scholarly journals Clinical characteristics of imported and second-generation COVID-19 cases outside Wuhan, China: A multicenter retrospective study

2020 ◽  
Author(s):  
Puyu Shi ◽  
Guoxia Ren ◽  
Jun Yang ◽  
Zhiqiang Li ◽  
Shujiao Deng ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Hospital Admission ◽  
Symptom Onset ◽  
Lymphocyte Count ◽  
Clinical Characteristics ◽  
Second Generation ◽  
Discharge Rate ◽  
Ct Images ◽  
Chest Ct ◽  
Multicenter Cohort Study

AbstractBackgroundThe mortality of COVID-19 differs between countries and regions. By now, reports on COVID-19 are largely focused on first-generation cases. This study aimed to clarify the clinical characteristics of imported and second-generation cases.MethodsThis retrospective, multicenter cohort study included 134 confirmed COVID-19 cases from 9 cities outside Wuhan. Epidemiological, clinical and outcome data were extracted from medical records and were compared between severe and non-severe cases. We further profiled the dynamic laboratory findings of some patients.Results34.3% of the 134 patients were severe cases, and 11.2% had complications. As of March 7, 2020, 91.8% patients were discharged and one patient (0.7%) died. The median age was 46 years. The median interval from symptom onset to hospital admission was 4.5 (IQR 3-7) days. The median lymphocyte count was 1.1×109/L. Age, lymphocyte count, CRP, ESR, DBIL, LDH, HBDH showed difference between severe and no-severe cases (all P<0.05). Baseline lymphocyte count was higher in the survived patients than in the non-survivor case, and it increased as the condition improved, but declined sharply when death occurred. The IL-6 level displayed a downtrend in survivors, but rose very high in the death case. Pulmonary fibrosis was found on later chest CT images in 51.5% of the pneumonia cases.ConclusionImported and second-generation cases outside Wuhan had a better prognosis than initial cases in Wuhan. Lymphocyte count and IL-6 level could be used for evaluating prognosis. Pulmonary fibrosis as the sequelae of COVID-19 should be taken into account.SummaryImported and second-generation cases manifested less complications, lower fatality, and higher discharge rate than initial cases, which may be related to the shorter interval from symptom onset to hospital admission, younger age, and higher lymphocyte count of the imported and second-generation patients. Lymphocyte count and IL-6 level could be used as indicators for evaluating prognosis. Pulmonary fibrosis was found in later chest CT images in more than half of the pneumonia cases and should be taken into account.

scholarly journals Clinical characteristics of imported and second-generation COVID-19 cases outside Wuhan, China: A multicenter retrospective study

2020 ◽  
Author(s):  
Puyu Shi ◽  
Guoxia Ren ◽  
Jun Yang ◽  
Zhiqiang Li ◽  
Shujiao Deng ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Lymphocyte Count ◽  
Clinical Characteristics ◽  
First Generation ◽  
Second Generation ◽  
Outcome Data ◽  
Multicenter Cohort Study ◽  
Laboratory Findings ◽  
Reactive Protein ◽  
Very High

Abstract Background: The mortality of COVID-19 differs between countries and regions. By now, reports on COVID-19 are largely focused on first-generation cases. This study aimed to clarify the clinical characteristics of imported and second-generation cases. Methods : This retrospective, multicenter cohort study included 134 confirmed COVID-19 cases from 9 cities outside Wuhan. Epidemiological, clinical and outcome data were extracted from medical records and were compared between severe and non-severe cases. We further profiled the dynamic laboratory findings of some patients. Results : 34.3% of the 134 patients were severe cases, and 11.2% had complications. As of March 7, 2020, 91.8% patients were discharged and one patient (0.7%) died. Age, lymphocyte count, C-reactive protein, erythrocytes edimentation rate, direct bilirubin, lactate dehydrogenase, hydroxybutyrate dehydrogenase showed difference between severe and no-severe cases (all P<0.05). Baseline lymphocyte count was higher in the survived patients than in the non-survivor case, and it increased as the condition improved, but declined sharply when death occurred. The interleukin-6 level displayed a downtrend in survivors, but rose very high in the death case. Pulmonary fibrosis was found on later chest CT images in 51.5% of the pneumonia cases. Conclusion : Imported and second-generation cases outside Wuhan had a better prognosis than initial cases in Wuhan. Lymphocyte count and IL-6 level could be used for evaluating prognosis. Pulmonary fibrosis as the sequelae of COVID-19 should be taken into account.

scholarly journals Clinical characteristics of imported and second-generation coronavirus disease 2019 (COVID-19) cases in Shaanxi outside Wuhan, China: a multicentre retrospective study

2020 ◽  
Vol 148 ◽  
Author(s):  
Puyu Shi ◽  
Guoxia Ren ◽  
Jun Yang ◽  
Zhiqiang Li ◽  
Shujiao Deng ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Lymphocyte Count ◽  
Clinical Characteristics ◽  
Second Generation ◽  
C Reactive Protein ◽  
Laboratory Findings ◽  
Reactive Protein ◽  
Computed Tomography Images ◽  
Death Case ◽  
Very High

Abstract The mortality of coronavirus disease 2019 (COVID-19) differs between countries and regions. This study aimed to clarify the clinical characteristics of imported and second-generation cases in Shaanxi. This study included 134 COVID-19 cases in Shaanxi outside Wuhan. Clinical data were compared between severe and non-severe cases. We further profiled the dynamic laboratory findings of some patients. In total, 34.3% of the 134 patients were severe cases, 11.2% had complications. As of 7 March 2020, 91.8% patients were discharged and one patient (0.7%) died. Age, lymphocyte count, C-reactive protein, erythrocyte sedimentation rate, direct bilirubin, lactate dehydrogenase and hydroxybutyrate dehydrogenase showed difference between severe and no-severe cases (all P < 0.05). Baseline lymphocyte count was higher in survived patients than in non-survivor case, and it increased as the condition improved, but declined sharply when death occurred. The interleukin-6 (IL-6) level displayed a downtrend in survivors, but rose very high in the death case. Pulmonary fibrosis was found on later chest computed tomography images in 51.5% of the pneumonia cases. Imported and second-generation cases outside Wuhan had a better prognosis than initial cases in Wuhan. Lymphocyte count and IL-6 level could be used for evaluating prognosis. Pulmonary fibrosis as the sequelae of COVID-19 should be taken into account.

scholarly journals Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design For Prediction of Pulmonary Fibrosis Progression From Chest CT Images

2021 ◽  
Author(s):  
Alexander Wong ◽  
Jack Lu ◽  
Adam Dorfman ◽  
Paul McInnis ◽  
Mahmoud Famouri ◽  
...  
Keyword(s):  
Decision Making ◽  
Pulmonary Fibrosis ◽  
Network Design ◽  
Ct Images ◽  
Chest Ct ◽  
Correct Decision ◽  
Fibrosis Progression ◽  
Likelihood Score ◽  
Log Likelihood ◽  
Performance Validation

Abstract Background: Pulmonary fibrosis is a devastating chronic lung disease that causes irreparable lung tissue scarring and damage, resulting in progressive loss in lung capacity and has no known cure. A critical step in the treatment and management of pulmonary fibrosis is the assessment of lung function decline, with computed tomography (CT) imaging being a particularly effective method for determining the extent of lung damage caused by pulmonary fibrosis. Motivated by this, we introduce Fibrosis-Net, a deep convolutional neural network design tailored for the prediction of pulmonary fibrosis progression from chest CT images. More specifically, machine-driven design exploration was leveraged to determine a strong architectural design for CT lung analysis, upon which we build a customized network design tailored for predicting forced vital capacity (FVC) based on a patient's CT scan, initial spirometry measurement, and clinical metadata. Finally, we leverage an explainability-driven performance validation strategy to study the decision-making behaviour of Fibrosis-Net as to verify that predictions are based on relevant visual indicators in CT images.Results: Experiments using a patient cohort from the OSIC Pulmonary Fibrosis Progression Challenge showed that the proposed Fibrosis-Net is able to achieve a significantly higher modified Laplace Log Likelihood score than the winning solutions on the challenge. Furthermore, explainability-driven performance validation demonstrated that the proposed Fibrosis-Net exhibits correct decision-making behaviour by leveraging clinically-relevant visual indicators in CT images when making predictions on pulmonary fibrosis progress. Conclusion: Fibrosis-Net is able to achieve a significantly higher modified Laplace Log Likelihood score than the winning solutions on the OSIC Pulmonary Fibrosis Progression Challenge, and has been shown to exhibit correct decision-making behaviour when making predictions. Fibrosis-Net is available to the general public in an open-source and open access manner as part of the OpenMedAI initiative. While Fibrosis-Net is not yet a production-ready clinical assessment solution, we hope that its release will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon it.

scholarly journals The clinical characteristics of COVID-19: a retrospective analysis of 104 patients from the outbreak on board the Diamond Princess cruise ship in Japan

2020 ◽  
Author(s):  
Sakiko Tabata ◽  
Kazuo Imai ◽  
Shuichi Kawano ◽  
Mayu Ikeda ◽  
Tatsuya Kodama ◽  
...  
Keyword(s):  
Disease Progression ◽  
Symptom Onset ◽  
Clinical Characteristics ◽  
Serum Lactate ◽  
Chest Ct ◽  
Older Age ◽  
Cruise Ship ◽  
Radiological Findings ◽  
Novel Coronavirus ◽  
Observation Period

AbstractBackgroundThe ongoing outbreak of the coronavirus disease 2019 (COVID-19) is a global threat. Identification of markers for symptom onset and disease progression is a pressing issue. We compared the clinical features on admission among patients who were diagnosed with asymptomatic, mild, and severe COVID-19 at the end of observation.MethodsThis retrospective, single-center study included 104 patients with laboratory-confirmed COVID-19 from the mass infection on the Diamond Princess cruise ship from February 11 to February 25, 2020. Clinical records, laboratory data, and radiological findings were analyzed. Clinical outcomes were followed up until February 26, 2020. Clinical features on admission were compared among those with different disease severity at the end of observation. Univariate analysis identified factors associated with symptom onset and disease progression.FindingsThe median age was 68 years, and 54 patients were male. Briefly, 43, 41, and 20 patients on admission and 33, 43, and 28 patients at the end of observation had asymptomatic, mild, and severe COVID-19, respectively. Serum lactate hydrogenase levels were significantly higher in 10 patients who were asymptomatic on admission but developed symptomatic COVID-19 compared with 33 patients who remained asymptomatic throughout the observation period. Older age, consolidation on chest computed tomography, and lymphopenia on admission were more frequent in patients with severe COVID-19 than those with mild COVID-19 at the end of observation.InterpretationLactate dehydrogenase level is a potential predictor of symptom onset in COVID-19. Older age, consolidation on chest CT images, and lymphopenia might be risk factors for disease progression of COVID-19 and contribute to the clinical management.FundingNot applicable.Research in contextEvidence before this studyWe searched the PubMed database from its inception until March 1, 2020, for articles published in English using the keywords “novel coronavirus,” “2019 novel coronavirus,” “2019-nCoV,” “Severe acute respiratory syndrome coronavirus 2,” “SARS-CoV2,” “COVID-19,” “mass infection,” “herd infection,” “cruise ship,” “Diamond Princess,” “asymptomatic,” and “subclinical.” There were no published clinical studies featuring COVID-19 as a result of mass infection on board a cruise ship. We found published articles entitled “Characteristics of COVID-19 infection in Beijing” and “Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study,” which compared patients with asymptomatic, mild, and severe COVID-19. However, none of the studies described potential markers for symptom onset or disease progression in patients with COVID-19.Added value of this studyWe present the differences in clinical characteristics of 104 patients with laboratory-confirmed COVID-19 as a result of mass infection on the Diamond Princess cruise ship who were treated at Self-Defense Forces Central Hospital, Japan from February 11 to February 25, 2020. On admission, 43, 41, and 20 patients had asymptomatic, mild, and severe COVID-19, respectively, whereas 33, 43, and 28 patients were determined to have asymptomatic, mild, and severe COVID-19, respectively, at the end of observation. During the observation period, 10 of the 43 (23.3%) asymptomatic patients on admission developed symptoms of COVID-19. Conversely, eight of the 84 (9.5%) patients with asymptomatic and mild COVID-19 on admission developed severe disease during the observation period. The serum lactate dehydrogenase (LDH) levels were significantly higher in 10 patients who were initially asymptomatic on admission to the hospital and developed symptomatic COVID-19 during the observation period compared with 33 patients who remained asymptomatic throughout the observation period. The prevalence rates of consolidation on chest computed tomography (CT) images and lymphopenia were significantly higher in eight patients who developed severe COVID-19 during the observation period compared with the 76 patients with asymptomatic or mild disease at the end of the observation. Older age, consolidation on chest CT, and lymphopenia on admission were more frequent in patients with severe COVID-19 (n = 28) than those with mild COVID-19 (n = 43) at the end of observation. LDH level might be marker for symptom onset in patients with COVID-19, whereas older age, consolidation on chest CT imaging, and lymphopenia are potential risk factors for disease progression. The current report findings will contribute to the improvement of clinical management in patients with COVID-19.Implications of all the available evidenceSerum LDH level is a potential predictor of symptom onset of COVID-19, whereas older age, consolidation on chest CT imaging, and lymphopenia have potential utility as markers for disease progression.

COVID-19 pneumonia diagnosis using a simple 2D deep learning framework with a single chest CT image (Preprint)

2020 ◽  
Author(s):  
Jinseok Lee
Keyword(s):  
Deep Learning ◽  
Diagnostic Performance ◽  
Ct Images ◽  
Chest Ct ◽  
University Hospital ◽  
Detection Accuracy ◽  
Ct Image ◽  
Test Dataset ◽  
Learning Framework ◽  
Testing Dataset

BACKGROUND The coronavirus disease (COVID-19) has explosively spread worldwide since the beginning of 2020. According to a multinational consensus statement from the Fleischner Society, computed tomography (CT) can be used as a relevant screening tool owing to its higher sensitivity for detecting early pneumonic changes. However, physicians are extremely busy fighting COVID-19 in this era of worldwide crisis. Thus, it is crucial to accelerate the development of an artificial intelligence (AI) diagnostic tool to support physicians. OBJECTIVE We aimed to quickly develop an AI technique to diagnose COVID-19 pneumonia and differentiate it from non-COVID pneumonia and non-pneumonia diseases on CT. METHODS A simple 2D deep learning framework, named fast-track COVID-19 classification network (FCONet), was developed to diagnose COVID-19 pneumonia based on a single chest CT image. FCONet was developed by transfer learning, using one of the four state-of-art pre-trained deep learning models (VGG16, ResNet50, InceptionV3, or Xception) as a backbone. For training and testing of FCONet, we collected 3,993 chest CT images of patients with COVID-19 pneumonia, other pneumonia, and non-pneumonia diseases from Wonkwang University Hospital, Chonnam National University Hospital, and the Italian Society of Medical and Interventional Radiology public database. These CT images were split into a training and a testing set at a ratio of 8:2. For the test dataset, the diagnostic performance to diagnose COVID-19 pneumonia was compared among the four pre-trained FCONet models. In addition, we tested the FCONet models on an additional external testing dataset extracted from the embedded low-quality chest CT images of COVID-19 pneumonia in recently published papers. RESULTS Of the four pre-trained models of FCONet, the ResNet50 showed excellent diagnostic performance (sensitivity 99.58%, specificity 100%, and accuracy 99.87%) and outperformed the other three pre-trained models in testing dataset. In additional external test dataset using low-quality CT images, the detection accuracy of the ResNet50 model was the highest (96.97%), followed by Xception, InceptionV3, and VGG16 (90.71%, 89.38%, and 87.12%, respectively). CONCLUSIONS The FCONet, a simple 2D deep learning framework based on a single chest CT image, provides excellent diagnostic performance in detecting COVID-19 pneumonia. Based on our testing dataset, the ResNet50-based FCONet might be the best model, as it outperformed other FCONet models based on VGG16, Xception, and InceptionV3.

scholarly journals Clinical characteristics of inpatients with coronavirus disease 2019 (COVID-19) in Sichuan province

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wen Wang ◽  
Lei Chen ◽  
Qiao He ◽  
Mingqi Wang ◽  
Mei Liu ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Clinical Features ◽  
Medical Records ◽  
Clinical Characteristics ◽  
Sichuan Province ◽  
Chest Ct ◽  
Shortness Of Breath ◽  
Course Of Disease ◽  
West China ◽  
Radiologic Abnormality

Abstract Background The outbreak of COVID-19 has resulted in serious concerns in China and abroad. To investigate clinical features of confirmed and suspected patients with COVID-19 in west China, and to examine differences between severe versus non-severe patients. Methods Patients admitted for COVID-19 between January 21 and February 11 from fifteen hospitals in Sichuan Province, China were included. Experienced clinicians trained with methods abstracted data from medical records using pre-defined, pilot-tested forms. Clinical characteristics between severe and non-severe patients were compared. Results Of the 169 patients included, 147 were laboratory-confirmed, 22 were suspected. For confirmed cases, the most common symptoms from onset to admission were cough (70·7%), fever (70·5%) and sputum (33·3%), and the most common chest CT patterns were patchy or stripes shadowing (78·0%); throughout the course of disease, 19·0% had no fever, and 12·4% had no radiologic abnormality; twelve (8·2%) received mechanical ventilation, four (2·7%) were transferred to ICU, and no death occurred. Compared to non-severe cases, severe ones were more likely to have underlying comorbidities (62·5% vs 26·2%, P = 0·001), to present with cough (92·0% vs 66·4%, P = 0·02), sputum (60·0% vs 27·9%, P = 0·004) and shortness of breath (40·0% vs 8·2%, P <  0·0001), and to have more frequent lymphopenia (79·2% vs 43·7%, P = 0·003) and eosinopenia (84·2% vs 57·0%, P = 0·046). Conclusions The symptoms of patients in west China were relatively mild, and an appreciable proportion of infected cases had no fever, warranting special attention.

Impact of detecting plasma EGFR mutations with ultrasensitive liquid biopsy in outcomes of NSCLC patients treated with first- or second-generation EGFR-TKIs

2021 ◽  
pp. 1-13
Author(s):  
Oscar Arrieta ◽  
Juan-Manuel Hernández-Martínez ◽  
Edgar Montes-Servín ◽  
David Heredia ◽  
Andrés F. Cardona ◽  
...  
Keyword(s):  
Disease Progression ◽  
Clinical Characteristics ◽  
Detection Rate ◽  
Second Generation ◽  
Elevated Serum ◽  
Positive Finding ◽  
Response Evaluation ◽  
Mutational Status ◽  
Nsclc Patients ◽  
Egfr Tkis

BACKGROUND: Few trials have evaluated the utility of liquid biopsies to detect epidermal growth factor receptor mutations (EGFRm) at the time of response evaluation and its association with the clinical characteristics and outcomes of non-small-cell lung cancer (NSCLC) patients. OBJECTIVE: This study aimed to evaluate, in a real-world clinical setting, the prevalence of plasma EGFRm and its association with the clinical characteristics, response and survival outcomes of NSCLC patients under treatment with EGFR-tyrosine kinase inhibitors (EGFR-TKIs). METHODS: This observational study enrolled advanced or metastatic NSCLC patients, with confirmed tumor EGFRm, receiving treatment with first- or second-generation EGFR-TKIs. Blood samples for the detection of plasma EGFRm were collected at the time of response evaluation and processed using the Target Selector™ assay. The main outcomes were the detection rate of plasma EGFRm, median Progression-Free Survival (PFS) and Overall Survival (OS) according to plasma EGFR mutational status. RESULTS: Of 84 patients, 50 (59.5%) had an EGFRm detected in plasma. After a median follow-up of 21.1 months, 63 patients (75%) had disease progression. The detection rate of plasma EGFRm was significantly higher in patients with disease progression than in patients with partial response or stable disease (68.3% versus 33.3%; P< 0.01). PFS and OS were significantly longer in patients without plasma EGFRm than among patients with plasma EGFRm (14.3 months [95% CI, 9.25–19.39] vs 11.0 months [95% CI, 8.61–13.46]; P= 0.034) and (67.8 months [95% CI, 39.80–95.94] vs 32.0 months [95% CI, 17.12–46.93]; P= 0.006), respectively. A positive finding in LB was associated with the presence of ⩾ 3 more metastatic sites (P= 0.028), elevated serum carcinoembryonic (CEA) at disease progression (P= 0.015), and an increase in CEA with respect to baseline levels (P= 0.038). CONCLUSIONS: In NSCLC patients receiving EGFR-TKIs, the detection of plasma EGFRm at the time of tumor response evaluation is associated with poor clinical outcomes.

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