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1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323715

ABSTRACT

Objective: We aimed to describe the chest CT findings in sixty-seven patients infected by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Method and material: We retrospectively reviewed 67 patients hospitalized in Ruian People's Hospital. All the patients received the positive diagnosis of SARS-CoV-2 infection. The CT and clinical data were collected between January 23 rd , 2020 and February 10 th , 2020. The CT images were analyzed by the senior radiologists. Conclusion: There are 54 patients with positive CT findings and 13 patients with negative CT findings. The typical CT findings in hospitalized patients with SARS-CoV-2 infection were ground glass opacities (42/54), lesions located in the peripheral area (50/54), multiple lesions (46/54), and lesions located in the lower lobes (42/54). There were less typical CT findings, including air bronchogram (18/54), pleural thickening or pleural effusion (14/54), consolidation (12/54), lesions in the upper lobes (12/54), interlobular septal thickening (11/54), reversed halo sign (9/54), single lesion (8/54), air cavities (4/54), bronchial wall thickening (3/54), and intrathoracic lymph node enlargement (2/54).

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315568

ABSTRACT

Background: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pneumonia (COVID-19) with high sensitivity and popularity. Machine learning was adept in discovering intricate structures from CT images and achieved expert-level performance in medical image analysis. Methods: : An integrated machine learning framework on chest CT images for differentiating COVID-19 from general pneumonia (GP) was developed and validated. Seventy-three confirmed COVID-19 cases were consecutively enrolled together with twenty-seven confirmed general pneumonia patients from Ruian People’s Hospital, from January 2020 to March 2020. To accurately classify COVID-19, region of interest (ROI) delineation was implemented based on ground glass opacities (GGOs) before feature extraction. Then, 34 statistical texture features of COVID-19 and GP ROI images were extracted, including 13 gray level co-occurrence matrix (GLCM) features, 15 gray level-gradient co-occurrence matrix (GLGCM) features and 6 histogram features. High dimensional features impact the classification performance. Thus, ReliefF algorithm was leveraged to select features. The relevance of each features was the average weights calculated by ReliefF in n times. Features with relevance lager than the empirically set threshold T were selected. After feature selection, the optimal feature set along with 4 other selected feature combinations for comparison were applied to the ensemble of bagged tree (EBT) and four other machine learning classifiers including support vector machine (SVM), logistic regression (LR), decision tree (DT), and K-nearest neighbor with Minkowski distance equal weight (KNN) using 10-fold cross-validation. Results: and Conclusions: The classification accuracy (ACC), sensitivity (SEN), specificity (SPE) of our proposed method yield 94.16%, 88.62% and 100.00%, respectively. The area under the receiver operating characteristic curve (AUC) was 0.99. The experimental results indicate that the EBT algorithm with statistical textural features based on GGOs for differentiating COVID-19 from general pneumonia achieved high transferability, efficiency, specificity, sensitivity, and impressive accuracy, which is beneficial for inexperienced doctors to more accurately diagnose COVID-19 and essential for controlling the spread of the disease.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312495

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) is an emerging viral disease. Here, we reported the clinical features, management, and short-term outcomes of COVID-19 patients in Wenzhou, an area outside Wuhan. Methods: : Patients admitted to the Infectious Diseases Department of Ruian People's Hospital in Wenzhou, from January 21 to February 7, 2020, were recruited. Medical data on epidemiological history, demographics, clinical characteristics, laboratory tests, computerized tomography (CT) examination, treatment, and short-term outcomes were retrospectively reviewed. Blood biochemistry and routine tests were examined using standard methods and automatic machines. CT examination was performed again for several times during the hospitalization as necessary. Results: : A total of 67 confirmed COVID-19 cases were diagnosed;64 (95.4%) were common cases and three (4.5%) severe cases. The most common symptoms at admission were fever (86.6%), cough (77.6%), productive cough (52.2%), chest distress (17.9%), and sore throat (11.9%), followed by diarrhea (7.4%), headache (7.4%), shortness of breath (6.0%), dizziness (4.5%), muscular soreness (4.5%), and running nose (4.5%). Thirty patients (47.8%) had increased C-reactive protein levels. The CT radiographs at admission showed abnormal findings in 54 (80.6%) patients. The patients were treated mainly by oxygen therapy and antiviral drugs. By February 17, 2020, none of the 67 patients died and no infection occurred among medical staff in the department. Fifty-four (80.6%) patients were completely recovered and all others were improving. Conclusion: Cases in Wenzhou are mild, with good prognosis. Timely and appropriate screening, diagnosis, and treatment are the key to achieve the good outcomes.

4.
Front Endocrinol (Lausanne) ; 12: 604100, 2021.
Article in English | MEDLINE | ID: covidwho-1150686

ABSTRACT

Background and Aim: Circulating levels of interleukin (IL)-6, a well-known inflammatory cytokine, are often elevated in coronavirus disease-2019 (COVID-19). Elevated IL-6 levels are also observed in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). Our study aimed to describe the association between circulating IL-6 levels and MAFLD at hospital admission with risk of severe COVID-19. Methods: A total of 167 patients with laboratory-confirmed COVID-19 from three Chinese hospitals were enrolled. Circulating levels of IL-2, IL-4, IL-6, IL-10, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ were measured at admission. All patients were screened for fatty liver by computed tomography. Forty-six patients were diagnosed as MAFLD. Results: Patients with MAFLD (n = 46) had higher serum IL-6 levels (median 7.1 [interquartile range, 4.3-20.0] vs. 4.8 [2.6-11.6] pg/mL, p = 0.030) compared to their counterparts without MAFLD (n = 121). After adjustment for age and sex, patients with MAFLD had a ~2.6-fold higher risk of having severe COVID-19 than those without MAFLD. After adjustment for age, sex and metabolic co-morbidities, increased serum IL-6 levels remained associated with higher risk of severe COVID-19, especially among infected patients with MAFLD (adjusted-odds ratio 1.14, 95% CI 1.05-1.23; p = 0.002). There was a significant interaction effect between serum IL-6 levels and MAFLD for risk of severe COVID-19 (p for interaction = 0.008). Conclusions: Patients with MAFLD and elevated serum IL-6 levels at admission are at higher risk for severe illness from COVID-19.


Subject(s)
COVID-19/complications , Fatty Liver/epidemiology , Interleukin-6/blood , Metabolic Diseases/physiopathology , SARS-CoV-2/isolation & purification , Severity of Illness Index , Adolescent , Adult , Aged , COVID-19/transmission , COVID-19/virology , China/epidemiology , Fatty Liver/blood , Fatty Liver/pathology , Fatty Liver/virology , Female , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors , Young Adult
5.
Med Sci Monit ; 27: e929708, 2021 Apr 11.
Article in English | MEDLINE | ID: covidwho-1148368

ABSTRACT

BACKGROUND Since the outbreak of COVID-19 in December 2019, there have been 96 623 laboratory-confirmed cases and 4784 deaths by December 29 in China. We aimed to analyze the risk factors and the incidence of thrombosis from patients with confirmed COVID-19 pneumonia. MATERIAL AND METHODS Eighty-eight inpatients with confirmed COVID-19 pneumonia were reported (31 critical cases, 33 severe cases, and 24 common cases). The thrombosis risk factor assessment, laboratory results, ultrasonographic findings, and prognoses of these patients were analyzed, and compared among groups with different severity. RESULTS Nineteen of the 88 cases developed DVT (12 critical cases, 7 severe cases, and no common cases). In addition, among the 18 patients who died, 5 were diagnosed with DVT. Positive correlations were observed between the increase in D-dimer level (≥5 µg/mL) and the severity of COVID-19 pneumonia (r=0.679, P<0.01), and between the high Padua score (≥4) and the severity (r=0.799, P<0.01). In addition, the CRP and LDH levels on admission had positive correlations with the severity of illness (CRP: r=0.522, P<0.01; LDH: r=0.600, P<0.01). A negative correlation was observed between the lymphocyte count on admission and the severity of illness (r=-0.523, P<0.01). There was also a negative correlation between the lymphocyte count on admission and mortality in critical patients (r=-0.499, P<0.01). Univariable logistic regression analysis showed that the occurrence of DVT was positively correlated with disease severity (crude odds ratio: 3.643, 95% CI: 1.218-10.896, P<0.05). CONCLUSIONS Our report illustrates that critically or severely ill patients have an associated high D-dimer value and high Padua score, and illustrates that a low threshold to screen for DVT may help improve detection of thromboembolism in these groups of patients, especially in asymptomatic patients. Our results suggest that early administration of prophylactic anticoagulant would benefit the prognosis of critical patients with COVID-19 pneumonia and would likely reduce thromboembolic rates.


Subject(s)
COVID-19/complications , Fibrin Fibrinogen Degradation Products/analysis , Venous Thrombosis/epidemiology , Adult , Aged , Asymptomatic Diseases , COVID-19/blood , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , China/epidemiology , Female , Hospital Mortality , Humans , Incidence , Lower Extremity/blood supply , Lower Extremity/diagnostic imaging , Male , Middle Aged , Patient Admission , Prognosis , Retrospective Studies , Risk Assessment/methods , Risk Assessment/statistics & numerical data , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Ultrasonography , Venous Thrombosis/blood , Venous Thrombosis/diagnosis , Venous Thrombosis/etiology
6.
J Gastroenterol Hepatol ; 36(1): 204-207, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1032413

ABSTRACT

BACKGROUND AND AIM: Coronavirus disease 2019 (COVID-19) has attracted increasing worldwide attention. While diabetes is known to aggravate COVID-19 severity, it is not known whether nondiabetic patients with metabolic dysfunction are also more prone to more severe disease. The association of metabolic associated fatty liver disease (MAFLD) with COVID-19 severity in nondiabetic patients was investigated here. METHODS: The study cohort comprised 65 patients with (i.e. cases) and 65 patients without MAFLD (i.e. controls). Each case was randomly matched with one control by sex (1:1) and age (±5 years). The association between the presence of MAFLD (as exposure) and COVID-19 severity (as the outcome) was assessed by binary logistic regression analysis. RESULTS: In nondiabetic patients with COVID-19, the presence of MAFLD was associated with a four-fold increased risk of severe COVID-19; the risk increased with increasing numbers of metabolic risk factors. The association with COVID-19 severity persisted after adjusting for age, sex, and coexisting morbid conditions. CONCLUSION: Health-care professionals caring for nondiabetic patients with COVID-19 should be cognizant of the increased likelihood of severe COVID-19 in patients with MAFLD.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Fatty Liver/complications , Adolescent , Adult , Aged , Case-Control Studies , China , Cohort Studies , Fatty Liver/diagnosis , Female , Humans , Logistic Models , Male , Middle Aged , Risk Factors , Severity of Illness Index , Young Adult
7.
J Med Virol ; 92(11): 2804-2812, 2020 11.
Article in English | MEDLINE | ID: covidwho-935146

ABSTRACT

A pandemic of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection broke out all over the world; however, epidemiological data and viral shedding in pediatric patients are limited. We conducted a retrospective, multicenter study, and followed-up with all children from the families with SARS-CoV-2 infected members in Zhejiang Province, China. All infections were confirmed by testing the SARS-CoV-2 RNA with real-time reverse transcription PCR method, and epidemiological data between children and adults in the same families were compared. Effect of antiviral therapy was evaluated observationally and fecal-viral excretion times among groups with different antiviral regiments were compared with Kaplan-Meier plot. By 29 February 2020, 1298 cases from 883 families were confirmed with SARS-CoV-2 infection and 314 of which were families with children. Incidence of infection in child close contacts was significantly lower than that in adult contacts (13.2% vs 21.2%). The mean age of 43 pediatric cases was 8.2 years and mean incubation period was 9.1 days. Forty (93.0%) were family clustering. Thirty-three children had coronavirus disease 2019 (20 pneumonia) with mild symptoms and 10 were asymptomatic. Fecal SARS-CoV-2 RNA detection was positive in 91.4% (32/35) cases and some children had viral excretion time over 70 days. Viral clearance time was not different among the groups treated with different antiviral regiments. No subsequent infection was observed in family contacts of fecal-viral-excreting children. Children have lower susceptibility of SARS-CoV-2 infection, longer incubation, and fecal-viral excretion time. Positive results of fecal SARS-CoV-2 RNA detection were not used as indication for hospitalization or quarantine.


Subject(s)
COVID-19/epidemiology , Feces/virology , SARS-CoV-2/physiology , Virus Shedding , Adolescent , Antiviral Agents/therapeutic use , COVID-19/transmission , Carrier State/epidemiology , Carrier State/virology , Child , Child, Preschool , China/epidemiology , Family , Female , Hospitalization , Humans , Incidence , Infant , Male , Retrospective Studies , Risk Factors , SARS-CoV-2/pathogenicity
8.
BMC Infect Dis ; 20(1): 841, 2020 Nov 13.
Article in English | MEDLINE | ID: covidwho-926311

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging viral disease. Here, we report the clinical features, management, and short-term outcomes of COVID-19 patients in Wenzhou, China, an area outside Wuhan. METHODS: Patients admitted to the Infectious Diseases Department of Ruian People's Hospital in Wenzhou, from January 21 to February 7, 2020, were recruited. Medical data on epidemiological history, demographics, clinical characteristics, laboratory tests, chest computerized tomography (CT) examination, treatment, and short-term outcomes were retrospectively reviewed. Blood biochemistry and routine tests were examined using standard methods and automatic machines. CT examination was performed several times during hospitalization as necessary. RESULTS: A total of 67 confirmed COVID-19 cases were diagnosed; 64 (95.4%) were common cases and three (4.5%) were severe cases. The most common symptoms at admission were fever (86.6%), cough (77.6%), productive cough (52.2%), chest distress (17.9%), and sore throat (11.9%), followed by diarrhea (7.4%), headache (7.4%), shortness of breath (6.0%), dizziness (4.5%), muscular soreness (4.5%), and running nose (4.5%). Thirty patients (47.8%) had increased C-reactive protein levels. The CT radiographs at admission showed abnormal findings in 54 (80.6%) patients. The patients were treated mainly by oxygen therapy and antiviral drugs. By March 3, 2020, all 67 patients completely recovered and had negative nucleic acid tests. The patients were discharged from the hospital and transferred to a medical observation isolation center for further observation. CONCLUSION: Cases of COVID-19 in Wenzhou are milder and have a better prognosis, compared to those in Wuhan. Timely and appropriate screening, diagnosis, and treatment are the key to achieve good outcomes.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Adolescent , Adult , Aged , Antiviral Agents/therapeutic use , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , COVID-19 , Child , Child, Preschool , China/epidemiology , Comorbidity , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Coronavirus Infections/transmission , Cough/virology , Diarrhea/virology , Female , Fever/virology , Hospitalization , Humans , Male , Mass Screening , Middle Aged , Patient Discharge , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , Pneumonia, Viral/transmission , Pregnancy , Respiratory Rate , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Tomography, X-Ray Computed , Travel , Treatment Outcome , Young Adult
9.
Ann Am Thorac Soc ; 17(10): 1231-1237, 2020 10.
Article in English | MEDLINE | ID: covidwho-858611

ABSTRACT

Rationale: Many clinical studies have focused on the epidemiological and clinical characteristics of inpatients with coronavirus disease (COVID-19). However, there are few reports about the clinical follow-up of discharged patients.Objectives: To describe the follow-up of patients with COVID-19 in Wenzhou City, Zhejiang, China.Methods: We retrospectively reviewed 4-week follow-ups in patients with COVID-19, including computed tomographic (CT) chest scanning, blood testing, and oropharyngeal-swab testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ribonucleic acid. The chest CT scans and blood tests were performed on the last day before discharge and 2 weeks and 4 weeks after discharge. The oropharyngeal-swab tests were performed at both 1 week and 2 weeks after discharge. Fifty-one patients with common COVID-19 were enrolled in the study. All the CT and clinical data were collected between January 23 and March 28, 2020.Results: Compared with the abnormalities found on the the last CT scans before discharge, the abnormalities in the lungs at the first and second follow-ups after discharge had been gradually absorbed. The cases with focal ground-glass opacity were reduced from 17.7% to 9.8% of cases. The cases with multiple ground-glass opacities decreased from 80.4% to 23.5%. The cases with consolidation were reduced from 49.0% to 2.0%. The cases with interlobular septal thickening were reduced from 80.4% to 35.3%. The cases with subpleural lines were reduced from 29.4% to 7.8%. The cases with irregular lines were reduced from 41.2% to 15.7%. The lung lesions of 25.5% patients were shown to be fully absorbed on the first CT scans after discharge, and the rate of lung recovery increased to 64.7% after the second follow-up. Nucleic-acid test results became recurrently positive in 17.6% of discharged patients, of whom only 33.3% complained of clinical symptoms. There were no differences in the characteristics of the last CT scans before discharge between the patients with recurrently positive test results and the patients with negative test results. The lung damage was fully absorbed in 55.6% of discharged patients with recurrence of positive test results for SARS-CoV-2 ribonucleic acid.Conclusions: The lung damage due to COVID-19 could be reversible for patients with common COVID-19. A few cases showed recurring positive results of nucleic-acid tests after discharge.


Subject(s)
Aftercare , Clinical Laboratory Techniques , Coronavirus Infections , Lung/diagnostic imaging , Pandemics , Patient Discharge/statistics & numerical data , Pneumonia, Viral , Tomography, X-Ray Computed/methods , Aftercare/methods , Aftercare/statistics & numerical data , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , China/epidemiology , Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/therapy , Female , Humans , Male , Middle Aged , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Pneumonia, Viral/therapy , Retrospective Studies , SARS-CoV-2
12.
Transl Lung Cancer Res ; 9(4): 1516-1527, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-782600

ABSTRACT

BACKGROUND: Radiological manifestations of coronavirus disease 2019 (COVID-19) featured ground-glass opacities (GGOs), especially in the early stage, which might create confusion in differential diagnosis with early lung cancer. We aimed to specify the radiological characteristics of COVID-19 and early lung cancer and to unveil the discrepancy between them. METHODS: One hundred and fifty-seven COVID-19 patients and 374 early lung cancer patients from four hospitals in China were retrospectively enrolled. Epidemiological, clinical, radiological, and pathological characteristics were compared between the two groups using propensity score-matched (PSM) analysis. RESULTS: COVID-19 patients had more distinct symptoms, tended to be younger (P<0.0001), male (P<0.0001), and had a higher body mass index (P=0.014). After 1:1 PSM, 121 matched pairs were identified. Regarding radiological characteristics, patients with a single lesion accounted for 17% in COVID-19 and 89% in lung cancer (P<0.0001). Most lesions were peripherally found in both groups. Lesions in COVID-19 involved more lobes (median 3.5 vs. 1; P<0.0001) and segments (median 6 vs. 1; P<0.0001) and tended to have multiple types (67%) with patchy form (54%). Early lung cancer was more likely to have a single type (92%) with oval form (66%). Also, COVID-19 and early lung cancer either had some distinctive features on computed tomography (CT) images. CONCLUSIONS: Both COVID-19 and early lung cancers showed GGOs, with similar but independent features. The imaging characteristics should be fully understood and combined with epidemiological history, pathogen detection, laboratory tests, short-term CT reexamination, and pathological results to aid differential diagnosis.

13.
Biomed Eng Online ; 19(1): 66, 2020 Aug 19.
Article in English | MEDLINE | ID: covidwho-721304

ABSTRACT

BACKGROUND: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pneumonia (COVID-19) with high sensitivity and popularity. Machine learning was adept in discovering intricate structures from CT images and achieved expert-level performance in medical image analysis. METHODS: An integrated machine learning framework on chest CT images for differentiating COVID-19 from general pneumonia (GP) was developed and validated. Seventy-three confirmed COVID-19 cases were consecutively enrolled together with 27 confirmed general pneumonia patients from Ruian People's Hospital, from January 2020 to March 2020. To accurately classify COVID-19, region of interest (ROI) delineation was implemented based on ground-glass opacities (GGOs) before feature extraction. Then, 34 statistical texture features of COVID-19 and GP ROI images were extracted, including 13 gray-level co-occurrence matrix (GLCM) features, 15 gray-level-gradient co-occurrence matrix (GLGCM) features and 6 histogram features. High-dimensional features impact the classification performance. Thus, ReliefF algorithm was leveraged to select features. The relevance of each feature was the average weights calculated by ReliefF in n times. Features with relevance larger than the empirically set threshold T were selected. After feature selection, the optimal feature set along with 4 other selected feature combinations for comparison were applied to the ensemble of bagged tree (EBT) and four other machine learning classifiers including support vector machine (SVM), logistic regression (LR), decision tree (DT), and K-nearest neighbor with Minkowski distance equal weight (KNN) using tenfold cross-validation. RESULTS AND CONCLUSIONS: The classification accuracy (ACC), sensitivity (SEN), specificity (SPE) of our proposed method yield 94.16%, 88.62% and 100.00%, respectively. The area under the receiver operating characteristic curve (AUC) was 0.99. The experimental results indicate that the EBT algorithm with statistical textural features based on GGOs for differentiating COVID-19 from general pneumonia achieved high transferability, efficiency, specificity, sensitivity, and impressive accuracy, which is beneficial for inexperienced doctors to more accurately diagnose COVID-19 and essential for controlling the spread of the disease.


Subject(s)
Coronavirus Infections/complications , Image Processing, Computer-Assisted , Machine Learning , Pneumonia, Viral/complications , Pneumonia/complications , Pneumonia/diagnosis , COVID-19 , Female , Humans , Male , Pandemics , Tomography, X-Ray Computed
14.
Radiol Infect Dis ; 7(3): 97-105, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-644939

ABSTRACT

OBJECTIVE: To explore the clinical and radiological characteristics of COVID-19 patients with progressive and non-progressive CT manifestations. METHODS: 160 patients with COVID-19 were retrospectively included from Wenzhou and Wuhan, China. CT features including lesion position, attenuation, form and total scores (0-4) at the segment level were evaluated. Other images signs were also assessed. 65 patients were classified as progressive (group 1) and 95 as non-progressive CT (group 2) groups according to score changes between the initial and second CT. RESULTS: Symptoms onset-initial CT interval time in group 1 [5 (2, 7) days] were significantly shorter than that in group 2 [10 (8, 14) days] (P < 0.001). Group 2 had higher radiological scores, with more lobes and segments affected, and other CT signs (P < 0.05). In group 1, radiological scores, the number of lobes and segments affected as well as lesions in both peripheral and central distribution, mixed ground grass opacity and consolidation density, and patchy form increased in the second CT (P < 0.05). More reticular pattern, subpleural linear opacity and bronchial dilatation were also found (P < 0.05). CONCLUSION: Typically radiological characteristics of progressive CT patients could potentially help to predict changes and increase understanding of the natural history of COVID-19.

15.
Epidemiol Infect ; 148: e137, 2020 07 06.
Article in English | MEDLINE | ID: covidwho-633285

ABSTRACT

From 21 January 2020 to 9 February 2020, three family clusters involving 31 patients with coronavirus disease 2019 were identified in Wenzhou, China. The epidemiological and clinical characteristics of the family cluster patients were analysed and compared with those of 43 contemporaneous sporadic cases. The three index cases transmitted the infection to 28 family members 2-10 days before illness onset. Overall, 28 of the 41 sporadic cases and three of 31 patients in the family clusters came back from Wuhan (65.12 vs. 9.68%, P< 0.001). In terms of epidemiological characters and clinical symptoms, no significant differences were observed between the family cluster and sporadic cases. However, the lymphocyte counts of sporadic cases were significantly lower than those of family cluster cases ((1.32 ± 0.55) × 109/l vs. (1.63 ± 0.70) × 109/l, P = 0.037), and the proportion of hypoalbuminaemia was higher in sporadic cases (18/43, 41.86%) than in the family clusters (6/31, 19.35%) (P < 0.05). Within the family cluster, the second- and third-generation cases had milder clinical manifestations, without severe conditions, compared with the index and first-generation cases, indicating that the virulence gradually decreased following passage through generations within the family clusters. Close surveillance, timely recognition and isolation of the suspected or latent patient is crucial in preventing family cluster infection.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , COVID-19 , China/epidemiology , Cluster Analysis , Contact Tracing , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Family , Female , Humans , Infectious Disease Incubation Period , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , SARS-CoV-2 , Travel
16.
BMC Med Imaging ; 20(1): 70, 2020 06 23.
Article in English | MEDLINE | ID: covidwho-612125

ABSTRACT

BACKGROUND: We aimed to describe the chest CT findings in sixty-seven patients infected by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We retrospectively reviewed 67 patients hospitalized in Ruian People's Hospital. All the patients received the positive diagnosis of SARS-CoV-2 infection. The CT and clinical data were collected between January 23rd, 2020 and February 10th, 2020. The CT images were analyzed by the senior radiologists. RESULTS: There are 54 patients with positive CT findings and 13 patients with negative CT findings. The typical CT findings in hospitalized patients with SARS-CoV-2 infection were ground glass opacities (42/54), lesions located in the peripheral area (50/54), multiple lesions (46/54), and lesions located in the lower lobes (42/54). There were less typical CT findings, including air bronchogram (18/54), pleural thickening or pleural effusion (14/54), consolidation (12/54), lesions in the upper lobes (12/54), interlobular septal thickening (11/54), reversed halo sign (9/54), single lesion (8/54), air cavities (4/54), bronchial wall thickening (3/54), and intrathoracic lymph node enlargement (2/54). CONCLUSIONS: CT features can play an important role in the early diagnosis and follow-up of COVID-19 patients.


Subject(s)
Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiography, Thoracic/methods , Tomography, X-Ray Computed/methods , Adult , Aged , Betacoronavirus , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Retrospective Studies , SARS-CoV-2
17.
Liver Int ; 40(9): 2160-2163, 2020 09.
Article in English | MEDLINE | ID: covidwho-611716

ABSTRACT

The Corona Virus Disease 2019 (COVID-19) pandemic has attracted increasing worldwide attention. While metabolic-associated fatty liver disease (MAFLD) affects a quarter of world population, its impact on COVID-19 severity has not been characterized. We identified 55 MAFLD patients with COVID-19, who were 1:1 matched by age, sex and obesity status to non-aged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients without MAFLD. Our results demonstrate that in patients aged less than 60 years with COVID-19, MAFLD is associated with an approximately fourfold increase (adjusted odds ratio 4.07, 95% confidence interval 1.20-13.79, P = .02) in the probability for severe disease, after adjusting for confounders. Healthcare professionals caring for patients with COVID-19 need to be aware that there is a positive association between MAFLD and severe illness with COVID-19.


Subject(s)
Coronavirus Infections/complications , Fatty Liver/complications , Pneumonia, Viral/complications , Adult , Betacoronavirus , COVID-19 , China/epidemiology , Cohort Studies , Coronavirus Infections/epidemiology , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2
19.
Eur Radiol ; 30(12): 6797-6807, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-620570

ABSTRACT

OBJECTIVES: To develop a predictive model and scoring system to enhance the diagnostic efficiency for coronavirus disease 2019 (COVID-19). METHODS: From January 19 to February 6, 2020, 88 confirmed COVID-19 patients presenting with pneumonia and 80 non-COVID-19 patients suffering from pneumonia of other origins were retrospectively enrolled. Clinical data and laboratory results were collected. CT features and scores were evaluated at the segmental level according to the lesions' position, attenuation, and form. Scores were calculated based on the size of the pneumonia lesion, which graded at the range of 1 to 4. Air bronchogram, tree-in-bud sign, crazy-paving pattern, subpleural curvilinear line, bronchiectasis, air space, pleural effusion, and mediastinal and/or hilar lymphadenopathy were also evaluated. RESULTS: Multivariate logistic regression analysis showed that history of exposure (ß = 3.095, odds ratio (OR) = 22.088), leukocyte count (ß = - 1.495, OR = 0.224), number of segments with peripheral lesions (ß = 1.604, OR = 1.604), and crazy-paving pattern (ß = 2.836, OR = 2.836) were used for establishing the predictive model to identify COVID-19-positive patients (p < 0.05). In this model, values of area under curve (AUC) in the training and testing groups were 0.910 and 0.914, respectively (p < 0.001). A predicted score for COVID-19 (PSC-19) was calculated based on the predictive model by the following formula: PSC-19 = 2 × history of exposure (0-1 point) - 1 × leukocyte count (0-2 points) + 1 × peripheral lesions (0-1 point) + 2 × crazy-paving pattern (0-1 point), with an optimal cutoff point of 1 (sensitivity, 88.5%; specificity, 91.7%). CONCLUSIONS: Our predictive model and PSC-19 can be applied for identification of COVID-19-positive cases, assisting physicians and radiologists until receiving the results of reverse transcription-polymerase chain reaction (RT-PCR) tests. KEY POINTS: • Prediction of RT-PCR positivity is crucial for fast diagnosis of patients suspected of having coronavirus disease 2019 (COVID-19). • Typical CT manifestations are advantageous for diagnosing COVID-19 and differentiation of COVID-19 from other types of pneumonia. • A predictive model and scoring system combining both clinical and CT features were herein developed to enable high diagnostic efficiency for COVID-19.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , Tomography, X-Ray Computed/methods , Adult , COVID-19 , Coronavirus Infections/epidemiology , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Predictive Value of Tests , Retrospective Studies , SARS-CoV-2
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