS

Workers with higher scores (six to seven points) had a significantly increased risk of developing severe disease (OR = 9.73; 95% CI, 1.53 to 35.56) and clinical sequelae (OR = 5.22; 95% CI, 1.80 to 15.16) than those with lower scores (0 to 3).

CONCLUSION

The "COVID-19 Occupational Vulnerability Index" may predict the risk of severe COVID-19 disease and clinical sequelae among healthcare workers.

Adverse Cardiovascular Effects of Anti-COVID-19 Drugs

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or COVID-19 infection is the cause of the ongoing global pandemic. Mortality from COVID-19 infection is particularly high in patients with cardiovascular diseases. In addition, COVID-19 patients with preexisting cardiovascular comorbidities have a higher risk of death. Main cardiovascular complications of COVID-19 are myocardial infarction, myocarditis, acute myocardial injury, arrhythmias, heart failure, stroke, and venous thromboembolism. Therapeutic interventions in terms of drugs for COVID-19 have many cardiac adverse effects. Here, we review the relative therapeutic efficacy and adverse effects of anti-COVID-19 drugs.

The Macklin Effect in COVID-19

From the mere outlook of the ongoing pandemic, coronavirus (severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2) seems to target mainly the respiratory system, but more evolving evidence has advocated its multi-organ involvement. While various complications have been reported in coronavirus disease 2019 (COVID-19) patients, spontaneous pneumomediastinum (SP) remains an uncommon complication.

Critical appraisal of the mechanisms of gastrointestinal and hepatobiliary infection by COVID-19

COVID-19 represents a novel infectious disease induced by SARS-CoV-2. It has to date affected 24,240,000 individuals and killed 2,735,805 people worldwide. The highly infectious virus attacks mainly the lung, causing fever, cough, and fatigue in symptomatic patients, but also pneumonia in severe cases. However, growing evidence highlights SARS-CoV-2-mediated extrarespiratory manifestations, namely, gastrointestinal (GI) and hepatic complications. The detection of 1) the virus in the GI system (duodenum, colon, rectum, anal region, and feces); 2) the high expression of additional candidate coreceptors/auxiliary proteins to facilitate the virus entry; 3) the abundant viral angiotensin-converting enzyme 2 receptor; 4) the substantial expression of host transmembrane serine protease 2, necessary to induce virus-cell fusion; 5) the viral replication in the intestinal epithelial cells; and 6) the primarily GI disorders in the absence of respiratory symptoms lead to increased awareness of the risk of disease transmission via the fecal-oral route. The objectives of this review are to provide a brief update of COVID-19 pathogenesis and prevalence, present a critical overview of its GI and liver complications that affect clinical COVID-19 outcomes, clarify associated mechanisms (notably microbiota-related), define whether gut/liver disorders occur more frequently among critically ill patients with COVID-19, determine the impact of COVID-19 on preexisting gut/liver complications and vice versa, and discuss the available strategies for prevention and treatment to improve prognosis of the patients. The novel SARS-CoV-2 can cause gastrointestinal and hepatobiliary manifestations. Metagenomics studies of virobiota in response to SARS-CoV-2 infection are necessary to highlight the contribution of bacterial microflora to COVID-19 phenotype, which is crucial for developing biomarkers and therapeutics.

Roles of certain biochemical and hematological parameters in predicting mortality and ICU admission in COVID-19 patients

OBJECTIVE

In this study, we aimed to retrospectively analyze the roles of certain hematological and biochemical parameters in predicting mortality and intensive care unit admission in patients diagnosed with coronavirus disease 2019 (COVID-19).

METHODS

We analyzed the complete blood count and biochemical parameters of 186 COVID-19 patients by using the polymerase chain reaction test. Whether these parameters can be used to predict intensive care unit admission and mortality in the COVID-19 patients was investigated.

RESULTS

The complete blood count and biochemical parameters of COVID-19 patients and in those admitted to intensive care unit were compared. The red cell distribution width, ferritin, lactate dehydrogenase, D-dimer, C-reactive protein, prothrombin time, and creatinine levels were found to be the most significant parameters. We found that these parameters are significant for predicting not only intensive care unit admission, but also the mortality of the patients admitted to the intensive care unit.

CONCLUSIONS

We determined that the most effective parameters to predict intensive care unit admission and mortality in COVID-19 patients are ferritin, lactate dehydrogenase, D-dimer, C-reactive protein, red cell distribution width, creatinine, and intensive care unit. Close monitoring of these parameters and early intervention in alterations are of vital importance.

The risk factors and related hospitalizations for cases with positive and negative COVID-19 tests: A case-control study

BACKGROUND

The aim of this study was to evaluate the risk factors for hospitalizations of cases with positive and negative COVID-19 tests.

METHODS

In this case-control study, the case and control groups consisted of 292 COVID-19 patients and 296 non-COVID-19 patients. Patients who referred to a reference laboratory in Tehran (Iran) in March 2020 were selected and interviewed. The patients were contacted by telephone and data were recorded through a questionnaire.

RESULTS

The sample of this study consisted of 588 patients (349 [59%] females, 239 [41%] males) with a mean age of 42 ± 15. The results of this study showed that comorbidities like diabetes (OR = 7.42), hypertension (OR = 4.85), asthma and respiratory diseases (OR = 5.64) in addition to symptoms including fever (OR = 6.67), chills (OR = 11.2), anorexia (OR = 11.3), dyspnea (OR = 4.8), weakness and lethargy (OR = 5.7) were the most predictive variables for hospitalization of non-COVID-19 cases. Furthermore, demographical variables like male gender (OR = 3.71), high age (>50; OR = 3.12), BMI (>25; OR = 2.37), travel (OR = 2.79), comorbidities including diabetes (OR = 5.26), hypertension (OR = 3.7) and underlying immunosuppressant patients receiving corticosteroid therapy (OR = 3.62) in addition to symptoms like anorexia [OR = 2.55] and dyspnea (OR = 6.99) tend to increase the risk of hospital admission in COVID-19 patients, suggesting their predictive values for hospitalization of COVID-19 patients.

CONCLUSION

Our results indicated that different factors tend to increase the odds of hospital admission in patients with positive and negative COVID-19 tests, suggesting their predictive values for hospitalization.

Covid-19 and non-communicable diseases: evidence from a systematic literature review

BACKGROUND

Since early 2020, the Covid-19 pandemic has engulfed the world. Amidst the growing number of infections and deaths, there has been an emphasis of patients with non-communicable diseases as they are particularly susceptible to the virus. The objective of this literature review is to systematize the available evidence on the link between non-communicable diseases and Covid-19.

METHODS

We have conducted a systematic review of the literature on Covid-19 and non-communicable diseases from December, 2019 until 15th of November, 2020. The search was done in PubMed and in doing so we used a variety of searching terms in order to isolate the final set of papers. At the end of the selection process, 45 papers were selected for inclusion in the literature review.

RESULTS

The results from the review indicate that patients with certain chronic illnesses such as diabetes, hypertension (and other cardiovascular diseases), chronic respiratory illnesses, chronic kidney and liver conditions are more likely to be affected by Covid-19. More importantly, once they do get infected by the virus, patients with chronic illnesses have a much higher likelihood of having worse clinical outcomes (developing a more severe form of the disease or dying) than an average patient. There are two hypothesized channels that explain this strong link between the chronic illnesses enumerated above and Covid 19: (i) increased ACE2 (angiotensin-converting enzyme 2) receptor expressions, which facilitates the entry of the virus into the host body; and (ii) hyperinflammatory response, referred to as "cytokine storm". Finally, the literature review does not find any evidence that diabetes or hypertension related medications exacerbate the overall Covid-19 condition in chronic illness patients.

CONCLUSIONS

Thus, the evidence points out to 'business as usual' disease management model, although with greater supervision. However, given the ongoing Covid-19 vulnerabilities among people with NCDs, prioritizing them for the vaccination process should also figure high on the agenda on health authorities.

Diabetes is most important cause for mortality in COVID-19 hospitalized patients: Systematic review and meta-analysis

The presence of SARS-CoV-2 was officially documented in Europe at the end of February 2020. Despite many observations, the real impact of COVID-19 in the European Union (EU), its underlying factors and their contribution to mortality and morbidity outcomes were never systematically investigated. The aim of the present work is to provide an overview and a meta-analysis of main predictors and of country differences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-associated mortality rate (MR) in hospitalized patients. Out of 3714 retrieved articles, 87 studies were considered, including 35,486 patients (mean age 60.9 ± 8.2 years) and 5867 deaths. After adjustment for confounders, diabetes mellitus was the best predictors of MR in an age- and sex-dependent manner, followed by chronic pulmonary obstructive diseases and malignancies. In both the US and Europe, MR was higher than that reported in Asia (25[20;29] % and 20[17;23] % vs. 13[10;17]%; both p < 0.02). Among clinical parameters, dyspnea, fatigue and myalgia, along with respiratory rate, emerged as the best predictors of MR. Finally, reduced lymphocyte and platelet count, along with increased D-dimer levels, all significantly contributed to increased mortality. The optimization of glucose profile along with an adequate thrombotic complications preventive strategy must become routine practice in diseased SARS-CoV-2 infected patients.

The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study

BACKGROUND

The coronavirus disease of 2019 (COVID-19) has quickly spread to all corners of the world since its emergence in Wuhan, China in December of 2019. The disease burden has been heterogeneous across regions of the world, with Americas leading in cumulative cases and deaths, followed by Europe, Southeast Asia, Eastern Mediterranean, Africa and Western Pacific. Initial responses to COVID-19 also varied between governments, ranging from proactive containment to delayed intervention. Understanding these variabilities allow high burden countries to learn from low burden countries on ways to create more sustainable response plans in the future.

METHODS

This study used a mixed-methods approach to perform cross-country comparisons of pandemic responses in the United States (US), Brazil, Germany, Australia, South Korea, Thailand, New Zealand, Italy and China. These countries were selected based on their income level, relative COVID-19 burden and geographic location. To rationalize the epidemiological variability, a list of 14 indicators was established to assess the countries' preparedness, actual response, and socioeconomic and demographic profile in the context of COVID-19.

RESULTS

As of 1 April 2021, the US had the highest cases per million out of the nine countries, followed by Brazil, Italy, Germany, South Korea, Australia, New Zealand, Thailand and China. Meanwhile, Italy ranked first out of the nine countries' total deaths per million, followed by the US, Brazil, Germany, Australia, South Korea, New Zealand, China and Thailand. The epidemiological differences between these countries could be explained by nine indicators, and they were 1) leadership, governance and coordination of response, 2) communication, 3) community engagement, 4) multisectoral actions, 5) public health capacity, 6) universal health coverage, 7) medical services and hospital capacity, 8) demography and 9) burden of non-communicable diseases.

CONCLUSION

The COVID-19 pandemic manifests varied outcomes due to differences in countries' vulnerability, preparedness and response. Our study rationalizes why South Korea, New Zealand, Thailand, Australia and China performed better than the US, Italy and Brazil. By identifying the strengths of low burden countries and weaknesses of hotspot countries, we elucidate factors constituting an effective pandemic response that can be adopted by leaders in preparation for re-emerging public health threats.

Multiple domains of functioning in older adults during the pandemic: design and basic characteristics of the Longitudinal Aging Study Amsterdam COVID-19 questionnaire

The Longitudinal Aging Study Amsterdam (LASA) is an ongoing cohort study among older adults in the Netherlands. Respondents are usually interviewed approximately every 3 years. Because of the exceptional situation of the COVID-19 pandemic, it was decided to add an extra assessment in between, consisting of a postal/digital questionnaire with measures assessing the impact of the COVID-19 situation, as well as a selection of measures from regular LASA measurement cycles covering the physical, social and mental domains. In total, 1128 LASA respondents aged 62-102 years provided data, just after the first wave of the pandemic in 2020. This paper describes the methods and design of the LASA COVID-19 questionnaire, as well as the basic characteristics of the sample, including an overview of impactful situations experienced by older adults during the first months of the pandemic. The data of the questionnaire may be used to study the impact of the COVID-19 pandemic on multiple domains of functioning in older adults.

An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors

Experts have predicted that COVID-19 may prevail for many months or even years before it can be completely eliminated. A major problem in its cure is its early screening and detection, which will decide on its treatment. Due to the fast contactless spreading of the virus, its screening is unusually difficult. Moreover, the results of COVID-19 tests may take up to 48 h. That is enough time for the virus to worsen the health of the affected person. The health community needs effective means for identification of the virus in the shortest possible time. In this study, we invent a medical device utilized consisting of composable sensors to monitor remotely and in real-time the health status of those who have symptoms of the coronavirus or those infected with it. The device comprises wearable medical sensors integrated using the Arduino hardware interfacing and a smartphone application. An IoT framework is deployed at the backend through which various devices can communicate in real-time. The medical device is applied to determine the patient's critical status of the effects of the coronavirus or its symptoms using heartbeat, cough, temperature and Oxygen concentration (SpO2) that are evaluated using our custom algorithm. Until now, it has been found that many coronavirus patients remain asymptomatic, but in case of known symptoms, a person can be quickly identified with our device. It also allows doctors to examine their patients without the need for physical direct contact with them to reduce the possibility of infection. Our solution uses rule-based decision-making based on the physiological data of a person obtained through sensors. These rules allow to classify a person as healthy or having a possibility of infection by the coronavirus. The advantage of using rules for patient's classification is that the rules can be updated as new findings emerge from time to time. In this article, we explain the details of the sensors, the smartphone application, and the associated IoT framework for real-time, remote screening of COVID-19.

Potential COVID-19 Therapeutic Agents and Vaccines: An Evidence-Based Review

Since the early days of 2020, the severe acute respiratory syndrome coronavirus 2 pandemic has become a global health concern. Currently, some therapies and vaccines have received US Food and Drug Administration approval or emergency use authorization for the management of coronavirus disease 2019. According to the pathophysiology of the disease, several medications have been evaluated in different clinical conditions of the disease. Evidence-based reviewing and categorizing these medications can guide the clinicians to select the proper medications according to each patient's condition. Therefore, we performed this review to categorize the coronavirus disease 2019 potential therapeutics and vaccines.

COVID-19 in People Living with HIV: A Systematic Review and Meta-Analysis

COVID-19 is a global health emergency. People living with human immunodeficiency virus (PLHIV) have concerns about whether they have a higher risk of getting the infection and suffer worse COVID-19 outcomes. Findings from studies on these questions have largely been inconsistent. We aimed to determine the epidemiological characteristics, clinical signs and symptoms, blood parameters, and clinical outcomes among PLHIV who contracted COVID-19. Relevant studies were identified through Medline, Cinahl, and PubMed databases. A random-effects model was used in meta-analyses with a 95% confidence interval. Eighty-two studies were included in the systematic review and sixty-seven studies for the meta-analysis. The pooled incidence proportion of COVID-19 among PLHIV was 0.9% (95% CI 0.6%, 1.1%) based on the data from seven cohort studies. Overall, 28.4% were hospitalised, of whom, 2.5% was severe-critical cases and 3.5% needed intensive care. The overall mortality rate was 5.3%. Hypertension was the most commonly reported comorbidity (24.0%). Fever (71.1%) was the most common symptom. Chest imaging demonstrated a wide range of abnormal findings encompassing common changes such as ground glass opacities and consolidation as well as a spectrum of less common abnormalities. Laboratory testing of inflammation markers showed that C-reactive protein, ferritin, and interleukin-6 were frequently elevated, albeit to different extents. Clinical features as well as the results of chest imaging and laboratory testing were similar in highly active antiretroviral therapy (HAART)-treated and non-treated patients. PLHIV were not found to be at higher risk for adverse outcomes of COVID-19. Hence, in COVID-19 management, it appears that they can be treated the same way as HIV negative individuals. Nevertheless, as the pandemic situation is rapidly evolving, more evidence may be needed to arrive at definitive recommendations.

Predictive Biomarkers of COVID-19 Severity in SARS-CoV-2 Infected Patients with Obesity and Metabolic Syndrome

In SARS-CoV-2-infected patients, obesity, hypertension, and diabetes are dangerous factors that may result in death. Priority in detection and specific therapies for these patients are necessary. We wanted to investigate the impact of obesity and metabolic syndrome (MS) on the clinical course of COVID-19 and whether prognostic biomarkers described are useful to predict the evolution of COVID-19 in patients with obesity or MS. This prospective cohort study included 303 patients hospitalized for COVID-19. Participants were first classified according to the presence of obesity; then, they were classified according to the presence of MS. Clinical, radiologic, and analytical parameters were collected. We reported that patients with obesity presented moderate COVID-19 symptoms and pneumonia, bilateral pulmonary infiltrates, and needed tocilizumab more frequently. Meanwhile, patients with MS presented severe pneumonia and respiratory failure more frequently, they have a higher mortality rate, and they also showed higher creatinine and troponin levels. The main findings of this study are that IL-6 is a potential predictor of COVID-19 severity in patients with obesity, while troponin and LDH can be used as predictive biomarkers of COVID-19 severity in MS patients. Therefore, treatment for COVID-19 in patients with obesity or MS should probably be intensified and personalized.