A cross-sectional comparison of epidemiological and clinical features of patients with coronavirus disease (COVID-19) in Wuhan and outside Wuhan, China

Lei, Ziying; Cao, Huijuan; Jie, Yusheng; Huang, Zheping; Guo, Xiaoyan; Chen, Junfeng; Peng, Liang; Cao, Hong; Dai, Xiaoling; Liu, Jing; Li, Xuejun; Zhu, Jianyun; Xu, Wenxiong; Chen, Dabiao; Gao, Zhiliang; He, Jian; Li, Bing

doi:10.1016/j.tmaid.2020.101664

Cited by 69 publications

(58 citation statements)

References 26 publications

(30 reference statements)

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“…Ninety‐two articles (of which four included pregnant patients) reported adult patients infected with SARS‐CoV‐2. Eleven articles included paediatric population, and four articles reported both adults and children infected with SARS‐CoV‐2 2,7,14‐118 . (Tables S1, S2 and S3) A total of 20 874 patients were included, of which 38 were pregnant patients, 395 were paediatric patients and the rest were adult patients.…”

Section: Resultsmentioning

confidence: 99%

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Systematic review with meta‐analysis: liver manifestations and outcomes in COVID‐19

Kulkarni

Kumar

Tevethia

et al. 2020

Aliment Pharmacol Ther

219

310

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Summary Background The incidence of elevated liver chemistries and the presence of pre‐existing chronic liver disease (CLD) have been variably reported in COVID‐19. Aims To assess the prevalence of CLD, the incidence of elevated liver chemistries and the outcomes of patients with and without underlying CLD/elevated liver chemistries in COVID‐19. Methods A comprehensive search of electronic databases from 1 December 2019 to 24 April 2020 was done. We included studies reporting underlying CLD or elevated liver chemistries and patient outcomes in COVID‐19. Results 107 articles (n = 20 874 patients) were included for the systematic review. The pooled prevalence of underlying CLD was 3.6% (95% CI, 2.5‐5.1) among the 15 407 COVID‐19 patients. The pooled incidence of elevated liver chemistries in COVID‐19 was 23.1% (19.3‐27.3) at initial presentation. Additionally, 24.4% (13.5‐40) developed elevated liver chemistries during the illness. The pooled incidence of drug‐induced liver injury was 25.4% (14.2‐41.4). The pooled prevalence of CLD among 1587 severely infected patients was 3.9% (3%‐5.2%). The odds of developing severe COVID‐19 in CLD patients was 0.81 (0.31‐2.09; P = 0.67) compared to non‐CLD patients. COVID‐19 patients with elevated liver chemistries had increased risk of mortality (OR‐3.46 [2.42‐4.95, P < 0.001]) and severe disease (OR‐2.87 [95% CI, 2.29‐3.6, P < 0.001]) compared to patients without elevated liver chemistries. Conclusions Elevated liver chemistries are common at presentation and during COVID‐19. The severity of elevated liver chemistries correlates with the outcome of COVID‐19. The presence of CLD does not alter the outcome of COVID‐19. Further studies are needed to analyse the outcomes of compensated and decompensated liver disease.

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Section: Resultsmentioning

confidence: 99%

“…Seventy‐six articles, including 13 141 patients, described elevated liver chemistries at initial presentation 7,14‐34,46,47,49‐52,54‐75,77‐84,86,88‐93,102‐112 . The incidence of elevated liver chemistries varied from 1.1% to 68% in COVID‐19 patients 84,89 .…”

Section: Resultsmentioning

confidence: 99%

Systematic review with meta‐analysis: liver manifestations and outcomes in COVID‐19

Kulkarni

Kumar

Tevethia

et al. 2020

Aliment Pharmacol Ther

219

310

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“…The lack of adequate medical resources became already evident in some developed countries and is more dramatic in the developing ones. It has been reported that in Guangzhou, China, where all patients with mild and moderate COVID-19 receive appropriate care and treatment at an early stage of the illness, their prognosis is better than that for patients in Wuhan, where they are more likely to be admitted to ICU and succumb to the disease (5). The difference between these two cities underscores the importance of appropriate care and treatment for early mild cases, particularly for patients at high risk of disease progression.…”

Section: Discussionmentioning

confidence: 99%

“…It has been reported that patients in Guangzhou, China, had a better prognosis than in Wuhan. Patients in Wuhan were more likely to be admitted to an ICU and had higher mortality (5). This difference highlights the importance of appropriate care and treatment in early mild cases, especially in patients at high risk of disease progression.…”

Section: Introductionmentioning

confidence: 96%

A Composite Index Predicts Disease Progression in Early Stages of COVID-19: a Propensity Score-matched Cohort Study

et al. 2020

Preprint

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Background: Thus far, studies on COVID-19 have focused on the epidemiology of the disease and clinical characteristics of patients (14-19), as well as on the risk factors associated with mortality during hospitalization in critical COVID-19 cases. However, no research has been performed on the prediction of progression in patients in the early stages of the disease. The aim of this work was to identify the early predictors of COVID-19 progression.Methods: The study included 338 patients with COVID-19 treated at two hospitals in Wuhan, Chian, from December, 2019 to March, 2020. Predictors of the progression of COVID-19 from mild to severe stages were selected by the logistic regression analysis. The predictive accuracy was evaluated further in the propensity score-matched cohort.Results: COVID-19 progression to severe and critical stages was confirmed in 78(23.1%) patients. The average value of the neutrophil-to-lymphocyte ratio (NLR) was higher in patients in the disease progression group than in the improvement group. Multivariable logistic regression analysis revealed that elevated NLR, LDH, and IL-10, were independent predictors of disease progression. The optimal cut-off value of NLR for predicting the progression of COVID-19 was 3.75. In the propensity score-matched cohort, NLR ≥ 3.75 was still an independent predictor of COVID-19 progression after multivariate analysis.Conclusions: The performed analysis demonstrates that NLR qualiﬁes as an independent predictor of disease progression in COVID-19 patients at the early stage of the disease. The combined evaluation of NLR and LDH improved the accuracy of the prediction of COVID-19 progression. Assessment of predictors might facilitate early identification of COVID-19 patients at high risk for disease progression and ensure timely administration of appropriate treatment to prevent mild cases from becoming severe.

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“…Comparisons of COVID-19 epidemics among countries have been discussed in some articles [5][6][7]. The assumption of homogeneity of variance should be preliminarily ensured for the comparison of groups [8][9][10].…”

Section: Comparisons Of Covid-19 Epidemics and The Limitationsmentioning

confidence: 99%

Comparison of COVID-19 Patterns Between Severely-Struck Italy and the Rest of the Worlds: An Observational Study

Jen

Yeh

Lin³

et al. 2020

Preprint

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Background The country of Italy was placed on lockdown when the number of cases of COVID-19 increased exponentially. It is of great concern which countries/regions would have the most similar patterns to Italy and the comparison of patterns, assuming homogeneity of variance within datasets, among regions worldwide, became necessary. There were no results in past literature regarding the identification of COVID-19 patterns among countries/regions. We were therefore motivated to propose an appropriate mathematic method, using a specific country/region (e.g., Italy), for example, in detecting similar patterns at the respective peak of the outbreak. A visual display highlighting COVID-19 patterns was proposed in this study using vector mathematics.Methods We downloaded COVID-19 outbreak numbers with confirmed cases in countries/regions on a daily basis from the Github website. The top peak point was identified for each country/region. Next, thirteen-time points were assigned before and after the inflection point. COVID-19 patterns were assessed by inspecting both similarity and distance using angle(or cosine theta in trigonometric function) and Chi-square statistics. Two sets of data on confirmed cases, one based on cases per 100,000 population and the other does not, were compared using rankings as well as four quadrants divided by similarity and distance. An app was developed to display regions with similar COVID-19 patterns to the selected country.Results The top four countries presenting with the most similar COVID-19 patterns to Italy were Switzerland, Norway, Iceland, and Luxembourg with Chi-square statistics per one freedom degree at 0.12, 0.37, 0.58, and 0.80, respectively, based on a population of 100,000. Visualizations with four quadrants and world map were shown on Google Maps. Rank correlation in rankings was − 0.03 between two sets of confirmed cases with and without using the basis of cases per population of 100,000.Conclusion We proposed and demonstrated a method using both criteria of similarity and distance from vectors in mathematics to identify countries that are most similar to Italy in terms of the pattern at the peak of the outbreak. The app was developed to display countries/regions with the most similar COVID-19 patterns to the targeted country/region using a dashboard laid on Google Maps. This method can be generalized and applied to study other countries/regions for the current pandemic and other past infectious disease in history.

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A cross-sectional comparison of epidemiological and clinical features of patients with coronavirus disease (COVID-19) in Wuhan and outside Wuhan, China

Cited by 69 publications

References 26 publications

Systematic review with meta‐analysis: liver manifestations and outcomes in COVID‐19

Systematic review with meta‐analysis: liver manifestations and outcomes in COVID‐19

A Composite Index Predicts Disease Progression in Early Stages of COVID-19: a Propensity Score-matched Cohort Study

Comparison of COVID-19 Patterns Between Severely-Struck Italy and the Rest of the Worlds: An Observational Study

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