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Medicine (Baltimore) ; 100(12): e25083, 2021 Mar 26.
Article in English | MEDLINE | ID: covidwho-1150005


ABSTRACT: The purpose of this study was to investigate the predictive value of combined clinical and imaging features, compared with the clinical or radiological risk factors only. Moreover, the expected results aimed to improve the identification of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) patients who may have critical outcomes.This retrospective study included laboratory-confirmed SARS-COV-2 cases between January 18, 2020, and February 16, 2020. The patients were divided into 2 groups with noncritical illness and critical illness regarding severity status within the hospitalization. Univariable and multivariable logistic regression models were used to explore the risk factors associated with clinical and radiological outcomes in patients with SARS-COV-2. The ROC curves were performed to compare the prediction performance of different factors.A total of 180 adult patients in this study included 20 critical patients and 160 noncritical patients. In univariate logistic regression analysis, 15 risk factors were significantly associated with critical outcomes. Of importance, C-reactive protein (1.051, 95% confidence interval 1.024-1.078), D-dimer (1.911, 95% CI, 1.050-3.478), and CT score (1.29, 95% CI, 1.053-1.529) on admission were independent risk factors in multivariate analysis. The combined model achieved a better performance in disease severity prediction (P = .05).CRP, D-dimer, and CT score on admission were independent risk factors for critical illness in adults with SARS-COV-2. The combined clinical and radiological model achieved better predictive performance than clinical or radiological factors alone.

COVID-19/epidemiology , COVID-19/physiopathology , Diagnostic Techniques and Procedures/statistics & numerical data , Adult , Aged , C-Reactive Protein/analysis , Female , Fibrin Fibrinogen Degradation Products/analysis , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2 , Severity of Illness Index , Tomography, X-Ray Computed
Jpn J Radiol ; 39(6): 589-597, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1144386


PURPOSE: To describe the prognostic value of pulmonary artery (PA) trunk enlargement on the admission of in-hospital patients with severe COVID-19 infection by unenhanced CT image. MATERIALS AND METHODS: In-hospital patients confirmed COVID-19 from January 18, 2020, to March 7, 2020, were retrospectively enrolled. PA trunk diameters on admission and death events were collected to calculate the optimum cutoff using a receiver operating characteristic curve. According to the cutoff, the subjects on admission were divided into two groups. Then the in-hospital various parameters were compared between the two groups to assess the predictive value of PA trunk diameter. RESULTS: In the 180 enrolled in-hospital patients (46.99 ± 14.95 years; 93 (51.7%) female, 14 patients (7.8%) died during their hospitalization. The optimum cutoff PA trunk diameter to predict in-hospital mortality was > 29 mm with a sensitivity of 92.59% and a specificity of 91.11%. Kaplan-Meier survival curves for PA trunk diameter on admission showed that a PA trunk diameter > 29 mm was a significant predictor of subsequent death (log-rank < 0.001, median survival time of PA > 29 mm was 28 days). CONCLUSION: PA trunk enlargement can be a useful predictive factor for distinguishing between mild and severe COVID-19 disease progression.

COVID-19/mortality , COVID-19/pathology , Pulmonary Artery/pathology , Adult , COVID-19/diagnostic imaging , Dilatation, Pathologic/diagnostic imaging , Female , Hospital Mortality , Hospitalization , Humans , Male , Middle Aged , Prognosis , Pulmonary Artery/diagnostic imaging , ROC Curve , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed/methods
Curr Med Sci ; 41(1): 31-38, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1084475


The outbreak of coronavirus disease 2019 (COVID-19) posed an unprecedented threat to health care providers (HCPs) in Wuhan, China, especially for nurses who were frequently exposed to infected or suspected patients. Limited information was available about the working experience of nurses in fighting against the pandemic. To learn the physical and psychological responses of nurses during the pandemic and explore the potential determinants, we conducted a large-scale survey in Wuhan. This multicenter cross-sectional study enrolled 5521 nurses who worked in designated hospitals, mobile cabins, or shelters during the pandemic. A structured online questionnaire was distributed to assess the physical discomforts, emotional distress and cognitive reactions of nurses at work, and the log-binomial regression analysis was performed to explore potential determinants. A considerable proportion of nurses had symptoms of physical discomforts [3677 (66.6%)] and emotional distress [4721 (85.5%)]. Nurses who were directly involved in the care of patients (i.e., care for severe patients: RR, 2.35; 95% CI, 1.95-2.84), with irregular work schedules (RR, 2.36; 95% CI, 1.95-2.87), and working overtime (RR, 1.34; 95% CI, 1.08-1.65) were at a higher risk for physical discomforts. Nurses who were directly involved in the care of patients (i.e., care for severe patients: RR, 1.78; 95% CI, 1.40-2.29), with irregular work schedules (RR, 3.39; 95% CI, 2.43-4.73), and working overtime (RR, 1.51; 95% CI, 1.12-2.04) were at a higher risk for emotional distress. Therefore, formulating reasonable work schedules and improving workforce systems are necessary to alleviate the physical and emotional distress of nurses during the pandemic.

COVID-19/nursing , Nurses/psychology , Occupational Stress/psychology , Workload/psychology , Adult , COVID-19/psychology , China , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Surveys and Questionnaires