Host susceptibility to severe COVID-19 and establishment of a host risk score: findings of 487 cases outside Wuhan

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.

A multi-center study of COVID-19 patient prognosis using deep learning-based CT image analysis and electronic health records

PURPOSE

As of August 30th, there were in total 25.1 million confirmed cases and 845 thousand deaths caused by coronavirus disease of 2019 (COVID-19) worldwide. With overwhelming demands on medical resources, patient stratification based on their risks is essential. In this multi-center study, we built prognosis models to predict severity outcomes, combining patients' electronic health records (EHR), which included vital signs and laboratory data, with deep learning- and CT-based severity prediction.

METHOD

We first developed a CT segmentation network using datasets from multiple institutions worldwide. Two biomarkers were extracted from the CT images: total opacity ratio (TOR) and consolidation ratio (CR). After obtaining TOR and CR, further prognosis analysis was conducted on datasets from INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3. For each data cohort, generalized linear model (GLM) was applied for prognosis prediction.

RESULTS

For the deep learning model, the correlation coefficient of the network prediction and manual segmentation was 0.755, 0.919, and 0.824 for the three cohorts, respectively. The AUC (95 % CI) of the final prognosis models was 0.85(0.77,0.92), 0.93(0.87,0.98), and 0.86(0.75,0.94) for INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3 cohorts, respectively. Either TOR or CR exist in all three final prognosis models. Age, white blood cell (WBC), and platelet (PLT) were chosen predictors in two cohorts. Oxygen saturation (SpO2) was a chosen predictor in one cohort.

CONCLUSION

The developed deep learning method can segment lung infection regions. Prognosis results indicated that age, SpO2, CT biomarkers, PLT, and WBC were the most important prognostic predictors of COVID-19 in our prognosis model.

Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score

Background

COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate.

Methods

This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers.

Results

Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p=e^{(−2.4475+0.02492age − 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH)}/1+e^{(−2.4475+ 0.02492age − 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH)}.

Conclusions

Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission.

Viral Respiratory Tract Pathogens During the COVID-19 Pandemic

Objective

This study aimed to report viral respiratory pathogens during the coronavirus disease 2019 (COVID-19) pandemic.

Materials and Methods

Other viral pathogens were identified. COVID-19 immunoglobulin M and immunoglobulin G were detected.

Results

Of the 56 samples collected from women, 2 (3.5%) were positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whereas 8 (10%) of the 80 samples from men were positive for SARS-CoV-2. The number of respiratory syncytial virus-A-positive cases was 6 (10.7%) in women and 14 (17.5%) in men. Two (3.5%) of the women were positive for parainfluenza-3, and 6 of the men were positive for influenza-B. The number of human metapneumovirus (HMPV)-positive women and men was 6 (10.7%) and 6 (7.5%), respectively. Rhinovirus caused 14.2% and 10% of the cases in men and women, respectively. With a ratio of 10.7% in women and 7.5% in men; SARS-CoV-2, with a ratio of 10% in men and 3.5% in women; influenza-B, with a ratio of 7.5% in men; and parainfluenza-3 and 4, with a ratio of 3.5% in women. SARS-CoV-2 had a mean incidence rate of 7% in men and women. The antibody screening results reveal that antibody formation did not occur in 3 women among the 10 patients who were diagnosed with COVID-19, and antibody formation occurred in 2 of 7 men. Antibody formation occurred in 5 women (16.6%) and 7 men (20.5%) among the 58 patients who were positive for other respiratory tract pathogens. However, 23 (29.5%) of the blood samples collected from 78 individuals who were negative for the COVID-19 agent and other respiratory tract viral pathogens were positive for the COVID-19 antibody.

Conclusion

Because the climate is colder than normal in areas settled at higher altitudes, more than one pathogens act together. In addition, respiratory infections are seen in all seasons. This causes the diseases to be fewer and milder than in other regions.

Early vs. Late Onset Cardiac Injury and Mortality in Hospitalized COVID-19 Patients in Wuhan

Background: Increasing evidence points to cardiac injury (CI) as a common coronavirus disease 2019 (COVID-19) related complication. The characteristics of early CI (occurred within 72 h of admission) and late CI (occurred after 72 h of admission) and its association with mortality in COVID-19 patients is unknown.

Methods: This retrospective study analyzed patients confirmed with COVID-19 in Union Hospital (Wuhan, China) from Jan 29th to Mar 15th, 2020. Clinical outcomes (discharge, or death) were monitored to April 15, 2020, the latest date of follow-up. Demographic, clinical, laboratory, as well as treatment and prognosis were collected and analyzed in patients with early, late CI and without CI.

Results: A total of 196 COVID-19 patients were included for analysis. The median age was 65 years [interquartile range (IQR) 56–73 years], and 112 (57.1%) were male. Of the 196 COVID-19 patients, 49 (25.0%) patients had early and 20 (10.2%) patients had late CI, 56.6% developed Acute-Respiratory-Distress-Syndrome (ARDS) and 43 (21.9%) patients died. Patients with any CI were more likely to have developed ARDS (87.0 vs. 40.2%) and had a higher in-hospital mortality than those without (52.2 vs. 5.5%, P < 0.001). Among CI subtypes, a significantly higher risk of in-hospital death was found in patients with early CI with recurrence [19/49 patients, adjusted odds ratio (OR) = 7.184, 95% CI 1.472–35.071] and patients with late CI (adjusted OR = 5.019, 95% CI 1.125–22.388) compared to patients with early CI but no recurrence.

Conclusions: CI can occur early on or late after, the initial 72 h of admission and is associated with ARDS and an increased risk of in-hospital mortality. Both late CI and recurrent CI after the initial episode were associated with worse outcomes than patients with early CI alone. This study highlights the importance of early examination and periodical monitoring of cardiac biomarkers, especially for patients with early CI or at risk of clinical deterioration.

Role of testosterone in SARS-CoV-2 infection: A key pathogenic factor and a biomarker for severe pneumonia

OBJECTIVES

To investigate the association between sex hormones and the severity of coronavirus disease 2019 (COVID-19). Furthermore, associations between sex hormones and systemic inflammation markers, viral shedding and length of hospital stay were studied.

DESIGN AND METHODS

This case-control study included a total of 48 male patients with COVID-19 admitted to an Italian reference hospital. The 24 cases were patients with PaO₂/FiO₂ <250 mmHg and who needed ventilatory support during hospitalization (severe COVID-19). The 24 controls were selected in a 1:1 ratio, matched by age, from patients who maintained PaO₂/FiO₂ >300 mmHg at all times and who may have required low-flow oxygen supplementation during hospitalization (mild COVID-19). For each group, sex hormones were evaluated on hospital admission.

RESULTS

Patients with severe COVID-19 (cases) had a significantly lower testosterone level compared with patients with mild COVID-19 (controls). Median total testosterone (TT) was 1.4 ng/mL in cases and 3.5 ng/mL in controls (P = 0.005); median bioavailable testosterone (BioT) was 0.49 and 1.21 in cases and controls, respectively (P = 0.008); and median calculated free testosterone (cFT) was 0.029 ng/mL and 0.058 ng/mL in cases and controls, respectively (P = 0.015). Low TT, low cFT and low BioT were correlated with hyperinflammatory syndrome (P = 0.018, P = 0.048 and P = 0.020, respectively) and associated with longer length of hospital stay (P = 0.052, P = 0.041 and P = 0.023, respectively). No association was found between sex hormone level and duration of viral shedding, or between sex hormone level and mortality rate.

CONCLUSIONS

A low level of testosterone was found to be a marker of clinical severity of COVID-19.

National early warning score on admission as risk factor for invasive mechanical ventilation in COVID-19 patients: A STROBE-compliant study

The coronavirus disease (COVID-19) has become a global pandemic. Invasive mechanical ventilation is recommended for the management of patients with COVID-19 who have severe respiratory symptoms. However, various complications can develop after its use. The efficient and appropriate management of patients requires the identification of factors associated with an aggravation of COVID-19 respiratory symptoms to a degree where invasive mechanical ventilation becomes necessary, thereby enabling clinicians to prevent such ventilation. This retrospective study included 138 inpatients with COVID-19 at a tertiary hospital. We evaluated the differences in the demographic and clinical data between 27 patients who required invasive mechanical ventilation and 111 patients who did not. Multivariate logistic regression analysis indicated that the duration of fever, national early warning score (NEWS), and lactate dehydrogenase (LDH) levels on admission were significantly associated with invasive mechanical ventilation in this cohort. The optimal cut-off values were: fever duration ≥1 day (sensitivity 100.0%, specificity 54.95%), NEWS ≥7 (sensitivity 72.73%, specificity 92.52%), and LDH >810 mg/dL (sensitivity 56.0%, specificity 90.29%). These findings can assist in the early identification of patients who will require invasive mechanical ventilation. Further studies in larger patient populations are recommended to validate our findings.

How Prevalent Is Cancer in Confirmed Cases with Coronaviruses and Severe Acute Respiratory Syndromes?

Novel coronavirus disease 2019 (COVID-19) has posed a crucial hazard to global health. The new species share similarities with the two previously emerged entities: severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) that have caused outbreaks in 2002 and 2012, respectively. Interestingly, all of these coronaviruses can cause potentially fatal respiratory syndromes, though behave differently in patients with cancer compared to patients without cancer. Accordingly, the present chapter aims to, through a systematic investigation, estimate the prevalence of cancer among COVID-19, SARS, and MERS confirmed cases. Our analysis based on data from 78 studies with SARS, MERS, and COVID-19 confirmed cases showed that the prevalence of cancer (4.94%) stands at fourth place after hypertension (20.8%), diabetes (11.39%), and cardiovascular diseases (7.46%). According to the findings of the present study, comorbidities are significantly more common in patients with MERS compared to patients with COVID-19 and SARS, and this was the cancer case as well. Further studies need to address whether or not patients with coronaviruses and cancer are different from patients with coronaviruses without cancer in terms of clinical manifestations, laboratory findings, outcomes, and men to women ratio.

Scoring system for identifying Japanese patients with COVID-19 at risk of requiring oxygen supply: A retrospective single-center study

Introduction

Japan is facing the threat of medical system collapse due to the rapid spread of coronavirus disease 2019 (COVID-19). The present scoring system may help assess disease severity and oxygen supply requirements in COVID-19 patients.

Methods

Data on patient characteristics at baseline and throughout hospitalization for COVID-19 were extracted from medical records. Disease severity was dichotomized into two categories without or with oxygen supply as asymptomatic, mild, and moderate illness (AMMI), and severe and critical illness (CSI). The AMMI and CSI groups were compared. Predictors of disease severity, previously identified in the outpatient setting, were included in multivariable logistic regression analysis; the obtained coefficients were converted to integers and assigned a score.

Results

A total of 206 patients diagnosed with COVID-19 were included in this study. Correlation between COVID-19 severity and medical information was examined by comparing AMMI and CSI. Age, hemodialysis, and C-reactive protein (CRP) levels were candidate predictors of the need for oxygen supply in patients with COVID-19. Coefficients associated with age, hemodialysis, and CRP were as follows: 1 × age (in years, coded as 0 for values of <50, and as 1 for values of ≥50) + 1 × hemodialysis (coded as 0 for “no”, and as 1 for “yes”) + 1 × CRP (in mg/dL, coded as 0 for values of <1.0, and as 1 for values of ≥1.0). Patients with scores of ≥2 points required oxygen supply (sensitivity, 68.4%; specificity, 79.0%)

Conclusion

The present model can help predict disease severity and oxygen requirements in COVID-19 patients in Japan.

The Interface of COVID-19 and Inpatient Psychiatry: Our Experience and Lessons Learned

The coronavirus disease 2019 (COVID-19) pandemic presented unprecedented challenges to the provision of inpatient psychiatric care. The nature of the physical plant, programmatic constraints, and the patient population required a rapid and agile approach to problem-solving under conditions of uncertainty and stress. Flexibility in decision-making, excellent communication, an effective working relationship with infection prevention and control experts, and attention to staff morale and support were important elements of successful provision of care to our inpatients. We present our experience, lessons learned, and recommendations should a resurgence of the pandemic or a similar crisis occur.

[Cardiac Involvement in COVID-19]

The novel coronavirus infection, COVID-19, is a highly contagious viral disease associated with acute, severe respiratory syndrome, which is based on the development of pronounced thrombo-inflammatory syndrome. As the number of patients with COVID-19 increased, heart damage has been reported, especially in patients with severe and critical COVID-19. This review describes the role of angiotensin-converting enzyme 2 receptor in the regulation of viral entry, the variety of damages to the heart and coronary arteries, and the importance of arterial hypertension and of the use of renin-angiotensin-aldosterone system inhibitors in the prognosis of patients with COVID-19.

Sustaining efficient immune functions with regular physical exercise in the COVID-19 era and beyond

The new coronavirus (SARS-CoV-2) appearance in Wuhan, China, did rise the new virus disease (COVID-19), which spread globally in a short time, leading the World Health Organization to declare a new global pandemic. To contain and mitigate the spread of SARS-CoV-2, specific public health procedures were implemented in virtually all countries, with a significant impact on society, making it difficult to keep the regular practice of physical activity. It is widely accepted that an active lifestyle contributes to the improvement of general health and preservation of cardiovascular, respiratory, osteo-muscular and immune system capacities. The positive effects of regular physical activity on the immune system have emerged as a pivotal trigger of general health, underlying the beneficial effects of physical activity on multiple physiological systems. Accordingly, recent studies have already pointed out the negative impact of physical inactivity caused by the social isolation imposed by the public sanitary authorities due to COVID-19. Nevertheless, there are still no current narrative reviews evaluating the real impact of COVID-19 on active lifestyle or even discussing the possible beneficial effects of exercise-promoted immune upgrade against the severity or progression of COVID-19. Based on the consensus in the scientific literature, in this review, we discuss how an exercise adherence could adequately improve immune responses in times of the 'COVID-19 Era and beyond'.

Prognostic factors for the severity of SARS-CoV-2 infection

Objectives

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a novel coronavirus that causes COVID-19. This disease is associated with leukocytosis with lymphopenia, neutrophilia, and elevated levels of d-dimer, and C-reactive protein, ferritin, procalcitonin, and lactate dehydrogenase. The aim of this study was to describe the clinical and analytical characteristics of hospitalized patients with SARS-CoV-2 infection and to identify prognostic factors of disease progression.

Methods

Patients were categorized into two groups based on COVID-19 severity. Study variables included demographic data, medical history, length of hospital stay, course of pneumonia, drug therapy, and analytical parameters. A descriptive and multivariate analysis was performed to identify prognostic factors for disease severity.

Results

The study population included 197 patients, of whom 127 had mild disease and 70 had severe COVID-19. Statistically significant differences were observed in most analytical parameters. The parameters included in the multivariate analysis were advanced age and elevated levels of leukocytes, CRP, GGT, and PCT at admission as prognostic factors for disease severity.

Conclusions

The prognostic factors for the severity of SARS-CoV-2 infection identified in this study (age, leukocytes, CRP, GGT, and PCT) will help predict the course of the disease at an early stage.

Epidemiological, clinical, and laboratory findings for patients of different age groups with confirmed coronavirus disease 2019 (COVID-19) in a hospital in Saudi Arabia

BACKGROUND

Although the coronavirus disease 2019 (COVID-19) pandemic continues to rage worldwide, clinical and laboratory studies of this disease have been limited in many countries. We investigated the epidemiologic, clinical, and laboratory findings of COVID-19 infected patients to identify the effective indicators correlated with the disease.

METHODS

A retrospective study was conducted at King Abdullah Hospital in Bisha Province, Saudi Arabia, from March 20 to June 30, 2020. Patients of different age groups were confirmed as having COVID-19 infection using a real-time polymerase chain reaction. The demographic, clinical, and laboratory data of the patients were statistically analyzed.

RESULTS

Of the 132 patients, 85 were male and 47 were female, with a mean age of 50.9 years (SD±16.7). The patients were elderly (n = 29) and adults (n = 103). Of these, 54 (40.9%) had comorbidities, (25%) were admitted to the intensive care unit (ICU), and 12 (9.1%) died. On admission, the main clinical manifestations were fever (84.1%), cough (64.4%), shortness of breath (25%), chest pain (20.5%), and fatigue (18.2%). In all patients, increased neutrophils and decreased lymphocytes were observed. Patients' lactate dehydrogenase (LDH) was elevated. C-reactive protein (CRP) was elevated in 48.5%, D-dimer in 43.2%, and the erythrocyte sedimentation rate (ESR) in 40.9% of patients. The elderly showed higher neutrophil (p = 0.011) and lower lymphocyte (p = 0.009) counts than adults. Glucose, creatine kinase-MB, LDH, bilirubin, D-dimer, and ESR were significantly higher in the elderly than in the adults. The COVID-19 death group had a higher leucocyte count (p = 0.036), and higher urea (p = 0.029) and potassium (p = 0.022) than the recovered group but had a lower hemoglobin concentration (p = 0.018). A significant association was determined between COVID-19 death and the presence of cardiovascular disease (χ2(1) = 16.297, p<0.001), hypertension (χ2(1) = 12.034, p = 0.001), renal failure (χ2(1) = 3.843, p = 0. 05), old age (t (130) = 4.9, p <0.001), and ICU admission (χ2(1) = 17.6 (1), p<0.001).

CONCLUSIONS

Investigating some of the laboratory and clinical parameters could help assess the disease progression, risk of mortality, and follow up patients who could progress to a fatal condition.

Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study

BACKGROUND

In the face of the current COVID-19 pandemic, the timely prediction of upcoming medical needs for infected individuals enables better and quicker care provision when necessary and management decisions within health care systems.

OBJECTIVE

This work aims to predict the medical needs (hospitalizations, intensive care unit admissions, and respiratory assistance) and survivability of individuals testing positive for SARS-CoV-2 infection in Portugal.

METHODS

A retrospective cohort of 38,545 infected individuals during 2020 was used. Predictions of medical needs were performed using state-of-the-art machine learning approaches at various stages of a patient's cycle, namely, at testing (prehospitalization), at posthospitalization, and during postintensive care. A thorough optimization of state-of-the-art predictors was undertaken to assess the ability to anticipate medical needs and infection outcomes using demographic and comorbidity variables, as well as dates associated with symptom onset, testing, and hospitalization.

RESULTS

For the target cohort, 75% of hospitalization needs could be identified at the time of testing for SARS-CoV-2 infection. Over 60% of respiratory needs could be identified at the time of hospitalization. Both predictions had >50% precision.

CONCLUSIONS

The conducted study pinpoints the relevance of the proposed predictive models as good candidates to support medical decisions in the Portuguese population, including both monitoring and in-hospital care decisions. A clinical decision support system is further provided to this end.

Global dynamics of SARS-CoV-2 clades and their relation to COVID-19 epidemiology

Expansion of COVID-19 worldwide increases interest in unraveling genomic variations of novel SARS-CoV-2 virus. Metadata of 408,493 SARS-CoV-2 genomes submitted to GISAID database were analyzed with respect to genomic clades and their geographic, age, and gender distributions. Of the currently known SARS-CoV-2 clades, clade GR was the most prevalent worldwide followed by GV then GH. Chronological analysis revealed expansion in SARS-CoV-2 clades carrying D614G mutations with the predominance of the newest clade, GV, in the last three months. D614G clades prevail in countries with more COVID-19 cases. Of them, the clades GH and GR were more frequently recovered from severe or deceased COVID-19 cases. In contrast, G and GV clades showed a significantly higher prevalence among asymptomatic patients or those with mild disease. Metadata analysis showed higher (p < 0.05) prevalence of severe/deceased cases among males than females and predominance of GR clade in female patients. Furthermore, severe disease/death was more prevalent (p < 0.05) in elderly than in adults/children. Higher prevalence of the GV clade in children compared to other age groups was also evident. These findings uniquely provide a statistical evidence on the adaptation-driven evolution of SARS-CoV-2 leading to altered infectivity, virulence, and mortality.

Hypertension, diabetes mellitus, and cerebrovascular disease predispose to a more severe outcome of COVID-19

INTRODUCTION

The world is currently facing the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The total number of cases of coronavirus disease 2019 (COVID-19) is rising daily and no vaccine has yet been approved. While the pathophysiology behind the virus is still being studied, many possible several risk factors using small sample sizes have been found.

MATERIAL AND METHODS

We conducted a pooled analysis using several databases such as Medline, Scopus, Wangfang, Web of Science, Research Square, medrxiv, and Google Scholar to identify studies reporting severe and non-severe groups of COVID-19 patients. The odds ratios as well as the 95% confidence intervals for hypertension, diabetes, and cerebrovascular disease leading to severe COVID-19 were calculated using R-software.

RESULTS

Fifty-three articles were used for our analysis and they involved 30,935 confirmed cases of COVID-19 from several countries across the world. The odds ratio for severe COVID-19 in hypertensive patients, diabetics, and patients with a history of cerebrovascular disease was 2.58 (95% confidence interval (CI): 2.16-3.08, from 53 studies), 2.17 (95% CI: 1.72-2.74, from 44 studies), and 2.63 (95% CI: 1.80-3.85, from 25 studies), respectively.

CONCLUSIONS

Our analysis confirms that patients with hypertension, diabetes, or cerebrovascular disease are at a higher risk of a severe outcome of COVID-19. It is thus vital for physicians to identify the main risk factors for a severe outcome of this disease.

Informing the public health response to COVID-19: a systematic review of risk factors for disease, severity, and mortality

BACKGROUND

Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has challenged public health agencies globally. In order to effectively target government responses, it is critical to identify the individuals most at risk of coronavirus disease-19 (COVID-19), developing severe clinical signs, and mortality. We undertook a systematic review of the literature to present the current status of scientific knowledge in these areas and describe the need for unified global approaches, moving forwards, as well as lessons learnt for future pandemics.

METHODS

Medline, Embase and Global Health were searched to the end of April 2020, as well as the Web of Science. Search terms were specific to the SARS-CoV-2 virus and COVID-19. Comparative studies of risk factors from any setting, population group and in any language were included. Titles, abstracts and full texts were screened by two reviewers and extracted in duplicate into a standardised form. Data were extracted on risk factors for COVID-19 disease, severe disease, or death and were narratively and descriptively synthesised.

RESULTS

One thousand two hundred and thirty-eight papers were identified post-deduplication. Thirty-three met our inclusion criteria, of which 26 were from China. Six assessed the risk of contracting the disease, 20 the risk of having severe disease and ten the risk of dying. Age, gender and co-morbidities were commonly assessed as risk factors. The weight of evidence showed increasing age to be associated with severe disease and mortality, and general comorbidities with mortality. Only seven studies presented multivariable analyses and power was generally limited. A wide range of definitions were used for disease severity.

CONCLUSIONS

The volume of literature generated in the short time since the appearance of SARS-CoV-2 has been considerable. Many studies have sought to document the risk factors for COVID-19 disease, disease severity and mortality; age was the only risk factor based on robust studies and with a consistent body of evidence. Mechanistic studies are required to understand why age is such an important risk factor. At the start of pandemics, large, standardised, studies that use multivariable analyses are urgently needed so that the populations most at risk can be rapidly protected.

REGISTRATION

This review was registered on PROSPERO as CRD42020177714 .

[Covid-19 in kidney transplantation: Lessons from the French Registry]

The Covid-19 pandemic hits the French transplant population on March 3, 2020. Very quickly, a French registry was set up on behalf of the French Society of Transplantation allowing the collection of confirmed cases of Covid-19 occurring in kidney transplant recipients in almost all French centers. The analysis of this registry in conjunction with the data from the Agence de la Biomédecine (Cristal) has enabled us to obtain instructive results. We first showed that the incidence of severe forms among transplant patients hospitalized for Covid-19 was 46% and that their mortality was 22.8%. The risk factors for severe forms and mortality are described. Then we showed, by comparing transplant patients with immunocompetent patients matched for the main severity factors of the disease, that mortality among transplant patients was higher (17.9% vs 11.4%; P<0.001). In multivariate analysis, a creatinine level at admission above 115 μmol/L was associated with death, whereas being transplanted was not. Finally, comparing the transplant cohort with patients on the kidney transplant waiting list during the period from February to June 2020, we found that patients on the waiting list had a higher Covid-19-related excess mortality than transplant patients, mainly in areas of low viral circulation. In conclusion, the French Registry of transplant patients with Covid-19, which was rapidly set up at the beginning of the epidemic, has already enabled us to draw several lessons about this initially unknown infection, particularly in kidney transplant patients, a population which appeared to be particularly at risk.

Impact of Chronic Kidney Disease on Severity and Mortality in COVID-19 Patients: A Systematic Review and Meta-analysis

Coronavirus disease 19 (COVID-19) has affected over 180 countries, resulting in global mass death. It has been reported that patients with underlying disease are more likely to contract the disease and become critically ill. The impact of chronic kidney disease (CKD) on the severity of COVID-19 has been underlined in the literature. In this analysis, we have provided evidence of an association between CKD and COVID-19. We followed the PRISMA protocol and conducted a literature search using Google Scholar, EMBASE, PubMed, and Clinical trail.gov. The initial search yielded 2102 articles. We included 20 cohorts based on inclusion criteria reporting an association between CKD and COVID-19 after excluding irrelevant articles, including review articles and duplicates. We conducted pooled prevalence of CKD and meta-analysis to estimate the odds ratio (OR), 95% confidence interval (CI) using Cochrane RevMan (version 5.4, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration), and R programming language version 4.16-2 (University of Auckland, New Zealand). Our study involved 4350 patients from different countries, and 212 (4.9%) patients had CKD. Among 20 cohorts, 57.27% were male with a median age of 55.5 years. Eight hundred sixty-six patients developed severe COVID-19, and out of which, 39 (4.5%) were CKD patients. CKD patients had a significantly increased risk of severe disease as compared to non-CKD patients with a pooled OR of 2.15 (95% CI 1.16-4.01) (I2=41; p=0.02). Out of 443 COIVD-19 patients who died, 85 patients had CKD, with a prevalence of 19.18%. CKD patients had an increased risk of death as compared to non-CKD patients with a pooled OR of 5.58 (95% CI 3.27-9.54) (I2=0; p<0.00001). CKD is manifested as a common underlying disease in COVID-19 patients who had a worse prognosis, including mortality.

High Systolic Blood Pressure at Hospital Admission Is an Important Risk Factor in Models Predicting Outcome of COVID-19 Patients

BACKGROUND

The risk that coronavirus disease 2019 (COVID-19) patients develop critical illness that can be fatal depends on their age and immune status and may also be affected by comorbidities like hypertension. The goal of this study was to develop models that predict outcome using parameters collected at admission to the hospital.

METHODS AND RESULTS

This is a retrospective single-center cohort study of COVID-19 patients at the Seventh Hospital of Wuhan City, China. Forty-three demographic, clinical, and laboratory parameters collected at admission plus discharge/death status, days from COVID-19 symptoms onset, and days of hospitalization were analyzed. From 157 patients, 120 were discharged and 37 died. Pearson correlations showed that hypertension and systolic blood pressure (SBP) were associated with death and respiratory distress parameters. A penalized logistic regression model efficiently predicts the probability of death with 13 of 43 variables. A regularized Cox regression model predicts the probability of survival with 7 of above 13 variables. SBP but not hypertension was a covariate in both mortality and survival prediction models. SBP was elevated in deceased compared with discharged COVID-19 patients.

CONCLUSIONS

Using an unbiased approach, we developed models predicting outcome of COVID-19 patients based on data available at hospital admission. This can contribute to evidence-based risk prediction and appropriate decision-making at hospital triage to provide the most appropriate care and ensure the best patient outcome. High SBP, a cause of end-organ damage and an important comorbid factor, was identified as a covariate in both mortality and survival prediction models.

The common risk factors for progression and mortality in COVID-19 patients: a meta-analysis

Coronavirus disease 2019 (COVID-19), defined by the World Health Organization (WHO), has affected more than 50 million patients worldwide and caused a global public health emergency. Therefore, there is a recognized need to identify risk factors for COVID-19 severity and mortality. A systematic search of electronic databases (PubMed, Embase and Cochrane Library) for studies published before September 29, 2020, was performed. Studies that investigated risk factors for progression and mortality in COVID-19 patients were included. A total 344,431 participants from 34 studies were included in this meta-analysis. Regarding comorbidities, cerebrovascular disease (CVD), chronic kidney disease (CKD), coronary heart disease (CHD), and malignancy were associated with an increased risk of progression and mortality in COVID-19 patients. Regarding clinical manifestations, sputum production was associated with a dramatically increased risk of progression and mortality. Hemoptysis was a risk factor for death in COVID-19 patients. In laboratory examinations, increased neutrophil count, decreased lymphocyte count, decreased platelet count, increased C-reactive protein (CRP), coinfection with bacteria or fungi, increased alanine aminotransferase (ALT) and creatine kinase (CK), increased N-terminal pronatriuretic peptide (NT-proBNP), and bilateral pneumonia in CT/X-ray were significantly more frequent in the severe group compared with the non-severe group. Moreover, the proportion of patients with increased CRP and total bilirubin (TBIL) was also significantly higher in the deceased group than in the survival group. CVD, CKD, sputum production, increased neutrophil count, decreased lymphocyte count, decreased platelet count, increased CRP, coinfection with bacteria or fungi, increased ALT and CK, increased NT-proBNP, and bilateral pneumonia in CT/X-ray were associated with an increased risk of progression in COVID-19 patients. Moreover, the proportion of patients with increased sputum production, hemoptysis, CRP and TBIL was also significantly higher in the deceased group.

Cutaneous Manifestations in Patients With COVID-19: Clinical Characteristics and Possible Pathophysiologic Mechanisms

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections soon led to a pandemic with serious health, economic, political, and cultural repercussions across the globe. The disease caused by SARS-CoV-2, coronavirus disease 2019 (COVID-19), is a multisystemic disease that requires a multidisciplinary approach involving specialists from all fields and levels of care. In this article, we review the literature on the diverse cutaneous manifestations associated with COVID-19. We also describe the pathophysiologic mechanisms proposed to date and their possible association with these manifestations. Finally, we propose a system for classifying the cutaneous manifestations of COVID-19 according to their underlying pathophysiologic mechanisms and prognosis.

Unsupervised cluster analysis of SARS-CoV-2 genomes reflects its geographic progression and identifies distinct genetic subgroups of SARS-CoV-2 virus

Over 10,000 viral genome sequences of the SARS-CoV-2virus have been made readily available during the ongoing coronavirus pandemic since the initial genome sequence of the virus was released on the open access Virological website (http://virological.org/) early on January 11. We utilize the published data on the single stranded RNAs of 11,132 SARS-CoV-2 patients in the GISAID database, which contains fully or partially sequenced SARS-CoV-2 samples from laboratories around the world. Among many important research questions which are currently being investigated, one aspect pertains to the genetic characterization/classification of the virus. We analyze data on the nucleotide sequencing of the virus and geographic information of a subset of 7640 SARS-CoV-2 patients without missing entries that are available in the GISAID database. Instead of modeling the mutation rate, applying phylogenetic tree approaches, and so forth, we here utilize a model-free clustering approach that compares the viruses at a genome-wide level. We apply principal component analysis to a similarity matrix that compares all pairs of these SARS-CoV-2 nucleotide sequences at all loci simultaneously, using the Jaccard index. Our analysis results of the SARS-CoV-2 genome data illustrates the geographic and chronological progression of the virus, starting from the first cases that were observed in China to the current wave of cases in Europe and North America. This is in line with a phylogenetic analysis which we use to contrast our results. We also observe that, based on their sequence data, the SARS-CoV-2 viruses cluster in distinct genetic subgroups. It is the subject of ongoing research to examine whether the genetic subgroup could be related to diseases outcome and its potential implications for vaccine development.

The Impact of Previous History of Bariatric Surgery on Outcome of COVID-19. A Nationwide Medico-Administrative French Study

PURPOSE

To determine the risk of invasive mechanical ventilation and death in obese individuals with a history of bariatric surgery (BS) admitted for COVID-19.

METHODS

All obese inpatients recorded during a hospital stay by the French National Health Insurance were included, and their electronic health data were reviewed retrospectively. Patients who had undergone bariatric surgery comprised the BS group and patients with obesity but no history of BS served as controls. The primary outcome was COVID-19-related death and the secondary outcome was the need for invasive mechanical ventilation.

RESULTS

4,248,253 obese individuals aged 15-75 years were included and followed for a mean observation time of 5.43 ± 2.93 years. 8286 individuals with a previous diagnosis of obesity were admitted for COVID-19 between January 1 and May 15, 2020. Of these patients, 541 had a history of BS and 7745 did not. The need for invasive mechanical ventilation and death occurred in 7% and 3.5% of the BS group versus 15% and 14.2% of the control group, respectively. In logistic regression, the risk of invasive mechanical ventilation was independently associated with increasing age, male sex, and hypertension, and mortality was independently associated with increasing age, male sex, history of heart failure, cancer, and diabetes, whereas BS had an independent protective effect. Two random exact matching tests confirmed the protective effect of BS.

CONCLUSION

This nationwide study showed that BS is independently associated with a reduced risk of death and invasive mechanical ventilation in obese individuals with COVID-19.

Social determinants of COVID-19 incidence and outcomes: A rapid review

Early reports indicate that the social determinants of health are implicated in COVID-19 incidence and outcomes. To inform the ongoing response to the pandemic, we conducted a rapid review of peer-reviewed studies to examine the social determinants of COVID-19. We searched Ovid MEDLINE, Embase, PsycINFO, CINAHL and Cochrane Central Register of Controlled Trials from December 1, 2019 to April 27, 2020. We also searched the bibliographies of included studies, COVID-19 evidence repositories and living evidence maps, and consulted with expert colleagues internationally. We included studies identified through these supplementary sources up to June 25, 2020. We included English-language peer-reviewed quantitative studies that used primary data to describe the social determinants of COVID-19 incidence, clinical presentation, health service use and outcomes in adults with a confirmed or presumptive diagnosis of COVID-19. Two reviewers extracted data and conducted quality assessment, confirmed by a third reviewer. Forty-two studies met inclusion criteria. The strongest evidence was from three large observational studies that found associations between race or ethnicity and socioeconomic deprivation and increased likelihood of COVID-19 incidence and subsequent hospitalization. Limited evidence was available on other key determinants, including occupation, educational attainment, housing status and food security. Assessing associations between sociodemographic factors and COVID-19 was limited by small samples, descriptive study designs, and the timeframe of our search. Systematic reviews of literature published subsequently are required to fully understand the magnitude of any effects and predictive utility of sociodemographic factors related to COVID-19 incidence and outcomes. PROSPERO: CRD4202017813.

Efficacy of COVID-19 outbreak management in a skilled nursing facility based on serial testing for early detection and control

SARS-CoV-2 has a high risk of outbreak in long-term skilled nursing facilities (SNF). Coronavirus disease (COVID-19) has high mortality rates among the elderly with chronic health conditions. Following identification of COVID-19 index case in a SNF, serial point-prevalence was implemented with reverse transcription-polymerase chain reaction (RT-PCR) and immunochromatographic assays. Active surveillance and early isolation of infected patients were implemented. Out of 23 SNF residents and 26 healthcare workers (HCW), 18 (78%) and 12 (46%) tested positive for SARS-CoV-2, respectively. High proportion (38%) of positive patients were asymptomatic and RT-PCR was positive up to six days before symptoms. Five (21.74%) residents were hospitalized with COVID-19, and 2 (9%) died; only 1 (4%) HCW needed to be hospitalized and no staff members died. Active surveillance helped COVID-19 control and management in a SNF. Testing symptomatic individuals only may fail to identify and isolate all persons contributing to transmission. In high-risk elderly, only symptoms screening may not be enough for outbreak control.

Predictors of clinical deterioration in patients with suspected COVID-19 managed in a 'virtual hospital' setting: a cohort study

OBJECTIVE

Identify predictors of clinical deterioration in a virtual hospital (VH) setting for COVID-19.

DESIGN

Real-world prospective observational study.

SETTING

VH remote assessment service in West Hertfordshire NHS Trust, UK.

PARTICIPANTS

Patients with suspected COVID-19 illness enrolled directly from the community (postaccident and emergency (A&E) or medical intake assessment) or postinpatient admission.

MAIN OUTCOME MEASURE

Death or (re-)admission to inpatient hospital care during VH follow-up and for 2 weeks post-VH discharge.

RESULTS

900 patients with a clinical diagnosis of COVID-19 (455 referred from A&E or medical intake and 445 postinpatient) were included in the analysis. 76 (8.4%) of these experienced clinical deterioration (15 deaths in admitted patients, 3 deaths in patients not admitted and 58 additional inpatient admissions). Predictors of clinical deterioration were increase in age (OR 1.04 (95% CI 1.02 to 1.06) per year of age), history of cancer (OR 2.87 (95% CI 1.41 to 5.82)), history of mental health problems (OR 1.76 (95% CI 1.02 to 3.04)), severely impaired renal function (OR for eGFR <30=9.09 (95% CI 2.01 to 41.09)) and having a positive SARS-CoV-2 PCR result (OR 2.0 (95% CI 1.11 to 3.60)).

CONCLUSIONS

These predictors may help direct intensity of monitoring for patients with suspected or confirmed COVID-19 who are being remotely monitored by primary or secondary care services. Further research is needed to confirm our findings and identify the reasons for increased risk of clinical deterioration associated with cancer and mental health problems.

Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COVID-19 disease severity and indicator of the need for mechanical ventilation, ARDS and mortality

BACKGROUND

COVID-19 pneumonia and subsequent respiratory failure is causing an immense strain on intensive care units globally. Early prediction of severe disease enables clinicians to avoid acute respiratory distress syndrome (ARDS) development and improve management of critically ill patients. The soluble receptor of advanced glycation endproducts (sRAGE) is a biomarker shown to predict ARDS. Although sRAGE level varies depending on the type of disease, there is limited information available on changes in sRAGE levels in COVID-19. Therefore, sRAGE was measured in COVID-19 patients to determine sRAGE level variation in COVID-19 severity and to examine its ability to predict the need for mechanical ventilation (MV) and mortality in COVID-19.

METHODS

In this single-centre observational cohort study in Germany, serum sRAGE during acute COVID-19, 20 weeks after the start of COVID-19 symptoms, as well as in control groups of non-COVID-19 pneumonia patients and healthy controls were measured using ELISA. The primary endpoint was severe disease (high-flow nasal oxygen therapy (HFNO)/MV and need of organ support). The secondary endpoints were respiratory failure with need of MV and 30-day mortality. The area under the curve (AUC), cut-off based on Youden's index and odds ratio with 95% CI for sRAGE were calculated with regard to prediction of MV need and mortality.

RESULTS

Serum sRAGE in 164 COVID-19 patients, 101 matched COVID-19 convalescent patients, 23 non-COVID-19 pneumonia patients and 15 healthy volunteers were measured. sRAGE level increased with COVID-19 severity, need for oxygen therapy, HFNO/MV, ARDS severity, need of dialysis and catecholamine support, 30-day mortality, sequential organ failure assessment (SOFA) and quick SOFA (qSOFA) score. sRAGE was found to be a good predictor of MV need in COVID-19 inpatients and mortality with an AUC of 0.871 (0.770-0.973) and 0.903 (0.817-0.990), respectively. When adjusted for male gender, age, comorbidity and SOFA score ≥ 3, sRAGE was independently associated with risk of need for HFNO/MV. When adjusted for SOFA score ≥ 3, sRAGE was independently associated with risk of need for MV.

CONCLUSIONS

Serum sRAGE concentrations are elevated in COVID-19 patients as disease severity increases. sRAGE should be considered as a biomarker for predicting the need for MV and mortality in COVID-19.

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.

Susceptibility to SARS-CoV-2 infection in patients undergoing chemotherapy and radiation therapy

The outbreak of the new coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly become a public health emergency of international concern, especially affecting the elderly people and patients with chronic disease, such as hypertension and respiratory syndromes. Patients undergoing chemotherapy treatment (e.g., bleomycin, cyclophosphamide, methotrexate, monoclonal antibodies, and paclitaxel therapy) are vulnerable to the development of respiratory syndromes induced by chemotherapeutic agents and are also more susceptible to viral infections as they are immunosuppressed. Neutropenia is an important risk factor for increased vulnerability to infections, as a respiratory syndrome involves an array of immune cells maintaining the balance between pathogen clearance and immunopathology. However, the differential diagnosis of pulmonary symptoms in cancer patients is broad, with complications being related to the malignancy itself, treatment toxicity, and infections. The risk factors depend on the specific type of cancer, chemotherapy, patient characteristics, and comorbidities. Thus, this review discusses the main events implicated in immunosuppression caused by chemotherapy and radiation therapy and the association of immunosuppression and other factors with SARS-CoV-2 infection susceptibility in cancer patients; and, importantly, how to deal with this situation in face of the current pandemic scenario.

Combination of Angiotensin (1-7) Agonists and Convalescent Plasma as a New Strategy to Overcome Angiotensin Converting Enzyme 2 (ACE2) Inhibition for the Treatment of COVID-19

Coronavirus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the most concerning health problem worldwide. SARS-CoV-2 infects cells by binding to angiotensin-converting enzyme 2 (ACE2). It is believed that the differential response to SARS-CoV-2 is correlated with the differential expression of ACE2. Several reports proposed the use of ACE2 pharmacological inhibitors and ACE2 antibodies to block viral entry. However, ACE2 inhibition is associated with lung and cardiovascular pathology and would probably increase the pathogenesis of COVID-19. Therefore, utilizing ACE2 soluble analogs to block viral entry while rescuing ACE2 activity has been proposed. Despite their protective effects, such analogs can form a circulating reservoir of the virus, thus accelerating its spread in the body. Levels of ACE2 are reduced following viral infection, possibly due to increased viral entry and lysis of ACE2 positive cells. Downregulation of ACE2/Ang (1-7) axis is associated with Ang II upregulation. Of note, while Ang (1-7) exerts protective effects on the lung and cardiovasculature, Ang II elicits pro-inflammatory and pro-fibrotic detrimental effects by binding to the angiotensin type 1 receptor (AT1R). Indeed, AT1R blockers (ARBs) can alleviate the harmful effects associated with Ang II upregulation while increasing ACE2 expression and thus the risk of viral infection. Therefore, Ang (1-7) agonists seem to be a better treatment option. Another approach is the transfusion of convalescent plasma from recovered patients with deteriorated symptoms. Indeed, this appears to be promising due to the neutralizing capacity of anti-COVID-19 antibodies. In light of these considerations, we encourage the adoption of Ang (1-7) agonists and convalescent plasma conjugated therapy for the treatment of COVID-19 patients. This therapeutic regimen is expected to be a safer choice since it possesses the proven ability to neutralize the virus while ensuring lung and cardiovascular protection through modulation of the inflammatory response.

Ensemble learning for poor prognosis predictions: A case study on SARS-CoV-2

OBJECTIVE

Risk prediction models are widely used to inform evidence-based clinical decision making. However, few models developed from single cohorts can perform consistently well at population level where diverse prognoses exist (such as the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] pandemic). This study aims at tackling this challenge by synergizing prediction models from the literature using ensemble learning.

MATERIALS AND METHODS

In this study, we selected and reimplemented 7 prediction models for COVID-19 (coronavirus disease 2019) that were derived from diverse cohorts and used different implementation techniques. A novel ensemble learning framework was proposed to synergize them for realizing personalized predictions for individual patients. Four diverse international cohorts (2 from the United Kingdom and 2 from China; N = 5394) were used to validate all 8 models on discrimination, calibration, and clinical usefulness.

RESULTS

Results showed that individual prediction models could perform well on some cohorts while poorly on others. Conversely, the ensemble model achieved the best performances consistently on all metrics quantifying discrimination, calibration, and clinical usefulness. Performance disparities were observed in cohorts from the 2 countries: all models achieved better performances on the China cohorts.

DISCUSSION

When individual models were learned from complementary cohorts, the synergized model had the potential to achieve better performances than any individual model. Results indicate that blood parameters and physiological measurements might have better predictive powers when collected early, which remains to be confirmed by further studies.

CONCLUSIONS

Combining a diverse set of individual prediction models, the ensemble method can synergize a robust and well-performing model by choosing the most competent ones for individual patients.

Impact of comorbidity burden on mortality in patients with COVID-19 using the Korean health insurance database

We aimed to investigate the impact of comorbidity burden on mortality in patients with coronavirus disease (COVID-19). We analyzed the COVID-19 data from the nationwide health insurance claims of South Korea. Data on demographic characteristics, comorbidities, and mortality records of patients with COVID-19 were extracted from the database. The odds ratios of mortality according to comorbidities in these patients with and without adjustment for age and sex were calculated. The predictive value of the original Charlson comorbidity index (CCI) and the age-adjusted CCI (ACCI) for mortality in these patients were investigated using the receiver operating characteristic (ROC) curve analysis. Among 7590 patients, 227 (3.0%) had died. After age and sex adjustment, hypertension, diabetes mellitus, congestive heart failure, dementia, chronic pulmonary disease, liver disease, renal disease, and cancer were significant risk factors for mortality. The ROC curve analysis showed that an ACCI threshold > 3.5 yielded the best cut-off point for predicting mortality (area under the ROC 0.92; 95% confidence interval 0.91–0.94). Our study revealed multiple risk factors for mortality in patients with COVID-19. The high predictive power of the ACCI for mortality in our results can support the importance of old age and comorbidities in the severity of COVID-19.

Hypertension is a clinically important risk factor for critical illness and mortality in COVID-19: A meta-analysis

AIMS

As reported, hypertension may play an important role in adverse outcomes of coronavirus disease-2019 (COVID-19), but it still had many confounding factors. The aim of this study was to explore whether hypertension is an independent risk factor for critical COVID-19 and mortality.

DATA SYNTHESIS

The Medline, PubMed, Embase, and Web of Science databases were systematically searched until November 2020. Combined odds ratios (ORs) with their 95% confidence interval (CIs) were calculated by using random-effect models, and the effect of covariates was analyzed using the subgroup analysis and meta-regression analysis. A total of 24 observational studies with 99,918 COVID-19 patients were included in the meta-analysis. The proportions of hypertension in critical COVID-19 were 37% (95% CI: 0.27 -0.47) when compared with 18% (95% CI: 0.14 -0.23) of noncritical COVID-19 patients, in those who died were 46% (95%CI: 0.37 -0.55) when compared with 22% (95% CI: 0.16 -0.28) of survivors. Pooled results based on the adjusted OR showed that patients with hypertension had a 1.82-fold higher risk for critical COVID-19 (aOR: 1.82; 95% CI: 1.19 - 2.77; P = 0.005) and a 2.17-fold higher risk for COVID-19 mortality (aOR: 2.17; 95% CI: 1.67 - 2.82; P < 0.001). Subgroup analysis results showed that male patients had a higher risk of developing to the critical condition than female patients (OR: 3.04; 95%CI: 2.06 - 4.49; P < 0.001) and age >60 years was associated with a significantly increased risk of COVID-19 mortality (OR: 3.12; 95% CI: 1.93 - 5.05; P < 0.001). Meta-regression analysis results also showed that age (Coef. = 2.3×10-2, P = 0.048) had a significant influence on the association between hypertension and COVID-19 mortality.

CONCLUSIONS

Evidence from this meta-analysis suggested that hypertension was independently associated with a significantly increased risk of critical COVID-19 and inhospital mortality of COVID-19.

The risk factors for severe patients with COVID-19 in China: A systematic review and meta-analysis

COVID-19 is spreading exponentially. In order to optimize medical resources allocation and reduce mortality, biomarkers are needed to differentiate between COVID-19 patients with or without severe diseases early as possible. We searched Ovid MEDLINE(R), Ovid EMBASE, CNKI, Wanfang, VIP databases, the Cochrane Library, and medRxiv for primary articles in English or Chinese up to March 30, 2020 to systematically evaluate the risk factors for severe patients in China. Mean difference or standardize mean difference and odds ratio with 95% confidence intervals were performed by random-effect or fixed models in cases of significant heterogeneity between studies. We used I2 to evaluate the magnitude of heterogeneity. A total of 54 articles involving about 7000 patients were eligible for this meta-analysis. In total, 52 of 67 parameters between severe and non-severe cases were significantly different. Elderly male patients with comorbidities including hypertension, diabetes, chronic obstructive pulmonary disease (COPD) cardiovascular disease, cerebrovascular disease, chronic kidney disease, or cancer were more common in severe COVID-19 patients. Regarding the clinical manifestations on admission, fever, cough, expectoration, dyspnea, chest distress, fatigue, headache, chills, anorexia, or abdominal pain were more prevalent in severe COVID-19 patients. The results of the clinical examination showed that high C-reactive protein (CRP), high lactate dehydrogenase (LDH), high D-dimer, and decreased T lymphocytes cells subsets, decreased lymphocyte may help clinicians predict the progression of severe illness in patients with COVID-19. Our findings will be conducive for clinician to stratify the COVID-19 patients to reduce mortality under the relative shortage of medical resources.

Early prediction keys for COVID-19 cases progression: A meta-analysis

Backgroundː

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), within few months of being declared as a global pandemic by WHO, the number of confirmed cases has been over 75 million and over 1.6 million deaths since the start of the Pandemic and still counting, there is no consensus on factors that predict COVID-19 case progression despite the diversity of studies that reported sporadic laboratory predictive values predicting severe progression. We review different biomarkers to systematically analyzed these values to evaluate whether are they are correlated with the severity of COVID-19 disease and so their ability to be a predictor for progression.

Methods

The current meta-analysis was carried out to identify relevant articles using eight different databases regarding the values of biomarkers and risk factors of significance that predict progression of mild or moderate cases into severe and critical cases. We defined the eligibility criteria using a PICO model.

Results

Twenty-two relevant articles were selected for meta-analysis the following biomarkers C-reactive protein, interleukin-6, LDH, neutrophil, %PD-1 expression, D-dimer, creatinine, AST and Cortisol all recorded high cut-off values linked to severe and critical cases while low lymphocyte count, and low Albumin level were recorded. Also, we meta- analyzed age and comorbidities as a risk factors of progression as hypertension, Diabetes and chronic obstructive lung diseases which significantly correlated with cases progression (p < 0.05).

Conclusions

ː The current meta-analysis is the first step for analysing and getting cut-off references values of significance for prediction COVID-19 case progression. More studies are needed on patients infected with SARS-CoV-2 and on a larger scale to establish clearer threshold values that predict progression from mild to severe cases. In addition, more biomarkers testing also help in building a scoring system for the prediction and guiding for proper timely treatment.

Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis

AIM

COVID-19 clinical presentation is heterogeneous, ranging from asymptomatic to severe cases. While there are a number of early publications relating to risk factors for COVID-19 infection, low sample size and heterogeneity in study design impacted consolidation of early findings. There is a pressing need to identify the factors which predispose patients to severe cases of COVID-19. For rapid and widespread risk stratification, these factors should be easily obtainable, inexpensive, and avoid invasive clinical procedures. The aim of our study is to fill this knowledge gap by systematically mapping all the available evidence on the association of various clinical, demographic, and lifestyle variables with the risk of specific adverse outcomes in patients with COVID-19.

METHODS

The systematic review was conducted using standardized methodology, searching two electronic databases (PubMed and SCOPUS) for relevant literature published between 1st January 2020 and 9th July 2020. Included studies reported characteristics of patients with COVID-19 while reporting outcomes relating to disease severity. In the case of sufficient comparable data, meta-analyses were conducted to estimate risk of each variable.

RESULTS

Seventy-six studies were identified, with a total of 17,860,001 patients across 14 countries. The studies were highly heterogeneous in terms of the sample under study, outcomes, and risk measures reported. A large number of risk factors were presented for COVID-19. Commonly reported variables for adverse outcome from COVID-19 comprised patient characteristics, including age >75 (OR: 2.65, 95% CI: 1.81-3.90), male sex (OR: 2.05, 95% CI: 1.39-3.04) and severe obesity (OR: 2.57, 95% CI: 1.31-5.05). Active cancer (OR: 1.46, 95% CI: 1.04-2.04) was associated with increased risk of severe outcome. A number of common symptoms and vital measures (respiratory rate and SpO2) also suggested elevated risk profiles.

CONCLUSIONS

Based on the findings of this study, a range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.

COVID-19 fatality rates in hospitalized patients: systematic review and meta-analysis

Background

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Although general and local public health report deathly cases, case fatality rates are still largely unknown. Thus, we sought to evaluate the mortality of COVID-19.

Methods

We searched PubMed and EMBASE databases for articles evaluating the clinical characteristics of COVID-19 patients that included clinical outcomes, between December 2020 and 24 April 2020. Two authors performed an independent selection using predefined terms of search.

Results

We retrieved 33 studies with a total of 13,398 patients with COVID-19 diagnosis. The mortality rate of the COVID‐19 patients was 17.1% (95% CI 12.7; 22.7, I² = 96.9%). For general patients admitted to the hospital (excluding critical care-only studies) the mortality rate of the COVID‐19 was 11.5% (95% CI 7.7; 16.9, I² = 96.7%). Among critical illness studies (n = 7) we found a 40.5% mortality (95% CI 31.2; 50.6, I² = 91.8%).

Conclusion

High COVID-19 mortality among general admitted patients and critical care cases should guide resources allocations and economic burden calculations during the pandemics.

Is COVID-19 infection more severe in kidney transplant recipients?

There are no studies which have compared the risk of severe COVID-19 and related mortality between transplant recipients and nontransplant patients. We enrolled two groups of patients hospitalized for COVID-19, that is, kidney transplant recipients (KTR) from the French Registry of Solid Organ Transplant (n = 306) and a single-center cohort of nontransplant patients (n = 795). An analysis was performed among subgroups matched for age and risk factors for severe COVID-19 or mortality. Severe COVID-19 was defined as admission (or transfer) to an intensive care unit, need for mechanical ventilation, or death. Transplant recipients were younger and had more comorbidities compared to nontransplant patients. They presented with higher creatinine levels and developed more episodes of acute kidney injury. After matching, the 30-day cumulative incidence of severe COVID-19 did not differ between KTR and nontransplant patients; however, 30-day COVID-19-related mortality was significantly higher in KTR (17.9% vs 11.4%, respectively, p = .038). Age >60 years, cardiovascular disease, dyspnea, fever, lymphopenia, and C-reactive protein (CRP) were associated with severe COVID-19 in univariate analysis, whereas transplant status and serum creatinine levels were not. Age >60 years, hypertension, cardiovascular disease, diabetes, CRP >60 mg/L, lymphopenia, kidney transplant status (HR = 1.55), and creatinine level >115 µmol/L (HR = 2.32) were associated with COVID-19-related mortality in univariate analysis. In multivariable analysis, cardiovascular disease, dyspnea, and fever were associated with severe disease, whereas age >60 years, cardiovascular disease, dyspnea, fever, and creatinine level>115 µmol/L retained their independent associations with mortality. KTR had a higher COVID-19-related mortality compared to nontransplant hospitalized patients.

Knowledge, socio-cognitive perceptions and the practice of hand hygiene and social distancing during the COVID-19 pandemic: a cross-sectional study of UK university students

BACKGROUND

During the first wave of the COVID-19 pandemic, social distancing and hand hygiene have been the primary means of reducing transmission in the absence of effective treatments or vaccines, but understanding of their determinants is limited. This study aimed to investigate knowledge and socio-cognitive perceptions, and their associations with such protective behaviours, in UK university students.

METHODS

A cross-sectional online survey of 293 students was undertaken on 13 May 2020. Survey questions addressed demographics, knowledge of the disease and effectiveness of the protective measures, risk perception, socio-cognitive perceptions (e.g. attitude, social support, and self-efficacy), habit, time factors and trust, as well as the hand hygiene and social distancing behaviours. Multiple linear regression was used to identify the strongest associations of potential determinants with behaviour.

RESULTS

Participants reported high levels of social distancing with 88.9% answering "Mostly" or "Always" for every activity, but only 42.0% reporting the same for all hand hygiene activities. Knowledge of the effectiveness of each activity in preventing transmission was high, with 90.7% and 93.5% respectively identifying at least 7 of 8 hand hygiene or 9 of 10 social distancing activities correctly. Habit (β = 0.39, p = 0.001) and time factors (β = 0.28, p = 0.001) were the greatest contributors to unique variance in hand hygiene behaviour, followed by ethnicity (β = - 0.13, p = 0.014) and risk perception (β = 0.13, p = 0.016). For social distancing behaviour, the determinants were self-efficacy (β = 0.25, p < 0.001), perceived advantages (β = 0.15, p = 0.022), trust in policy (β = 0.14, p = 0.026) and gender (β = - 0.14, p = 0.016). Regression models explained 40% hand hygiene and 25% social distancing variance.

CONCLUSIONS

This study indicated that communications about effectiveness of hand hygiene and social distancing behaviours had been effective in terms of knowledge acquisition. However, in the light of likely second waves of COVID-19, attention to maintaining social distancing behaviour and improving hand hygiene behaviour may need to address more difficult areas of changing habits, overcoming time factors and building trust, as well as interventions to increase self-efficacy and address risk perception concerns.

A systematic review of clinical and laboratory parameters associated with increased severity among COVID-19 patients

BACKGROUND AND AIMS

Corona virus disease 2019 (COVID-19) has been an extremely difficult pandemic to contain and it has affected more than 148 countries worldwide. The main aim of this systematic review is to provide a comprehensive summary of clinical and laboratory parameters that are associated with and indicative of increased severity among COVID-19 patients.

MATERIAL AND METHODS

All the available data from high-quality research articles relevant to the epidemiology, demographics, trends in hospitalization and outcomes, clinical signs and symptoms, diagnostic methods and treatment methods of COVID-19 were retrieved and evaluated for inclusion.

RESULTS

As per our review, the mean age of patients in the severe group was 59.3 years compared to 46.5 years in non severe group. COVID-19 was more severe among men than women. Clinical presentation was variable among different studies. and dyspnea was the factor indicating severe disease. Laboratory parameters associated with increased severity were lymphopenia <0.8 × 109/L, thrombocytopenia 100 × 109/L, leucocytosis TC > 11 × 109/L, procalcitonin >0.5 ng/mL, d dimer >2 mcg/mL, aspartate transaminase elevation >150U/L, LDH >250U/L.

CONCLUSION

This systematic review suggests that COVID-19 is a disease with varied clinical presentation and laboratory parameters. The commonest clinical symptoms were fever, cough and dyspnea. The laboratory parameters associated with severe disease were lymphopenia, elevated LDH, D dimer and Procalcitonin.

Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019

BACKGROUND

Uncertainty surrounding COVID-19 regarding rapid progression to acute respiratory distress syndrome and unusual clinical characteristics make discharge from a monitored setting challenging. A clinical risk score to predict 14-day occurrence of hypoxia, ICU admission, and death is unavailable.

OBJECTIVE

Derive and validate a risk score to predict suitability for discharge from a monitored setting among an early cohort of patients with COVID-19.

DESIGN

Model derivation and validation in a retrospective cohort. We built a manual forward stepwise logistic regression model to identify variables associated with suitability for discharge and assigned points to each variable. Event-free patients were included after at least 14 days of follow-up.

PARTICIPANTS

All adult patients with a COVID-19 diagnosis between March 1, 2020, and April 12, 2020, in 10 hospitals in Massachusetts, USA.

MAIN MEASURES

Fourteen-day composite predicting hypoxia, ICU admission, and death. We calculated a risk score for each patient as a predictor of suitability for discharge evaluated by area under the curve.

KEY RESULTS

Of 2059 patients with COVID-19, 1326 met inclusion. The 1014-patient training cohort had a mean age of 58 years, was 56% female, and 65% had at least one comorbidity. A total of 255 (25%) patients were suitable for discharge. Variables associated with suitability for discharge were age, oxygen saturation, and albumin level, yielding a risk score between 0 and 55. At a cut point of 30, the score had a sensitivity of 83% and specificity of 82%. The respective c-statistic for the derivation and validation cohorts were 0.8939 (95% CI, 0.8687 to 0.9192) and 0.8685 (95% CI, 0.8095 to 0.9275). The score performed similarly for inpatients and emergency department patients.

CONCLUSIONS

A 3-item risk score for patients with COVID-19 consisting of age, oxygen saturation, and an acute phase reactant (albumin) using point of care data predicts suitability for discharge and may optimize scarce resources.

[Factors associated with the occurrence of acute respiratory distress and death in patients with COVID-19 in Burkina Faso]

INTRODUCTION

The development of acute respiratory distress syndrome indicates a serious form of COVID-19. Although there have been several studies on the prognostic factors of its severe form, no such study has been conducted in Burkina Faso.

METHODS

This was a retrospective cohort study conducted from March 9 to June 9, 2020 in Ouagadougou, Burkina Faso which involved 456 patients with COVID-19.

RESULTS

Nearly a quarter of the patients (23.2%) had presented with acute respiratory distress and 44.3% of them died. Being over 65 years old (HR: 2.7; 95% CI: 1.5-5.1) and having hypertension (HR: 1.9; 95% CI: 1-3.5) were independently associated with the risk of mortality. However, after adjustment, only age over 65 years (HR: 2.3; 95% CI: 1.2-4.3) was a risk factor for death. The survival rate for patients over 65 was 38.5% at 7 days and 30.3% at 15 days.

CONCLUSIONS

Acute respiratory distress leading to death is mainly found in older people with COVID-19. Close monitoring of these high-risk patients may reduce the risk of death.

Clinical Characteristics and Outcomes in Patients with COVID-19 and Cancer: a Systematic Review and Meta-analysis

Much of routine cancer care has been disrupted due to the perceived susceptibility to SARS-CoV-2 infection in cancer patients. Here, we systematically review the current evidence base pertaining to the prevalence, presentation and outcome of COVID-19 in cancer patients, in order to inform policy and practice going forwards. A keyword-structured systematic search was conducted on Pubmed, Cochrane, Embase and MedRxiv databases for studies reporting primary data on COVID-19 in cancer patients. Studies were critically appraised using the NIH National Heart, Lung and Blood Institute's quality assessment tool set. The pooled prevalence of cancer as a co-morbidity in patients with COVID-19 and pooled in-hospital mortality risk of COVID-19 in cancer patients were derived by random-effects meta-analyses. In total, 110 studies from 10 countries were included. The pooled prevalence of cancer as a co-morbidity in hospitalised patients with COVID-19 was 2.6% (95% confidence interval 1.8%, 3.5%, I2: 92.0%). Specifically, 1.7% (95% confidence interval 1.3%, 2.3%, I2: 57.6.%) in China and 5.6% (95% confidence interval 4.5%, 6.7%, I2: 82.3%) in Western countries. Patients most commonly presented with non-specific symptoms of fever, dyspnoea and chest tightness in addition to decreased arterial oxygen saturation, ground glass opacities on computer tomography and non-specific changes in inflammatory markers. The pooled in-hospital mortality risk among patients with COVID-19 and cancer was 14.1% (95% confidence interval 9.1%, 19.8%, I2: 52.3%). We identified impeding questions that need to be answered to provide the foundation for an iterative review of the developing evidence base, and inform policy and practice going forwards. Analyses of the available data corroborate an unfavourable outcome of hospitalised patients with COVID-19 and cancer. Our findings encourage future studies to report detailed social, demographic and clinical characteristics of cancer patients, including performance status, primary cancer type and stage, as well as a history of anti-cancer therapeutic interventions.

Early prediction model for progression and prognosis of severe patients with coronavirus disease 2019

Coronavirus disease 2019 (COVID-19) has been a rampant worldwide health threat and we aimed to develop a model for early prediction of disease progression.This retrospective study included 124 adult inpatients with COVID-19 who presented with severe illness at admission and had a definite outcome (recovered or progressed to critical illness) during February 2020. Eighty-four patients were used as training cohort and 40 patients as validation cohort. Logistic regression analysis and receiver operating characteristic curve (ROC) analysis were used to develop and evaluate the prognostic prediction model.In the training cohort, the mean age was 63.4 ± 1.5 years, and male patients (48, 57%) were predominant. Forty-three (52%) recovered, and 41 (49%) progressed to critical. Decreased lymphocyte count (LC, odds ratio [OR] = 4.40, P = .026), elevated lactate dehydrogenase levels (LDH, OR = 4.24, P = .030), and high-sensitivity C-reactive protein (hsCRP, OR = 1.01, P = .025) at admission were independently associated with higher odds of deteriorated outcome. Accordingly, we developed a predictive model for disease progression based on the levels of the 3 risk factors (LC, LDH, and hsCRP) with a satisfactory performance in ROC analysis (area under the ROC curve [AUC] = 0.88, P < .001) and the best cut-off value was 0.526 with the sensitivity and specificity of 75.0% and 90.7%, respectively. Then, the model was internally validated by leave-one-out cross-validation with value of AUC 0.85 (P < .001) and externally validated in another validation cohort (26 recovered patients and 14 progressed patients) with AUC 0.84 (P < .001).We identified 3 clinical indicators of risk of progression and developed a severe COVID-19 prognostic prediction model, allowing early identification and intervention of high-risk patients being critically illness.

Prognostic value of CT integrated with clinical and laboratory data during the first peak of the COVID-19 pandemic in Northern Italy: A nomogram to predict unfavorable outcome

Purpose

To evaluate the prognostic role of chest computed tomography (CT), alone or in combination with clinical and laboratory parameters, in COVID-19 patients during the first peak of the pandemic.

Methods

A retrospective single-center study of 301 COVID-19 patients referred to our Emergency Department (ED) from February 25 to March 29, 2020. At presentation, patients underwent chest CT and clinical and laboratory examinations. Outcomes included discharge from the ED after improvement/recovery (positive outcome), or admission to the intensive care unit or death (poor prognosis). A visual quantitative analysis was formed using two scores: the Pulmonary Involvement (PI) score based on the extension of lung involvement, and the Pulmonary Consolidation (PC) score based on lung consolidation. The prognostic value of CT alone or integrated with other parameters was studied by logistic regression and ROC analysis.

Results

The impact of the CT PI score [≥15 vs. ≤ 6] on predicting poor prognosis (OR 5.71 95 % CI 1.93−16.92, P = 0.002) was demonstrated; no significant association was found for the PC score. Chest CT had a prognostic role considering the PI score alone (AUC 0.722) and when evaluated with demographic characteristics, comorbidities, and laboratory data (AUC 0.841). We, therefore, developed a nomogram as an easy tool for immediate clinical application.

Conclusions

Visual analysis of CT gives useful information to physicians for prognostic evaluations, even in conditions of COVID-19 emergency. The predictive value is increased by evaluating CT in combination with clinical and laboratory data.

Association of smoking history with severe and critical outcomes in COVID-19 patients: A systemic review and meta-analysis

Introduction

The highly infectious coronavirus disease 2019 (COVID-19) has now rapidly spread around the world. This meta-analysis was strictly focused on the influence of smoking history on the severe and critical outcomes on people with COVID-19 pneumonia.

Methods

A systematic literature search was conducted in eight online databases before 1 February 2021. All studies meeting our selection criteria were included and evaluated. Stata 14.0 software was used to analyze the data.

Results

A total of 109 articles involving 517,020 patients were included in this meta-analysis. A statistically significant association was discovered between smoking history and COVID-19 severity, the pooled OR was 1.55 (95%CI: 1.41-1.71). Smoking was significantly associated with the risk of admission to intensive care unit (ICU) (OR=1.73, 95%CI: 1.36-2.19), increased mortality (OR=1.58, 95%CI: 1.38-1.81), and critical diseases composite endpoints (OR=1.61, 95%CI: 1.35-1.93), whereas there was no relationship with mechanical ventilation. The pooled prevalence of smoking using the random effects model (REM) was 15% (95%CI: 14%-16%). Meta-regression analysis showed that age (P=0.004), hypertension (P=0.007), diabetes (P=0.029), chronic obstructive pulmonary disease (COPD) (P=0.001) were covariates that affect the association.

Conclusions

Smoking was associated with severe or critical outcomes and increased the risk of admission to ICU and mortality in COVID-19 patients, but not associated with mechanical ventilation. This association was more significant for former smokers than in current smokers. Current smokers also had a higher risk of developing severe COVID-19 compared with non-smokers. More detailed data, which are representative of more countries, are needed to confirm these preliminary findings.

Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review

OBJECTIVE

The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa.

DESIGN

A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa.

DATA SOURCES

Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv.

ELIGIBILITY CRITERIA

Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020.

DATA EXTRACTION AND SYNTHESIS

We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form.

RESULTS

Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths.

CONCLUSIONS

Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategies.