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1.
Eur Respir Rev ; 31(164)2022 Jun 30.
Article in English | MEDLINE | ID: covidwho-1928158

ABSTRACT

The incidental discovery of pre-clinical interstitial lung disease (ILD) has led to the designation of interstitial lung abnormalities (ILA), a radiological entity defined as the incidental finding of computed tomography (CT) abnormalities affecting more than 5% of any lung zone. Two recent documents have redefined the borders of this entity and made the recommendation to monitor patients with ILA at risk of progression. In this narrative review, we will focus on some of the limits of the current approach, underlying the potential for progression to full-blown ILD of some patients with ILA and the numerous links between subpleural fibrotic ILA and idiopathic pulmonary fibrosis (IPF). Considering the large prevalence of ILA in the general population (7%), restricting monitoring only to cases considered at risk of progression appears a reasonable approach. However, this suggestion should not prevent pulmonary physicians from pursuing an early diagnosis of ILD and timely treatment where appropriate. In cases of suspected ILD, whether found incidentally or not, the pulmonary physician is still required to make a correct ILD diagnosis according to current guidelines, and eventually treat the patient accordingly.


Subject(s)
Idiopathic Pulmonary Fibrosis , Lung Diseases, Interstitial , Disease Progression , Humans , Idiopathic Pulmonary Fibrosis/diagnostic imaging , Idiopathic Pulmonary Fibrosis/epidemiology , Incidental Findings , Lung/diagnostic imaging , Lung Diseases, Interstitial/diagnosis , Lung Diseases, Interstitial/epidemiology , Lung Diseases, Interstitial/therapy , Tomography, X-Ray Computed
2.
J Pers Med ; 12(4)2022 Apr 12.
Article in English | MEDLINE | ID: covidwho-1785791

ABSTRACT

Due to the increasing number of COVID-19-infected and vaccinated individuals, radiologists continue to see patients with COVID-19 pneumonitis and recall pneumonitis, which could result in additional workups and false-positive results. Moreover, cancer patients undergoing immunotherapy may show therapy-related pneumonitis during imaging management. This is otherwise known as immune checkpoint inhibitor-related pneumonitis. Following on from this background, radiologists should seek to know their patients' COVID-19 infection and vaccination history. Knowing the imaging features related to COVID-19 infection and vaccination is critical to avoiding misleading results and alarmism in patients and clinicians.

3.
Tomography ; 8(2): 1041-1051, 2022 04 06.
Article in English | MEDLINE | ID: covidwho-1776350

ABSTRACT

Since the first report of the outbreak in Wuhan, China in December 2019, as of 1 September 2021, the World Health Organization has confirmed more than 239 million cases of the novel coronavirus (SARS-CoV-2) infectious disease named coronavirus disease 2019 (COVID-19), with more than 4.5 million deaths. Although SARS-CoV-2 mainly involves the respiratory tract, it is considered to be a systemic disease. Imaging plays a pivotal role in the diagnosis of all manifestations of COVID-19 disease, as well as its related complications. The figure of the radiologist is fundamental in the management and treatment of the patient. The authors try to provide a systematic approach based on an imaging review of major multi-organ manifestations of this infection.


Subject(s)
COVID-19 , Disease Outbreaks , Emergencies , Humans , SARS-CoV-2 , World Health Organization
4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321820

ABSTRACT

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether chest X-ray (CXR) can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. CXR is a radiological technique that compared to computed tomography (CT) it is simpler, faster, more widespread and it induces lower radiation dose. We present a dataset including data collected from 820 patients by six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. We investigate the potential of artificial intelligence to predict the prognosis of such patients, distinguishing between severe and mild cases, thus offering a baseline reference for other researchers and practitioners. To this goal, we present three approaches that use features extracted from CXR images, either handcrafted or automatically by convolutional neuronal networks, which are then integrated with the clinical data. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.

5.
J Pers Med ; 11(10)2021 Sep 30.
Article in English | MEDLINE | ID: covidwho-1444254

ABSTRACT

OBJECTIVE: To report an overview and update on Artificial Intelligence (AI) and COVID-19 using chest Computed Tomography (CT) scan and chest X-ray images (CXR). Machine Learning and Deep Learning Approaches for Diagnosis and Treatment were identified. METHODS: Several electronic datasets were analyzed. The search covered the years from January 2019 to June 2021. The inclusion criteria were studied evaluating the use of AI methods in COVID-19 disease reporting performance results in terms of accuracy or precision or area under Receiver Operating Characteristic (ROC) curve (AUC). RESULTS: Twenty-two studies met the inclusion criteria: 13 papers were based on AI in CXR and 10 based on AI in CT. The summarized mean value of the accuracy and precision of CXR in COVID-19 disease were 93.7% ± 10.0% of standard deviation (range 68.4-99.9%) and 95.7% ± 7.1% of standard deviation (range 83.0-100.0%), respectively. The summarized mean value of the accuracy and specificity of CT in COVID-19 disease were 89.1% ± 7.3% of standard deviation (range 78.0-99.9%) and 94.5 ± 6.4% of standard deviation (range 86.0-100.0%), respectively. No statistically significant difference in summarized accuracy mean value between CXR and CT was observed using the Chi square test (p value > 0.05). CONCLUSIONS: Summarized accuracy of the selected papers is high but there was an important variability; however, less in CT studies compared to CXR studies. Nonetheless, AI approaches could be used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, COVID-19 diagnosis, and disease management.

6.
Med Image Anal ; 74: 102216, 2021 12.
Article in English | MEDLINE | ID: covidwho-1373186

ABSTRACT

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether artificial intelligence working with chest X-ray (CXR) scans and clinical data can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. Indeed, further to induce lower radiation dose than computed tomography (CT), CXR is a simpler and faster radiological technique, being also more widespread. In this respect, we present three approaches that use features extracted from CXR images, either handcrafted or automatically learnt by convolutional neuronal networks, which are then integrated with the clinical data. As a further contribution, this work introduces a repository that collects data from 820 patients enrolled in six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, suggesting that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.


Subject(s)
COVID-19 , Artificial Intelligence , Humans , Italy , SARS-CoV-2 , X-Rays
7.
J Pers Med ; 11(7)2021 Jul 06.
Article in English | MEDLINE | ID: covidwho-1302361

ABSTRACT

PURPOSE: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. MATERIALS AND METHODS: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. RESULTS: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8-21 days (after hospital admission) was an "advanced period" with the most severe lung disease involvement. After the extent of involvement started to decrease-particularly after 21 days-the absorption was more obvious. CONCLUSIONS: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.

8.
Int J Environ Res Public Health ; 18(12)2021 06 14.
Article in English | MEDLINE | ID: covidwho-1270052

ABSTRACT

The infection caused by novel beta-coronavirus (SARS-CoV-2) was officially declared a pandemic by the World Health Organization in March 2020. However, in the last 20 years, this has not been the only viral infection to cause respiratory tract infections leading to hundreds of thousands of deaths worldwide, referring in particular to severe acute respiratory syndrome (SARS), influenza H1N1 and Middle East respiratory syndrome (MERS). Although in this pandemic period SARS-CoV-2 infection should be the first diagnosis to exclude, many other viruses can cause pulmonary manifestations and have to be recognized. Through the description of the main radiological patterns, radiologists can suggest the diagnosis of viral pneumonia, also combining information from clinical and laboratory data.


Subject(s)
COVID-19 , Influenza A Virus, H1N1 Subtype , Influenza, Human , Middle East Respiratory Syndrome Coronavirus , Pneumonia, Viral , Humans , SARS-CoV-2
9.
Int J Environ Res Public Health ; 18(11)2021 05 21.
Article in English | MEDLINE | ID: covidwho-1247989

ABSTRACT

Breast cancer (BC) is the cancer with the highest incidence in women in the world. In this last period, the COVID-19 pandemic has caused in many cases a drastic reduction of routine breast imaging activity due to the combination of various factors. The survival of BC is directly proportional to the earliness of diagnosis, and especially during this period, it is at least fundamental to remember that a diagnostic delay of even just three months could affect BC outcomes. In this article we will review the state of the art of breast imaging, starting from morphological imaging, i.e., mammography, tomosynthesis, ultrasound and magnetic resonance imaging and contrast-enhanced mammography, and their most recent evolutions; and ending with functional images, i.e., magnetic resonance imaging and contrast enhanced mammography.


Subject(s)
Breast Neoplasms , COVID-19 , Breast Neoplasms/diagnostic imaging , Delayed Diagnosis , Female , Humans , Magnetic Resonance Imaging , Mammography , Pandemics , SARS-CoV-2
10.
Jpn J Radiol ; 39(8): 721-732, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1201614

ABSTRACT

Thoracic imaging is fundamental in the diagnostic route of Coronavirus disease 2019 (COVID-19) especially in patients admitted to hospitals. In particular, chest computed tomography (CT) has a key role in identifying the typical features of the infection. Ground-glass opacities (GGO) are one of the main CT findings, but their presence is not specific for this viral pneumonia. In fact, GGO is a radiological sign of different pathologies with both acute and subacute/chronic clinical manifestations. In the evaluation of a subject with focal or diffuse GGO, the radiologist has to know the patient's medical history to obtain a valid diagnostic hypothesis. The authors describe the various CT appearance of GGO, related to the onset of symptoms, focusing also on the ancillary signs that can help radiologist to obtain a correct and prompt diagnosis.


Subject(s)
COVID-19 , Lung , COVID-19/diagnostic imaging , Diagnosis, Differential , Humans , Lung/diagnostic imaging , Retrospective Studies , SARS-CoV-2
11.
Radiol Med ; 126(5): 722-728, 2021 May.
Article in English | MEDLINE | ID: covidwho-1037984

ABSTRACT

BACKGROUND: Preliminary reports suggest a hypercoagulable state in COVID-19. Deep vein thrombosis (DVT) is perceived as a frequent finding in hospitalized COVID-19 patients, but data describing the prevalence of DVT are lacking. OBJECTIVES: We aimed to report the prevalence of DVT in COVID-19 patients in general wards, blinded to symptoms/signs of disease, using lower extremities duplex ultrasound (LEDUS) in random patients. We tested the association of DVT with clinical, laboratory and inflammatory markers and also reported on the secondary endpoint of in-hospital mortality. PATIENTS/METHODS: n  = 263 COVID-19 patients were screened with LEDUS between March 01, 2020 and April 05, 2020 out of the overall n = 1012 admitted with COVID-19. RESULTS: DVT was detected in n = 67 screened patients (25.5%), n = 41 patients (15.6%) died during the index hospitalization. Multiple logistic regression demonstrated that only C-reactive protein (odds ratio 1.009, 95% CI 1.004-1.013, p < 0.001) was independently associated with the presence of DVT at LEDUS. Both age (odds ratio 1.101, 95% CI 1.054-1.150, p < 0.001) and C-reactive protein (odds ratio 1.012, 95% CI 1.006-1.018, p < 0.001) were instead significantly independently associated with in-hospital mortality. CONCLUSIONS: The main study finding is that DVT prevalence in COVID-19 patients admitted to general wards is 25.5%, suggesting it may be reasonable to screen COVID-19 patients for this potentially severe but treatable complication, and that inflammation, measured with serum C-reactive protein, is the main variable associated with the presence of DVT, where all other clinical or laboratory variables, age or D-dimer included, are instead not independently associated with DVT.


Subject(s)
COVID-19/complications , Venous Thrombosis/epidemiology , Venous Thrombosis/etiology , Aged , COVID-19 Testing , Cross-Sectional Studies , Female , Hospitals , Humans , Lower Extremity/diagnostic imaging , Male , Middle Aged , Prevalence , Ultrasonography, Doppler, Duplex , Venous Thrombosis/diagnosis
12.
Radiol Med ; 126(5): 661-668, 2021 May.
Article in English | MEDLINE | ID: covidwho-1006390

ABSTRACT

PURPOSE: The aims of our study are: (1) to estimate admission chest X-ray (CXR) accuracy during the descending phase of pandemic; (2) to identify specific CXR findings strictly associated with COVID-19 infection; and (3) to correlate lung involvement of admission CXR with patients' outcome. MATERIALS AND METHODS: We prospectively evaluated the admission CXR of 327 patients accessed to our institute during the Italian pandemic descending phase (April 2020). For each CXR were searched ground glass opacification (GGO), consolidation (CO), reticular-nodular opacities (RNO), nodules, excavations, pneumothorax, pleural effusion, vascular congestion and cardiac enlargement. For lung alterations was defined the predominance (upper or basal, focal or diffuse, central or peripheric, etc.). Then radiologists assessed whether CXRs were suggestive or not for COVID-19 infection. For COVID-19 patients, a prognostic score was applied and correlated with the patients' outcome. RESULTS: CXR showed 83% of specificity and 60% of sensitivity. GGO, CO, RNO and a peripheric, diffuse and basal prevalence showed good correlation with COVID-19 diagnosis. A logistic regression analysis pointed out GGO and a basal or diffuse distribution as independent predictors of COVID-19 diagnosis. The prognostic score showed good correlation with the patients' outcome. CONCLUSION: In our study, admission CXR showed a fair specificity and a good correlation with patients' outcome. GGO and others CXR findings showed a good correlation with COVID-19 diagnosis; besides GGO a diffuse or bibasal distribution resulted in independent variables highly suggestive for COVID-19 infection thus enabling radiologists to signal to clinicians radiologically suspect patients during the pandemic descending phase.


Subject(s)
COVID-19/diagnostic imaging , Emergency Service, Hospital , Radiography, Thoracic , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Correlation of Data , Female , Hospitalization , Humans , Italy/epidemiology , Male , Middle Aged , Prospective Studies , Young Adult
13.
Radiol Med ; 126(4): 570-576, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-947057

ABSTRACT

PURPOSE: Cerebrovascular disease (CVD) is considered a major risk factor for fatal outcome in COVID-19. We aimed to evaluate the possible association between computed tomography (CT) signs of chronic CVD and mortality in infected patients. MATERIALS AND METHODS: We performed a double-blind retrospective evaluation of the cerebral CT scans of 83 COVID-19 patients looking for CT signs of chronic CVD. We developed a rapid visual score, named CVD-CT, which summarized the possible presence of parietal calcifications and dolichosis, with or without ectasia, of intracranial arteries, areas of chronic infarction and leukoaraiosis. Statistical analysis was carried out with weighted Cohen's K test for inter-reader agreement and logistic regression to evaluate the association of in-hospital mortality with CVD-CT, chest X-ray (CXR) severity score (Radiographic Assessment of Lung Edema-RALE) for radiological assessment of pulmonary disease, sex and age. RESULTS: CVD-CT (odds ratio 1.6, 95% C.I. 1.2-2.1, p = 0.001) was associated with increased risk of mortality. RALE showed an almost significant association (odds ratio 1.05, 95% C.I. 1-1.1, p 0.06), whereas age and sex did not. CONCLUSION: CVD-CT is associated with risk of mortality in COVID-19 patients. The presence of CT signs of chronic CVD may be correlated to a condition of fragility of the circulatory system, which constitutes a key risk factor for death in infected patients.


Subject(s)
COVID-19/diagnostic imaging , COVID-19/mortality , Cerebrovascular Disorders/diagnostic imaging , Cerebrovascular Disorders/virology , Adult , Aged , Aged, 80 and over , COVID-19/complications , Cerebrovascular Disorders/mortality , Double-Blind Method , Edema/diagnostic imaging , Female , Humans , Lung/diagnostic imaging , Male , Middle Aged , Retrospective Studies , Risk Assessment/methods , SARS-CoV-2 , Tomography, X-Ray Computed
14.
International Journal of Environmental Research and Public Health ; 17(18):6914, 2020.
Article | MDPI | ID: covidwho-783872

ABSTRACT

Purpose: To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. Materials and methods: We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States;(2) Myrian, Intrasense, France;(3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Results: Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Conclusions: Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity;however, a great variability among quantitative measurements provided by computer tools should be considered.

15.
Acta Biomed ; 91(8-S): 51-59, 2020 07 13.
Article in English | MEDLINE | ID: covidwho-782628

ABSTRACT

Novel beta-coronavirus (2019-nCoV) is the cause of Coronavirus disease-19 (COVID-19), and on March 12th 2020, the World Health Organization defined COVID-19 as a controllable pandemic. Currently, the 2019 novel coronavirus (SARS-CoV-2) can be identified by virus isolation or viral nucleic acid detection; however, false negatives associated with the nucleic acid detection provide a clinical challenge. Imaging examination has become the indispensable means not only in the early detection and diagnosis but also in monitoring the clinical course, evaluating the disease severity, and may be presented as an important warning signal preceding the negative RT-PCR test results. Different radiological modalities can be used in different disease settings. Radiology Departments must be nimble in implementing operational changes to ensure continued radiology services and protect patients and staff health.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Diagnostic Imaging/standards , Pandemics , Pneumonia, Viral/diagnosis , Practice Guidelines as Topic , Radiography/standards , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Coronavirus Infections/epidemiology , Humans , Pneumonia, Viral/epidemiology , Reproducibility of Results , SARS-CoV-2
16.
Eur Radiol ; 30(12): 6635-6644, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-652558

ABSTRACT

OBJECTIVES: To perform an online survey aimed at evaluating the impact of COVID-19 on Italian radiology departments. METHODS: We launched a survey composed of 25 questions about how COVID-19 has changed the safety and organization of daily activity in Italian radiology units. RESULTS: A total of 2136/10,564 (20.2%) radiologists of the Italian Society of Medical and Interventional Radiology participated. Two-thirds performed at least one diagnostic/interventional procedure on COVID-19 patients. The 88.1% reported a reduction in the elective imaging volumes, with US, mammography, and MRI having shown the greater decrease (41.1%, 23.9%, and 21.1%, respectively). In 69.6% of cases, institutions had trouble getting personal protective equipment (PPE), especially public hospitals and southern institutions. Less than 30% of participants were subjected to RT-PCR swab test, although 81.5% believed that it should be done on all health workers and 70% suggested it as the most important measure to improve safety at work. Slightly more than half of participants declared to work safely and felt to be adequately protected by their institutions. Up to 20% of northern participants were redeployed to clinical services. The first imaging examination performed by admitted COVID-19 patients was chest radiography in 76.3% of cases. Almost half of participants reported that less than 30% of health workers were infected in their radiology department, with higher rates in northern regions and public institutions. CONCLUSIONS: This snapshot of the current situation in Italian radiology departments could be used to harmonize the organization of working activity in order to safely and effectively face this pandemic. KEY POINTS: • More than two-thirds of institutions had trouble getting PPE for health workers, with public hospitals and southern institutions that presented more procurement problems • A substantial drop of imaging volumes was observed in the vast majority of Italian radiology departments, mostly due to the decrease of ultrasound, mammography, and MRI, especially in private practice were working activity was stopped in 13.3% of institutions • RT-PCR swab to health workers was reported as the most suggested measure by Italian radiologists to improve safety at work, as more than 80% of them believed that it should be performed to all health workers, although less than 30% were subjected to this test.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Emergencies , Emergency Service, Hospital/statistics & numerical data , Pandemics , Pneumonia, Viral/diagnosis , Radiologists/statistics & numerical data , Adult , COVID-19 , Coronavirus Infections/epidemiology , Female , Humans , Italy/epidemiology , Male , Middle Aged , Personal Protective Equipment , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Surveys and Questionnaires
17.
Radiol Med ; 125(8): 730-737, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-591499

ABSTRACT

AIM: The purpose of this study is to describe the main chest radiological features (CXR) of COVID-19 and correlate them with clinical outcome. MATERIALS AND METHODS: This is a retrospective study involving patients with clinical-epidemiological suspect of COVID-19 infection, who performed CXRs at the emergency department (ED) of our University Hospital from March 1 to March 31, 2020. All patients performed RT-PCR nasopharyngeal and throat swab, CXR at the ED and clinical-epidemiological data. RT-PCR results were considered the reference standard. The final outcome was expressed as discharged or hospitalized patients into a medicine department or intensive care unit (ICU). RESULTS: Patients that had a RT-PCR positive for COVID-19 infection were 234 in total: 153 males (65.4%) and 81 females (34.6%), with a mean age of 66.04 years (range 18-97 years). Thirteen CXRs were negative for radiological thoracic involvement (5.6%). The following alterations were more commonly observed: 135 patients with lung consolidations (57.7%), 147 (62.8%) with GGO, 55 (23.5%) with nodules and 156 (66.6%) with reticular-nodular opacities. Patients with consolidations and GGO coexistent in the same radiography were 35.5% of total. Peripheral (57.7%) and lower zone distribution (58.5%) were the most common predominance. Moreover, bilateral involvement (69.2%) was most frequent than unilateral one. Baseline CXR sensitivity in our experience is about 67.1%. The most affected patients were especially males in the age group 60-79 years old (45.95%, of which 71.57% males). RALE score was slightly higher in male than in female patients. ANOVA with Games-Howell post hoc showed significant differences of RALE scores for group 1 vs 3 (p < 0.001) and 2 vs 3 (p = 0.001). Inter-reader agreement in assigning RALE score was very good (ICC: 0.92-with 95% confidence interval 0.88-0.95). CONCLUSION: In COVID-19, CXR shows patchy or diffuse reticular-nodular opacities and consolidation, with basal, peripheral and bilateral predominance. In our experience, baseline CXR had a sensitivity of 68.1%. The RALE score can be used in the emergency setting as a quantitative method of the extent of SARS-CoV-2 pneumonia, correlating with an increased risk of ICU admission.


Subject(s)
Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiography, Thoracic , Adolescent , Adult , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Emergency Service, Hospital , Female , Humans , Italy , Male , Middle Aged , Pandemics , Retrospective Studies , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2 , Sensitivity and Specificity
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