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

Background To limit the spread of SARS-CoV-2, an evidence-based understanding of the symptoms is critical to inform guidelines for quarantining and testing. The most common features are purported to be fever and a new persistent cough, although the global prevalence of these symptoms remains unclear. The aim of this systematic review is to determine the prevalence of symptoms associated with COVID-19 worldwide. Methods We searched PubMed, Embase, CINAHL, AMED, medRxiv and bioRxiv on 5th April 2020 for studies of adults (>16 years) with laboratory test confirmed COVID-19. No language or publication status restrictions were applied. Data were independently extracted by two review authors into standardised forms. All datapoints were independently checked by three other review authors. A random-effects model for pooling of binomial data was applied to estimate the prevalence of symptoms, subgrouping estimates by country. I2 was used to assess inter-study heterogeneity. Results Of 851 unique citations, 148 articles were included which comprised 24,410 adults with confirmed COVID-19 from 9 countries. The most prevalent symptoms were fever (78% [95% CI 75%-81%]; 138 studies, 21,701 patients; I2 94%), a cough (57% [95% CI 54%-60%]; 138 studies, 21,682 patients; I2 94%) and fatigue (31% [95% CI 27%-35%]; 78 studies, 13,385 patients; I2 95%). Overall, 19% of hospitalised patients required non-invasive ventilation (44 studies, 6,513 patients), 17% required intensive care (33 studies, 7504 patients), 9% required invasive ventilation (45 studies, 6933 patients) and 2% required extra-corporeal membrane oxygenation (12 studies, 1,486 patients). The mortality rate was 7% (73 studies, 10,402 patients). Conclusions We confirm that fever and cough are the most prevalent symptoms of adults infected by SARS-CoV-2. However, there is a large proportion of infected adults which symptoms-alone do not identify.

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The Prevalence of Symptoms in 24,410 Adults Infected by the Novel Coronavirus (SARS-CoV-2;COVID-19): A Systematic Review and Meta-Analysis of 148 Studies from 9 Countries

Background Currently, the epidemic of coronavirus disease 2019 (COVID-19) has begun to spread worldwide. We aim to explore reliable evidence for the diagnosis and treatment of the COVID-19 by analyzing all the published studies by Chinese scholars on the clinical and imaging features in novel coronavirus pneumonia caused by SARS-CoV-2. Methods We searched five medical databases including two Chinese and three English databases for all published articles on COVID-19 since the outbreak. A random-effects model was designed, and the imaging and clinical data from all studies were collected for meta-analysis. Results Overall, 31 articles and 46 959 patients were included, including 10 English articles and 21 Chinese articles. The results of meta-analysis showed that the most common clinical manifestations were fever (87.3%; 0.838-0.909), cough (58.1%; 0.502-0.660), dyspnea (38.3%; 0.246-0.520), muscle soreness or fatigue (35.5%; 0.253-0.456), and chest distress (31.2%; -0.024 to 0.648). The main imaging findings were bilateral pneumonia (75.7%; 0.639-0.871) and ground-glass opacification (69.9%; 0.602-0.796). Among the patients, the incidence that required intensive care unit (ICU) was (29.3%; 0.190-0.395), the incidence with acute respiratory distress syndrome was (28.8%; 0.147-0.429), the incidence with multiple organ dysfunction syndrome was (8.5%; -0.008 to 0.179), and the case fatality rate of patients with COVID-19 was (6.8%; 0.044-0.093). Conclusion COVID-19 is a new clinical infectious disease that mainly causes bilateral pneumonia and lung function deteriorates rapidly. Nearly a third of patients need to be admitted to the ICU, and patients are likely to present respiratory failure or even death.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmv.25822

Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2: A systematic review and meta-analysis.

The spectrum of neurological involvement in COVID-19 is not thoroughly understood. To the best of our knowledge, no systematic review with meta-analysis and a sub-group comparison between severe and non-severe cases has been published. The aim of this study is to assess the frequency of neurological manifestations and complications, identify the neurodiagnostic findings, and compare these aspects between severe and non-severe COVID-19 cases. A systematic search of PubMed, Scopus, EBSCO, Web of Science, and Google Scholar databases was conducted for studies published between the 1st of January 2020 and 22nd of April 2020. In addition, we scanned the bibliography of included studies to identify other potentially eligible studies. The criteria for eligibility included studies published in English language (or translated to English), those involving patients with COVID-19 of all age groups, and reporting neurological findings. Data were extracted from eligible studies. Meta-analyses were conducted using comprehensive meta-analysis software. Random-effects model was used to calculate the pooled percentages and means with their 95% confidence intervals (CIs). Sensitivity analysis was performed to assess the effect of individual studies on the summary estimate. A subgroup analysis was conducted according to severity. The main outcomes of the study were to identify the frequency and nature of neurological manifestations and complications, and the neuro-diagnostic findings in COVID-19 patients. 44 articles were included with a pooled sample size of 13,480 patients. The mean age was 50.3 years and 53% were males. The most common neurological manifestations were: Myalgia (22.2, 95% CI, 17.2 to 28.1%), taste impairment (19.6, 95% CI, 3.8 to 60.1%), smell impairment (18.3, 95% CI, 15.4 to 76.2%), headache (12.1, 95% CI, 9.1 to 15.8%), dizziness (11.3, 95% CI, 8.5 to 15.0%), and encephalopathy (9.4, 95% CI, 2.8 to 26.6%). Nearly 2.5% (95% CI, 1 to 6.1%) of patients had acute cerebrovascular diseases (CVD). Myalgia, elevated CK and LDH, and acute CVD were significantly more common in severe cases. Moreover, 20 case reports were assessed qualitatively, and their data presented separately. Neurological involvement is common in COVID-19 patients. Early recognition and vigilance of such involvement might impact their overall outcomes.

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Neurological manifestations and complications of coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis.

Meta-analyses have indicated that individuals with type 1 or type 2 diabetes are at increased risk of suffering a severe form of COVID-19 and have a higher mortality rate than the non-diabetic population Patients with diabetes have chronic, low-level systemic inflammation, which results in global cellular dysfunction underlying the wide variety of symptoms associated with the disease, including an increased risk of respiratory infection While the increased severity of COVID-19 amongst patients with diabetes is not yet fully understood, the common features associated with both diseases are dysregulated immune and inflammatory responses An additional key player in COVID-19 is the enzyme, angiotensin-converting enzyme 2 (ACE2), which is essential for adhesion and uptake of virus into cells prior to replication Changes to the expression of ACE2 in diabetes have been documented, but they vary across different organs and the importance of such changes on COVID-19 severity are still under investigation This review will examine and summarise existing data on how immune and inflammatory processes interplay with the pathogenesis of COVID-19, with a particular focus on the impacts that diabetes, endothelial dysfunction and the expression dynamics of ACE2 have on the disease severity

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Why Is COVID-19 More Severe in Patients With Diabetes? The Role of Angiotensin-Converting Enzyme 2, Endothelial Dysfunction and the Immunoinflammatory System

The purpose of our studies was to systematically assess the accuracy and clinical value of plasma calcitonin in patients with liver failure complicated with bacterial infection. In this study, we included prospective observational studies or randomized controlled trials on PCT. The quality of the studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Heterogeneity, pooled diagnostic odds ratio (DOR), pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, the area under the summary receiver operating characteristic curve (SROC), and metaregression analysis were performed using Stata16.0 software. Consequently, the studies revealed substantial heterogeneity (I2 = 96, 95% confidence interval (95% CI) = 94–99). The results of meta-analysis using random effect models suggested that the combined DOR was 10.67 (95% CI = 3.73–30.53). In addition, the threshold effect analysis showed that the threshold effect was 0.23 and the correlation coefficient was −0.48, indicating that there was no threshold effect. In the forest map, the DOR of each study and the combined DOR are not distributed along the same line, and Q = 2.2 × 1014, . Furthermore, the metaregression analysis of PCT study design, bacterial infection site, and mean age displayed that the values were >0.05. The combined sensitivity was 0.77 (95% CI = 0.54–0.90), the combined specificity was 0.76 (95% CI = 0.70–0.82), the combined positive likelihood ratio was 3.25 (95% CI = 2.33–4.52), the combined negative likelihood ratio was 0.30 (95% CI = 0.14–0.67), and the combined AUC was 0.80 (95% CI = 0.76–0.83). In conclusion, PCT has moderate diagnostic value for adult liver failure complicated with bacterial infection, and it is a better auxiliary diagnostic index for liver failure with bacterial infection. However, the results of procalcitonin must be carefully interpreted combined with medical history, physical examination, and microbiological assessment.

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Diagnostic Accuracy of Procalcitonin for Bacterial Infection in Liver Failure: A Meta-Analysis.

Background: 2019 novel coronavirus infection is high epidemical in China from January 2020 It is very important to detect it rapidly because of its high infect

The Epidemiological and Clinical Characteristics of 2019 Novel Coronavirus Infection in Changsha, China

<jats:p>To analyze the risk factors of invasive pulmonary fungal infections in patients with HBV-ACL, the clinical data and risk factors of 60 patients with HBV-ACLF complicated IPFI were analyzed retrospectively including clinical parameters, broad-spectrum antibiotics usage, neutropenia, invasive medical manipulations, serum total bilirubin, international normalized ratio (INR), and MELD scores were compared with non-IPFI. Risk factors were analyzed using mathematical tools. Candida species and Aspergillus were detected as the most prominent fungal strains (61.11% and 33.33%, respectively). The risk factors included prolong broad-spectrum antibiotic usage <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>4.362</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.008</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>, neutropenia <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>3.288</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.007</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>, invasive procedures <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>3.263</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.010</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>, serum total bilirubin <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>1.006</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.011</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>, INR <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M5\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>2.101</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.007</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>, and MELD scores <jats:inline-formula>\n                     <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M6\">\n                        <mfenced open=\"(\" close=\")\">\n                           <mrow>\n                              <mtext>OR</mtext>\n                              <mo>=</mo>\n                              <mn>1.074</mn>\n                              <mo>,</mo>\n                              <mi>P</mi>\n                              <mo>=</mo>\n                              <mn>0.008</mn>\n                           </mrow>\n                        </mfenced>\n                     </math>\n                  </jats:inline-formula>. Candida is the main IPFI strains in patients with HBV-ACLF. Broad-spectrum antibiotics usage, neutropenia, invasive manipulations, and the severity of ACLF might be risk factors for IPFI in patients with HBV-ACLF.</jats:p>

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Xinchun He

Papers

Diagnostic Accuracy of Procalcitonin for Bacterial Infection in Liver Failure: A Meta-Analysis.

The Epidemiological and Clinical Characteristics of 2019 Novel Coronavirus Infection in Changsha, China

Risk Factors of Invasive Pulmonary Fungal Infections in Patients with Hepatitis B Virus Related Acute-on-Chronic Liver Failure