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Chest CT for early detection and management of coronavirus disease (COVID-19): a report of 314 patients admitted to Emergency Department with suspected pneumonia.

ABSTRACT: PURPOSE:The purpose of our study was to assess the potential role of chest CT in the early detection of COVID-19 pneumonia and to explore its role in patient management in an adult Italian population admitted to the Emergency Department. METHODS:Three hundred and fourteen patients presented with clinically suspected COVID-19, from March 3 to 23, 2020, were evaluated with PaO2/FIO2 ratio from arterial blood gas, RT-PCR assay from nasopharyngeal swab sample and chest CT. Patients were classified as COVID-19 negative and COVID-19 positive according to RT-PCR results, considered as a reference. Images were independently evaluated by two radiologists blinded to the RT-PCR results and classified as "CT positive" or "CT negative" for COVID-19, according to CT findings. RESULTS:According to RT-PCR results, 152 patients were COVID-19 negative (48%) and 162 were COVID-19 positive (52%). We found substantial agreement between RT-PCR results and CT findings (p?

SUBMITTER: Gaia C

PROVIDER: S-EPMC7388438 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Chest CT for early detection and management of coronavirus disease (COVID-19): a report of 314 patients admitted to Emergency Department with suspected pneumonia.

Gaia Cartocci C Maria Chiara Colaiacomo C Silvia Lanciotti L Chiara Andreoli A Maria Luisa De Cicco C Giulia Brachetti B Silvia Pugliese P Lucia Capoccia C Alessandra Tortora T Annarita Scala S Cristina Valentini V Maria Almberger A Maria Rosaria D'Aprile D Giacinta Avventurieri A Riccardo Giura G Zaher Kharrub K Andrea Leonardi L Maddalena Boccia B Catalano Carlo C Paolo Ricci R

La Radiologia medica 20200729 10

<h4>Purpose</h4>The purpose of our study was to assess the potential role of chest CT in the early detection of COVID-19 pneumonia and to explore its role in patient management in an adult Italian population admitted to the Emergency Department.<h4>Methods</h4>Three hundred and fourteen patients presented with clinically suspected COVID-19, from March 3 to 23, 2020, were evaluated with PaO2/FIO2 ratio from arterial blood gas, RT-PCR assay from nasopharyngeal swab sample and chest CT. Patients we ...[more]

PMID: 32729028

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Project description:IntroductionCommunity-acquired pneumonia (CAP) requires prompt treatment, but its diagnosis is complex. Improvement of bacterial CAP diagnosis by biomarkers has been evaluated using chest X-ray infiltrate as the CAP gold standard, producing conflicting results. We analyzed the diagnostic accuracy of biomarkers in suspected CAP adults visiting emergency departments for whom CAP diagnosis was established by an adjudication committee which founded its judgment on a systematic multidetector thoracic CT scan.MethodsIn an ancillary study of a multi-center prospective study evaluating the impact of systematic thoracic CT scan on CAP diagnosis, sensitivity and specificity of C-reactive protein (CRP) and procalcitonin (PCT) were evaluated. Systematic nasopharyngeal multiplex respiratory virus PCR was performed at inclusion. An adjudication committee classified CAP diagnostic probability on a 4-level Likert scale, based on all available data.ResultsTwo hundred patients with suspected CAP were analyzed. The adjudication committee classified 98 patients (49.0 %) as definite CAP, 8 (4.0 %) as probable, 23 (11.5 %) as possible and excluded in 71 (35.5 %, including 29 patients with pulmonary infiltrates on chest X-ray). Among patients with radiological pulmonary infiltrate, 23 % were finally classified as excluded. Viruses were identified by PCR in 29 % of patients classified as definite. Area under the curve was 0.787 [95 % confidence interval (95 % CI), 0.717 to 0.857] for CRP and 0.655 (95 % CI, 0.570 to 0.739) for PCT to detect definite CAP. CRP threshold at 50 mg/L resulted in a positive predictive value of 0.76 and a negative predictive value of 0.75. No PCT cut-off resulted in satisfactory positive or negative predictive values. CRP and PCT accuracy was not improved by exclusion of the 25 (25.5 %) definite viral CAP cases.ConclusionsFor patients with suspected CAP visiting emergency departments, diagnostic accuracy of CRP and PCT are insufficient to confirm the CAP diagnosis established using a gold standard that includes thoracic CT scan. Diagnostic accuracy of these biomarkers is also insufficient to distinguish bacterial CAP from viral CAP.Trial registrationClinicalTrials.gov registry NCT01574066 (February 7, 2012).

Project description:ObjectivesTo utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents.MethodsA deep learning algorithm consisted of lesion detection, segmentation, and location was trained and validated in 14,435 participants with chest CT images and definite pathogen diagnosis. The algorithm was tested in a non-overlapping dataset of 96 confirmed COVID-19 patients in three hospitals across China during the outbreak. Quantitative detection performance of the model was compared with three radiological residents with two experienced radiologists' reading reports as reference standard by assessing the accuracy, sensitivity, specificity, and F1 score.ResultsOf 96 patients, 88 had pneumonia lesions on CT images and 8 had no abnormities on CT images. For per-patient basis, the algorithm showed superior sensitivity of 1.00 (95% confidence interval (CI) 0.95, 1.00) and F1 score of 0.97 in detecting lesions from CT images of COVID-19 pneumonia patients. While for per-lung lobe basis, the algorithm achieved a sensitivity of 0.96 (95% CI 0.94, 0.98) and a slightly inferior F1 score of 0.86. The median volume of lesions calculated by algorithm was 40.10 cm3. An average running speed of 20.3 s ± 5.8 per case demonstrated the algorithm was much faster than the residents in assessing CT images (all p < 0.017). The deep learning algorithm can also assist radiologists make quicker diagnosis (all p < 0.0001) with superior diagnostic performance.ConclusionsThe algorithm showed excellent performance in detecting COVID-19 pneumonia on chest CT images compared with resident radiologists.Key points• The higher sensitivity of deep learning model in detecting COVID-19 pneumonia were found compared with radiological residents on a per-lobe and per-patient basis. • The deep learning model improves diagnosis efficiency by shortening processing time. • The deep learning model can automatically calculate the volume of the lesions and whole lung.

Project description:BackgroundPatients commonly present to primary care services with upper and lower respiratory tract infections, and guidelines to help physicians investigate and treat acute cough due to suspected pneumonia and influenza are needed.MethodsA systematic search was carried out with eight patient, intervention, comparison, outcome questions related to acute cough due to suspected pneumonia or influenza.ResultsThere was a lack of randomized controlled trials in the setting of outpatients presenting with acute cough due to suspected pneumonia or influenza who were not hospitalized. Both clinical suggestions and research recommendations were made on the evidence available and CHEST Expert Cough Panel advice.ConclusionsFor outpatient adults with acute cough due to suspected pneumonia, we suggest the following clinical symptoms and signs are suggestive of pneumonia: cough; dyspnea; pleural pain; sweating, fevers, or shivers; aches and pains; temperature ? 38°C; tachypnea; and new and localizing chest examination signs. Those suspected of having pneumonia should undergo chest radiography to improve diagnostic accuracy. Although the measurement of C-reactive protein levels strengthens both the diagnosis and exclusion of pneumonia, there was no added benefit of measuring procalcitonin levels in this setting. We suggest that there is no need for routine microbiological testing. We suggest the use of empiric antibiotics according to local and national guidelines when pneumonia is suspected in settings in which imaging cannot be performed. Where there is no clinical or radiographic evidence of pneumonia, we do not suggest the routine use of antibiotics. There is insufficient evidence to make recommendations for or against specific nonantibiotic, symptomatic therapies. Finally, for outpatient adults with acute cough and suspected influenza, we suggest that initiating antiviral treatment (according to Centers for Disease Control and Prevention advice) within 48 hours of symptoms could be associated with decreased antibiotic use and hospitalization and improved outcomes.

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Chest CT for early detection and management of coronavirus disease (COVID-19): a report of 314 patients admitted to Emergency Department with suspected pneumonia.

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Chest CT for early detection and management of coronavirus disease (COVID-19): a report of 314 patients admitted to Emergency Department with suspected pneumonia.

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