Immune checkpoint inhibitor-related pneumonitis and COVID-19: a case-matched comparison of CT findings.

OBJECTIVES: To compare the radiological findings of immune checkpoint inhibitor-related pneumonitis (IRP) and COVID-19 pneumonia, evaluating the potential of the CO-RADS score to differentiate between them. METHODS: Two readers blindly reviewed chest CTs from age- and sex-matched groups of 33 patients with IRP and 33 patients with COVID-19 pneumonia. Each examiner evaluated the presence of 13 CT features, semiquantitatively scored lung involvement, and assigned a CO-RADS score. Inter-reader reliability in the assessment of CT features and CO-RADS categories was evaluated with Cohen's κ. Distribution differences between groups were evaluated with the χ2, Fisher's, and Mann-Whitney U tests. RESULTS: Substantial or higher inter-reader reliability was found in CO-RADS assignments (κ = 0.664) and in the evaluation of CT features (κ ≥ 0.638), among which the sole feature found to significantly differentiate IRP from COVID-19 pneumonia was unilateral presentation (p < 0.001). Lung involvement semiquantitative scores and CO-RADS scores were significantly higher (p < 0.001) in COVID patients (median involvement score 4, IQR 4-6; median CO-RADS score 5, IQR 4-5) than in IRP patients (median involvement score 2.5, IQR 2-4; median CO-RADS score 3, IQR 3-4) but exploratory analysis of CO-RADS specificity revealed comparatively low values, ranging between 51.5% (Reader 1) and 54.6% (Reader 2). CONCLUSIONS: CT features of IRP and COVID-19 pneumonia frequently overlap, save for the extent of lung involvement and bilaterality. In the current SARS-CoV-2 pandemic, the low specificity of the CO-RADS score for the differential diagnosis of COVID-19 pneumonia and IRP may prompt to reconsider the role of imaging in IRP work-up.

Diagnostic performance of CO-RADS for COVID-19: a systematic review and meta-analysis.

OBJECTIVES: To investigate the diagnostic performance of the coronavirus disease 2019 (COVID-19) Reporting and Data System (CO-RADS) for detecting COVID-19. METHODS: We searched PubMed, EMBASE, MEDLINE, Web of Science, Cochrane Library, and Scopus database until September 21, 2021. Statistical analysis included data pooling, forest plot construction, heterogeneity testing, meta-regression, and subgroup analyses. RESULTS: We included 24 studies with 8382 patients. The pooled sensitivity and specificity and the area under the curve (AUC) of CO-RADS ≥ 3 for detecting COVID-19 were 0.89 (95% confidence interval (CI) 0.85-0.93), 0.68 (95% CI 0.60-0.75), and 0.87 (95% CI 0.84-0.90), respectively. The pooled sensitivity and specificity and AUC of CO-RADS ≥ 4 were 0.83 (95% CI 0.79-0.87), 0.84 (95% CI 0.78-0.88), and 0.90 (95% CI 0.87-0.92), respectively. Cochran's Q test (p < 0.01) and Higgins I2 heterogeneity index revealed considerable heterogeneity. Studies with both symptomatic and asymptomatic patients had higher specificity than those with only symptomatic patients using CO-RADS ≥ 3 and CO-RADS ≥ 4. Using CO-RADS ≥ 4, studies with participants aged < 60 years had higher sensitivity (0.88 vs. 0.80, p = 0.02) and lower specificity (0.77 vs. 0.87, p = 0.01) than studies with participants aged > 60 years. CONCLUSIONS: CO-RADS has favorable performance in detecting COVID-19. CO-RADS ≥ 3/4 might be applied as cutoff values given their high sensitivity and specificity. However, there is a need for more well-designed studies on CO-RADS. KEY POINTS: • CO-RADS shows a favorable performance in detecting COVID-19. • CO-RADS ≥ 3 had a high sensitivity 0.89 (95% CI 0.85-0.93), and it may prove advantageous in screening the potentially infected people to prevent the spread of COVID-19. • CO-RADS ≥ 4 had high specificity 0.84 (95% CI 0.78-0.88) and may be more suitable for definite diagnosis of COVID-19.

Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system.

BACKGROUND: It is important to determine the correlation of the CO-RADS classification and computed tomography (CT) patterns of the lung with laboratory data. To investigate the relationship of CO-RADS categories and CT patterns with laboratory data in patients with a positive RT-PCR test. We also developed a structured total CT scoring system and investigated its correlation with the total CT scoring system. METHOD: The CT examinations of the patients were evaluated in terms of the CO-RADS classification, pattern groups and total CT score. Structured total CT score values were obtained by including the total CT score values and pattern values in a regression analysis. The CT data were compared according to the laboratory data. RESULTS: A total of 198 patients were evaluated. There were significant differences between the CO-RADS groups in terms of age, ICU transfer, oxygen saturation, creatinine, LDH, D-dimer, high-sensitivity cardiac troponin-T (hs-TnT), CRP, structured total CT score values, and total CT score values. A significant difference was also observed between the CT pattern groups and oxygen saturation, creatinine and CRP values. When the structured total CT score values and total CT score values were compared they were observed to be correlated. CONCLUSIONS: Creatinine can be considered as an important marker for the CO-RADS and pattern classifications in lung involvement. LDH can be considered as an important marker of parenchymal involvement, especially bilateral and diffuse involvement. The structured total CT scoring system is a new system that can be used as an alternative.

Spectrum of HRCT Scan Chest Findings in COVID-19 Patients as Categorized by Modified CO-RADS Classification.

Objectives: The Dutch Radiological Society developed CO-RADS classification, a system for the classification of CT scan chest findings among suspected COVID-19 patients. However due to some important issues it was modified by authors and then applied on our study population. The objective was to study the spectrum of lungs involvement as concluded by HRCT scan chest finding and classifying it using the "Modified CO-RADS classification". Methods: This cross-sectional study was conducted jointly by the departments of Medicine and Radiology, JPMC from January 16, 2021 to April 30, 2021. This study includes suspected cases of COVID-19 patients aged between 18-80 years who came for HRCT chest. Their data variables were recorded. HRCT findings were classified using "Modified CO-RADS classification". Patients' results of real time PCR for COVID-19 were also followed. Results: A total of 78 patients presented to the study department during this study period. Of them 85.8% were male (n=67) and 14.2% were female (n=11). Out of the 78 patients, 58 were tested positive for COVID-19 on first RT-PCR on follow up. Among positive two patients (3.4%) had CO-RADS-1, 4 patients (7%) had CO-RADS-2, 19 patients (32.75%) had CO-RADS-3, 21 patients (36.2%) had CO-RADS-4 while 12 patients (20.7%) had CO-RADS-5 category. (CO-RAD-6 category was omitted). Of the patient who had negative results on RT-PCR, five patients had CO-RADS-4 while three patients had CO-RADS-5. On repeat RT-PCR all (8/8) patients of category IV and V proved Covid-19 positive. Conclusion: HRCT scan chest can be used for quicker diagnosis of COVID-19 patients in patients with respiratory complaints in whom prompt diagnosis is required and when RT-PCR investigation process would be taking prolonged time due to over burden during pandemic situation. "CO-RADS classification after modification" proved more effective communicative tool to label and understand the severity of lung involvement in Covid-19 disease.

FEATURES OF COVID-19 PNEUMONIA DIAGNOSIS.

OBJECTIVE: The aim: The purpose of the study is to evaluate the clinical and laboratory features of COVID-19 pneumonia course, the diagnostic significance of laboratory methods for detecting the SARS-CoV-2 virus based on a retrospective analysis. PATIENTS AND METHODS: Materials and methods: We studied the case histories of 96 patients who were treated at the Municipal Non-Profit Enterprise "Lviv Clinical Emergency Care Hospital" for the period from 01/07/2020 to 31/07/2020 with a diagnosis of pneumonia, which corresponded to 5 points on the CO -RADS scale. We analyzed the clinical and laboratory signs of COVID-19 pneumonia depending on the results of the Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) tests to the SARS-CoV-2 infection (positive result of RT-qPCR was observed in the first group and negative - in the second group). RESULTS: Results: In both groups, no clinical differences in the course of the disease were found. The most common symptoms of coronavirus pneumonia were found with the same frequency in both patients with a laboratory-confirmed diagnosis and without it. A positive PCR test in nasopharyngeal and oropharyngeal swabs was more often detected during testing up to 10 days, in patients over 60 years of age and in severe COVID-19. CONCLUSION: Conclusions: The COVID-19 pneumonia diagnosis should be based on a combination of clinical, laboratory, and radiological signs of this disease. A negative PCR test result does not exclude the diagnosis of coronavirus disease. The test results are influenced by the timing of the sampling, the severity of the disease and the age of the patients.

Electrocardiographic QRS axis shift, rotation and COVID-19.

Background: In patients with coronavirus disease-2019 (COVID-19), severe dyspnea is the most dramatic complication. Severe respiratory difficulties may include electrocardiographic frontal QRS axis rightward shift (Rws) and clockwise rotation (Cwr). Aim: This study investigated the predictability of advanced lung tomography findings with QRS axis shift and rotation. Patients and Methods: This was a retrospective analysis of 160 patients. Patients were divided into the following two groups: normal (n = 80) and low (n = 80) oxygen saturation. These groups were further divided into four groups according to the rightward and leftward axis shift (Lws) on the electrocardiographic follow-up findings. These groups were compared in terms of electrocardiographic rotation (Cwr, counterclockwise rotation, or normal transition), tomographic stage (CO-RADS5(advanced)/CO-RADS1-4), electrocardiographic intervals, and laboratory findings. Results: In patients with low oxygen saturation, the amount of QRS axis shift, Cwr, and tomographic stage were significantly higher in the Rws group than in the Lws group. There were no differences in the above parameters between the Rws and Lws groups in patients with normal oxygen saturation. Logistic regression analysis revealed that the presence of Cwr and Rws independently increased the risk of CO-RADS5 by 18.9 and 4.6 fold, respectively, in patients with low oxygen saturation. Conclusion: In COVID-19 patients who have dyspnea with low oxygen saturation, electrocardiographically clockwise rotation with a rightward axis shift demonstrated good sensitivity (80% [0.657-0.943]) and specificity (80% [0.552->1]) for predicting advanced lung tomographic findings. ClinicalTrialsgov Identifier: NCT04698083.

Diagnostic performance and inter-observer variability of CO-RADS in the triage of patients with suspected COVID-19 infection: initial experience in Zagazig University Hospital.

Purpose: In many healthcare settings in developing nations, multislice computed tomography (MSCT) imaging may be the only available diagnostic modality for patients with suspected COVID-19 infection, due to a shortage of laboratory kits. This study aimed to evaluate the diagnostic performance and interobserver variability of CO-RADS (COVID-19 Reporting and Data System) in the triage of patients with suspected COVID-19 infection in Zagazig University Hospital. Material and methods: This study included 2500 patients with suspected COVID-19 infection, mean age 60.61 years ± 13.89. 61.4% were male. Unstable patients requiring urgent invasive ventilation, acute coronary syndrome patients, pregnant females, and patients with RT-PCR results available prior to MSCT were excluded from this study. RT-PCR was performed in all patients included in the study. Results: Fever and dry cough were the most common clinical symptoms, detected in 80.16% and 52.00%, respectively. The most common comorbidities were cardiovascular diseases, followed by chronic lung disease and diabetes, found in 27.36%, 22.80%, and 18.00%, respectively. Of the 1500 RT-PCR-positive patients, 40% had CO-RADS score 5, while 3.4% had CO-RADS score 1. Of the 1000 RT-PCR-negative patients, 36% had CO-RADS score 2 and 1% were scored as CO-RADS 5. There was excellent agreement in the studied patients as the weighted κ value was 0.846, which was more pronounced at CO-RADS 5 (24.40%). The sensitivity of CO-RADS was higher in the 2nd scenario (83.27% vs. 55.27%) while the specificity was higher in the 1st scenario (95% vs. 65%). Conclusion: The CO-RADS scoring system is a sensitive and specific method that can help in the diagnosis of COVID-19 during the peak of the COVID-19 pandemic. CO-RADS is a triage test in resource-constrained environments, assisting in the optimization of RT-PCR tests, isolation beds, and intensive care units.

Chest X-ray Findings and Hyponatremia in COVID-19 Pneumonia Patients.

BACKGROUND: The World Health Organization declared the coronavirus disease-2019 (COVID-19) a pandemic in December 2019. COVID-19 can affect most organs of the body but predominantly affects the lungs. Chest infection is associated with hyponatremia primarily due to inappropriate ectopic secretion of antidiuretic hormone. We conducted a six-month retrospective observational study to evaluate the relationship between chest X-ray (CXR) radiological findings and serum sodium levels. Our secondary goal was to assess the relationship between CXR findings and patient outcomes. AIM OF THE STUDY: To assess the relationship between the initial CXR findings, hyponatremia severity, and outcome in COVID-19 infected patients. MATERIALS AND METHODS: We conducted a retrospective review of CXR findings of COVID-19 patients aged > 18 years. The patients were healthy and had no history of hyponatremia before COVID-19 infection. All recruited patients were admitted to one of four hospitals in Qatar (Hazm Mebaireek General Hospital, Communicable Disease Center, and all affiliated quarantine centers managed under the Communicable Disease Centre, Mesaieed Hospital, and Ras Laffan Hospital) between March and June 2020. We excluded patients with factors that contributed to hyponatremia. Three score grades were established to describe the CXR findings. Patients were divided into three groups by the principal researcher according to their serum sodium levels. A radiologist evaluated the CXR findings with the patient and group information obscured. The principal researcher collected the X-ray scores for analysis with the serum sodium levels. We used SPSS for Windows, Version 15.0. (SPSS Inc., Chicago, IL, USA) and STATA Package Version 12.0 (StataCorp, College Station, TX, USA) to analyze the data. A p-value ≤  0.05 was considered significant. RESULTS: A total of 414 CXR patients with COVID-19 were recruited; 275 patients had hyponatremia and 139 had normal sodium levels and were used as the control group. Patients with normal serum sodium and hyponatremia were classified into three categories based on the CXR findings. Grade 0 (95), Grade 1 (43), and Grade 2 (137) hyponatremic patients were reported. The mean sodium levels were 133.6, 131.3, and 127.2 mmol/L for Grades 0, 1, and 2, respectively (p < 0.001). More than 95% of the patients who developed hyponatremia were >30 years. Moderate and severe hyponatremia was more prevalent in patients with Grade 1 or Grade 2 CXR findings and were >30 years. CONCLUSION: Serum sodium levels in COVID-19 patients correlated well with the severity of the CXR findings observed at the early disease stage. Furthermore, simple CXR scores can be used to identify COVID-19 patients at a higher risk of hyponatremia, length of hospital stay, medical care support type, and mortality.

Chest CT in the Emergency Department for Diagnosis of COVID-19 Pneumonia: Dutch Experience.

Background Clinicians need to rapidly and reliably diagnose coronavirus disease 2019 (COVID-19) for proper risk stratification, isolation strategies, and treatment decisions. Purpose To assess the real-life performance of radiologist emergency department chest CT interpretation for diagnosing COVID-19 during the acute phase of the pandemic, using the COVID-19 Reporting and Data System (CO-RADS). Materials and Methods This retrospective multicenter study included consecutive patients who presented to emergency departments in six medical centers between March and April 2020 with moderate to severe upper respiratory symptoms suspicious for COVID-19. As part of clinical practice, chest CT scans were obtained for primary work-up and scored using the five-point CO-RADS scheme for suspicion of COVID-19. CT was compared with severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction (RT-PCR) assay and a clinical reference standard established by a multidisciplinary group of clinicians based on RT-PCR, COVID-19 contact history, oxygen therapy, timing of RT-PCR testing, and likely alternative diagnosis. Performance of CT was estimated using area under the receiver operating characteristic curve (AUC) analysis and diagnostic odds ratios against both reference standards. Subgroup analysis was performed on the basis of symptom duration grouped presentations of less than 48 hours, 48 hours through 7 days, and more than 7 days. Results A total of 1070 patients (median age, 66 years; interquartile range, 54-75 years; 626 men) were included, of whom 536 (50%) had a positive RT-PCR result and 137 (13%) of whom were considered to have a possible or probable COVID-19 diagnosis based on the clinical reference standard. Chest CT yielded an AUC of 0.87 (95% CI: 0.84, 0.89) compared with RT-PCR and 0.87 (95% CI: 0.85, 0.89) compared with the clinical reference standard. A CO-RADS score of 4 or greater yielded an odds ratio of 25.9 (95% CI: 18.7, 35.9) for a COVID-19 diagnosis with RT-PCR and an odds ratio of 30.6 (95% CI: 21.1, 44.4) with the clinical reference standard. For symptom duration of less than 48 hours, the AUC fell to 0.71 (95% CI: 0.62, 0.80; P < .001). Conclusion Chest CT analysis using the coronavirus disease 2019 (COVID-19) Reporting and Data System enables rapid and reliable diagnosis of COVID-19, particularly when symptom duration is greater than 48 hours. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Elicker in this issue.

Tocilizumab improves survival in severe COVID-19 pneumonia with persistent hypoxia: a retrospective cohort study with follow-up from Mumbai, India.

BACKGROUND: Cytokine storm triggered by Severe Coronavirus Disease 2019 (COVID-19) is associated with high mortality. With high Interleukin -6 (IL-6) levels reported in COVID-19 related deaths in China, IL-6 is considered to be the key player in COVID-19 cytokine storm. Tocilizumab, a monoclonal antibody against IL-6 receptor, is used on compassionate grounds for treatment of COVID-19 cytokine storm. The aim of this study was to assess effect of tocilizumab on mortality due to COVID-19 cytokine storm. METHOD: This retrospective, observational study included patients of severe COVID-19 pneumonia with persistent hypoxia (defined as saturation 94% or less on supplemental Oxygen of 15 L per minute through non-rebreathing mask or PaO2/FiO2 ratio of less than 200) who were admitted to a tertiary care center in Mumbai, India, between 31st March to 5th July 2020. In addition to standard care, single Inj. Tocilizumab 400 mg was given intravenously to 151 consecutive COVID-19 patients with persistent hypoxia, from 13th May to 5th July 2020. These 151 patients were retrospectively analysed and compared with historic controls, ie consecutive COVID-19 patients with persistent hypoxia, defined as stated above (N = 118, from our first COVID-19 admission on 31st March to 12th May 2020 i.e., till tocilizumab was available in hospital). Univariate and multivariate Cox regression analysis was performed for identifying predictors of survival. Statistical analysis was performed using IBM SPSS version 26. RESULTS: Out of 269 (151 in tocilizumab group and 118 historic controls) patients studied from 31st March to 5th July 2020, median survival in the tocilizumab group was significantly longer than in the control group; 18 days (95% CI, 11.3 to 24.7) versus 9 days (95% CI, 5.7 to 12.3); log rank p 0.007. On multivariate Cox regression analysis, independent predictors of survival were use of tocilizumab (HR 0.621, 95% CI 0.427-0.903, P 0.013) and higher oxygen saturation. CONCLUSION: Tocilizumab may improve survival in severe COVID-19 pneumonia with persistent hypoxia. Randomised controlled trials on use of tocilizumab as rescue therapy in patients of severe COVID-19 pneumonia with hypoxia (PaO2/FiO2 less than 200) due to hyperinflammatory state, are warranted.

Diagnostic accuracy and inter-observer agreement with the CO-RADS lexicon for CT chest reporting in COVID-19.

PURPOSE: To measure the diagnostic accuracy and inter-observer agreement with the use of COVID-19 Reporting and Data System (CO-RADS) for detection of COVID-19 on CT chest imaging. METHODS: This retrospective study included 164 consecutive patients with clinical suspicion of COVID-19 in whom a CT chest examination was performed at a single institution between April 2020 and July 2020. Of them, 101 patients was RT-PCR positive for COVID-19. Six readers with varying radiological experience (two each of chest radiologists, general radiologists, and radiologists in training) independently assigned a CO-RADS assessment category for each CT chest study. The Fleiss' K was used to quantify inter-observer agreement. The inter-observer agreement was also assessed based on the duration of onset of symptoms to CT scan. ROC curve analysis was used to determine the diagnostic accuracy of CO-RADS. The area under curve was calculated to determine the reader accuracy for detection of COVID-19 lung involvement with RT-PCR as reference standards. The data sets were plotted in ROC space, and Youden's J statistic was calculated to determine the threshold cut-off CO-RADS category for COVID-19 positivity. RESULTS: There was overall moderate inter-observer agreement between all readers (Fleiss' K 0.54 [95% CI 0.54, 0.54]), with substantial agreement among chest radiologists (Fleiss' K 0.68 [95% CI 0.67, 0.68]), general radiologists (Fleiss' K 0.61 [95% CI 0.61, 0.61]), and moderate agreement among radiologists-in-training (Fleiss' K 0.56 [95% CI 0.56, 0.56]). There was overall moderate inter-observer agreement in early disease (stages 1 and 2), with cumulative Fleiss' K 0.45 [95% CI 0.45, 0.45]). The overall AUC for CO-RADS lexicon scheme to accurately diagnose COVID-19 yielded 0.92 (95% CI 0.91, 0.94) with strong concordance within and between groups, of chests radiologists with AUC of 0.91 (95% CI 0.88, 0.94), general radiologists with AUC 0.96 (95% CI 0.94, 0.98), and radiologists in training with AUC of 0.90 (95% CI 0.87, 0.94). For detecting COVID-19, ROC curve analysis yielded CO-RADS > 3 as the cut-off threshold with sensitivity 90% (95% CI 0.88, 0.93), and specificity of 87% (95% CI 0.83, 0.91). CONCLUSION: Readers across different levels of experience could accurately identify COVID-19 positive patients using the CO-RADS lexicon with moderate inter-observer agreement and high diagnostic accuracy.

Use of the COVID-19 Reporting and Data System (CO-RADS) classification and chest computed tomography involvement score (CT-IS) in COVID-19 pneumonia.

PURPOSE: The increasing tendency of chest CT usage throughout the COVID-19 epidemic requires new tools and a systematic scheme for diagnosing and assessing the lung involvement in Coronavirus Disease 2019 (COVID-19). To investigate the use of the COVID-19 Reporting and Data System (CO-RADS) classification and chest CT Involvement Score (CT-IS) in COVID-19 pneumonia. MATERIAL AND METHODS: This retrospective study enrolled 280 hospitalized patients diagnosed with COVID-19 pneumonia in a tertiary hospital in Turkey. All patients underwent non-contrast CT chest imaging. Two radiologists interpreted all CT images according to CO-RADS classification without knowing the clinical features, laboratory findings. We used CT involvement score (CT-IS) for assessing chest CT images of COVID-19 patients. Also, we examined the relationship between CT-IS and clinical outcomes in COVID-19 patients. RESULTS: Of the patients, 111(39.6%) had positive real-time reverse transcriptase-polymerase chain reaction (RT-PCR) results. CO-RADS 5 group patients had statistically significant positive RT-PCR results than the other groups (P < 0.001). All of the CO-RADS 2 group patients (30) had negative RT-PCR results. The mean total CT-IS in CO-RADS 2 group was 3.4 ± 2.8. The mean total CT-IS in CO-RADS 5 group was 8.2 ± 4.7. Total CT-IS was statistically significantly different among CO-RADS groups (P < 0.001). The mean total CT-IS was statistically significantly different between survivors and patients died of COVID-19 pneumonia (P < 0.001). CONCLUSIONS: CO-RADS is useful in detecting COVID-19 disease, even if RT-PCR testing is negative. CT-IS is also helpful as an imaging tool for evaluation of the severity and extent of COVID-19 pneumonia.

Clinical and radiological characteristics in patients with SARS-CoV-2-associated pneumonia. A descriptive study in a secondary care center.

INTRODUCTION: Real-time reverse-transcription polymerase chain reaction (RT-PCR) is the gold standard for establishing the diagnosis of coronavirus disease 2019 (COVID-19). Chest computed tomography (CCT), as a diagnostic complement, classifies tomographic findings according to the COVID-19 Reporting and Data System (CO-RADS). OBJECTIVE: To determine CCT sensitivity and specificity for COVID-19 diagnosis. METHODS: We reviewed RT-PCR results, as well as their respective CCTs. All CCTs were classified according to CO-RADS. CCT sensitivity and specificity were evaluated using the RT-PCR result that was closest to that of CCT as reference. RESULTS: We included 412 patients, out of whom 277 were males (46-70 years) and 130 were females (45-71 years); with 181 negative and 231 positive tests, a sensitivity of 92.15% and specificity of 79.32% were obtained. Mortality increased after six hospitalization days, in males and in CO-RADS 4, 5 and 6 in comparison with CO-RADS 1, 2 and 3. CONCLUSIONS: Early diagnosis plays a decisive role in the prognosis of SARS-CoV-2-associated pneumonia. Although RT-PCR is current gold standard, false negatives are common; for this reason, CCT helps to confirm suspected cases, even at early stages. This imaging technique is an accessible and fundamental study for classification, diagnosis and prognosis.

INTRODUCCIÓN: La reacción en cadena de la polimerasa con transcripción inversa en tiempo real (RT-PCR) es el estándar de oro para establecer el diagnóstico de enfermedad por coronavirus 2019 (COVID-19). La tomografía computarizada de tórax (TCT), como complemento diagnóstico, clasifica los hallazgos tomográficos de acuerdo con el sistema CO-RADS (COVID-19 Reporting and Data System). OBJETIVO: Determinar la sensibilidad y especificidad de la TCT para el diagnóstico de COVID-19. MÉTODOS: Consultamos los resultados de RT-PCR, así como sus respectivas TCT. Todas las TCT se clasificaron de según CO-RADS. Se evaluó sensibilidad y especificidad de la TCT utilizando el resultado de RT-PCR más cercano de TCT como referencia. RESULTADOS: Incluimos 412 pacientes, incluyendo 277 hombres (46-70 años) y 130 mujeres (45-71 años), con 181 pruebas negativas y 231 positivas; obteniendo sensibilidad del 92.15% y especificidad del 79.32%. La mortalidad aumentó después de seis días de hospitalización, en el sexo masculino y en CO-RADS 4, 5 y 6 en comparación con CO-RADS 1, 2 y 3. CONCLUSIONES: El diagnóstico temprano es decisivo en el pronóstico de la neumonía SARS CoV 2. Aunque la RT-PCR es el estándar de oro actual, los falsos negativos son frecuentes, por lo que la TCT ayuda a confirmar los casos sospechosos, incluso en etapas tempranas. Este estudio de imagen es un estudio accesible y fundamental para la clasificación, diagnóstico y pronóstico.

Overt hematochezia : A rare gastrointestinal presentation in patients with corona virus disease 2019.

World health care systems are affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and its associated disease, coronavirus disease 2019 (COVID-19). This new human pathogen mostly affects the respiratory system, but various extrapulmonary pathologies have been reported in the literature. It seems that the gastrointestinal system is one of the target organs for SARS-CoV- 2. Diarrhea as a long-term bowel symptom is not rare, although its occurrence is not as high as that of fever and cough.

Chest CT for triage during COVID-19 on the emergency department: myth or truth?

PURPOSE: We aimed to investigate the diagnostic performance of chest CT compared with first RT-PCR results in adult patients suspected of COVID-19 infection in an ED setting. We also constructed a predictive machine learning model based on chest CT and additional data to improve the diagnostic accuracy of chest CT. METHODS: This study's cohort consisted of 319 patients who underwent chest CT and RT-PCR testing at the ED. Patient characteristics, demographics, symptoms, vital signs, laboratory tests, and chest CT results (CO-RADS) were collected. With first RT-PCR as reference standard, the diagnostic performance of chest CT using the CO-RADS score was assessed. Additionally, a predictive machine learning model was constructed using logistic regression. RESULTS: Chest CT, with first RT-PCR as a reference, had a sensitivity, specificity, PPV, and NPV of 90.2%, 88.2%, 84.5%, and 92.7%, respectively. The prediction model with CO-RADS, ferritin, leucocyte count, CK, days of complaints, and diarrhea as predictors had a sensitivity, specificity, PPV, and NPV of 89.3%, 93.4%, 90.8%, and 92.3%, respectively. CONCLUSION: Chest CT, using the CO-RADS scoring system, is a sensitive and specific method that can aid in the diagnosis of COVID-19, especially if RT-PCR tests are scarce during an outbreak. Combining a predictive machine learning model could further improve the accuracy of diagnostic chest CT for COVID-19. Further candidate predictors should be analyzed to improve our model. However, RT-PCR should remain the primary standard of testing as up to 9% of RT-PCR positive patients are not diagnosed by chest CT or our machine learning model.

Patient Characteristics and Predictors of Pulmonary Embolism in Patients Infected with COVID - 19 in Upper Egypt.

Background: A little is known about the risk factors and predictors of pulmonary embolism (PE) in Coronavirus disease 2019 (Covid-19) infected patients. Therefore, we directed this study to investigate the predictors of PE in patients infected with Covid - 19 in Upper Egypt. Methods: We conducted a retrospective cohort study on 297 patients infected with COVID-19, aged ≥ 18 years old. Suspicion of COVID-19 infection was based on the World Health Organization (WHO) criteria and confirmed by nasal and pharyngeal swab for real-time reverse transcriptase-polymerase chain reaction (RT-PCR) analysis. The patient was also determined to have COVID-19 when CT results that were thought to be typical for COVID-19 and clinical data that were compatible were present. Results: PE was diagnosed in 18.2% of patients. We found that the incidence of PE was significantly higher in older patients, females, those with higher BMI, hypertensive patients, diabetics, and patients with co-morbidities. Also, PE was significantly higher in patients presented with dyspnea, chest pain, longer duration of symptoms at hospital admission, and lower oxygen concentration. The mean serum Hb level, platelet count, TLC and absolute lymphocytic count were markedly reduced in those who had PE. All the patients who developed PE had a CO-RADS scale five on their CT chest scan. Age > 65, BMI > 25, DM, and associated co-morbidities were the independent patients' characteristics associated with the development of PE after the multivariate regression analysis. Conclusion: PE is a common complication of Covid 19 infection. PE is associated with a variety of clinical and laboratory parameters in univariate analysis, but age > 65, BMI > 25, DM, and associated co-morbidities were the independent patients' characteristics associated with the development of PE in those infected with Covid-19.

Inter-observer Variability in the Analysis of CO-RADS Classification for COVID-19 Patients.

During the early stages of the pandemic, computed tomography (CT) of the chest, along with serological and clinical data, was frequently utilized in diagnosing COVID-19, particularly in regions facing challenges such as shortages of PCR kits. In these circumstances, CT scans played a crucial role in diagnosing COVID-19 and guiding patient management. The COVID-19 Reporting and Data System (CO-RADS) was established as a standardized reporting system for cases of COVID-19 pneumonia. Its implementation necessitates a high level of agreement among observers to prevent any potential confusion. This study aimed to assess the inter-observer agreement between physicians from different specialties with variable levels of experience in their CO-RADS scoring of CT chests for confirmed COVID-19 patients, and to assess the feasibility of applying this reporting system to those having little experience with it. All chest CT images of patients with positive RT-PCR tests for COVID-19 were retrospectively reviewed by seven observers. The observers were divided into three groups according to their type of specialty (three radiologists, three house officers, and one pulmonologist). The observers assessed each image and categorized the patients into five CO-RADS groups. A total of 630 participants were included in this study. The inter-observer agreement was almost perfect among the radiologists, substantial among a pulmonologist and the house officers, and moderate-to-substantial among the radiologists, the pulmonologist, and the house officers. There was substantial to almost perfect inter-observer agreement when reporting using the CO-RADS among observers with different experience levels. Although the inter-observer variability among the radiologists was high, it decreased compared to the pulmonologist and house officers. Radiologists, house officers, and pulmonologists applying the CO-RADS can accurately and promptly identify typical CT imaging features of lung involvement in COVID-19.

Metabolic characterization of structural lung changes in patients with findings suggestive of incidental COVID-19 pneumonia on 18F-FDG PET/CT. Pathophysiological insights from multimodal images obtained during the pandemic.

PURPOSE: To evaluate the metabolic uptake of different tomographic signs observed in patients with incidental structural findings suggestive of COVID-19 pneumonia through 18F-FDG PET/CT. MATERIALS AND METHODS: We retrospectively analyzed 596 PET/CT studies performed from February 21, 2020 to April 17, 2020. After excluding 37 scans (non-18F-FDG PET tracers and brain studies), we analyzed the metabolic activity of several structural changes integrated in the CO-RADS score using the SUVmax of multimodal studies with 18F-FDG. RESULTS: Forty-three patients with 18F-FDG PET/CT findings suggestive of COVID-19 pneumonia were included (mean age: 68±12.3 years, 22 male). SUVmax values were higher in patients with CO-RADS categories 5-6 than in those with lower CO-RADS categories (6.1±3.0 vs. 3.6±2.1, p=0.004). In patients with CO-RADS 5-6, ground-glass opacities, bilaterality and consolidations exhibited higher SUVmax values (p-values of 0.01, 0.02 and 0.01, respectively). Patchy distribution and crazy paving pattern were also associated with higher SUVmax (p-values of 0.002 and 0.01). After multivariate analysis, SUVmax was significantly associated with a positive structural diagnosis of COVID-19 pneumonia (odds ratio=0.63, 95% confidence interval=0.41-0.90; p=0.02). The ROC curve of the regression model intended to confirm or rule out the structural diagnosis of COVID-19 pneumonia showed an AUC of 0.77 (standard error=0.072, p=0.003). CONCLUSIONS: In those patients referred for standard oncologic and non-oncologic indications (43/559; 7.7%) during pandemic, imaging with 18F-FDG PET/CT is a useful tool during incidental detection of COVID-19 pneumonia. Several CT findings characteristic of COVID-19 pneumonia, specifically those included in diagnostic CO-RADS scores (5-6), were associated with higher SUVmax values.

Effects of Patient-Based Imaging Artifacts On CT Diagnosis of COVID-19 and Its Severity.

PURPOSE: To investigate the effects of patient-induced artifacts on the diagnostic performance of the COVID-19 Reporting and Data System (CO-RADS) and the computed tomography chest severity score (CT-SS). METHODS: A single-center retrospective analysis of patients aged 18 years and older who were admitted to the authors' hospital with laboratory-confirmed COVID-19 and underwent chest CT between July and November 2021 was conducted. Patients' chest CT scans were examined by 3 radiologists for CT-SS and CO-RADS classifications. Patient-based artifacts, including metal artifacts, incomplete projection artifacts, motion artifacts, and insufficient inspiration, were identified by 3 readers who were unaware of each other. For statistical analysis, interreader agreement was investigated using Fleiss kappa () agreement analysis. RESULTS: The study population included 549 patients with a median age of 66 years (IQR, 55-75 years), 321 (58.5%) of whom were men. According to the overall CO-RADS classification, the highest interreader agreement was in patients without CT artifacts ( = 0.924), while the lowest interreader agreement was in patients with motion artifacts ( = 0.613). For the CO-RADS 1 and 2 patient groups, insufficient inspiration decreased the interreader agreement most ( = 0.712 and = 0.250, respectively). For the CO-RADS 3, 4, and 5 patient groups, motion artifacts reduced the interreader agreement most ( = 0.464, = 0.453, and = 0.705, respectively). For total CT-SS, the highest kappa value was in patients without artifacts ( = 0.574), while the lowest kappa value was in patients with motion artifacts ( = 0.374). DISCUSSION: The CT technologist can avoid patient-induced artifacts by placing patients carefully on the CT table, giving patients necessary instructions before CT acquisition, and selecting optimal scanning parameters. The authors are not aware of another study in the literature investigating the effects of patient-based artifacts on interreader agreement of CO-RADS classification and CT-SS for COVID-19. CONCLUSION: CT artifacts degrade image quality and might lead to interreader disagreement of CO-RADS classification and CT-SS for patients with COVID-19.

Chest CT diagnostic potential as a tool for early detection of suspected COVID-19 cases in pandemic peaks.

INTRODUCTION: The emergence of severe acute respiratory syndrome coronavirus disease (COVID-19) in China at the end of 2019 caused a massive global outbreak that has become a major public health issue. AIM: Our aim was to investigate the diagnostic potential of chest CT in screening patients suspected of having COVID-19 in high-prevalence settings. MATERIALS AND METHODS: This is a real-life, prospective, observational study involving 260 patients. All patients received chest CT scan at the emergency department (ED) of Kaspela University Hospital, Plovdiv, Bulgaria and RT-PCR testing for suspected COVID-19 from March 27 to December 31, 2020. COVID-19 likelihood was assessed by assigning each CT scan to a particular category of the COVID-19 Reporting and Data System (CO-RADS). IBM SPSS v. 26 was used to process the data. RESULTS: The male-to-female distribution ratio was 1.4:1 - 150 (57.7%) males vs. 110 (42.3%) females (p=0.014). The median age was 55 yrs (range 46-65 yrs). Discharged patients were 247 (95.0%), the rest died in the COVID-19 intensive care unit. Males were 4.13 times more likely to be diagnosed with CO-RADS≥3 score than females. Increasing age was associated with an increased likelihood of being classified with higher CO-RADS scores. The ROC curves analysis demonstrated that CO-RADS ≥3 was the optimal cutoff for discrimi-nating between a positive and negative PCR (Youden's index J=0.67), with an AUC of 0.825 (95% CI 0.72-0.93), sensitivity of 91.9% (95% CI 87.7%-95.1%), specificity of 75.0% (95% CI 53.3%-90.2%) and accuracy of 76.4% (95% CI 70.7%-81.4%). CONCLUSIONS: The results of this study reveal that a CT examination can provide a quick and accurate diagnosis of patients with sus-pected COVID-19 infection, whereas the PCR test is time-consuming, and the delay in receiving results can be substantial when the incidence curve begins to grow rapidly.