Literature DB >> 32618262

Feasibility, Reproducibility, and Clinical Validity of a Quantitative Chest X-Ray Assessment for COVID-19.

Marcello A Orsi1, Giancarlo Oliva1, Tahereh Toluian2, Carlo Valenti Pittino2, Marta Panzeri3, Michaela Cellina1.   

Abstract

Chest X-ray (CXR) is an essential first-line tool in COVID-19 pneumonia diagnosis and management. Our study aimed at assessing 1) CXR manifestations, frequency, and distribution; 2) the feasibility and repeatability of a CXR severity score; and 3) the correlation between the CXR severity score and clinical and laboratory parameters. We reviewed baseline CXRs and clinical data of consecutive patients who presented to our emergency department and resulted positive at SARS-CoV-2 reverse transcriptase-PCR oropharyngeal swab test from March 1, 2020 to April 6, 2020. Lung abnormalities and their distribution were analyzed. A score of CXR severity was assigned by two radiologists, independently, according to the extent of lung involvement, with a maximum score of 8 for CXR. Correlations between the CXR score and the clinical data were assessed. One hundred fifty-five patients were included; 143/155 (92%) were positive at baseline CXR. Ground-glass opacity was the most common finding (141/143, 99%). Involvement was mainly bilateral (96/143, 67%), with peripheral distribution (79/143, 55%). The mean CXR severity score was 3.3 (±2); interobserver agreement was excellent, with a Cohen's K correlation coefficient of 0.901. The CXR score showed a significant positive correlation with C-reactive protein, lactate dehydrogenase, and fever duration, and a negative correlation with oxygen saturation. Chest X-ray findings are in line with those reported by computed tomography studies. The use of a visual CXR score, easy to assess and highly reproducible, can reflect the clinical severity and help the patients' management.

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Mesh:

Year:  2020        PMID: 32618262      PMCID: PMC7410416          DOI: 10.4269/ajtmh.20-0535

Source DB:  PubMed          Journal:  Am J Trop Med Hyg        ISSN: 0002-9637            Impact factor:   2.345


INTRODUCTION

From its outbreak in Wuhan, Hubei Province, China, COVID-19 spread worldwide, with 5 million confirmed cases, on May 22.[1] Pneumonia represents its most common manifestation; therefore, chest computed tomography (CT) has taken on an important role, in the diagnosis, follow-up, and therapy efficacy evaluation of COVID-19 disease.[2-5] Because of the constantly increasing numbers of positive patients, the execution of chest CT in all patients suspected or positive for COVID-19 infection is not feasible, because of the overwork in radiology departments and the need to designate a CT machine dedicated to COVID-19–suspected or positive patients only, with strict infection control protocols.[6] The American College of Radiology[7] recommends the use of chest CT only in selected hospitalized symptomatic patients and advises the use of a portable X-ray machine to avoid moving patients and to minimize the risk of cross infection. Although chest X-ray (CXR) might have limited sensitivity for COVID-19 pneumonia, because it could miss subtle ground-glass opacifications (GGOs), it is important for the follow-up, evaluation of potential supervening complications, and the first-line evaluation of patients with a high pretest odds of COVID-19 pneumonia.[8] Moreover, we have to consider that COVID-19 is rapidly spreading also in developing countries, where healthcare systems are weaker, and the availability of CT scanner is poor, and COVID-19 could potentially have the greatest impact.[9] Thanks to its wide availability, quick execution, and acquisition at the patient’s bed, CXR represents a cheap first-line tool in the assessment of lung parenchyma abnormalities, also in COVID-19 patients. The appropriate use of CXR on arrival in the emergency department (ED) has been successful in speeding up the management of patients.[10] The recent radiological literature has been focused on chest CT findings of COVID-19 pneumonia, whereas, to the best of our knowledge, only a few data are available on the radiographic appearance of this infection.[11-13] Standardized quantitative reporting could be useful to define the disease severity and help clinical management. Therefore, our study aimed at assessing 1) the CXR manifestations of COVID-19 infection, their frequency, and distribution; 2) the repeatability of the CXR severity score from Wong et al.[11]; and 3) the correlation between the CXR severity score and clinical and laboratory parameters.

MATERIALS AND METHODS

This retrospective study was approved by our Institutional Review Board; patients’ consent was obtained.

Patients’ clinical and laboratory data.

We reviewed baseline CXRs, clinical data, and blood tests of consecutive patients admitted to our ED from March 1, 2020 to April 6, 2020, who complained symptoms suspected for COVID-19 infection (cough, fever, or dyspnea), with confirmed COVID-19 positivity reverse transcriptase–PCR (RT-PCR) test from the oropharyngeal swab, carried out in the first 5 days from admission. Inclusion criteria were as follows: patients age > 18 years; RT-PCR testing positive result; and availability of complete clinical data and blood test analysis. For each patient, the following data were collected by two radiology residents in consensus, under the supervision of an experienced radiologist, from our ED electronic database: symptoms on ED admission, oxygen saturation (SpO2), temperature (in Celsius degrees), days from the onset of fever, lactate dehydrogenase (LDH), C-reactive protein (CRP), and comorbidities (diabetes, arterial hypertension, chronic renal insufficiency, chronic obstructive pulmonary disease, asthma, cardiovascular disorders, and oncological history).

Imaging acquisition and analysis.

All CXRs were acquired as computed or digital radiographs, in the posteroanterior or anteroposterior (AP) projection, based on the patients’ clinical condition, following our standard acquisition protocols. Two radiologists (MC, radiologist with 9 years of experience; MO, radiologist with 7 years of experience) in consensus assessed for each CXR: 1) the presence of lung abnormalities, diagnosed as consolidation, GGOs, or nodules, according to the Fleischner Society glossary of terms[14] (Figure 1); 2) their distribution, classified into i) “peripheral” (the outer one-third of the lung), “central” (the inner two-thirds of the lung), or “both”; and into ii) “unilateral” or “bilateral.” The presence of pleural effusion was recorded.
Figure 1.

(A–C) Examples of chest X-ray abnormalities. (A) A 37-year-old woman with a 3-day fever, cough, and conjunctivitis. Chest X-ray shows a focal ground-glass opacity involving the lower field of the left lung (white rectangle). (B) An 86-year-old woman presented with dyspnea (SpO2 88%), fever, and cough. Chest X-ray shows an area of consolidation in the middle-lower left fields (black rectangle). Ground-glass opacification (GGO) is recognizable in the right lung. (C) A 77-year-old man with a history of diabetes and arterial hypertension presented to the emergency department with a 7-day fever (38°C), dry cough, and dyspnea with low SpO2 (84%). Chest X-ray shows bilateral consolidations in middle lung fields (black rectangles). Bilateral areas of GGOs are also recognizable, particularly evident in the lower field of the right lung (white rectangle).

(A–C) Examples of chest X-ray abnormalities. (A) A 37-year-old woman with a 3-day fever, cough, and conjunctivitis. Chest X-ray shows a focal ground-glass opacity involving the lower field of the left lung (white rectangle). (B) An 86-year-old woman presented with dyspnea (SpO2 88%), fever, and cough. Chest X-ray shows an area of consolidation in the middle-lower left fields (black rectangle). Ground-glass opacification (GGO) is recognizable in the right lung. (C) A 77-year-old man with a history of diabetes and arterial hypertension presented to the emergency department with a 7-day fever (38°C), dry cough, and dyspnea with low SpO2 (84%). Chest X-ray shows bilateral consolidations in middle lung fields (black rectangles). Bilateral areas of GGOs are also recognizable, particularly evident in the lower field of the right lung (white rectangle). A “CXR severity score,” according to Wong et al.,[11] was assigned, independently, by two radiologists (MP, radiologist with 7 years of experience; GO, radiologist with 25 years of experience), depending on the extent of involvement by consolidation or GGOs (0 = no involvement, 1 = < 25%, 2 = 25–50%, 3 = 50–75%, and 4 = > 75% involvement), for each lung, with a maximum score of 8 for CXR. Some examples are provided in Figure 2.
Figure 2.

(A–D) Examples of chest X-ray (CXR) score assignment. (A) Chest X-ray showing a focal area of ground-glass opacifications (GGOs) in the upper field of the right lung (black arrow). The involvement of the right lung was < 25%; therefore, the CXR severity score assigned was 1. (B) Chest X-ray showing bilateral areas of GGOs involving the lower lung zones (black arrows). On both the left and right lungs, the involvement was < 50%; therefore, the score was 2 for each lung, with a global score of 4. (C) Chest X-ray showing huge areas of GGOs with bilateral involvement (black arrows), and saving of the upper field of the right lung; the extension on the left side was > 75% (score 4), whereas the involvement on the right side was < 75% (score 3); therefore, the overall score was 4 + 3 = 7. (D) Chest X-ray showing bilateral involvement, with areas of GGOs and consolidation (black arrows) involving all the lung fields. On both the left and right lungs, the involvement was > 75% (score 4); therefore, the global score was 4 + 4 = 8.

(A–D) Examples of chest X-ray (CXR) score assignment. (A) Chest X-ray showing a focal area of ground-glass opacifications (GGOs) in the upper field of the right lung (black arrow). The involvement of the right lung was < 25%; therefore, the CXR severity score assigned was 1. (B) Chest X-ray showing bilateral areas of GGOs involving the lower lung zones (black arrows). On both the left and right lungs, the involvement was < 50%; therefore, the score was 2 for each lung, with a global score of 4. (C) Chest X-ray showing huge areas of GGOs with bilateral involvement (black arrows), and saving of the upper field of the right lung; the extension on the left side was > 75% (score 4), whereas the involvement on the right side was < 75% (score 3); therefore, the overall score was 4 + 3 = 7. (D) Chest X-ray showing bilateral involvement, with areas of GGOs and consolidation (black arrows) involving all the lung fields. On both the left and right lungs, the involvement was > 75% (score 4); therefore, the global score was 4 + 4 = 8.

Statistical analysis.

Values were checked with a one-sample Kolmogorov–Smirnov test for normality. The interobserver agreement was calculated through the Cohen k coefficient. Correlations between values were evaluated through Spearman’s correlation coefficient. Kruskal–Wallis H test and Mann–Whitney U test were used to evaluate differences between independent groups. The relationships among the CXR severity score, radiological features, and clinical and laboratory parameters were investigated fitting a logistic regression model. P < 0.05 was regarded as statistically significant. Statistical analysis was performed using SPSS 20 (IBM, Chicago, IL).

RESULTS

One hundred fifty-five patients (101, 65%, males, and 54, 35%, females; age range: 30–95 years; mean age: 64 ± 16 years) were included. Their clinical characteristics are summarized in Table 1. Fever (81%), cough (54%), and dyspnea (37%) were the most frequent symptoms. The average time from fever onset was 7 ± 3.6 days. The most common comorbidity was hypertension (38%).
Table 1

Characteristics of patients, clinical presentation, and comorbidities

CharacteristicValue
 Number of patients (N = 155)
 Gender, n (%)Male 101 (65)
Female 54 (35)
 Mean age (years), mean (±SD)64 (±16.1)
Clinical presentation
 Fever, n (%)126 (81)
  High fever (T° > 38°C), n (%)37 (24)
  Days of fever, mean (±SD)7 (±3.6)
 Cough, n (%)83 (54)
 Dyspnea, n (%)58 (37)
 Gastrointestinal symptoms, n (%)19 (12)
 Chest pain, n (%)8 (5)
 Conjunctivitis, n (%)3 (2)
 Hemoptysis, n (%)2 (1)
 Oxygen saturation level (SaO2), mean (±SD) (%)92 (±6.6)
Comorbidities, n (%)
 Hypertension48 (31)
 Cardiovascular disease29 (19)
 Diabetes12 (8)
 Chronic obstructive pulmonary disease9 (6)
 Oncological disease9 (6)
 Chronic kidney disease6 (4)
 Asthma3 (2)
Characteristics of patients, clinical presentation, and comorbidities On admission, all patients underwent blood sampling and oropharyngeal swab test for RT-PCR analysis; negative tests in symptomatic patients were repeated up to three times. Baseline RT-PCR resulted positive in 143/155 (92%) of cases, with 12/155 (8%) falsely negative results.

Image acquisition and analysis.

All 155 patients had CXR on admission; 125 (81%) were performed in the AP projection; 143/155 (92%) CXRs showed pulmonary abnormalities, whereas 12/155 (8%) were negative. Ground-glass opacification was the most common finding (141/143, 99%), followed by consolidation (60/143, 42%). Involvement was mainly bilateral (96/143, 67%), with prevalent peripheral distribution (79/143, 55%). Overall, radiographic findings are listed in Table 2.
Table 2

Chest X-ray acquisition, types of abnormalities, and their distribution

CharacteristicValue
 CXR (N = 155), n (%)
  Positive CXR143 (92)
  Negative CXR12 (8)
 Anteroposterior acquisition, n (%)125 (81)
 Posteroanterior acquisition, n (%)30 (19)
Chest abnormalities, n (%)
 GGOs141 (91)
 Consolidation60 (39)
 Both GGOs and consolidation58 (37)
 Pleural effusion15 (10)
Distribution of parenchymal abnormalities, n (%)
 Peripheral79 (51)
 Central20 (13)
 Both44 (28)
 Bilateral96 (62)
 Monolateral47 (30)

CXR = chest X-ray; GGOs = ground-glass opacifications.

Chest X-ray acquisition, types of abnormalities, and their distribution CXR = chest X-ray; GGOs = ground-glass opacifications. The mean CXR score was 3.3 (±2); 61/155 (39%) of patients presented a low score (0–3), whereas 10/155 (6%) showed a very high score (7–8). Interobserver agreement in the CXR score assignment was excellent, with a Cohen’s K correlation coefficient of 0.901. The CXR score showed significant positive correlation with CRP (P < 0.001), LDH (P < 0.001), and fever duration (P = 0.01), and a significant negative correlation with SpO2 (P < 0.001), with r-values of 0.545, 0.770, 0.253, and −0.547, respectively (Figures 3–5). A very high CXR score (> 6) was found only in patients with dyspnea, at the limits of statistical significance (P = 0.06). No significant correlation was found between CXR score and temperature, cough, and comorbidities (P > 0.05).
Figure 3.

Chest X-ray severity score showed a significant positive correlation with C-reactive protein blood levels (P < 0.001; r-value 0.545). This figure appears in color at www.ajtmh.org.

Figure 5.

Chest X-ray severity score showed a significant negative correlation with oxygen saturation (P < 0.001; r-value −0.547).This figure appears in color at www.ajtmh.org.

Chest X-ray severity score showed a significant positive correlation with C-reactive protein blood levels (P < 0.001; r-value 0.545). This figure appears in color at www.ajtmh.org. Chest X-ray severity score showed a significant positive correlation with lactate dehydrogenase blood levels (P < 0.001; r-value 0.770). This figure appears in color at www.ajtmh.org. Chest X-ray severity score showed a significant negative correlation with oxygen saturation (P < 0.001; r-value −0.547).This figure appears in color at www.ajtmh.org.

DISCUSSION

Chest X-ray is an essential tool for assessment of lung abnormalities in routine and emergency settings. Its main advantages are the wide availability, rapid execution, and acquisition at the patient’s bed with portable machines to limit the risk of cross infection.[6,10] In the management of COVID-19–positive patients, it is important to define the severity of pneumonia.[15] Chest X-ray is less sensitive than chest CT in mild or early COVID-19 pneumonia.[11] However, the rapid spread of COVID-19 has resulted in scenarios characterized by high pretest probability, more advanced stages of the disease at presentation, and limited resources.[16] As the prevalence of COVID-19 increases, CXR gains importance in diagnosis and definition of severity disease; therefore, it is important to validate a reporting method that allows not only the description of the disease but also the assessment of its grading in a quantitative and reproducible manner. Wong et al.[11] proposed a radiographic score for COVID-19 pneumonia based on the percentage extension of consolidation and GGOs. In their study, at baseline, the prevalent symptoms were fever (60%) and cough (41%); 31% of patients had normal CXR, and no patient had a CXR score > 6. In our cohort, typical symptoms were more frequent (fever 81% and cough 54%); only 8% of patients presented negative CXR, and 6% of patients showed a high score (> 6). These differences can be explained by the fact that patients presented to our ED with a more advanced disease; therefore, in this context, CXR proved to be an adequate tool for COVID-19 pneumonia, detecting anomalies in the vast majority (92%) of positive cases on admission. In the study by Wong et al.,[11] consolidation was the most common finding (47%), followed by GGOs (33%). In our cohort, instead, GGOs were almost always present in positive CXRs (99%), accompanied by consolidation in 42% of cases, a result in line with findings previously described for CT. COVID-19 pneumonia showed a characteristic distribution; both in our study and in the one by Wong et al., chest abnormalities were found predominantly bilateral in 67% and 63% of cases and with a peripheral distribution in 51% and 55% of CXR, respectively. These findings are in line with the features observed on chest CT.[2-5] Quantifying COVID-19 pneumonia could be very important in the clinical management, and the tool must be as reproducible as possible. Our study analyzes the interobserver reliability of the CXR severity score, with an excellent result (Cohen’s K correlation coefficient = 0.901). Another study evaluated the agreement between radiologists, with a similar result.[17] A significant direct correlation was found between the CXR severity score and blood levels of LDH and CRP. Moreover, the CXR score showed a significant inverse correlation, with SPO2 confirming that this score represents a good indicator of respiratory function. Direct correlation between COVID-19 pneumonia severity, blood values, and SPO2 has been previously reported for chest CT.[2,18,19] Days from fever onset directly correlated with the CXR score. This is in agreement with the fact that the disease usually progresses in a few days from an almost asymptomatic phase to the development of severe pneumonia and that an early therapeutic approach to these patients could potentially reduce the critical cases.[20] Chest X-ray score showed no correlation with comorbidities; for this reason, we can assume that the test is not altered by the presence of preexisting diseases, but the severity of pneumonia. The results listed earlier need to be confirmed with a larger cohort of patients and performed in different hospitals and various conditions for validation. The main limitation of this study is the absence of a reference standard imaging for comparison, as chest CT was not routinely performed in COVID-19 patients at our institution. In conclusion, our results support the role of CXR as a first-line diagnostic tool in symptomatic COVID-19 patients, in particular in a high pretest probability environment and/or limited resources scenario. Moreover, the use of a radiological score can result in a clearer communication with the clinicians and a more effective patient management.
  18 in total

1.  How imaging should properly be used in COVID-19 outbreak: an Italian experience.

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Journal:  Diagn Interv Radiol       Date:  2020-05       Impact factor: 2.630

2.  The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society.

Authors:  Geoffrey D Rubin; Christopher J Ryerson; Linda B Haramati; Nicola Sverzellati; Jeffrey P Kanne; Suhail Raoof; Neil W Schluger; Annalisa Volpi; Jae-Joon Yim; Ian B K Martin; Deverick J Anderson; Christina Kong; Talissa Altes; Andrew Bush; Sujal R Desai; Onathan Goldin; Jin Mo Goo; Marc Humbert; Yoshikazu Inoue; Hans-Ulrich Kauczor; Fengming Luo; Peter J Mazzone; Mathias Prokop; Martine Remy-Jardin; Luca Richeldi; Cornelia M Schaefer-Prokop; Noriyuki Tomiyama; Athol U Wells; Ann N Leung
Journal:  Radiology       Date:  2020-04-07       Impact factor: 11.105

3.  CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV).

Authors:  Michael Chung; Adam Bernheim; Xueyan Mei; Ning Zhang; Mingqian Huang; Xianjun Zeng; Jiufa Cui; Wenjian Xu; Yang Yang; Zahi A Fayad; Adam Jacobi; Kunwei Li; Shaolin Li; Hong Shan
Journal:  Radiology       Date:  2020-02-04       Impact factor: 11.105

4.  Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study.

Authors:  Heshui Shi; Xiaoyu Han; Nanchuan Jiang; Yukun Cao; Osamah Alwalid; Jin Gu; Yanqing Fan; Chuansheng Zheng
Journal:  Lancet Infect Dis       Date:  2020-02-24       Impact factor: 25.071

5.  Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19.

Authors:  Ho Yuen Frank Wong; Hiu Yin Sonia Lam; Ambrose Ho-Tung Fong; Siu Ting Leung; Thomas Wing-Yan Chin; Christine Shing Yen Lo; Macy Mei-Sze Lui; Jonan Chun Yin Lee; Keith Wan-Hang Chiu; Tom Wai-Hin Chung; Elaine Yuen Phin Lee; Eric Yuk Fai Wan; Ivan Fan Ngai Hung; Tina Poy Wing Lam; Michael D Kuo; Ming-Yen Ng
Journal:  Radiology       Date:  2020-03-27       Impact factor: 11.105

6.  Radiology Department Preparedness for COVID-19: Facing an Unexpected Outbreak of the Disease.

Authors:  Marcello Alessandro Orsi; Antonio Giancarlo Oliva; Michaela Cellina
Journal:  Radiology       Date:  2020-03-31       Impact factor: 11.105

7.  Imaging manifestations and diagnostic value of chest CT of coronavirus disease 2019 (COVID-19) in the Xiaogan area.

Authors:  K Wang; S Kang; R Tian; X Zhang; X Zhang; Y Wang
Journal:  Clin Radiol       Date:  2020-03-23       Impact factor: 2.350

Review 8.  Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease.

Authors:  Mingzhi Li; Pinggui Lei; Bingliang Zeng; Zongliang Li; Peng Yu; Bing Fan; Chuanhong Wang; Zicong Li; Jian Zhou; Shaobo Hu; Hao Liu
Journal:  Acad Radiol       Date:  2020-03-20       Impact factor: 3.173

9.  Radiology Department Preparedness for COVID-19: Radiology Scientific Expert Review Panel.

Authors:  Mahmud Mossa-Basha; Carolyn C Meltzer; Danny C Kim; Michael J Tuite; K Pallav Kolli; Bien Soo Tan
Journal:  Radiology       Date:  2020-03-16       Impact factor: 11.105

10.  The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia.

Authors:  Kunhua Li; Jiong Wu; Faqi Wu; Dajing Guo; Linli Chen; Zheng Fang; Chuanming Li
Journal:  Invest Radiol       Date:  2020-06       Impact factor: 10.065

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1.  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.

Authors:  Nevin Aydin; Pinar Yildiz; Döndü Üsküdar Cansu; Elif Gündogdu; Rüya Mutluay; Göknur Yorulmaz; Melisa Sahin Tekin; Evin Kocaturk; I Özkan Alatas; Elif Doyuk Kartal; Nurettin Erben; Gül Durmaz; Nilgun Kasifoglu; Tercan Us; Garip Sahin; Cengiz Bal; Senay Yilmaz; Cengiz Korkmaz
Journal:  BMC Med Imaging       Date:  2022-07-20       Impact factor: 2.795

2.  Usefulness of Hospital Admission Chest X-ray Score for Predicting Mortality and ICU Admission in COVID-19 Patients.

Authors:  Trieu-Nghi Hoang-Thi; Duc-Tuan Tran; Hai-Dang Tran; Manh-Cuong Tran; Tra-My Ton-Nu; Hong-Minh Trinh-Le; Hanh-Nhi Le-Huu; Nga-My Le-Thi; Cong-Trinh Tran; Nhat-Nam Le-Dong; Anh-Tuan Dinh-Xuan
Journal:  J Clin Med       Date:  2022-06-20       Impact factor: 4.964

3.  Can the Usage of the Chest X-Ray Scoring During Hospitalization in Patients with COVID-19 Predict the Severity of the Disease?

Authors:  Selma Aydoğan Eroğlu; Zeynep Çagavi; Tekin Yıldız; Zuhal Karakurt; On Behalf Of Covid Interest Group
Journal:  Turk Thorac J       Date:  2021-05

Review 4.  COVID-19 pneumonia-ultrasound, radiographic, and computed tomography findings: a comprehensive pictorial essay.

Authors:  Michaela Cellina; Carlo Martinenghi; Pietro Marino; Giancarlo Oliva
Journal:  Emerg Radiol       Date:  2021-01-30

5.  Automatic Evaluation of the Lung Condition of COVID-19 Patients Using X-ray Images and Convolutional Neural Networks.

Authors:  Ivan Lorencin; Sandi Baressi Šegota; Nikola Anđelić; Anđela Blagojević; Tijana Šušteršić; Alen Protić; Miloš Arsenijević; Tomislav Ćabov; Nenad Filipović; Zlatan Car
Journal:  J Pers Med       Date:  2021-01-04

6.  Correlation between Chest X-Ray Severity in COVID-19 and Age in Mexican-Mestizo Patients: An Observational Cross-Sectional Study.

Authors:  Arturo Albrandt-Salmeron; Ruby Espejo-Fonseca; Ernesto Roldan-Valadez
Journal:  Biomed Res Int       Date:  2021-04-29       Impact factor: 3.411

7.  Systemic Inflammation and Complement Activation Parameters Predict Clinical Outcome of Severe SARS-CoV-2 Infections.

Authors:  Silke Huber; Mariam Massri; Marco Grasse; Verena Fleischer; Sára Kellnerová; Verena Harpf; Ludwig Knabl; Ludwig Knabl; Tatjana Heiner; Moritz Kummann; Magdalena Neurauter; Günter Rambach; Cornelia Speth; Reinhard Würzner
Journal:  Viruses       Date:  2021-11-26       Impact factor: 5.048

8.  SARS-CoV-2 and dengue virus coinfection in an adult with beta-thalassemia (trait): A case report from Bangladesh with literature review.

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Journal:  Heliyon       Date:  2021-10-20

9.  Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study.

Authors:  Masoud Baikpour; Alex Carlos; Ryan Morasse; Hannah Gissel; Victor Perez-Gutierrez; Jessica Nino; Jose Amaya-Suarez; Fatimatu Ali; Talya Toledano; Joseph Arampulikan; Menachem Gold; Usha Venugopal; Anjana Pillai; Kennedy Omonuwa; Vidya Menon
Journal:  J Clin Med       Date:  2022-04-12       Impact factor: 4.964

10.  Identification of Exertional Hypoxia and Its Implications in SARS-CoV-2 Pneumonia.

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Journal:  Am J Trop Med Hyg       Date:  2020-10       Impact factor: 3.707

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