Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu

Zheng, Yongli; Xu, Hong; Yang, Ming; Zeng, Yilan; Chen, Hong; Liu, Ru; Li, Qingfeng; Zhang, Na; Wang, Dan

doi:10.1016/j.jcv.2020.104366

Cited by 164 publications

(166 citation statements)

References 9 publications

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“…High levels of two inflammatory markers, CRP and ESR, were found to be associated with the severity of COVID‐19 during hospitalization in this study, thus confirming earlier results 23,24 . Similar findings emerged for FDP and PT, which were confirmed by a previous report to be moderately or markedly elevated in all cases of COVID‐19 involving death 25,26 . Interestingly, differences in these indicators were not observed between severe and moderate COVID‐19 patients in the postdischarge recovery stages, except for total proteins.…”

Section: Discussionsupporting

confidence: 91%

A comparative study of the laboratory features of COVID‐19 and other viral pneumonias in the recovery stage

Guo-lian

Sun

et al. 2020

Clinical Laboratory Analysis

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Background Clinical recovery does not mean full recovery. It is necessary to explore the aftereffects of COVID‐19 in patients and compare the laboratory features of COVID‐19 and other viral pneumonias in the recovery stages. Methods Forty‐seven cases of COVID‐19 and 45 cases of other viral pneumonias (control) were included in this study. The laboratory parameters were compared between COVID‐19 and control patients as well as severe and moderate COVID‐19 patients from the clinical recovery stage to the 4 weeks postdischarge recovery stage. Results A higher RDW‐CV level and neutrophil percentage and lower levels of total proteins, lymphocytes, eosinophils, and MCH were found in COVID‐19 patients compared with those in controls from the clinical recovery to the postdischarge recovery stages. Further analysis showed that decreases in lymphocytes, total proteins, and SOD and elevations in neutrophils, FDP, CRP, and ESR were more common in severe than moderate cases of COVID‐19 during hospitalization; however, differences in these indicators, except total proteins, were not observed in the postdischarge recovery stages. Additionally, only 76.9% of COVID‐19 patients were positive for IgG antibodies against SARS‐CoV‐2 in the convalescence stage, and one patient that was negative for specific IgG was reinfected. Conclusions This study demonstrated that patients recovering from COVID‐19 might need better care than that patients with other viral pneumonias due to the possibility of having poor immunity and nutritional conditions. These findings provide new insights to improve the understanding of COVID‐19 and improve care for patients affected by these kinds of pandemics in the future.

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Section: Discussionsupporting

confidence: 91%

A comparative study of the laboratory features of COVID‐19 and other viral pneumonias in the recovery stage

Guo-lian

Sun

et al. 2020

Clinical Laboratory Analysis

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“…A smaller subset of patients in the data set had absolute lymphocyte subset counts for B cells and NK cells reported. For publications with median and IQR or range reported, the mean and standard deviation were extrapolated according to Wan et al (26) There is an apparent outlier in reported lymphocyte counts in one publication with increased total lymphocyte counts but decreased CD4+ and CD8+ T‐cells counts in critical vs. noncritical patients, and this outlier in lymphocyte count was removed from the data analysis (16). The mean cell counts in “mild/moderate” and “severe/critical” COVID‐19 groups reported in each publication are shown in Figure 1.…”

Section: Resultsmentioning

confidence: 99%

“…CD4+ and/or CD8+ T‐cell counts from COVID‐19 patients with different disease severity status were reported in all 20 publications, and 10 of them also included CD19+ B cell and CD16 + CD56+ NK cell counts. These 20 peer‐reviewed publications were selected for meta‐analysis in this brief report (6‐25).…”

Section: Methodsmentioning

confidence: 99%

Lymphocyte Subset Counts in COVID‐19 Patients: A Meta‐Analysis

et al. 2020

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A reduced peripheral blood absolute lymphocyte count with an elevated neutrophil count has been a consistent observation in hospitalized coronavirus disease 2019 (COVID‐19) patients. In this brief meta‐analysis, the reduction of lymphocyte subset counts in COVID‐19 patients was investigated across 20 peer‐reviewed studies meeting criteria for reporting lymphocyte subset counts and COVID‐19 disease severity. CD4+ T cell, CD8+ T cell, B cell, NK cell, and total lymphocyte cell counts all showed statistically significant reduction in patients with severe/critical COVID‐19 disease compared to mild/moderate disease. T‐cell subsets showed the largest standardized magnitude of change. In some studies, multivariate analysis has shown that CD4 and/or CD8 T‐cells counts are independently predictive of patient outcomes. © 2020 International Society for Advancement of Cytometry

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“…Nevertheless, most current epidemiological investigation studies based on individual data primarily focus on describing the characteristics of COVID-19 infections, such as mortality, age distribution and sex ratio. [9][10][11][12] Information about exposure behaviors and contacts is normally provided by unstructured reports; it is heavily time-consuming to extract useful information from these reports to construct disease transmission networks.…”

Section: Introductionmentioning

confidence: 99%

The construction and visualization of the transmission networks for COVID-19: A potential solution for contact tracing and assessments of epidemics

Luo

Pei-hua

et al. 2020

Preprint

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The WHO described coronavirus disease 2019 (COVID-19) as a pandemic due to the speed and scale of its transmission. Without effective interventions, the rapidly increasing number of COVID-19 cases would greatly increase the burden of clinical treatments. Identifying the transmission sources and pathways is of vital importance to block transmission and allocate limited public health resources. According to the relationships among cases, we constructed disease transmission network graphs for the COVID-19 epidemic through a visualization technique based on individual reports of epidemiological data. We proposed an analysis strategy of the transmission network with the epidemiological data in Tianjin and Chengdu. The transmission networks showed different transmission characteristics. In Tianjin, an imported case can produce an average of 2.9 secondary infections and ultimately produce up to 4 generations of infections, with a maximum of 6 cases generated before being identified. In Chengdu, 45 noninformative cases and 24 cases with vague exposure information made it difficult to provide accurate information by the transmission network. The proposed analysis framework of visualized transmission networks can trace the transmission source and contacts, assess the current situation of transmission and prevention, and provide evidence for the global response and control of the COVID-19 pandemic.

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Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu

Cited by 164 publications

References 9 publications

A comparative study of the laboratory features of COVID‐19 and other viral pneumonias in the recovery stage

A comparative study of the laboratory features of COVID‐19 and other viral pneumonias in the recovery stage

Lymphocyte Subset Counts in COVID‐19 Patients: A Meta‐Analysis

The construction and visualization of the transmission networks for COVID-19: A potential solution for contact tracing and assessments of epidemics

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