Analysis of clinical characteristics and laboratory findings of 95 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a retrospective analysis

Zhang, Gemin; Zhang, Jie; Wang, Bowen; Zhu, Xionglin; Wang, Qiang; Qiu, Shiming

doi:10.1186/s12931-020-01338-8

Cited by 264 publications

(167 citation statements)

References 12 publications

Supporting

Mentioning

142

Contrasting

Unclassified

Order By: Relevance

“…Some literature supported the hypothesis that a little known yet powerful function of neutrophils-the ability to form neutrophil extracellular traps-may contribute to organ damage and death in COVID-19 [19]. Previous studies showed neutrophil count was notably related to disease severity [20,21]. Neutrophil infiltration was noted in two recent reports on the pathological findings from autopsied COVID-19 patients [22,23].…”

Section: Discussionmentioning

confidence: 90%

Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters

Zhang

Chen

et al. 2020

Eur J Nucl Med Mol Imaging

View full text Add to dashboard Cite

Purpose To quantify the severity of 2019 novel coronavirus disease (COVID-19) on chest CT and to determine its relationship with laboratory parameters. Methods Patients with real-time fluorescence polymerase chain reaction (RT-PCR)-confirmed COVID-19 between January 01 and February 18, 2020, were included in this study. Laboratory parameters were retrospectively collected from medical records. Severity of lung changes on chest CT of early, progressive, peak, and absorption stages was scored according to the percentage of lung involvement (5 lobes, scores 1-5 for each lobe, range 0-20). Relationship between CT scores and laboratory parameters was evaluated by the Spearman rank correlation. The Bonferroni correction adjusted significance level was at 0.05/4 = 0.0125. Results A total of 84 patients (mean age, 47.8 ± 12.0 years [standard deviation]; age range, 24-80 years) were evaluated. The patients underwent a total of 339 chest CT scans with a median interval of 4 days (interquartile range, 3-5 days). Median chest CT scores peaked at 4 days after the beginning of treatment and then declined. CT score of the early stage was correlated with neutrophil count (r = 0.531, P = 0.011). CT score of the progressive stage was correlated with neutrophil count (r = 0.502, P < 0.001), white blood cell count (r = 0.414, P = 0.001), C-reactive protein (r = 0.511, P < 0.001), procalcitonin (r = 0.423, P = 0.004), and lactose dehydrogenase (r = 0.369, P = 0.010). However, CT scores of the peak and absorption stages were not correlated with any parameter (P > 0.0125). No sex difference occurred regarding CT score (P > 0.05). Conclusion Severity of lung abnormalities quantified on chest CT might correlate with laboratory parameters in the early and progressive stages. However, larger cohort studies are necessary.

show abstract

Section: Discussionmentioning

confidence: 90%

Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters

Zhang

Chen

et al. 2020

Eur J Nucl Med Mol Imaging

View full text Add to dashboard Cite

show abstract

“…At the beginning of December 2019, a new virus caused an increase in atypical pneumonia at the city of Wuhan in China. The virus was isolated, sequenced and identified as a new type of coronavirus [1]. The virus was called SARS-CoV-2 and the disease associated with that virus was called COVID-19 [2].…”

Section: Introductionmentioning

confidence: 99%

An SEIARD epidemic model for COVID-19 in Mexico: mathematical analysis and state-level forecast

León

Pérez

Ávila-Vales

2020

Preprint

View full text Add to dashboard Cite

We propose an SEIARD mathematical model to investigate the current outbreak of coronavirus disease in Mexico. Our model incorporates the asymptomatic infected individuals, who represent the majority of the infected population (with symptoms or not) and could play an important role in spreading the virus without any knowledge. We calculate the basic reproduction number (R 0 ) via the next-generation matrix method and estimate the per day infection, death and recovery rates. The local stability of the disease free equilibrium is established in terms of R 0 . A sensibility analysis is performed to determine the relative importance of the model parameters to the disease transmission. We calibrate the parameters of the SEIARD model to the reported number of infected cases and fatalities for several states in Mexico by minimizing the sum of squared errors and attempt to forecast the evolution of the outbreak until August 2020.

show abstract

“…Reducing mortality of critically ill patients with COVID‐19 needs early medical intervention, which requires emergency physicians to quickly select severe patients from a large number of patients 8–10 . Thus, rapid and effective assessment of these patients is a crucial task in the emergency department (ED).…”

mentioning

confidence: 99%

Comparing Rapid Scoring Systems in Mortality Prediction of Critically Ill Patients With Novel Coronavirus Disease

Qiu

2020

Academic Emergency Medicine

155

128

View full text Add to dashboard Cite

Objectives: Rapid and early severity-of-illness assessment appears to be important for critically ill patients with novel coronavirus disease . This study aimed to evaluate the performance of the rapid scoring system on admission of these patients.Methods: A total of 138 medical records of critically ill patients with COVID-19 were included in the study.Demographic and clinical characteristics on admission used for calculating Modified Early Warning Score (MEWS) and Rapid Emergency Medicine Score (REMS) and outcomes (survival or death) were collected for each case and extracted for analysis. All patients were divided into two age subgroups (<65 years and ≥65 years). The receiver operating characteristic (ROC) curve analyses were performed for overall patients and both subgroups.Results: The median [25th quartile, 75th quartile] of MEWS of survivors versus nonsurvivors were 1 [1, 2] and 2 [1, 3] and those of REMS were 5 [2, 6] and 7 [6, 10], respectively. In overall analysis, the area under the ROC curve for the REMS in predicting mortality was 0.833 (95% confidence interval [CI] = 0.737 to 0.928), higher than that of MEWS (0.677, 95% CI = 0.541 to 0.813). An optimal cutoff of REMS (≥6) had a sensitivity of 89.5%, a specificity of 69.8%, a positive predictive value of 39.5%, and a negative predictive value of 96.8%. In the analysis of subgroup of patients aged <65 years, the area under the ROC curve for the REMS in predicting mortality was 0.863 (95% CI = 0.743 to 0.941), higher than that of MEWS (0.603, 95% CI = 0.462 to 0.732). Conclusion:To our knowledge, this study was the first exploration on rapid scoring systems for critically ill patients with COVID-19. The REMS could provide emergency clinicians with an effective adjunct risk stratification tool for critically ill patients with COVID-19, especially for the patients aged <65 years. The effectiveness of REMS for screening these patients is attributed to its high negative predictive value.From the

show abstract

Analysis of clinical characteristics and laboratory findings of 95 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a retrospective analysis

Cited by 264 publications

References 12 publications

Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters

Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters

An SEIARD epidemic model for COVID-19 in Mexico: mathematical analysis and state-level forecast

Comparing Rapid Scoring Systems in Mortality Prediction of Critically Ill Patients With Novel Coronavirus Disease

Contact Info

Product

Resources

About