Clinical symptoms,comorbidities and complications in severe and non-severe patients with COVID-19: A systematic review and meta-analysis without cases duplication

Background:The pandemic of COVID-19 poses a challenge to global healthcare. The mortality rates of severe cases range from 8.1% to 38%, and it is particularly important to identify risk factors that aggravate the disease.Methods:We performed a systematic review of the literature with meta-analysis, using 7 databases to identify studies reporting on clinical characteristics, comorbidities and complications in severe and non-severe patients with COVID-19. All the observational studies were included. We performed a random or fixed effects model meta-analysis to calculate the pooled proportion and 95% confidence interval (CI). Measure of heterogeneity was estimated by Cochran''s Q statistic, I² index and P value.Results:A total of 4881 cases from 25 studies related to COVID-19 were included. The most prevalent comorbidity was hypertension (severe: 33.4%, 95% CI: 25.4%–41.4%; non-severe 21.6%, 95% CI: 9.9%–33.3%), followed by diabetes (severe: 14.4%, 95% CI: 11.5%–17.3%; non-severe: 8.5%, 95% CI: 6.1%–11.0%). The prevalence of acute respiratory distress syndrome, acute kidney injury and shock were all higher in severe cases, with 41.1% (95% CI: 14.1%–68.2%), 16.4% (95% CI: 3.4%–29.5%) and 19.9% (95% CI: 5.5%–34.4%), rather than 3.0% (95% CI: 0.6%–5.5%), 2.2% (95% CI: 0.1%–4.2%) and 4.1% (95% CI: −4.8%–13.1%) in non-severe patients, respectively. The death rate was higher in severe cases (30.3%, 95% CI: 13.8%–46.8%) than non-severe cases (1.5%, 95% CI: 0.1%–2.8%).Conclusion:Hypertension, diabetes and cardiovascular diseases may be risk factors for severe COVID-19.     

The impact of coronavirus disease 2019 (COVID-19) on liver injury in China: A systematic review and meta-analysis

Introduction:The evidence for the incidence and severity of liver injury in Chinese patients with coronavirus disease 2019 (COVID-19) is still controversial. The purpose of this study was to summarize the incidence of liver injury and the differences between liver injury markers among different patients with COVID-19 in China.Methods:Computer searches of PubMed, Embase, China National Knowledge Infrastructure (CNKI) and medRxiv were used to obtain reports on the incidence and markers of liver injury in Chinese patients with COVID-19, from January 1, 2020 to April 10, 2020. (No. CRD42020181350)Results:A total of 57 reports from China were included, including 9889 confirmed cases of COVID-19 infection. The results of the meta-analysis showed that among the patients with early COVID-19 infection in China, the incidence of liver injury events was 24.7% (95% CI, 23.4%–26.4%). Liver injury in severe patients was more common than that in non-severe patients, with a risk ratio of 2.07 (95% CI, 1.77–2.43). Quantitative analysis showed that the severe the coronavirus infection, the higher the level of alanine aminotransferase (ALT), aspertate aminotransferase (AST), total bilirubin (TB), alkaline phosphatase (ALP), γ-glutamyl transpeptidase (GGT), and the lower the level of albumin (ALB).Conclusion:There is a certain risk of liver injury in Chinese patients with COVID-19, and the risk and degree of liver injury are related to the severity of COVID-19.     

Association between the peripheral blood eosinophil counts and COVID-19: A meta-analysis

Background:The conclusions about the relationship between eosinophil counts and the severity of coronavirus disease 2019 (COVID-19) were controversial, so we updated the evidences and reassessed it.Methods:We searched the PubMed, Cochrane library, Excerpta Medica Database, and Web of Science to compare the eosinophil counts about non-severe disease group (mild pneumonia, moderate pneumonia, non-critical disease and recovery group) and severe disease group (severe pneumonia, critical pneumonia, critical disease and death group) in COVID-19.Results:A total of 1228 patients from 10 studies were included. Compared with non-severe group, severe group had strikingly lower average eosinophil counts (SMD 0.65, 95% confidence intervals [CI] 0.29–1.01; P < .001). The result of subgroup analysis of different countries showed SMD 0.66, 95% CI 0.26–1.06; P < .001. Another subgroup analysis between mild-moderate pneumonia versus severe-critical pneumonia showed SMD 0.69, 95% CI 0.25–1.13; P < .001, and no significant risk of publication bias (Begg test 0.063 and Egger test 0.057) in this subgroup. The heterogeneity was substantial, but the sensitivity analyses showed no significant change when individual study was excluded, which suggested the crediblity and stablity of our results.Conclusions:The eosinophil counts had important value as an indicator of severity in patients with COVID-19.PROSPERO registration number:CRD42020205497.     

Obesity or increased body mass index and the risk of severe outcomes in patients with COVID-19: A protocol for systematic review and meta-analysis

Background:To assess the effect of obesity or a high body mass index (BMI) on the risk of severe outcomes in patients with coronavirus disease 2019 (COVID-19).Methods:Studies on the relationship between BMI or obesity and COVID-19 since December 2019. The odds ratio (OR) and weighted mean difference (WMD) with their 95% confidence intervals (CIs) were used to assess the effect size.Results:BMI was significantly increased in COVID-19 patients with severe illness (WMD: 1.18; 95% CI: 0.42–1.93), who were admitted to an intensive care unit (ICU) (WMD: 1.46; 95% CI: 0.96–1.97), who required invasive mechanical ventilation (IMV) (WMD: 2.70, 95% CI: 1.05–4.35) and who died (WMD: 0.91, 95% CI: 0.02–1.80). In Western countries, obesity (BMI of ≥30 kg/m²) increased the risk of hospitalization (OR: 2.08; 95% CI: 1.22–3.54), admission to an ICU (OR: 1.54; 95% CI: 1.29–1.84), need for IMV (OR: 1.73, 95% CI: 1.38–2.17), and mortality (OR: 1.43; 95% CI: 1.17–1.74) of patients with COVID-19. In the Asian population, obesity (BMI of ≥28 kg/m²) increased the risk of severe illness (OR: 3.14; 95% CI: 1.83–5.38). Compared with patients with COVID-19 and a BMI of <25 kg/m², those with a BMI of 25–30 kg/m² and ≥30 kg/m² had a higher risk of need for IMV (OR: 2.19, 95% CI: 1.30–3.69 and OR: 3.04; 95% CI: 1.76–5.28, respectively). The risk of ICU admission in patients with COVID-19 and a BMI of ≥30 kg/m² was significantly higher than in those with a BMI of 25–30 kg/m² (OR: 1.49; 95% CI: 1.00–2.21).Conclusion:As BMI increased, the risks of hospitalization, ICU admission, and need for IMV increased, especially in COVID-19 patients with obesity.Ethics and dissemination:This systematic review and meta-analysis does not require an ethics approval as it does not collect any primary data from patients.     

The effect of glucocorticoids on mortality in severe COVID-19 patients: Evidence from 13 studies involving 6612 cases

Background:Since the start of the coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need for effective therapies for patients with COVID-19. In this study, we aimed to assess the therapeutic efficacy of glucocorticoids in severe COVID-19.Methods:A systematic literature search was performed across PubMed, Web of Science, EMBASE, and the Cochrane Library (up to June 26, 2021). The literature investigated the outcomes of interest were mortality and invasive mechanical ventilation.Results:The search identified 13 studies with 6612 confirmed severe COVID-19 patients. Our meta-analysis found that using glucocorticoids could significantly decrease COVID-19 mortality (hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.45–0.79, P < .001), relative to non-use of glucocorticoids. Meanwhile, using glucocorticoids also could significantly decrease the risk of progression to invasive mechanical ventilation for severe COVID-19 patients (HR = 0.69, 95% CI 0.58–0.83, P < .001). Compared with using dexamethasone (HR = 0.68, 95% CI 0.50–0.92, P = .012), methylprednisolone use had a better therapeutic effect for reducing the mortality of patients (HR = 0.35, 95% CI 0.19–0.64, P = .001).Conclusion:The result of this meta-analysis showed that using glucocorticoids could reduce mortality and risk of progression to invasive mechanical ventilation in severe COVID-19 patients.     

The first wave of the COVID-19 pandemic in Spain: characterisation of cases and risk factors for severe outcomes,as at 27 April 2020

BackgroundThe first wave of the coronavirus disease (COVID-19) pandemic spread rapidly in Spain, one of Europe’s most affected countries. A national lockdown was implemented on 15 March 2020.AimTo describe reported cases and the impact of national lockdown, and to identify disease severity risk factors.MethodsNational surveillance data were used to describe PCR-confirmed cases as at 27 April 2020. We compared case characteristics by severity categories (hospitalisation, admission to intensive care unit (ICU), death) and identified severity risk factors using multivariable regression.ResultsThe epidemic peaked on 20 March. Of 218,652 COVID-19 cases, 45.4% were hospitalised, 4.6% were admitted to ICU and 11.9% died. Among those who died, 94.8% had at least one underlying disease. Healthcare workers (HCWs) represented 22.9% of cases. Males were more likely to have severe outcomes than females. Cardiovascular disease was a consistent risk factor. Patients with pneumonia had higher odds of hospitalisation (odds ratio (OR): 26.63; 95% confidence interval (CI): 25.03–28.33). The strongest predictor of death was age ≥ 80 years (OR: 28.4; 95% CI: 19.85–40.78). Among underlying diseases, chronic renal disease had highest odds of death (OR: 1.47; 95% CI: 1.29–1.68).ConclusionsCOVID-19 case numbers began declining 6 days after the national lockdown. The first wave of the COVID-19 pandemic in Spain had a severe impact on elderly people. Patients with cardiovascular or renal conditions were at higher risk for severe outcomes. A high proportion of cases were HCWs. Enhanced surveillance and control measures in these subgroups are crucial during future COVID-19 waves.     

Influenza Vaccine: Influenza vaccine during the 2019–2020 season and COVID-19 risk: A case-control study in Québec

BackgroundWe carried out a case-control study that examined whether receipt of the inactivated influenza vaccine during the 2019–2020 season impacted on the risk of coronavirus disease 2019 (COVID-19), as there was a concern that the vaccine could be detrimental through viral interference.MethodsA total of 920 cases with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (diagnosed between March and October 2020) and 2,123 uninfected controls were recruited from those who were born in Québec between 1956 and 1976 and who had received diagnostic services at two hospitals (Montréal and Sherbrooke, Québec). After obtaining consent, a questionnaire was administered by phone. Data were analyzed by logistic regression.ResultsAmong healthcare workers, inactivated influenza vaccine received during the previous influenza season was not associated with increased COVID-19 risk (AOR: 0.99, 95% CI: 0.69–1.41). Among participants who were not healthcare workers, influenza vaccination was associated with lower odds of COVID-19 (AOR: 0.73, 95% CI 0.56–0.96).ConclusionWe found no evidence that seasonal influenza vaccine increased the risk of developing COVID-19.     

Clinical,laboratory, and imaging features of pediatric COVID-19: A systematic review and meta-analysis

Pediatric cases of coronavirus disease 2019 (COVID-19) have been reported. This meta-analysis was aimed at describing the clinical, laboratory, and imaging characteristics of children with COVID-19 based on published data of pediatric COVID-19 cases.Search of PubMed, Embase, Web of Sciences, Science Direct, and Google Scholar for articles published until December 14, 2020, that described the clinical, laboratory, and imaging features of children with COVID-19. Data were extracted independently by 2 authors. Random-effects meta-analysis models were used to report pooled results.Clinical data from 2874 children with COVID-19 from 37 articles were finally included for quantitative analyses. Fever (48.5%, 95% CI: 41.4%–55.6%) and cough (40.6%, 95% CI: 33.9%–47.5%) were the most common symptoms; asymptomatic infection and severe cases, respectively, accounted for 27.7% (95% CI: 19.7%–36.4%) patients and 1.1% of the 1933 patients included. Laboratory tests showed 5.5% (95% CI: 2.8%–8.9%) of the patients had lymphopenia. The pooled prevalence of leukopenia was 7.3% (95% CI: 3.4%–12.2%), and the C-reactive protein level was high in 14.0% (95% CI: 6.8%–22.8%). Chest computed tomography showed unilateral and bilateral lesions, and ground-glass opacity in 29.4% (95% CI: 24.8%–34.3%) and 24.7% (95% CI: 18.2%–31.6%), and 32.9% (95% CI: 25.3%–40.9%), respectively, and normal in approximately 36.0% (95% CI: 27.7%–44.7%).We found that children with COVID-19 had relatively mild disease, with quite a lot of asymptomatic infections and low rate of severe illness. Data from more regions are needed to determine the prevention and treatment strategies for children with COVID-19.     

Prior Immunosuppressive Therapy and Severe Illness Among Patients Diagnosed with SARS-CoV-2: a Community-Based Study

BackgroundAn estimated 10 million people in the USA are immunocompromised, a risk factor for severe COVID-19. Data informing whether immune-mediated medications lead to more severe infection are sparse.ObjectiveDetermine whether outpatient immunosuppressive therapies that treat autoimmune inflammatory disease or prevent solid organ transplant rejection are associated with severe illness after diagnosis with SARS-CoV-2DesignRetrospective cohort studyParticipantsAdults with a positive PCR nasal swab for SARS-CoV-2 from February 25 to September 9, 2020, cared for within a large integrated health care organizationMain MeasuresExposure was defined as an outpatient fill of prednisone, immunomodulator, small-molecule, or biologic therapy in the 105 days prior to a positive SARS-CoV-2 PCR test. The main outcome was either hospitalization, ICU admission, or death within 45 days after diagnosis of SARS-CoV-2. Multivariable logistic regression models were adjusted for age, race, gender, body mass index, comorbidities, and autoimmune disease.Key ResultsA total of 39,686 adults had a positive PCR test. In the primary analysis, prior prednisone use was associated with severe illness after diagnosis with SARS-CoV-2 (odds ratio (OR) 1.31; 95% confidence interval (CI) 1.08–1.60); however, immunomodulator (OR 0.88; 95% CI 0.57–1.34) and biologic/small-molecule therapy (OR 1.26; 95% CI 0.79–2.00) were not. Secondary analyses showed variable risk among therapies: Janus-kinase inhibitors had an increased odds of severe illness (OR 3.35; 95% CI 1.16–9.67), thiopurines/conventionaldisease-modifying antirheumatic drugs had a reduced odds (OR 0.53; 95% CI 0.32–0.88), and tumor necrosis factor inhibitors were not associated (OR 0.45; 95% CI 0.18–1.08).Conclusions and RelevanceOutpatient use of prednisone is associated with severe illness after diagnosis of SARS-CoV-2. Immunomodulator and biologic/small-molecule therapy were not associated, but different risk subgroups were identified. Our findings can inform risk-benefit discussions in the clinic and risk-based recommendations for patients on these therapies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-021-07152-2.     

Neurological Manifestations and Long-term Sequelae in Hospitalized Patients with COVID-19

Objective Various neurological manifestations have been increasingly reported in coronavirus disease 2019 (COVID-19). We determined the neurological features and long-term sequelae in hospitalized COVID-19 patients. Methods We retrospectively studied 95 consecutive hospitalized patients with COVID-19 between March 1 and May 13, 2020. Acute neurological presentations (within two weeks of the symptom onset of COVID-19) were compared between 60 non-severe and 35 severely infected patients who required high-flow oxygen. In the 12 ventilated patients (the most severe group), we evaluated neurological complications during admission, subacute neurological presentations, and neurological sequelae (51 and 137 days from the onset [median], respectively). Results Of the 95 patients (mean age 53 years old; 40% women), 63% had acute neurological presentations, with an increased prevalence in cases of severe infections (83% vs. 52%, p＜0.001). Impaired consciousness and limb weakness were more frequent in severe patients than in non-severe ones (0% vs. 49%; p＜0.001, and 0% vs. 54%; p＜0.001, respectively). In the most severe group (mean age 72 years old; 42% women), 83% of patients had neurological complications [cerebrovascular disease (17%), encephalopathy (82%), and neuropathy (55%)], and 92% had subacute neurological presentations [impaired consciousness (17%), higher brain dysfunction (82%), limb weakness (75%), and tremor (58%)]. Neurological sequelae were found in 83% of cases, including higher brain dysfunction (73%), limb weakness (50%), and tremor (58%). Conclusions Neurological manifestations are common in COVID-19, with the possibility of long-lasting sequelae.     

Incidence of thromboembolic complications in hospitalized COVID-19 patients in a medical ward in Japan: A single-center retrospective and prospective observational study

Background:A high incidence of thromboembolic complications is one of the hallmarks of COVID-19. However, there may be a difference in the incidence of thromboembolic complications between Asian and Western people. In addition, few prospective studies have been conducted to determine the incidence of thromboembolic complications in hospitalized COVID-19 patients in medical wards in Japan.Methods:A single-center retrospective and prospective cohort study was conducted to determine the incidence of thromboembolic complications in symptomatic COVID-19 patients in a medical ward in a Japanese hospital. All 1116 consecutive COVID-19 patients who were admitted to our hospital from November 1, 2020, to October 26, 2021, were included. The primary outcome was any thromboembolic complications, which included venous thromboembolism, myocardial infarction, ischemic stroke, and other arterial embolisms.Results:The median patient age was 50 (IQR, 37–61), 402 (36.0%) were women, 1005 (90.1%) were Japanese, the median body mass index was 24.1 (IQR, 21.6–27.2), and 43 (3.9%) had Padua scores of at least 4 points at admission. Regarding the severity of COVID-19, 543 (48.7%), 315 (28.2%), 204 (18.3%), and 54 (4.8%) patients had mild, moderate, severe, and critical COVID-19, respectively. Nine patients (0.8%) died, and 47 patients (4.2%) were transferred to other hospitals for intensive care. The primary outcome occurred in only 5 patients (0.5%; 95% CI, 0.1–0.8) and consisted of 3 ischemic strokes, 2 limb ischemia events, and one asymptomatic pulmonary embolism. Even in the 204 patients with severe COVID-19, the prevalence of thromboembolic complications was only 2.5% (95% CI, 0.3–4.6).Conclusion:Thromboembolic complications of COVID-19 are rare even in severe cases in a medical ward in a Japanese hospital. Further studies are needed to identify severe COVID-19 patients with a higher risk for thromboembolic complications in Japan.     

Prognostic impact of atrial fibrillation in patients with severe acute respiratory syndrome coronavirus 2 infection

The prognostic impact of atrial fibrillation (AF) in patients with severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection has not been well evaluated. We estimated the prognostic implications of AF in SARS-CoV-2 confirmed patients.The OpenData4Covid19 (https://hira-covid19.net) project is a global research collaboration on coronavirus disease (COVID-19), hosted by the Ministry of Health and Welfare of Korea and the Health Insurance Review and Assessment Service of Korea. This dataset comprises all COVID-19-tested patients and their individual histories of medical service use from January 1, 2017 to May 15, 2020. All patients >19 years with confirmed SARS-CoV-2 infection were included. The primary endpoint was a composite of death and intensive care unit admission.In total, 7162 adults with SARS-CoV-2 infection were included in this study. The prevalence of AF was 1.8% (n = 130). Patients with AF had unfavorable characteristics, such as older age and higher prevalence of comorbidities. The primary endpoint was more common in patients with AF than in those without (33.9% vs 12.9%, P < .001). In the multivariable model, age (odds ratio [OR]: 1.035, 95% confidence interval [CI]: 1.030–1.040), female sex (OR: 0.618, 95% CI: 0.535–0.713), diabetes (OR: 1.341, 95% CI: 1.093–1.580), and chronic kidney disease (OR: 2.714, 95% CI: 1.541–4.777) were associated with the primary endpoint. However, AF was not an independent predictor of the primary endpoint (OR: 1.402, 95% CI: 0.932–2.108).Patients with AF and concomitant SARS-CoV-2 infection had more comorbidities and a worse prognosis. However, an independent association between AF and adverse clinical outcomes was not evident.     

Post-traumatic Stress Disorder Among COVID-19 Survivors at 3-Month Follow-up After Hospital Discharge

BackgroundPost-traumatic stress disorder (PTSD) is a severe but treatable mental disorder that develops after a life-threatening traumatic event. Coronavirus disease 19 (COVID-19) hospitalisation is a potentially traumatic experience, especially in severe cases. Furthermore, the unprecedented context of the severe acute respiratory syndrome coronavirus 2 pandemic, with daily media bombardment about COVID-19 mortality, may have amplified life-threatening perception also in patients with moderate infection. The aim of this study was to assess the prevalence and risk factors of PTSD at 3-month follow-up in patients hospitalised for COVID-19 infection.DesignIn this cohort follow-up study conducted in a large Italian academic COVID-19 hospital, 115 recruited survivors were contacted by telephone 3 months after discharge to home care. The Posttraumatic Stress Disorder Checklist for DSM-5 was administered. Multivariate logistic regression models were used to analyse risk factors for the development of PTSD.Key ResultsA total of 10.4% of the sample received a PCL-5-based diagnosis of PTSD. Other 8.6% of the sample received a diagnosis of subthreshold PTSD, which leads to significant levels of distress and impairment. Multivariate regression analysis indicated that previous psychiatric diagnosis (odds ratio (OR) = 6.3, 95% confidence interval (CI): 3.7–78.6, p < 0.001) and obesity (OR = 3.51, 95% CI: 1.4–857.9, p = 0.03) were risk factors for developing PTSD. Chronic pulmonary diseases approached significance as a risk factor (OR = 6.03, 95% CI: 1.0–37.1, p = 0.053). Male sex was a protective factor (OR=0.04, 95% CI: 0.0–0.041, p = 0.007).ConclusionsPTSD and subthreshold PTSD rates in patients hospitalised for COVID-19 are worrying. Female sex and pre-existing mental disorders are established risk factors for PTSD, while the prospective association with obesity needs further investigation. Clinicians treating COVID-19 should consider screening for PTSD at follow-up assessments in patients discharged from the hospital.KEY WORDS: post-traumatic stress disorder, COVID-19, SARS-CoV-2, mental health, hospitalisation     

Prevalence and risk factors for postinfectious cough in discharged patients with coronavirus disease 2019 (COVID-19)

BackgroundCough is one of the most common symptoms of coronavirus disease 2019 (COVID-19). However, the prevalence of persistent cough in recovered patients with COVID-19 during a longer follow-up remained unknown. This study aims to investigate the prevalence, and risk factors for postinfectious cough in COVID-19 patients after discharge.MethodsWe conducted a follow-up study for 129 discharged patients with laboratory-confirmed COVID-19 in two large hospitals located in Hubei Province, China from January 2020 to December 2020. Baseline demographics, comorbidities and smoking history were extracted from the medical record. Current symptoms and severity were recorded by a uniform questionnaire. Spirometry, diffuse function and chest computed tomography (CT) were performed on part of patients who were able to return to the outpatient department at follow-up.ResultsThe median (interquartile range) follow-up time was 8.1 (7.9–8.5) months after discharge. The mean (standard deviation) age was 51.5 (14.9) years and 57 (44.2%) were male. A total of 27 (20.9%) patients had postinfectious cough (>3 weeks), 6 patients (4.7%) had persistent cough by the end of follow-up, including 3 patients with previous chronic respiratory diseases or current smoking. Other symptoms included dyspnea (6, 4.7%), sputum (4, 3.1%), fatigue (4, 3.1%), and anorexia (4, 3.1%) by the end of follow-up. Thirty-six of 41 (87.8%) patients showed impaired lung function or diffuse function, and 39 of 50 (78.0%) patients showed abnormal CT imaging. Patients with postinfectious cough demonstrated more severe and more frequent cough during hospitalization (P<0.001), and more chronic respiratory diseases (P=0.01). In multivariate logistic regression analysis, digestive symptoms during hospitalization [odds ratio (OR) 2.95, 95% confidence interval (CI): 1.10–7.92] and current smoking (OR 6.95, 95% CI: 1.46–33.14) were significantly associated with postinfectious cough of COVID-19.ConclusionsA small part of patients developed postinfectious cough after recovery from COVID-19, few patients developed chronic cough in spite of a higher proportion of impaired lung function and abnormal lung CT image. Current smoking and digestive symptoms during hospitalization were risk factors for postinfectious cough in COVID-19.     

Epidemiological characteristics and outcomes of COVID-19 cases: mortality inequalities by socio-economic status,Barcelona, Spain, 24 February to 4 May 2020

BackgroundPopulation-based studies characterising outcomes of COVID-19 in European settings are limited, and effects of socio-economic status (SES) on outcomes have not been widely investigated. AimWe describe the epidemiological characteristics of COVID-19 cases, highlighting incidence and mortality rate differences across SES during the first wave in Barcelona, Catalonia, Spain.MethodsThis population-based study reports individual-level data of laboratory-confirmed COVID-19 cases diagnosed from 24 February to 4 May 2020, notified to the Public Health Agency of Barcelona and followed until 15 June 2020. We analysed end-of-study vital status and the effects of chronic conditions on mortality using logistic regression. Geocoded addresses were linked to basic health area SES data, estimated using the composed socio-economic index. We estimated age-standardised incidence, hospitalisation, and mortality rates by SES.ResultsOf 15,554 COVID-19-confirmed cases, the majority were women (n = 9,028; 58%), median age was 63 years (interquartile range: 46–83), 8,046 (54%) required hospitalisation, and 2,287 (15%) cases died. Prevalence of chronic conditions varied across SES, and multiple chronic conditions increased risk of death (≥ 3, adjusted odds ratio: 2.3). Age-standardised rates (incidence, hospitalisation, mortality) were highest in the most deprived SES quartile (incidence: 1,011 (95% confidence interval (CI): 975–1,047); hospitalisation: 619 (95% CI: 591–648); mortality: 150 (95% CI: 136–165)) and lowest in the most affluent (incidence: 784 (95% CI: 759–809); hospitalisation: 400 (95% CI: 382–418); mortality: 121 (95% CI: 112–131)).ConclusionsCOVID-19 outcomes varied markedly across SES, underscoring the need to implement effective preventive strategies for vulnerable populations.     

Computed tomography features of COVID-19 in children: A systematic review and meta-analysis

Background:There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes.Objectives:To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice.Data sources:We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu.Methods:Reports on chest CT imaging features of children with COVID-19 from January 1, 2020 to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software.Results:Thirty-seven articles (1747 children) were included in this study. The heterogeneity of meta-analysis results ranged from 0% to 90.5%. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8%–70.6%), with a rate of 61.0% (95% CI: 50.8%–71.2%) in China and 67.8% (95% CI: 57.1%–78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7%–48.3%), multiple lung lobe lesions was 65.1% (95% CI: 55.1%–67.9%), and bilateral lung lesions was 61.5% (95% CI: 58.8%–72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported 3 cases of white lung, another reported 2 cases of pneumothorax, and another 1 case of bullae.Conclusions:The lung CT results of children with COVID-19 are usually normal or slightly atypical. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool.     

Impact of Race and Socioeconomic Status on Outcomes in Patients Hospitalized with COVID-19

BackgroundThe impact of race and socioeconomic status on clinical outcomes has not been quantified in patients hospitalized with coronavirus disease 2019 (COVID-19).ObjectiveTo evaluate the association between patient sociodemographics and neighborhood disadvantage with frequencies of death, invasive mechanical ventilation (IMV), and intensive care unit (ICU) admission in patients hospitalized with COVID-19.DesignRetrospective cohort study.SettingFour hospitals in an integrated health system serving southeast Michigan.ParticipantsAdult patients admitted to the hospital with a COVID-19 diagnosis confirmed by polymerase chain reaction.Main MeasuresPatient sociodemographics, comorbidities, and clinical outcomes were collected. Neighborhood socioeconomic variables were obtained at the census tract level from the 2018 American Community Survey. Relationships between neighborhood median income and clinical outcomes were evaluated using multivariate logistic regression models, controlling for patient age, sex, race, Charlson Comorbidity Index, obesity, smoking status, and living environment.Key ResultsBlack patients lived in significantly poorer neighborhoods than White patients (median income: $34,758 (24,531–56,095) vs. $63,317 (49,850–85,776), p < 0.001) and were more likely to have Medicaid insurance (19.4% vs. 11.2%, p < 0.001). Patients from neighborhoods with lower median income were significantly more likely to require IMV (lowest quartile: 25.4%, highest quartile: 16.0%, p < 0.001) and ICU admission (35.2%, 19.9%, p < 0.001). After adjusting for age, sex, race, and comorbidities, higher neighborhood income ($10,000 increase) remained a significant negative predictor for IMV (OR: 0.95 (95% CI 0.91, 0.99), p = 0.02) and ICU admission (OR: 0.92 (95% CI 0.89, 0.96), p < 0.001).ConclusionsNeighborhood disadvantage, which is closely associated with race, is a predictor of poor clinical outcomes in COVID-19. Measures of neighborhood disadvantage should be used to inform policies that aim to reduce COVID-19 disparities in the Black community.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-020-06527-1.KEY WORDS: COVID-19, disparities, disadvantage, socioeconomic status, race