Dataset Information

CT characteristics and diagnostic value of COVID-19 in pregnancy.

ABSTRACT: OBJECTIVE:To investigate the computed tomography (CT) characteristics and diagnostic value of novel coronavirus pneumonia (NCP or COVID-19) in pregnancy. METHODS:This study included ten pregnant women infected with COVID-19, treated in the Zhongnan Hospital of Wuhan University from January 20, 2020 to February 6, 2020. Clinical and chest CT data were collected and clinical symptoms, laboratory indicators, and CT images were analyzed to explore CT characteristics and diagnostic value for COVID-19 during pregnancy. RESULTS:Laboratory examination showed that white blood cell count was normal in nine patients, and slightly higher in one patient (10.23 × 109). The lymphocyte ratio decreased in two patients by 12% and 14%, respectively. The levels of C-reactive protein was elevated in seven patients (range, 21.16-60.3 mg/L) and the levels of D-dimer was increased in eight patients (range, 507-2141 ng/mL). Six patients had low levels of total protein (range, 35.3-56.5 mg/L). Two patients showed small patchy ground glass opacity (GGO) involving single lung, while eight patients showed multilobe GGO in both the lungs, with partial consolidation. Peripheral and non-peripheral lesion distributions were seen in ten (100%) and four (40%) patients, respectively. There were four patients who had signs of intra-bronchial air-bronchogram, six patients had small bilateral pleural effusions, while none had lymphadenopathy. Dynamic observations were performed in four patients after COVID-19 treatment. Among these four patients, one patient showed normal on the initial examination, and new lesions were observed after 3 days; 1 patient showed progression after 7 days of treatment, with expansion of the lesion area; and the other 2 patients showed improvement after 14 days of treatment, with reduction in the density and area of lesions and appearance of linear opacity. CONCLUSIONS:The CT characteristics of COVID-19 in pregnancy were mainly observed in early and progressive stages, and multiple new lesions were common. And there were consolidations of varying sizes and degrees within the lesion. Moreover, the original ground glass lesions could be fused or partially absorbed. Six patients had small bilateral pleural effusion. In summary, CT scans can play an important role in early screening, dynamic observation, and efficacy evaluation of suspected or confirmed cases of pregnant women with COVID-19.

SUBMITTER: Gong X

PROVIDER: S-EPMC7331988 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CT characteristics and diagnostic value of COVID-19 in pregnancy.

Gong XiaoMing X Song Lu L Li Hang H Li Li L Jin Wei W Yu KaiHu K Zhang Xiaochun X Li Hongjun H Ke HengNing H Lu ZhiYan Z

PloS one 20200702 7

<h4>Objective</h4>To investigate the computed tomography (CT) characteristics and diagnostic value of novel coronavirus pneumonia (NCP or COVID-19) in pregnancy.<h4>Methods</h4>This study included ten pregnant women infected with COVID-19, treated in the Zhongnan Hospital of Wuhan University from January 20, 2020 to February 6, 2020. Clinical and chest CT data were collected and clinical symptoms, laboratory indicators, and CT images were analyzed to explore CT characteristics and diagnostic val ...[more]

PMID: 32614854

Similar Datasets

Project description:ObjectiveTo explore the value of CT texture analysis (CTTA) for determining coronavirus disease 2019 (COVID-19) severity.MethodsThe clinical and CT data of 81 patients with COVID-19 were retrospectively analyzed. The texture features were extracted using LK2.1. The two-sample t test or Mann-Whitney U test was used to find the significant features. Minimum redundancy and maximum relevance (MRMR) method was performed to find the features with maximum correlation and minimum redundancy. These features were then used to construct a radiomics texture model to discriminate the severe patients using multivariate logistic regression method. Besides, a clinical model was also built. ROC analyses were conducted to evaluate the performance of two models. The correlations of clinical features and textural features were analyzed using the Spearman correlation analysis.ResultsOf the total cases included, 60 were common and 21 were severe. (1) For textural features, 20 radiomics features selected by MRMR showed good performance in discriminating the two groups (AUC > 70%). (2) For clinical features, chi-square tests or Mann-Whitney U tests identified 16 clinical features as significant, and 12 were discriminative (p < 0.05) between two groups analyzed by univariate logistic analysis. Of these, 10 had an AUC > 70%. (3) Prediction models for textural features and clinical features were established, and both showed high predictive accuracy. The AUC values of textural features and clinical features were 0.93 (0.86-1.00) and 0.95 (0.95-0.99), respectively. (4) The Spearman correlation analysis showed that most textural and clinical features had above-moderate correlations with disease severity (> 0.4).ConclusionTexture analysis can provide reliable and objective information for differential diagnosis of COVID-19.Key points• CT texture analysis can well differentiate common and severe COVID-19 patients. • Some textural features showed above-moderate correlations with clinical factors. • CT texture analysis can provide useful information to judge the severity of COVID-19.

Project description:INTRODUCTION:Pulmonary opacities in COVID-19 increase throughout the illness and peak after ten days. The radiological literature mainly focuses on CT findings. The purpose of this study was to assess the diagnostic and prognostic value of chest radiographs (CXR) for coronavirus disease 2019 (COVID-19) at presentation. METHODS:We retrospectively identified consecutive reverse transcription polymerase reaction-confirmed COVID-19 patients (n = 104, 75% men) and patients (n = 75, 51% men) with repeated negative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests. Two radiologists blindly and independently reviewed the CXRs, documented findings, assigned radiographic assessment of lung edema (RALE) scores, and predicted the patients' COVID-19 status. We calculated interobserver reliability. The score use for diagnosis and prognosis of COVID-19 was evaluated with the area under the receiver operating characteristic curve. RESULTS:The overall RALE score failed to identify COVID-19 patients at presentation. However, the score was inversely correlated with a COVID-19 diagnosis within ?2 days, and a positive correlation was found six days after symptom onset.Interobserver agreement with regard to separating normal from abnormal CXRs was moderate (k = 0.408) with low specificity (25% and 27%). Definite pleural effusion had almost perfect agreement (k = 0.833) and substantially reduced the odds of a COVID-19 diagnosis. Disease distribution and experts' opinion on COVID-19 status had only fair interobserver agreement. The RALE score interobserver reliability was moderate to good (intraclass correlation coefficient = 0.745). A high RALE score predicted a poor outcome (intensive care unit hospitalization, intubation, or death) in COVID-19 patients; a score of ?5 substantially increased the odds of having a poor outcome. CONCLUSION:Chest radiography was found not to be a valid diagnostic tool for COVID-19, as normal or near-normal CXRs are more likely early in the disease course. Pleural effusions at presentation suggest a diagnosis other than COVID-19. More extensive lung opacities at presentation are associated with poor outcome in COVID-19 patients. Thus, patients with more than minimal opacities should be monitored closely for clinical deterioration. This clinical application of CXR is its greatest strength in COVID-19 as it impacts patient care.

Project description:BackgroundTo date, several types of laboratory tests for coronavirus disease 2019 (COVID-19) diagnosis have been developed. However, the clinical importance of serum severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid antigen (N-Ag) remains to be fully elucidated. In this study, we sought to investigate the value of serum SARS-CoV-2 N-Ag for COVID-19 diagnosis and to analyze N-Ag characteristics in COVID-19 individuals.MethodsSerum samples collected from 215 COVID-19 patients and 65 non-COVID-19 individuals were used to quantitatively detect N-Ag via chemiluminescent immunoassay according to the manufacturer's instructions.ResultsThe sensitivity and specificity of the N-Ag assay were 64.75% (95% confidence interval (95% CI) [55.94-72.66%]) and 100% (95% CI [93.05-100.00%]), respectively, according to the cut-off value recommended by the manufacturer. The receiver operating characteristic (ROC) curve showed a sensitivity of 100.00% (95% CI [94.42-100.00%]) and a specificity of 71.31% (95% CI [62.73-78.59%]). The positive rates and levels of serum SARS-CoV-2 N-Ag were not related to sex, comorbidity status or disease severity of COVID-19 (all P < 0.001). Compared with RT‒PCR, there was a lower positive rate of serum N-Ag for acute COVID-19 patients (P < 0.001). The positive rate and levels of serum SARS-CoV-2 N-Ag in acute patients were significantly higher than those in convalescent patients (all P < 0.001). In addition, the positive rate of serum SARS-CoV-2 N-Ag in acute COVID-19 patients was higher than that of serum antibodies (IgM, IgG, IgA and neutralizing antibodies (Nab)) against SARS-CoV-2 (all P < 0.001). However, the positive rate of serum SARS-CoV-2 N-Ag in convalescent COVID-19 patients was significantly lower than that of antibodies (all P < 0.001).ConclusionSerum N-Ag can be used as a biomarker for early COVID-19 diagnosis based on appropriate cut-off values. In addition, our study also demonstrated the relationship between serum N-Ag and clinical characteristics.

Project description:Background: Since December 2019, Coronavirus disease 2019 (COVID-19) has emerged as an international pandemic. COVID-19 patients with myocardial injury might need special attention. However, understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID-19 patients. Methods: This retrospective, single-center study finally included 304 hospitalized COVID-19 cases confirmed by real-time RT-PCR from January 11 to March 25, 2020. Myocardial injury was determined by serum high-sensitivity troponin I (Hs-TnI). The primary endpoint was COVID-19 associated mortality. Results: Of 304 COVID-19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID-19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C-reactive protein (CRP, median, 84.9 vs 28.5 mg/L, p<0.001), procalcitonin levels (median, 0.29 vs 0.06 ng/ml, p<0.001), inflammatory and immune response markers; more frequent need for noninvasive ventilation, invasive mechanical ventilation; and was associated with higher mortality incidence (hazard ratio, HR=7.02, 95% confidence interval, CI, 4.45-11.08, p<0.001) than those without myocardial injury. Myocardial injury (HR=4.55, 95% CI, 2.49-8.31, p<0.001), senior age, CRP levels, and novel coronavirus pneumonia (NCP) types on admission were independent predictors to mortality in COVID-19 patients. Conclusions: COVID patients with myocardial injury on admission is associated with more severe clinical presentation and biomarkers. Myocardial injury and higher HsTNI are both strongest independent predictors to COVID related mortality after adjusting confounding factors. In addition, senior age, CRP levels and NCP types are also associated with mortality. Trial registration: Not applicable.

Dataset Information

CT characteristics and diagnostic value of COVID-19 in pregnancy.

Publications

CT characteristics and diagnostic value of COVID-19 in pregnancy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets