Correction to: Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis

Abstract Background Since the COVID-19 outbreak, pulmonary involvement was one of the most significant concerns in assessing patients. In the current study, we evaluated patient’s signs, symptoms, and laboratory data on the first visit to predict the severity of pulmonary involvement and their outcome regarding their initial findings. Methods All referred patients to the COVID-19 clinic of a tertiary referral university hospital were evaluated from April to August 2020. Four hundred seventy-eight COVID-19 patients with positive real-time reverse-transcriptase-polymerase chain reaction (RT-PCR) or highly suggestive symptoms with computed tomography (CT) imaging results with typical findings of COVID-19 were enrolled in the study. The clinical features, initial laboratory, CT findings, and short-term outcomes (ICU admission, mortality, length of hospitalization, and recovery time) were recorded. In addition, the severity of pulmonary involvement was assessed using a semi-quantitative scoring system (0–25). Results Among 478 participants in this study, 353 (73.6%) were admitted to the hospital, and 42 (8.7%) patients were admitted to the ICU. Myalgia (60.4%), fever (59.4%), and dyspnea (57.9%) were the most common symptoms of participants at the first visit. A review of chest CT scans showed that Ground Glass Opacity (GGO) (58.5%) and consolidation (20.7%) were the most patterns of lung lesions. Among initial clinical and laboratory findings, anosmia (P = 0.01), respiratory rate (RR) with a cut point of 25 (P = 0.001), C-reactive protein (CRP) with a cut point of 90 (P = 0.002), white Blood Cell (WBC) with a cut point of 10,000 (P = 0.009), and SpO2 with a cut point of 93 (P = 0.04) was associated with higher chest CT score. Lung involvement and consolidation lesions on chest CT scans were also associated with a more extended hospitalization and recovery period. Conclusions Initial assessment of COVID-19 patients, including symptoms, vital signs, and routine laboratory tests, can predict the severity of lung involvement and unfavorable outcomes.

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Predictors of The Chest CT Score in COVID-19 Patients: A Cross-Sectional Study

10.21203/rs.3.rs-777254/v1 ◽

2021 ◽

Author(s):

Niloofar Ayoobi Yazdi ◽

Abdolkarim Haji ghadery ◽

SeyedAhmad Seyedalinaghi ◽

Fatemeh Jafari ◽

Sirous Jafari ◽

...

Keyword(s):

Recovery Period ◽

Laboratory Data ◽

Pulmonary Involvement ◽

Chest Ct ◽

University Hospital ◽

Ct Scans ◽

Initial Assessment ◽

Lung Involvement ◽

Cut Point ◽

Imaging Results

Abstract Background: Since the COVID-19 outbreak, pulmonary involvement was one of the most significant concerns in assessing patients. In the current study, we evaluated patient’s signs, symptoms, and laboratory data on the first visit to predict the severity of pulmonary involvement and their outcome regarding their initial findings.Methods: All referred patients to the CODID-19 clinic of a tertiary referral university hospital were evaluated from April to August 2020. Four hundred seventy-eight COVID-19 patients with positive real-time reverse-transcriptase-polymerase chain reaction (RT-PCR) or highly suggestive symptoms with computed tomography(CT) imaging results with typical findings of COVID-19 were enrolled in the study. The clinical features, initial laboratory, CT findings, and short-term outcomes (ICU admission, mortality, length of hospitalization, and recovery time) were recorded. In addition, the severity of pulmonary involvement was assessed using a semi-quantitative scoring system (0-25). Results: Among 478 participants in this study, 353 (73.6%) were admitted to the hospital, and 57 (11.9%) patients were admitted to the ICU. Myalgia (60.3%), fever (59.3%), and dyspnea (57.8%) were the most common symptoms of participants at the first visit. A review of chest CT scans showed that Ground Glass Opacity (GGO) (58.5%) and consolidation (20.7%) were the most patterns of lung lesions. Among initial clinical and laboratory findings, anosmia (P = 0.01), respiratory rate (RR) with a cut point of 25 (P = 0.001), C-reactive protein (CRP) with a cut point of 90 (P = 0.002), white Blood Cell (WBC) with a cut point of 10,000 (P = 0.009), and SpO2 with a cut point of 93 (P = 0.04) was associated with higher chest CT score. Lung involvement and consolidation lesions on chest CT scans were also associated with a more extended hospitalization and recovery period.Conclusions: Initial assessment of COVID-19 patients, including symptoms, vital signs, and routine laboratory tests, can predict the severity of lung involvement and unfavorable outcomes.

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Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis

La radiologia medica ◽

10.1007/s11547-020-01293-w ◽

2020 ◽

Author(s):

Cappabianca Salvatore ◽

Fusco Roberta ◽

de Lisio Angela ◽

Paura Cesare ◽

Clemente Alfredo ◽

...

Keyword(s):

Artificial Intelligence ◽

Clinical Laboratory ◽

Laboratory Data ◽

Lung Parenchyma ◽

Chest Ct ◽

Critical Conditions ◽

Lung Involvement ◽

Laboratory Findings ◽

Visual Score ◽

Healthy Lung

Abstract Objective To evaluate by means of regression models the relationships between baseline clinical and laboratory data and lung involvement on baseline chest CT and to quantify the thoracic disease using an artificial intelligence tool and a visual scoring system to predict prognosis in patients with COVID-19 pneumonia. Materials and methods This study included 103 (41 women and 62 men; 68.8 years of mean age—range, 29–93 years) with suspicious COVID-19 viral infection evaluated by reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test. All patients underwent CT examinations at the time of admission in addition to clinical and laboratory findings recording. All chest CT examinations were reviewed using a structured report. Moreover, using an artificial intelligence tool we performed an automatic segmentation on CT images based on Hounsfield unit to calculate residual healthy lung parenchyma, ground-glass opacities (GGO), consolidations and emphysema volumes for both right and left lungs. Two expert radiologists, in consensus, attributed at the CT pulmonary disease involvement a severity score using a scale of 5 levels; the score was attributed for GGO and consolidation for each lung, and then, an overall radiological severity visual score was obtained summing the single score. Univariate and multivariate regression analysis was performed. Results Symptoms and comorbidities did not show differences statistically significant in terms of patient outcome. Instead, SpO2 was significantly lower in patients hospitalized in critical conditions or died while age, HS CRP, leukocyte count, neutrophils, LDH, d-dimer, troponin, creatinine and azotemia, ALT, AST and bilirubin values were significantly higher. GGO and consolidations were the main CT patterns (a variable combination of GGO and consolidations was found in 87.8% of patients). CT COVID-19 disease was prevalently bilateral (77.6%) with peripheral distribution (74.5%) and multiple lobes localizations (52.0%). Consolidation, emphysema and residual healthy lung parenchyma volumes showed statistically significant differences in the three groups of patients based on outcome (patients discharged at home, patients hospitalized in stable conditions and patient hospitalized in critical conditions or died) while GGO volume did not affect the patient's outcome. Moreover, the overall radiological severity visual score (cutoff ≥ 8) was a predictor of patient outcome. The highest value of R-squared (R2 = 0.93) was obtained by the model that combines clinical/laboratory findings at CT volumes. The highest accuracy was obtained by clinical/laboratory and CT findings model with a sensitivity, specificity and accuracy, respectively, of 88%, 78% and 81% to predict discharged/stable patients versus critical/died patients. Conclusion In conclusion, both CT visual score and computerized software-based quantification of the consolidation, emphysema and residual healthy lung parenchyma on chest CT images were independent predictors of outcome in patients with COVID-19 pneumonia.

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The association between clinical laboratory data and chest CT findings explains disease severity in a large Italian cohort of COVID-19 patients

BMC Infectious Diseases ◽

10.1186/s12879-021-05855-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Simone Canovi ◽

◽

Giulia Besutti ◽

Efrem Bonelli ◽

Valentina Iotti ◽

...

Keyword(s):

Clinical Laboratory ◽

Laboratory Data ◽

Organ Damage ◽

Cross Sectional Study ◽

Chest Ct ◽

Arterial Oxygen ◽

Emergency Rooms ◽

Cross Sectional ◽

Ct Findings ◽

Patient Prognosis

Abstract Background Laboratory data and computed tomography (CT) have been used during the COVID-19 pandemic, mainly to determine patient prognosis and guide clinical management. The aim of this study was to evaluate the association between CT findings and laboratory data in a cohort of COVID-19 patients. Methods This was an observational cross-sectional study including consecutive patients presenting to the Reggio Emilia (Italy) province emergency rooms for suspected COVID-19 for one month during the outbreak peak, who underwent chest CT scan and laboratory testing at presentation and resulted positive for SARS-CoV-2. Results Included were 866 patients. Total leukocytes, neutrophils, C-reactive protein (CRP), creatinine, AST, ALT and LDH increase with worsening parenchymal involvement; an increase in platelets was appreciable with the highest burden of lung involvement. A decrease in lymphocyte counts paralleled worsening parenchymal extension, along with reduced arterial oxygen partial pressure and saturation. After correcting for parenchymal extension, ground-glass opacities were associated with reduced platelets and increased procalcitonin, consolidation with increased CRP and reduced oxygen saturation. Conclusions Pulmonary lesions induced by SARS-CoV-2 infection were associated with raised inflammatory response, impaired gas exchange and end-organ damage. These data suggest that lung lesions probably exert a central role in COVID-19 pathogenesis and clinical presentation.

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Visual and quantitative assessment of COVID-19 pneumonia on chest CT: The relationship with disease severity and clinical findings

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405617666210215142528 ◽

2021 ◽

Vol 17 ◽

Author(s):

Furkan Kaya ◽

Petek Şarlak Konya ◽

Emin Demirel ◽

Neşe Demirtürk ◽

Semiha Orhan ◽

...

Keyword(s):

Hospital Stay ◽

Disease Severity ◽

Pearson Correlation ◽

Laboratory Data ◽

Length Of Hospital Stay ◽

Chest Ct ◽

Laboratory Findings ◽

Pneumonia Severity ◽

High Attenuation ◽

The Relationship

Background: Lungs are the primary organ of involvement of COVID-19, and the severity of pneumonia in COVID-19 patients is an important cause of morbidity and mortality. Aim: We aimed to evaluate the visual and quantitative pneumonia severity on chest computed tomography (CT) in patients with coronavirus disease 2019 (COVID-19) and compare the CT findings with clinical and laboratory findings. Methods: We retrospectively evaluated adult COVID-19 patients who underwent chest CT, clinical scores, laboratory findings, and length of hospital stay. Two independent radiologists visually evaluated the pneumonia severity on chest CT (VSQS). Quantitative CT (QCT) assessment was performed using a free DICOM viewer, and the percentage of the well-aerated lung (%WAL), high-attenuation areas (%HAA) at different threshold values, and mean lung attenuation (MLA) values were calculated. The relationship between CT scores and the clinical, laboratory data, and length of hospital stay were evaluated in this cross-sectional study. The student's t-test and chi-square test were used to analyze the differences between variables. The Pearson correlation test analyzed the correlation between variables. The diagnostic performance of the variables was assessed using receiver operating characteristic (ROC) analysis was used. Results: The VSQS and QCT scores were significantly correlated with procalcitonin, d-dimer, ferritin, and C-reactive protein levels. Both VSQ and QCT scores were significantly correlated with disease severity (p<0.001). Among the QCT parameters, the %HAA-600 value showed the best correlation with the VSQS (r=730,p<0.001). VSQS and QCT scores had high sensitivity and specificity in distinguishing disease severity and predicting prolonged hospitalization. Conclusion: The VSQS and QCT scores can help manage the COVID-19 and predict the duration of hospitalization.

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DIAGNOSTIC ROLE OF CHEST CT USING CO-RADS CATEGORIZATION IN SARS-COV-2 INFECTION WITH EMPHASIS ON IMPACT OF CT IN PATIENTS WITH DELAYED OR NEGATIVE INITIAL RTPCR TEST

10.36106/ijar/9301921 ◽

2021 ◽

pp. 51-52

Author(s):

Tharani Putta ◽

Kaushik Deconda

Keyword(s):

Diagnostic Performance ◽

Virus Disease ◽

Vital Role ◽

Chest Ct ◽

Lung Involvement ◽

Test Results ◽

Rt Pcr ◽

Diagnostic Role ◽

Pcr Test

BACKGROUND AND OBJECTIVE: Role of chest CT in diagnosis of corona virus disease 2019 (COVID-19) has been controversial. The purpose of this study is to evaluate the diagnostic performance of chest CT when utilizing COVID-19 Reporting and Data System (CO-RADS). METHODOLOGY: Retrospective study including consecutive patients with positive SARS-CoV-2 RT-PCR test (initial or repeat test) and chest CT done in our institute between June and September 2020. Spectrum of CT ndings, CO-RADS score and 25 point CT severity score (CTSS) were recorded. RESULTS: A total of 300 consecutive patients with SARS-CoV-2 infection were included in the analysis. Out of the 168 patients who underwent CT prior to positive RT-PCR result, 125 (74.4%) had CO-RADS 3, 4 or 5 score on chest CT. 32 study patients (10.6%) had initial negative RT-PCR of which 24 (75%) had CO-RADS 4 or 5 score. Of the total patients with CO-RADS 3 to 5 score (227), 20 (8.8%) had severe lung involvement (CTSS 18-25), 83 (36.6%) had moderate lung involvement (CTSS 8-17) and 124 (54.6%) had mild lung involvement (CTSS 1-7). The mean CTSS was 7.9 with mean lobar score being higher in lower lobes (RLL=1.82, LLL=1.78) compared to the upper and middle lobes (RUL=1.61, RML=1.19, LUL=1.53). CONCLUSION:CT using CO-RADS scoring system has good diagnostic performance. In addition to assessing disease severity, it plays a vital role in triage of patients with suspected COVID-19 especially when there is limited availability of SARS-CoV-2 RT-PCR tests, delay in RT-PCR test results or in negative RT-PCR cases when there is high index of clinical suspicion.

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Eosinopenia in COVID-19 Patients: A Retrospective Analysis

Microorganisms ◽

10.3390/microorganisms8121929 ◽

2020 ◽

Vol 8 (12) ◽

pp. 1929

Author(s):

Narcisse Ndieugnou Djangang ◽

Lorenzo Peluso ◽

Marta Talamonti ◽

Antonio Izzi ◽

Pierre Alain Gevenois ◽

...

Keyword(s):

Ct Scan ◽

Retrospective Analysis ◽

Predictive Accuracy ◽

Laboratory Finding ◽

Laboratory Data ◽

High Body Mass Index ◽

Chest Ct ◽

Diagnostic Methods ◽

Chest Ct Scan ◽

Pcr Test

Objectives: The aim of this study was to assess the diagnostic role of eosinophils count in COVID-19 patients. Methods: Retrospective analysis of patients admitted to our hospital with suspicion of COVID-19. Demographic, clinical and laboratory data were collected on admission. Eosinopenia was defined as eosinophils < 100 cells/mm3. The outcomes of this study were the association between eosinophils count on admission and positive real-time reverse transcription polymerase chain reaction (rRT-PCR) test and with suggestive chest computerized tomography (CT) of COVID-19 pneumonia. Results: A total of 174 patients was studied. Of those, 54% had positive rRT-PCR for SARS-CoV-2. A chest CT-scan was performed in 145 patients; 71% showed suggestive findings of COVID-19. Eosinophils on admission had a high predictive accuracy for positive rRT-PCR and suggestive chest CT-scan (area under the receiver operating characteristic—ROC curve, 0.84 (95% CIs 0.78–0.90) and 0.84 (95% CIs 0.77–0.91), respectively). Eosinopenia and high LDH were independent predictors of positive rRT-PCR, whereas eosinopenia, high body mass index and hypertension were predictors for suggestive CT-scan findings. Conclusions: Eosinopenia on admission could predict positive rRT-PCR test or suggestive chest CT-scan for COVID-19. This laboratory finding could help to identify patients at high-risk of COVID-19 in the setting where gold standard diagnostic methods are not available.

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The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia

Scientific Reports ◽

10.1038/s41598-020-76141-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Hui-Bin Tan ◽

Fei Xiong ◽

Yuan-Liang Jiang ◽

Wen-Cai Huang ◽

Ye Wang ◽

...

Keyword(s):

Machine Learning ◽

Predictive Value ◽

Laboratory Data ◽

Texture Features ◽

Chest Ct ◽

Automatic Machine ◽

Classification Model ◽

Control Group ◽

Ct Image ◽

Severe Group

Abstract To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML). 136 moderate and 83 severe patients were selected from the patients with COVID-19 pneumonia. The clinical and laboratory data were collected for statistical analysis. The texture features of the Non-focus area of the first chest CT of patients with COVID-19 pneumonia were extracted, and then the classification model of the first chest CT of COVID-19 pneumonia was constructed by using these texture features based on the Auto-ML method of radiomics, The area under curve(AUC), true positive rate(TPR), true negative rate (TNR), positive predictive value(PPV) and negative predictive value (NPV) of the operating characteristic curve (ROC) were used to evaluate the accuracy of the first chest CT image classification model in patients with COVID-19 pneumonia. The TPR, TNR, PPV, NPV and AUC of the training cohort and test cohort of the moderate group and the control group, the severe group and the control group, the moderate group and the severe group were all greater than 95% and 0.95 respectively. The non-focus area of the first CT image of COVID-19 pneumonia has obvious difference in different clinical types. The AUTO-ML classification model of Radiomics based on this difference can be used to predict the clinical types of COVID-19 pneumonia.

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Is there a Relationship between the Blood Group and the Percentage of Lung Involvement in COVID-19‘S Patients?

Austin Journal of Radiology ◽

10.26420/austinjradiol.2021.1153 ◽

2021 ◽

Vol 8 (8) ◽

Author(s):

Ghaznavi H ◽

◽

Elahimanesh F ◽

Keyword(s):

Faculty Member ◽

Blood Group ◽

Significant Relationship ◽

Clinical Studies ◽

Blood Groups ◽

Chest Ct ◽

Lung Involvement ◽

Main Hospital ◽

Clinical Presentations

As a faculty member who is teaching students in the main hospital of coronavirus - Tohid hospital - in Sanandaj, Iran. I want to share my experiences in confronting the chest CT of COVID-19 patients. What we saw in chest CT of these patients was the different percentage of lung involvement in blood groups. The percentage of lung involvement in patients with blood group O was noticeably higher than other blood groups. Unfortunately, a high percentage of outpatients with high lung involvement in chest CT were old and were unaware of their blood group, therefore we cannot claim that there is a significant relationship between lung involvement and blood group in COVID-19 patients. To the best of our knowledge, clinical presentations and papers have not yet addressed this issue, therefore proof of this relationship requires clinical studies

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Possible relationship between esophageal dilatation and severity of M. abscessus pulmonary disease

PLoS ONE ◽

10.1371/journal.pone.0261866 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0261866

Author(s):

Hiromichi Hara ◽

Keitaro Okuda ◽

Jun Araya ◽

Hirofumi Utsumi ◽

Daisuke Takekoshi ◽

...

Keyword(s):

Pulmonary Disease ◽

Medical Records ◽

Severe Disease ◽

Laboratory Data ◽

Mycobacterium Abscessus ◽

Chest Ct ◽

Maximum Diameter ◽

Esophageal Dilatation ◽

Lung Lesions ◽

Factors Associated

Objectives Recently, incidence of Mycobacterium abscessus (Mab) pulmonary disease (Mab-PD) is increasing worldwide. We aimed to identify factors associated with severity of Mycobacterium abscessus (Mab) pulmonary disease (Mab-PD). Methods All patients diagnosed as Mab-PD based on the official ATS/IDSA statement between 2017 January 1 and 2021 July 31 were included (n = 13). We reviewed medical records, bacteriological and laboratory data of the patients. Severity of lung lesions and esophageal diameters in chest CT were quantitatively evaluated. Gaffky score in the sputum was used as airway mycobacterial burden. We explored the factors associated with high CT score and high Gaffky score. Results Maximum diameter of esophagus (MDE) in severe disease (CT score≧10) was greater than that in milder disease (CT score<10) (18.0±7.9mm, 9.3±3.1mm, respectively, p = 0.01), and MDE was well correlated with CT score (R = 0.69, p = 0.007). MDE in high mycobacterial burden group (Gaffky score ≧5) tended to be greater than that in low mycobacterial burden group (Gaffky score <5) (16.1±6.8mm, 10.1±5.5mm, respectively, p = 0.12), and MDE was well correlated with Gaffky score (R = 0.68, p = 0.009). Lung lesions were bilateral and predominant in middle or lower lobes. Conclusions Esophageal dilatation was correlated with severity of Mab-PD and airway mycobacterial burden. Gastroesophageal reflux might be associated with Mab disease progression.

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