Severe acute respiratory syndrome: temporal lung changes at thin-section CT in 30 patients

Long-term outcomes of survivors with influenza A H1N1 virus-induced severe pneumonia and ARDS: a single-center prospective cohort study

Introduction

Systematic evaluation of long-term outcomes in survivors of H1N1 is still lacking. This study aimed to characterize long-term outcomes of severe H1N1-induced pneumonia and acute respiratory distress syndrome (ARDS).

Method

This was a single-center, prospective, cohort study. Survivors were followed up for four times after discharge from intensive care unit (ICU) by lung high-resolution computed tomography (HRCT), pulmonary function assessment, 6-minute walk test (6MWT), and SF-36 instrument.

Result

A total of 60 survivors of H1N1-induced pneumonia and ARDS were followed up for four times. The carbon monoxide at single breath (DLCO) of predicted values and the 6MWT results didn't continue improving after 3 months. Health-related quality of life didn't change during the 12 months after ICU discharge. Reticulation or interlobular septal thickening on HRCT did not begin to improve significantly until the 12-month follow-up. The DLCO of predicted values showed negative correlation with the severity degree of primary disease and reticulation or interlobular septal thickening, and a positive correlation with physical functioning. The DLCO of predicted values and reticulation or interlobular septal thickening both correlated with the highest tidal volume during mechanical ventilation. Levels of fibrogenic cytokines had a positive correlation with reticulation or interlobular septal thickening.

Conclusion

The improvements in pulmonary function and exercise capacity, imaging, and health-related quality of life had different time phase and impact on each other during 12 months of follow-up. Long-term outcomes of pulmonary fibrosis might be related to the lung injury and excessive lung fibroproliferation at the early stage during ICU admission.

COVID-19 pneumonia assessed at a private hospital, a field hospital, and a public-referral hospital: population analysis, chest computed tomography findings, and outcomes

Objective

To compare a private quaternary referral hospital, a public tertiary hospital, and a field hospital dedicated to patients with COVID-19, regarding patients' characteristics, clinical parameters, laboratory, imaging findings, and outcomes of patients with confirmed diagnosis of COVID-19.

Methods

Retrospective multicenter observational study that assessed the association of clinical, laboratory and CT data of 453 patients with COVID-19, and also their outcomes (hospital discharge or admission, intensive care unit admission, need for mechanical ventilation, and mortality caused by COVID-19).

Results

The mean age of patients was 55 years (±16 years), 58.1% of them were male, and 41.9% were female. Considering stratification by the hospital of care, significant differences were observed in the dyspnea, fever, cough, hypertension, diabetes mellitus parameters, and CT score (p < 0.05). Significant differences were observed in ward admission rates, with a lower rate in the private hospital (40.0%), followed by the public hospital (74.1%), and a higher rate in the field hospital (89.4%). Regarding intensive care unit admission, there was a higher rate in the public hospital (25.2%), followed by the private hospital (15.5%), and a lower rate in the field hospital (9.9%). In the analysis of the discharge and death outcomes, it was found that there was a higher number of patients discharged from the private hospital (94.2%), compared to the field hospital (90.1%) and public hospital (82.3%) and a higher number of deaths in the public hospital (17.7%) compared to the private hospital and field hospital (5.8 and 0% respectively).

Conclusion

The analysis of the data regarding the population treated with COVID-19 during the first wave in different levels of care in the public and private health systems in the city of São Paulo revealed statistically significant differences between the populations, reflecting distinct outcomes.

Correlation between chest computed tomography findings and pulmonary function test results in the post-recovery phase of COVID-19

OBJECTIVE

The radiological and functional lung sequelae in COVID-19 survivors remain unclear. We compared the chest computed tomography findings of COVID-19 patients with normal and abnormal pulmonary function test results in the post-recovery phase.

METHODS

The data of consecutive patients who underwent pulmonary function tests and chest computed tomography within 14 days after recovery from COVID-19 at two medical centers between May and October 2020 were collected retrospectively. Two thoracic radiologists who were blinded to the clinical information and pulmonary function test results classified the patients according to the computed tomography features, evidence of fibrotic-like changes, and semi-quantitative quantification of the extent of pulmonary abnormalities. The clinical characteristics and computed tomography findings of patients with normal pulmonary function test results were compared with those of patients with abnormal results.

RESULTS

A total of 101 COVID-19 survivors, comprising 48 ambulatory and 53 hospitalized patients, were included at a median of 95 days from initial symptom onset. Computed tomography revealed fibrotic-like changes in 10.9% of patients. A reduction in the diffusion capacity of carbon monoxide was the most common lung function abnormality (19.8%). Abnormal diffusion capacity of carbon monoxide was associated with the presence and extension of lung opacities on chest computed tomography scans and fibrotic pulmonary abnormalities. The sensitivity, specificity, and accuracy of reduced diffusion capacity of carbon monoxide for detecting fibrotic-like pulmonary changes on chest computed tomography scans were 72.7%, 87.8%, and 86.1%, respectively.

CONCLUSION

Our study suggests that the presence of an abnormal diffusion capacity of carbon monoxide in the post-recovery phase of COVID-19 is associated with a greater risk of long-term parenchymal lung disease, as evidenced by the presence of fibrotic-like changes on chest computed tomography scans, such as traction bronchiectasis and architectural distortion.

Long-term complications after infection with SARS-CoV-1, influenza and MERS-CoV - Lessons to learn in long COVID?

The COVID-19 pandemic has affected millions of people worldwide, and while the mortality rate remains the primary concern, it is becoming increasingly apparent that many COVID-19 survivors experience long-term sequelae, representing a major concern for both themselves and healthcare providers. Comparing long-term sequelae following COVID-19 to those of other respiratory viruses such as influenza, MERS-CoV, and SARS-CoV-1 is an essential step toward understanding the extent and impact of these sequelae. A literature search was carried out using the PubMed. database. Search-terms included "persistent", "long-term", "chronic", and MeSH-terms for SARS-CoV-1, MERS-CoV and Influenza. Only English-language articles were selected. Articles were screened by title/abstract and full-text readings. Key points for comparison were persistent symptoms > 4 weeks, virus type, study design, population size, admission status, methods, and findings. Thirty-one articles were included: 19 on SARS-CoV-1, 10 on influenza, and 2 on MERS-CoV-survivors. Damage to the respiratory system was the main long-term manifestation after the acute phase of infection. Quality of life-related and psychological sequelae were the second and third most widely reported symptoms, respectively. Consistent with long-term sequelae from COVID-19, persisting cardiovascular, neurological, musculoskeletal, gastrointestinal impairments were also reported. In summary, the long-term sequelae following COVID-19 are a significant concern, and while long-term sequelae following influenza, MERS-CoV, and SARS-CoV-1 have also been reported, their prevalence and severity are less clear. It is essential to continue to study and monitor the long-term effects of all respiratory viruses so as to improve our understanding and develop strategies for prevention and treatment.

Chest computed tomography severity score is a reliable predictor of mortality in patients with chronic obstructive pulmonary disease co-infected with COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic is considered a global health crisis. The data related to chronic obstructive pulmonary disease (COPD) patients with COVID-19 are incomplete, especially the findings of the chest computed tomography (CT). The aim of the current study was to investigate the severity of the disease of COVID-19 in patients with COPD based on CT severity score and to evaluate its predictive power in the mortality of patients.

METHODS

In a retrospective study, demographic, clinical, and CT scan findings of COPD patients with COVID-19 were extracted from March 2020 to February 2022. CT severity score was determined based on the extent and nature of involvement of lungs in CT scan findings. By performing receiver operating characteristics (ROC) and Kaplan-Meier survival analysis were determined the disease severity and survival probability.

RESULTS

The most frequent radiological findings in chest CT scan included ground glass opacities (89.3%), consolidations (51.8%), crazy-paving pattern (46.4%), and septal thickening (35.7%). The mean CT severity score of deceased patients (34.61 ± 18.73) was significantly higher than recovered patients (16.71 ± 14.01, p < 0.001). Based on the ROC and Kaplan-Meier survival curves, it was revealed that CT severity score was a valuable criteria in the diagnosis of mortality in COPD patients with COVID-19.

CONCLUSION

The findings of this study revealed that the CT severity scoring in COPD patients with COVID-19 was valuable in identifying poor prognosis, although further studies are needed.

Psittacosis caused severe community-acquired pneumonia accompanied by acute hypoxic respiratory failure: a multicenter retrospective cohort study from China

INTRODUCTION

Psittacosis can cause severe community-acquired pneumonia (CAP). The clinical manifestations of psittacosis range from subclinical to fulminant psittacosis with multi-organ failure. It is essential to summarize the clinical characteristic of patients with severe psittacosis accompanied by acute hypoxic respiratory failure (AHRF).

METHODS

This retrospective study included patients with severe psittacosis caused CAP accompanied by AHRF from 19 tertiary hospitals of China. We recorded the clinical data, antimicrobial therapy, respiratory support, complications, and outcomes. Chlamydia psittaci was detected on the basis of metagenomic next-generation sequencing performed on bronchoalveolar lavage fluid samples. Patient outcomes were compared between the treatment methods.

RESULTS

This study included 45 patients with severe CAP and AHRF caused by psittacosis from April 2018 to May 2021. The highest incidence of these infections was between September and April. There was a history of poultry contact in 64.4% of the patients. The median PaO2/FiO2 of the patients was 119.8 (interquartile range, 73.2 to 183.6) mmHg. Four of 45 patients (8.9%) died in the ICU, and the median ICU duration was 12 days (interquartile range, 8 to 21) days. There were no significant differences between patients treated with fluoroquinolone initially and continued after the diagnosis, fluoroquinolone initially followed by tetracycline, and fluoroquinolone combined with tetracycline.

CONCLUSION

Psittacosis caused severe CAP seems not rare, especially in the patients with the history of exposure to poultry or birds. Empirical treatment that covers atypical pathogens may benefit such patients, which fluoroquinolones might be considered as an alternative.

Quantitative evaluation of CT scan images to determinate the prognosis of COVID-19 patient using deep learning

The purpose of this research is to evaluate the accuracy of AI-assisted quantification in comparison to conventional CT parameters reviewed by a radiologist in predicting the severity, progression, and clinical outcome of disease. The current study is a cross-sectional study that was conducted on patients with the diagnosis of COVID-19 and underwent a pulmonary CT scan between August 23th, 2021 to December 21th, 2022. The initial CT scan on admission was used for imaging analysis. The presence of ground glass opacity (GGO), and consolidation were visually evaluated. CT severity score was calculated according to a semi-quantitative method. In addition, AI based quantification of GGO and consolidation volume were also performed. 291 patients (mean age: 64.7 ± 7; 129 males) were included. GGO + consolidation was more frequently revealed in progress-to-severe group whereas pure GGO was more likely to be found in non-severe group. Compared to non-severe group, patients in progress-to-severe group had larger GGO volume percentage (40.6%± 11.9%versus 21.7%± 8.8%, p ˂0.001) as well as consolidation volume percentage (4.8% ± 2% versus 1.9% ± 1%, p < 0.001). Among imaging parameters, consolidation volume percentage and the largest area under curve (AUC) in discriminating non-severe from progress-to-severe group (AUC = 0.91, p < 0.001). According to multivariate regression, consolidation volume was the strongest predictor for disease progression. In conclusion, the consolidation volume measured on the initial chest CT was the most accurate predictor of disease progression, and a larger consolidation volume was associated with a poor clinical outcome. In patients with COVID-19, AI-assisted lesion quantification was useful for risk stratification and prognosis evaluation.

Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients

BACKGROUND

Severe courses and high hospitalization rates were ubiquitous during the first pandemic SARS-CoV-2 waves. Thus, we aimed to examine whether integrative diagnostics may aid in identifying vulnerable patients using crucial data and materials obtained from COVID-19 patients hospitalized between 2020 and 2021 (n = 52). Accordingly, we investigated the potential of laboratory biomarkers, specifically the dynamic cell decay marker cell-free DNA and radiomics features extracted from chest CT.

METHODS

Separate forward and backward feature selection was conducted for linear regression with the Intensive-Care-Unit (ICU) period as the initial target. Three-fold cross-validation was performed, and collinear parameters were reduced. The model was adapted to a logistic regression approach and verified in a validation naïve subset to avoid overfitting.

RESULTS

The adapted integrated model classifying patients into "ICU/no ICU demand" comprises six radiomics and seven laboratory biomarkers. The models' accuracy was 0.54 for radiomics, 0.47 for cfDNA, 0.74 for routine laboratory, and 0.87 for the combined model with an AUC of 0.91.

CONCLUSION

The combined model performed superior to the individual models. Thus, integrating radiomics and laboratory data shows synergistic potential to aid clinic decision-making in COVID-19 patients. Under the need for evaluation in larger cohorts, including patients with other SARS-CoV-2 variants, the identified parameters might contribute to the triage of COVID-19 patients.

CT Approach to Lung Injury

Diffuse alveolar damage (DAD), which represents the pathologic changes seen after acute lung injury, is caused by damage to all three layers of the alveolar wall and can ultimately result in alveolar collapse with loss of the normal pulmonary architecture. DAD has an acute phase that predominantly manifests as airspace disease at CT owing to filling of the alveoli with cells, plasma fluids, and hyaline membranes. DAD then evolves into a heterogeneous organizing phase, with mixed airspace and interstitial disease characterized by volume loss, architectural distortion, fibrosis, and parenchymal loss. Patients with DAD have a severe clinical course and typically require prolonged mechanical ventilation, which may result in ventilator-induced lung injury. In those patients who survive DAD, the lungs will remodel over time, but most will have residual findings at chest CT. Organizing pneumonia (OP) is a descriptive term for a histologic pattern characterized by intra-alveolar fibroblast plugs. The significance and pathogenesis of OP are controversial. Some authors regard it as part of a spectrum of acute lung injury, while others consider it a marker of acute or subacute lung injury. At CT, OP manifests with various forms of airspace disease that are most commonly bilateral and relatively homogeneous in appearance at individual time points. Patients with OP most often have a mild clinical course, although some may have residual findings at CT. In patients with DAD and OP, imaging findings can be combined with clinical information to suggest the diagnosis in many cases, with biopsy reserved for difficult cases with atypical findings or clinical manifestations. To best participate in the multidisciplinary approach to patients with lung injury, radiologists must not only recognize these entities but also describe them with consistent and meaningful terminology, examples of which are emphasized in the article. © RSNA, 2023 See the invited commentary by Kligerman et al in this issue. Quiz questions for this article are available in the supplemental material.

The 21st century disaster: The COVID-19 epidemiology, risk factors and control

The 21st century will be indelible in the world as ruin of the outbreak of COVID-19 was arose in Wuhan, China has now spread all over the world, up to August 2020. This study was based on the factors affecting the epidemiology of this virus in human societies of global concern. We studied the articles published in journals on various aspects of nCoVID19. The Wikipedia and WHO situation reports have also been searched out for related information. Outcomes were followed up until 2020. The COVID-19 is a virus with pandemic potential which may continue to cause regular infection in human. The pandemic outbreak of COVID-19 threatened public health across the globe in form of system as reflected in the shape of emergency. Approximately 21 million humans are infected and 759,400 have lost their lives till 2020 in all over the world. We have described epidemiological features, reservoirs, transmission, incubation period, rate of fatality, management including recent clinical chemotherapeutic approach and preventive measurements and masses which are at risk of COVID19. This virus causes viral pneumonia when it attacks on respiratory system and multiple failure which can leads to life threatening complications. It is believed to be zoonotic importance although it is not clear from which animal and how it is transmitted. Zoonotic transmission of COVID-19 has not yet known by science. The current study will help to establish a baseline for early effective control of this rapidly spreading severe viral illness. The available data on COVID-19 indicates that older males with comorbidities would have been more infected, which can result in severe respiratory complications. Implementation of preventive measurements, investigation of proper chemotherapeutics and detection of cross species transmission agents must be ensured.

Multiomic characterisation of the long-term sequelae of SARS survivors: a clinical observational study

BACKGROUND

We aimed to characterise the long-term health outcomes of survivors of severe acute respiratory syndrome (SARS) and determine their recovery status and possible immunological basis.

METHODS

We performed a clinical observational study on 14 health workers who survived SARS coronavirus infection between Apr 20, 2003 and Jun 6, 2003 in Haihe Hospital (Tianjin, China). Eighteen years after discharge, SARS survivors were interviewed using questionnaires on symptoms and quality of life, and received physical examination, laboratory tests, pulmonary function tests, arterial blood gas analysis, and chest imaging. Plasma samples were collected for metabolomic, proteomic, and single-cell transcriptomic analyses. The health outcomes were compared 18 and 12 years after discharge. Control individuals were also health workers from the same hospital but did not infect with SARS coronavirus.

FINDINGS

Fatigue was the most common symptom in SARS survivors 18 years after discharge, with osteoporosis and necrosis of the femoral head being the main sequelae. The respiratory function and hip function scores of the SARS survivors were significantly lower than those of the controls. Physical and social functioning at 18 years was improved compared to that after 12 years but still worse than the controls. Emotional and mental health were fully recovered. Lung lesions on CT scans remained consistent at 18 years, especially in the right upper lobe and left lower lobe lesions. Plasma multiomics analysis indicated an abnormal metabolism of amino acids and lipids, promoted host defense immune responses to bacteria and external stimuli, B-cell activation, and enhanced cytotoxicity of CD8⁺ T cells but impaired antigen presentation capacity of CD4⁺ T cells.

INTERPRETATION

Although health outcomes continued to improve, our study suggested that SARS survivors still suffered from physical fatigue, osteoporosis, and necrosis of the femoral head 18 years after discharge, possibly related to plasma metabolic disorders and immunological alterations.

FUNDING

This study was funded by the Tianjin Haihe Hospital Science and Technology Fund (HHYY-202012) and Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-063B, TJYXZDXK-067C).

Can a chest HRCT-based crash course on COVID-19 cases make inexperienced thoracic radiologists readily available to face the next pandemic?

OBJECTIVE

To test the inter-reader agreement in assessing lung disease extent, HRCT signs, and Radiological Society of North America (RSNA) categorization between a chest-devoted radiologist (CR) and two HRCT-naïve radiology residents (RR1 and RR2) after the latter attended a COVID-19-based chest high-resolution computed tomography (HRCT) "crash course".

METHODS

The course was built by retrospective inclusion of 150 patients who underwent HRCT for COVID-19 pneumonia between November 2020 and January 2021. During a first 10-days-long "training phase", RR1 and RR2 read a pool of 100/150 HRCTs, receiving day-by-day access to CR reports as feedback. In the subsequent 2-days-long "test phase", they were asked to report 50/150 HRCTs with no feedback. Test phase reports of RR1/RR2 were then compared with CR using unweighted or linearly-weighted Cohen's kappa (k) statistic and intraclass correlation coefficient (ICC).

RESULTS

We observed almost perfect agreement in assessing disease extent between RR1-CR (k = 0.83, p < 0.001) and RR2-CR (k = 0.88, p < 0.001). The agreement between RR1-CR and RR2-CR on consolidation, crazy paving pattern, organizing pneumonia (OP) pattern, and pulmonary artery (PA) diameter was substantial (k = 0.65 and k = 0.68), moderate (k = 0.42 and k = 0.51), slight (k = 0.10 and k = 0.20), and good-to-excellent (ICC = 0.87 and ICC = 0.91), respectively. The agreement in providing RSNA categorization was moderate for R1 versus CR (k = 0.56) and substantial for R2 versus CR (k = 0.67).

CONCLUSION

HRCT-naïve readers showed an acceptable overall agreement with CR, supporting the hypothesis that a crash course can be a tool to readily make non-subspecialty radiologists available to cooperate in reading high burden of HRCT examinations during a pandemic/epidemic.

Association between emphysema and other pulmonary computed tomography patterns in COVID-19 pneumonia

To evaluate the chest computed tomography (CT) findings of patients with Corona Virus Disease 2019 (COVID-19) on admission to hospital. And then correlate CT pulmonary infiltrates involvement with the findings of emphysema. We analyzed the different infiltrates of COVID-19 pneumonia using emphysema as the grade of pneumonia. We applied open-source assisted software (3D Slicer) to model the lungs and lesions of 66 patients with COVID-19, which were retrospectively included. we divided the 66 COVID-19 patients into the following two groups: (A) 12 patients with less than 10% emphysema in the low-attenuation area less than -950 Hounsfield units (%LAA-950), (B) 54 patients with greater than or equal to 10% emphysema in %LAA-950. Imaging findings were assessed retrospectively by two authors and then pulmonary infiltrates and emphysema volumes were measured on CT using 3D Slicer software. Differences between pulmonary infiltrates, emphysema, Collapsed, affected of patients with CT findings were assessed by Kruskal-Wallis and Wilcoxon test, respectively. Statistical significance was set at p < 0.05. The left lung (A) affected left lung 20.00/affected right lung 18.50, (B) affected left lung 13.00/affected right lung 11.50 was most frequently involved region in COVID-19. In addition, collapsed left lung, (A) collapsed left lung 4.95/collapsed right lung 4.65, (B) collapsed left lung 3.65/collapsed right lung 3.15 was also more severe than the right one. There were significant differences between the Group A and Group B in terms of the percentage of CT involvement in each lung region (p < 0.05), except for the inflated affected total lung (p = 0.152). The median percentage of collapsed left lung in the Group A was 20.00 (14.00-30.00), right lung was 18.50 (13.00-30.25) and the total was 19.00 (13.00-30.00), while the median percentage of collapsed left lung in the Group B was 13.00 (10.00-14.75), right lung was 11.50 (10.00-15.00) and the total was 12.50 (10.00-15.00). The percentage of affected left lung is an independent predictor of emphysema in COVID-19 patients. We need to focus on the left lung of the patient as it is more affected. The people with lower levels of emphysema may have more collapsed segments. The more collapsed segments may lead to more serious clinical feature.

Identification of circulating microRNA profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS

There is a limited understanding of the pathophysiology of postacute pulmonary sequelae in severe COVID-19. The aim of current study was to define the circulating microRNA (miRNA) profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS. The study included patients who developed ARDS secondary to SARS-CoV-2 infection (n = 167) and a group of infected patients who did not develop ARDS (n = 33). Patients were evaluated 3 months after hospital discharge. The follow-up included a complete pulmonary evaluation and chest computed tomography. Plasma miRNA profiling was performed using RT-qPCR. Random forest was used to construct miRNA signatures associated with lung diffusing capacity for carbon monoxide (D_LCO) and total severity score (TSS). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted. D_LCO< 80% predicted was observed in 81.8% of the patients. TSS showed a median [P₂₅;P₇₅] of 5 [2;8]. The miRNA model associated with D_LCO comprised miR-17-5p, miR-27a-3p, miR-126-3p, miR-146a-5p and miR-495-3p. Concerning radiologic features, a miRNA signature composed by miR-9-5p, miR-21-5p, miR-24-3p and miR-221-3p correlated with TSS values. These associations were not observed in the non-ARDS group. KEGG pathway and GO enrichment analyses provided evidence of molecular mechanisms related not only to profibrotic or anti-inflammatory states but also to cell death, immune response, hypoxia, vascularization, coagulation and viral infection. In conclusion, diffusing capacity and radiological features in survivors from SARS-CoV-2-induced ARDS are associated with specific miRNA profiles. These findings provide novel insights into the possible molecular pathways underlying the pathogenesis of pulmonary sequelae.

Trial registration:ClinicalTrials.gov identifier: NCT04457505..

Trial registration:ISRCTN.org identifier: ISRCTN16865246..

Comparison of clinical characteristics and outcome measures of PCR-positive and PCR-negative patients diagnosed as COVID-19: Analyses focusing on the older adults

PURPOSE

While the definitive diagnosis of COVID-19 relies on PCR confirmation of the virus, the sensitivity of this technique is limited. The clinicians had to go on with the clinical diagnosis of COVID-19 in selected cases. We aimed to compare PCR-positive and PCR-negative patients diagnosed as COVID-19 with a specific focus on older adults.

METHODS

We studied 601 hospitalized adults. The demographics, co-morbidities, triage clinical, laboratory characteristics, and outcomes were noted. Differences between the PCR (+) and (-) cases were analyzed. An additional specific analysis focusing on older adults (≥65 years) (n = 184) was performed.

RESULTS

The PCR confirmation was present in 359 (59.7 %). There was not any difference in terms of age, sex, travel/contact history, hospitalization duration, ICU need, the time between first symptom/hospitalization to ICU need, ICU days, or survival between PCR-positive and negative cases in the total study group and older adults subgroup. The only symptoms that were different in prevalence between PCR-confirmed and unconfirmed cases were fever (73.3 % vs. 64 %, p = 0.02) and fatigue/myalgia (91.1 % vs. 79.3 %, p = 0.001). Bilateral diffuse pneumonia was also more prevalent in PCR-confirmed cases (20 % vs. 13.3 %, p = 0.03). In older adults, the PCR (-) cases had more prevalent dyspnea (72.2 % vs. 51.4 %, p = 0.004), less prevalent fatigue/myalgia (70.9 % vs. 88.6 %, p = 0.002).

CONCLUSION

The PCR (+) and (-) cases displayed very similar disease phenotypes, courses, and outcomes with few differences between each other. The presence of some worse laboratory findings may indicate a worse immune protective response in PCR (-) cases.

Comparison of Chest CT and RT-PCR Assay for Indication of Disease Course of Coronavirus Disease 2019 (COVID-19) Pneumonia

BACKGROUND

COVID-19 patients' courses vary in length, indicating a variable prognosis. The disease duration revealed by different examination methods may differ.

OBJECTIVE

The study aims to compare the differences in the disease course of patients with COVID-19 by chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) assay and explore the factors that affect the course of the illness.

METHODS

106 patients confirmed with COVID-19 were enrolled and divided into two groups (age <60 years and age ≥60 years). The clinical characteristics of the two groups were analyzed. The intervals from symptoms onset to initial positive time point (ISIP), symptoms onset to the initial negative time point (ISIN), and initial positive to initial negative time point (IIPN) indicated by chest CT and RTPCR assay were analyzed. Multiple regression analysis was performed to assess the correlations between independent factors and the intervals.

RESULTS

Chest CT showed an earlier positive time point, a later negative time point, and a longer disease duration than the RT-PCR assay (P<.001, respectively). Older patients over 60 years old showed a later negative time point and a longer disease duration by chest CT than younger patients (P<.01 vs. P<.05, respectively). The CT score and clinical grades of older patients were greater than those of younger patients (P<.001, respectively). Age and clinical grades were significantly correlated with the disease course shown by chest CT (P<.05, respectively), and CT score was positively correlated with the illness course shown by chest CT and RT-PCR assay (P<.01, respectively).

CONCLUSION

The disease course revealed by chest CT and RT-PCR assay was asynchronous. Chest CT showed a 17-day longer period compared to the RT-PCR assay. Older patients had a longer duration than younger ones. A prolonged course is predicted by increasing age, CT score, and clinical grades.

Clinical Characterizations and Radiological Findings of COVID-19: A 4 Case Report

BACKGROUND

Coronavirus disease 2019 (COVID-19, previously known as novel coronavirus [2019-nCoV]), first reported in China, has now been declared a global health emergency by World Health Organization. The clinical severity ranges from asymptomatic individuals to death. Here, we report clinical features and radiological changes of a cured family cluster infected with COVID-19.

CASE PRESENTATION

In this report, we enrolled a family of 4 members who were admitted to our hospital in January 2020. We performed a detailed analysis of each patient's records. All patients underwent chest computed tomography (CT) examination with 120 kilovolts peak and 150 kilovolt-ampere. Realtime polymerase chain reaction (RT-PCR) examinations for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid were done using nasopharyngeal swabs.

CONCLUSION

In the family members infected with COVID-19 who were accompanied by other diseases or had low immunity, the pneumonia was prone to be aggravated.

Temporal changes of lung computed tomography findings pulmonary COVID-19 infection

OBJECTIVES

COVID-19 infection demonstrates characteristic findings in chest CT. The optimal timing of repeated CT scans still needs to be clarified, and the optimal time to assess imaging clearance in COVID-19 is still unknown. It is crucial to have a roadmap of the imaging course of COVID-19 pneumonia to develop guidelines for prompt diagnosis of pulmonary complications, especially fibrosis, at the earliest stage.

PURPOSE

To assess the temporal changes of chest CT findings in patients with COVID-19 pneumonia and evaluate the rate of a complete resolution and determine the patients are at excessive risk for residual parenchymal abnormalities.

MATERIALS AND METHODS

This retrospective observational study included 48 patients with real-time polymerase chain reaction-confirmed COVID-19 who were admitted to three academic hospitals. These patients underwent at least one initial chest CT before or after admission and at least one follow-up CT scan four weeks or more after the onset of the symptoms. All chest CTs were categorized according to time of performance into four groups, including the first week, second week, third-fourth week, and more than 28 days. Lung involvement was categorized as predominantly alveolar (ground-glass opacity and consolidation), organizing pneumonia, and reticular patterns. The severity of involvement was also evaluated by the reader.

RESULTS

Forty-eight patients and a total of 130 chest CT scans were evaluated. The alveolar pattern showed a gradual decrease in frequency from 91% in the first week to 9% after the fourth week of the disease but the organizing pneumonia pattern gradually increased with disease progression and the frequency of reticular pattern increased significantly after third week. Complete resolution of CT findings was seen in 17 patients (13.1%) and was significantly more prevalent in patients of younger age (p value<0.001) and with lower initial CT severity scores (p value=0.048). CT severity scores in the second week were significantly higher in ICU admitted patients (p value=0.003).

CONCLUSION

There are temporal patterns of lung abnormalities in patients with COVID-19 pneumonia. The predominant CT pattern was alveolar infiltrate in the first and second weeks of the disease, replaced with an organizing pneumonia pattern in the third and fourth weeks. Progression of lung involvement was correlated with ICU admission due to the highest CT severity score in the second and third weeks of presentation but not in the first week in patients who were admitted at ICU. Complete CT resolution was significantly more common in patients of younger age and lower initial CT severity scores.

Real-life Evidence of Lower Lung Virulence in COVID-19 Inpatients Infected with SARS-CoV-2 Omicron Variant Compared to Wild-Type and Delta SARS-CoV-2 Pneumonia

In vitro and animal models described lower replication capacity and virulence of SARS-CoV-2 Omicron lineage in lower respiratory airways compared to wild type and other variants of concern (oVOCs). Among adult subjects admitted to our hospital (Turin, Italy) due to wild type, oVOCs, and Omicron SARS-CoV-2-related pneumonia (n = 100 for each lineage), the cases of Omicron pneumonia showed lower degree of lung parenchyma involvement (aβ -1.471, p = 0.037), less tendency to parenchyma consolidation (aOR 0.500, p = 0.011), and better respiratory functions (assessed by ambient air arterial blood gas analysis). After adjusting for demographic, previous immunity, and comorbidities, Omicron pneumonia still associated with lower risk of respiratory failure (for severe respiratory failure, Wild-type versus Omicron aOR 15.6, p = 0.005 and oVOCs versus Omicron aOR 31.7, p < 0.001). These observations are in line with preliminary findings from in vitro and animal models and could explain why Omicron infection has been associated with lower mortality and hospitalization in human.

Semi-quantitative evaluation of chest computed tomography for coronavirus disease 2019 in a critical care unit: A case-control study

The spread of abnormal opacity on chest computed tomography (CT) has been reported as a predictor of coronavirus disease 2019 (COVID-19) severity; however, the relationship between CT findings and prognosis in patients with severe COVID-19 remains unclear. The objective of this study was to evaluate the extent of abnormal opacity on chest CT and its association with prognosis in patients with COVID-19 in a critical care medical center, using a simple semi-quantitative method. This single-center case-control study included patients diagnosed with severe COVID-19 pneumonia who were admitted to a critical care center. The diagnosis of COVID-19 was based on positive results of a reverse transcription polymerase chain reaction test. All patients underwent non-contrast whole-body CT upon admission. Six representative axial chest CT images were selected for each patient to evaluate the extent of lung lesions. The percentage of the area involved in the representative CT images was visually assessed by 2 radiologists and scored on 4-point scale to obtain the bedside CT score, which was compared between patients who survived and those who died using the Mann-Whitney U test. A total of 63 patients were included in this study: 51 survived and 12 died after intensive treatment. The inter-rater reliability of bedside scores between the 2 radiologists was acceptable. The median bedside CT score of the survival group was 12.5 and that of the mortality group was 16.5; the difference between the 2 groups was statistically significant. The degree of opacity can be easily scored using representative CT images in patients with severe COVID-19 pneumonia, without sophisticated software. A greater extent of abnormal opacity is associated with poorer prognosis. Predicting the prognosis of patients with severe COVID-19 could facilitate prompt and appropriate treatment.

Renalase Challenges the Oxidative Stress and Fibroproliferative Response in COVID-19

The hallmark of the coronavirus disease 2019 (COVID-19) pathophysiology was reported to be an inappropriate and uncontrolled immune response, evidenced by activated macrophages, and a robust surge of proinflammatory cytokines, followed by the release of reactive oxygen species, that synergistically result in acute respiratory distress syndrome, fibroproliferative lung response, and possibly even death. For these reasons, all identified risk factors and pathophysiological processes of COVID-19, which are feasible for the prevention and treatment, should be addressed in a timely manner. Accordingly, the evolving anti-inflammatory and antifibrotic therapy for severe COVID-19 and hindering post-COVID-19 fibrosis development should be comprehensively investigated. Experimental evidence indicates that renalase, a novel amino-oxidase, derived from the kidneys, exhibits remarkable organ protection, robustly addressing the most powerful pathways of cell trauma: inflammation and oxidative stress, necrosis, and apoptosis. As demonstrated, systemic renalase administration also significantly alleviates experimentally induced organ fibrosis and prevents adverse remodeling. The recognition that renalase exerts cytoprotection via sirtuins activation, by raising their NAD⁺ levels, provides a “proof of principle” for renalase being a biologically impressive molecule that favors cell protection and survival and maybe involved in the pathogenesis of COVID-19. This premise supports the rationale that renalase's timely supplementation may prove valuable for pathologic conditions, such as cytokine storm and related acute respiratory distress syndrome. Therefore, the aim for this review is to acknowledge the scientific rationale for renalase employment in the experimental model of COVID-19, targeting the acute phase mechanisms and halting fibrosis progression, based on its proposed molecular pathways. Novel therapies for COVID-19 seek to exploit renalase's multiple and distinctive cytoprotective mechanisms; therefore, this review should be acknowledged as the thorough groundwork for subsequent research of renalase's employment in the experimental models of COVID-19.

SARS-CoV-2 infection: Pathogenesis, Immune Responses, Diagnosis

COVID-19 has emerged as the most alarming infection of the present time instigated by the virus SARS-CoV-2. In spite of advanced research technologies, the exact pathophysiology and treatment of the condition still need to be explored. However, SARS-CoV-2 has several structural and functional similarities that resemble SARS-CoV and MERS-CoV which may be beneficial in exploring the possible treatment and diagnostic strategies for SARS-CoV-2. This review discusses the pathogen phenotype, genotype, replication, pathophysiology, elicited immune response and emerging variants of SARS-CoV-2 and their similarities with other similar viruses. SARS-CoV-2 infection is detected by a number of diagnostics techniques, their advantages and limitations are also discussed in detail. The review also focuses on nanotechnology-based easy and fast detection of SARS-CoV-2 infection. Various pathways which might play a vital role during SARS-CoV-2 infection have been elaborately discussed since immune response plays a major role during viral infections.

The return visit, outcome and predicting factors of return visit among suspected COVID-19 outpatients

Rate of return visit, predicting factors of return visit and occurrence of adverse events in suspected to be or likely cases of COVID-19 patients who received outpatient treatment. This is a retrospective observational cohort study on patients (> 16 years), suspected to be or likely cases of COVID-19 who were visited in a respiratory emergency department and subsequently discharged home. Patients' baseline characteristics were extracted from medical charts. All patients were followed-up for 7 days after their first visit. Patients' outcomes during the7-day follow-up, as well as the severity of pulmonary involvement based on imaging were recorded. A total number of 601 patients (350 men and 251 women) were recruited. The rate of return visit was 27.74% (144 patients) with 6.74% (34 patients) experiencing a poor outcome. Six factors with a significant odds ratio were predictors of poor outcome in patients who received outpatient treatment, namely, older age [odds ratio = 3.278, 95% confidence interval: 1.115-9.632], days from onset of symptoms [1.068, 1.003-1.137], and history of diabetes [6.373, 2.271-17.883]). Predictors of favorable outcome were female gender [0.376, 0.158-0.894], oxygen saturation > 93% [0.862, 0.733-1.014], smoking habit [0.204, 0.045-0.934]. The findings of this study demonstrate that the rate of return visit with poor outcome in patients who received outpatient treatment was reasonably low. Age, male sex, diabetes mellitus and pulmonary disease are predicting factors of poor outcome in these COVID-19 patients who received outpatient management.

Advancements in Testing Strategies for COVID-19

The SARS-CoV-2 coronavirus, also known as the disease-causing agent for COVID-19, is a virulent pathogen that may infect people and certain animals. The global spread of COVID-19 and its emerging variation necessitates the development of rapid, reliable, simple, and low-cost diagnostic tools. Many methodologies and devices have been developed for the highly sensitive, selective, cost-effective, and rapid diagnosis of COVID-19. This review organizes the diagnosis platforms into four groups: imaging, molecular-based detection, serological testing, and biosensors. Each platform's principle, advancement, utilization, and challenges for monitoring SARS-CoV-2 are discussed in detail. In addition, an overview of the impact of variants on detection, commercially available kits, and readout signal analysis has been presented. This review will expand our understanding of developing advanced diagnostic approaches to evolve into susceptible, precise, and reproducible technologies to combat any future outbreak.

Lung Ultrasound in Patients With SARS-COV-2 Pneumonia: Correlations With Chest Computed Tomography, Respiratory Impairment, and Inflammatory Cascade

OBJECTIVES

Lung ultrasound (LUS) might be comparable to chest computed tomography (CT) in detecting parenchymal and pleural pathology, and in monitoring interstitial lung disease. We aimed to describe LUS characteristics of patients during the hospitalization for COVID-19 pneumonia, and to compare the extent of lung involvement at LUS and chest-CT with inflammatory response and the severity of respiration impairment.

METHODS

During a 2-week period, we performed LUS and chest CT in hospitalized patients affected by COVID-19 pneumonia. Dosages of high sensitivity C-reactive protein (HS-CRP), d-dimer, and interleukin-6 (IL-6) were also obtained. The index of lung function (P/F ratio) was calculated from the blood gas test. LUS and CT scoring were assessed using previously validated scores.

RESULTS

Twenty-six consecutive patients (3 women) underwent LUS 34 ± 14 days from the early symptoms. Among them, 21 underwent CT on the same day of LUS. A fair association was found between LUS and CT scores (R = 0.45, P = .049), which became stronger if the B-lines score on LUS was not considered (R = 0.57, P = .024). LUS B-lines score correlated with IL-6 levels (R = 0.75, P = .011), and the number of involved lung segments detected by LUS correlated with the P/F ratio (R = 0.60, P = .019) but not with HS-CRP and d-Dimer levels. No correlations were found between CT scores and inflammations markers or P/F.

CONCLUSION

In patients with COVID-19 pneumonia, LUS was correlated with both the extent of the inflammatory response and the P/F ratio.

Possible Role of Matrix Metalloproteinases and TGF-β in COVID-19 Severity and Sequelae

The costs of coronavirus disease 2019 (COVID-19) are devastating. With millions of deaths worldwide, specific serological biomarkers, antiviral agents, and novel therapies are urgently required to reduce the disease burden. For these purposes, a profound understanding of the pathobiology of COVID-19 is mandatory. Notably, the study of immunity against other respiratory infections has generated reference knowledge to comprehend the paradox of the COVID-19 pathogenesis. Past studies point to a complex interplay between cytokines and other factors mediating wound healing and extracellular matrix (ECM) remodeling that results in exacerbated inflammation, tissue injury, severe manifestations, and a sequela of respiratory infections. This review provides an overview of the immunological process elicited after severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Also, we analyzed available data about the participation of matrix metalloproteinases (MMPs) and transforming growth factor-beta (TGF-β) in immune responses of the lungs. Furthermore, we discuss their possible implications in severe COVID-19 and sequela, including pulmonary fibrosis, and remark on the potential of these molecules as biomarkers for diagnosis, prognosis, and treatment of convalescent COVID-19 patients. Our review provides a theoretical framework for future research aimed to discover molecular hallmarks that, combined with clinical features, could serve as therapeutic targets and reliable biomarkers of the different clinical forms of COVID-19, including convalescence.

Machine learning based COVID -19 disease recognition using CT images of SIRM database

The COVID-19 pandemic, probably one of the most widespread pandemics humanity has encountered in the twenty first century, caused death to almost 1.75 M people worldwide, impacting almost 80 M lives with direct contact. In order to contain the spread of coronavirus, it is necessary to develop a reliant and quick method to identify those who are affected and isolate them until full recovery is made. The imagery knowledge has been shown to be useful for quick COVID-19 diagnosis. Though the scans of computational tomography (CT) demonstrate a range of viral infection signals, considering the vast number of images, certain visual characteristics are challenging to distinguish and can take a long time to be identified by radiologists. In this study for detection of the COVID-19, a dataset is formed by taking 3764 images. The feature extraction process is applied to the dataset to increase the classification performance. Techniques like Grey Level Co-occurrence Matrix (GLCM) and Discrete Wavelet Transform (DWT) are used for feature extraction. Then various machine learning algorithms applied such as Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), Multi- Level Perceptron, Naive Bayes, K-Nearest Neighbours and Random Forests are used for classification of COVID-19 disease detection. Sensitivity, Specificity, Accuracy, Precision, and F-score are the metrics used to measure the performance of different machine learning models. Among these machine learning models SVM with GLCM as feature extraction technique using 10-fold cross validation gives the best classification result with 99.70% accuracy, 99.80% sensitivity and 97.03% F-score. We also ran these tests on different data sets and found that the results are similar across those too, as discussed later in the results section.

Prognostic factors of worse outcome for hospitalized COVID-19 patients, with emphasis on chest computed tomography data: a retrospective study

Objective:

To evaluate anthropometric and clinical data, muscle mass, subcutaneous fat, spine bone mineral density, extent of acute pulmonary disease related to COVID-19, quantification of pulmonary emphysema, coronary calcium, and hepatic steatosis using chest computed tomography of hospitalized patients with confirmed diagnosis of COVID-19 pneumonia and verify its association with disease severity.

Methods:

A total of 123 adults hospitalized due to COVID-19 pneumonia were enrolled in the present study, which evaluated the anthropometric, clinical and chest computed tomography data (pectoral and paravertebral muscle area and density, subcutaneous fat, thoracic vertebral bodies density, degree of pulmonary involvement by disease, coronary calcium quantification, liver attenuation measurement) and their association with poorer prognosis characterized through a combined outcome of intubation and mechanical ventilation, need of intensive care unit, and death.

Results:

Age (p=0.013), body mass index (p=0.009), lymphopenia (p=0.034), and degree of pulmonary involvement of COVID-19 pneumonia (p<0.001) were associated with poor prognosis. Extent of pulmonary involvement by COVID-19 pneumonia had an odds ratio of 1,329 for a poor prognosis and a cutoff value of 6.5 for increased risk, with a sensitivity of 64.9% and specificity of 67.1%.

Conclusion:

The present study found an association of high body mass index, older age, extent of pulmonary involvement by COVID-19, and lymphopenia with severity of COVID-19 pneumonia in hospitalized patients.

Different chest CT scoring systems in patients with COVID-19: could baseline CT be a helpful tool in predicting survival in patients with matched ages and co-morbid conditions?

BACKGROUND

Computed tomography (CT) gives an idea about the prognosis in patients with COVID-19 lung infiltration.

PURPOSE

To evaluate the success rates of various scoring methods utilized in order to predict survival periods, on the basis of the imaging findings of COVID-19. Another purpose, on the other hand, was to evaluate the agreements among the evaluating radiologists.

MATERIAL AND METHODS

A total of 100 cases of known COVID-19 pneumonia, of which 50 were deceased and 50 were living, were included in the study. Pre-existing scoring systems, which were the Total Severity Score (TSS), Chest Computed Tomography Severity Score (CT-SS), and Total CT Score, were utilized, together with the Early Decision Severity Score (ED-SS), which was developed by our team, to evaluate the initial lung CT scans of the patients obtained at their initial admission to the hospital. The scans were evaluated retrospectively by two radiologists. Area under the curve (AUC) values were acquired for each scoring system, according to their performances in predicting survival times.

RESULTS

The mean age of the patients was 61 ± 14.85 years (age range = 18-87 years). There was no difference in co-morbidities between the living and deceased patients. The survival predicted AUC values of ED-SS, CT-SS, TSS, and Total CT Score systems were 0.876, 0.823, 0.753, and 0.744, respectively.

CONCLUSION

Algorithms based on lung infiltration patterns of COVID-19 may be utilized for both survival prediction and therapy planning.

Spectrum of Typical and Atypical Pulmonary CT Imaging Findings of COVID-19 Infection: A Retrospective Study

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. It was declared a public health emergency by WHO in January 2020. The definitive diagnostic test for COVID-19 is a real time polymerase chain reaction test (RT-PCR) which is highly specific, but sensitivity is variable. COVID-19 typically presents clinically with respiratory and systemic symptoms. The majority of the infected patients are asymptomatic during the course of the disease, which we have not included in our study. Imaging findings on high-resolution computed tomography (HRCT) chest are important to diagnose the disease in early stage, for treatment planning and to predict the patient prognosis. The purpose of our study was to characterize typical and atypical pulmonary and extra-pulmonary HRCT findings in patients with COVID-19 infection and to help in the management of patients. 

In this retrospective study, we have included 70 patients who had undergone HRCT examination of the chest in the Radiodiagnosis Department, Maharishi Markandeshwar Medical College, Kumarhatti, Solan, Himachal Pradesh, India. The HRCT findings of the chest of these patients in the study will be evaluated and data will be statistically analyzed.

Construction and Verification of a Predictive Model for Risk Factors in Children With Severe Adenoviral Pneumonia

OBJECTIVE

To construct and validate a predictive model for risk factors in children with severe adenoviral pneumonia based on chest low-dose CT imaging and clinical features.

METHODS

A total of 177 patients with adenoviral pneumonia who underwent low-dose CT examination were collected between January 2019 and August 2019. The assessment criteria for severe pneumonia were divided into mild group (N = 125) and severe group (N = 52). All cases divided into training cohort (N = 125) and validation cohort (N = 52). We constructed a prediction model by drawing a nomogram and verified the predictive efficacy of the model through the ROC curve, calibration curve and decision curve analysis.

RESULTS

The difference was statistically significant (P < 0.05) between the mild adenovirus pneumonia group and the severe adenovirus pneumonia group in gender, age, weight, body temperature, L/N ratio, LDH, ALT, AST, CK-MB, ADV DNA, bronchial inflation sign, emphysema, ground glass sign, bronchial wall thickening, bronchiectasis, pleural effusion, consolidation score, and lobular inflammation score. Multivariate logistic regression analysis showed that gender, LDH value, emphysema, consolidation score, and lobular inflammation score were severe independent risk factors for adenovirus pneumonia in children. Logistic regression was employed to construct clinical model, imaging semantic feature model, and combined model. The AUC values of the training sets of the three models were 0.85 (0.77-0.94), 0.83 (0.75-0.91), and 0.91 (0.85-0.97). The AUC of the validation set was 0.77 (0.64-0.91), 0.83 (0.71-0.94), and 0.85 (0.73-0.96), respectively. The calibration curve fit good of the three models. The clinical decision curve analysis demonstrates the clinical application value of the nomogram prediction model.

CONCLUSION

The prediction model based on chest low-dose CT image characteristics and clinical characteristics has relatively clear predictive value in distinguishing mild adenovirus pneumonia from severe adenovirus pneumonia in children and might provide a new method for early clinical prediction of the outcome of adenovirus pneumonia in children.

Giant compressive emphysema: a rare complication of COVID-19

Background

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a new ribonucleic acid (RNA) beta-coronavirus, responsible for a worldwide pandemic. Very few cases of SARS-COV-2-related emphysema have been described, except among patients with chronic obstructive pulmonary disease. The thoracic CT scan is the key examination for the diagnosis and allows to evaluate the severity of the pulmonary involvement. The prognosis of the patient with giant emphysema (GE) on coronavirus disease 2019 (COVID-19) in critical or severe form remains poor. We report an original case of COVID-19 pneumonia, critical form, complicated by a giant compressive left emphysema of 22.4 cm in a young subject without respiratory comorbidities.

Case presentation

A 34-year-old man was hospitalized for left laterothoracic pain. He had no prior medical history. The physical examination revealed tympany on percussion of the left lung. The CT scan confirmed COVID-19 pneumonia with 95% lung involvement. Also, the presence of a voluminous left sub pleural emphysema of 22.4 cm with compression of the ipsilateral pulmonary parenchyma as well as the mediastinal structures towards the right side. The diagnosis COVID-19 pneumonia, critical form, complicated by a compressive left giant emphysema was made. He was put on oxygen, a dual antibiotic therapy, a corticotherapy, and curative doses of enoxaparin. A thoracic drainage surgery was performed at 24th day of hospitalization, which confirmed the giant emphysema. The patient remains on long-term oxygen therapy.

Conclusion

The COVID-19 has polymorphic manifestations, pneumonia is the most important one. There are relatively few reports associating COVID-19 and emphysema; furthermore, reports associating COVID-19 and giant emphysema are extremely scarce. CT scans can confirm the diagnosis and differentiate it from a pneumothorax. The pulmonary prognosis of the association of COVID-19 in its severe or critical form with giant emphysema remains poor.

COVID-19 pandemic: CT chest in COVID-19 infection and prediction of patient’s ICU needs

Background

With the tremendous rise in COVID-19 infection and the shortage of real-time reverse transcription-polymerase chain reaction (RT-PCR) testing, we aimed to assess the role of CT in the detection of COVID-19 infection and the correlation with the patients’ management. A retrospective study was conducted on 600 patients who presented with symptoms suspicious for COVID-19 infection between March and the end of June 2020. The current study followed the RSNA recommendations in CT reporting and correlated with the RT-PCR. CT was reviewed and the severity score was correlated with the patient’s management.

Results

Four hundred sixty-six patients were included with a mean age of 46 + 14.8 years and 63.3 % were males. Three hundred forty patients were confirmed positive by RT-PCR. CT sensitivity was 92.6% while the RT-PCR was the reference. The CT specificity showed a gradual increase with the CT probability reaching 97.6% with high probability CT features. Ground-glass opacities (GGO) was the commonest findings 85.9% with a high incidence of bilateral, peripheral, and multilobar involvement (88%, 92.8%, and 92.8% respectively). Consolidation was found in 81.5% of the ICU patients and was the dominant feature in 66.7% of the ICU cases. CT severity score was significantly higher in ICU patients with a score of ≥ 14.

Conclusions

COVID-19 infection showed typical CT features which can be used as a rapid and sensitive investigation. Two CT phenotypes identified with the predominant consolidation phenotype as well as severity score can be used to determine infection severity and ICU need.

Correlation Between Low-Dose Chest Computed Tomography and RT-PCR Results for the Diagnosis of COVID-19: A Report of 27,824 Cases in Tehran, Iran

RATIONALE AND OBJECTIVES

Real-time polymerase chain reaction (RT-PCR) remains the gold standard for confirmation of Coronavirus Disease 2019 (COVID-19) despite having many disadvantages. Here, we investigated the diagnostic performance of chest computed tomography (CT) as an alternative to RT-PCR in patients with clinical suspicion of COVID-19 infection.

METHODS

In this descriptive cross-sectional study, 27,824 patients with clinical suspicion of COVID-19 infection who underwent unenhanced low-dose chest CT from 20 February, 2020 to 21 May, 2020 were evaluated. Patients were recruited from seven specifically designated hospitals for patients with COVID-19 infection affiliated to Shahid Beheshti University of Medical Sciences. In each hospital, images were interpreted by two independent radiologists. CT findings were considered as positive/negative for COVID-19 infection based on RSNA diagnostic criteria. Then, the correlation between the number of daily positive chest CT scans and number of daily PCR-confirmed cases and COVID-19-related deaths in Tehran province during this three-month period was assessed. The trends of admission rate and patients with positive CT scans were also evaluated.

RESULTS

A strong positive correlation between the numbers of daily positive CT scans and daily PCR-confirmed COVID-19 cases (r = 0.913, p < 0.001) was observed. Furthermore, in hospitals located in regions with a lower socioeconomic status, the admission rate and number of positive cases within this three-month period was higher as compared to other hospitals.

CONCLUSION

Low-dose chest CT is a safe, rapid and reliable alternative to RT-PCR for the diagnosis of COVID-19 in high-prevalence regions. In addition, our study provides further evidence for considering patients' socioeconomic status as an important risk factor for COVID-19.

Clinical Features and Temporal Lung Radiographic Changes in 25 Patients Recovering from COVID-19 Pneumonia: A Retrospective Case-Control Study

Background

Little is known of the changes in lung radiographic characteristics over time in patients recovering from COVID-19. This study analyzed the clinical features and temporal lung radiographic changes in patients with moderate and severe COVID-19 pneumonia who did not require invasive mechanical ventilation during the acute and convalescent periods.

Material/Methods

The data of 25 patients with COVID-19 pneumonia from January 29, 2020, to November 24, 2020, who did not require invasive mechanical ventilation and who were followed up were retrospectively collected. The 25 patients were divided into severe and moderate groups. Clinical characteristics and computed tomography (CT) manifestations were compared. A total of 121 consecutive thin-slice CT scans were collected at 4 weeks, 2 months, and 5 months after admission to evaluate lung abnormalities in the patients. The CT score was used to assess disease severity.

Results

The severe group had a lower rate of nucleic acid conversion within 10 days of admission and higher D-dimer, creatine kinase, and lactate dehydrogenase values. In the severe group, hospital stay was longer and hospitalization costs were higher. The average CT score of the severe group peaked in the second week, while the moderate group peaked in the first week and then decreased over time. There were no statistically significant differences in the average CT score between the 2 groups at the 5-month follow-up.

Conclusions

The pulmonary lesions of patients recovering from COVID-19 and who do not require invasive mechanical ventilation were gradually absorbed and resolved over time.

An outlook on coronavirus disease 2019 detection methods

Diagnostic testing plays a fundamental role in the mitigation and containment of coronavirus disease 2019 (COVID-19), as it enables immediate quarantine of those who are infected and contagious and is essential for the epidemiological characterization of the virus and estimating the number of infected cases worldwide. Confirmation of viral infections, such as COVID-19, can be achieved through two general approaches: nucleic acid amplification tests (NAATs) or molecular tests, and serological or antibody-based tests. The genetic material of the pathogen is detected in NAAT, and in serological tests, host antibodies produced in response to the pathogen are identified. Other methods of diagnosing COVID-19 include radiological imaging of the lungs and in vitro detection of viral antigens. This review covers different approaches available to diagnosing COVID-19 by outlining their advantages and shortcomings, as well as appropriate indications for more accurate testing.

•

Diagnostic tests to detect coronavirus disease 2019 (COVID-19).

•

Advantages and disadvantages associated with each detection method.

•

Implications for a more accurate and rapid testing of COVID-19 or other similar future emergent viruses.

CT of Post-Acute Lung Complications of COVID-19

The acute course of COVID-19 is variable and ranges from asymptomatic infection to fulminant respiratory failure. Patients recovering from COVID-19 can have persistent symptoms and CT abnormalities of variable severity. At 3 months after acute infection, a subset of patients will have CT abnormalities that include ground-glass opacity (GGO) and subpleural bands with concomitant pulmonary function abnormalities. At 6 months after acute infection, some patients have persistent CT changes to include the resolution of GGOs seen in the early recovery phase and the persistence or development of changes suggestive of fibrosis, such as reticulation with or without parenchymal distortion. The etiology of lung disease after COVID-19 may be a sequela of prolonged mechanical ventilation, COVID-19-induced acute respiratory distress syndrome (ARDS), or direct injury from the virus. Predictors of lung disease after COVID-19 include need for intensive care unit admission, mechanical ventilation, higher inflammatory markers, longer hospital stay, and a diagnosis of ARDS. Treatments of lung disease after COVID-19 are being investigated, including the potential of antifibrotic agents for prevention of lung fibrosis after COVID-19. Future research is needed to determine the long-term persistence of lung disease after COVID-19, its impact on patients, and methods to either prevent or treat it. © RSNA, 2021.

Longitudinal Radiological Findings in Patients With COVID-19 With Different Severities: From Onset to Long-Term Follow-Up After Discharge

Objective: This study aimed to investigate the evolution of radiological findings in the patients with coronavirus disease 2019 (COVID-19) pneumonia with different severities from onset to 1-year follow-up and identify the predictive factors for different pulmonary lesion absorption status in the patients infected with COVID-19.

Methods: A retrospective study was performed on the clinical and radiological features of 175 patients with COVID-19 pneumonia hospitalized at three institutions from January 21 to March 20, 2020. All the chest CT scans during hospitalization and follow-ups after discharge were collected. The clinical and radiological features from the chest CT scans both at the peak stage and before discharge from the hospital were used to predict whether the pulmonary lesions would be fully absorbed after discharge by Cox regression. Then, these patients were stratified into two groups with different risks of pulmonary lesion absorption, and an optimal timepoint for the first CT follow-up was selected accordingly.

Results: A total of 132 (75.4%) patients were classified into the non-severe group, and 43 (24.6%) patients were classified into the severe group, according to the WHO guidelines. The opacification in both the groups changed from ground-glass opacity (GGO) to consolidation and then from consolidation to GGO. Among the 175 participants, 135 (112 non-severe and 23 severe patients with COVID-19) underwent follow-up CT scans after discharge. Pulmonary residuals could be observed in nearly half of the patients (67/135) with the presentation of opacities and parenchymal bands. The parenchymal bands in nine discharged patients got fully absorbed during the follow-up periods. The age of patient [hazard ratio (HR) = 0.95, 95% CI, 0.95–0.99], level of lactate dehydrogenase (LDH) (HR = 0.99; 95% CI, 0.99–1.00), level of procalcitonin (HR = 8.72; 95% CI, 1.04–73.03), existence of diffuse lesions (HR = 0.28; 95% CI, 0.09–0.92), subpleural distribution of lesions (HR = 2.15; 95% CI, 1.17–3.92), morphology of residuals (linear lesion: HR = 4.58, 95% CI, 1.22–17.11; nodular lesion: HR = 33.07, 95% CI, 3.58–305.74), and pleural traction (HR = 0.41; 95% CI, 0.22–0.78) from the last scan before discharge were independent factors to predict the absorption status of COVID-19-related pulmonary abnormalities after discharge. According to a Kaplan–Meier analysis, the probability of patients of the low-risk group to have pulmonary lesions fully absorbed within 90 days reached 91.7%.

Conclusion: The development of COVID-19 lesions followed the trend from GGO to consolidation and then from consolidation to GGO. The CT manifestations and clinical and laboratory variables before discharge could help predict the absorption status of pulmonary lesions after discharge. The parenchymal bands could be fully absorbed in some COVID-19 cases. In this study, a Cox regression analysis indicated that a timepoint of 3 months since onset was optimal for the radiological follow-up of discharged patients.

Chest CT Patterns from Diagnosis to 1 Year of Follow-up in COVID-19

Background

The chest CT manifestations of COVID-19 from hospitalization to convalescence after 1 year are unknown.

Purpose

To assess chest CT manifestations of COVID-19 up to 1 year after symptom onset.

Materials and Methods

Patients were enrolled if they were admitted to the hospital because of COVID-19 and underwent CT during hospitalization at two isolation centers between January 27, 2020, and March 31, 2020. In a prospective study, three serial chest CT scans were obtained at approximately 3, 7, and 12 months after symptom onset and were longitudinally analyzed. The total CT score of pulmonary lobe involvement, ranging from 0 to 25, was assessed (score of 1–5 for each lobe). Univariable and multivariable logistic regression analyses were performed to explore independent risk factors for residual CT abnormalities after 1 year.

Results

A total of 209 study participants (mean age, 49 years ± 13 [standard deviation]; 116 women) were evaluated. CT abnormalities had resolved in 61% of participants (128 of 209) at 3 months and in 75% of participants (156 of 209) at 12 months. Among participants with chest CT abnormalities that had not resolved, there were residual linear opacities in 25 of the 209 participants (12%) and multifocal reticular or cystic lesions in 28 of the 209 participants (13%). Age 50 years or older, lymphopenia, and severe or aggravation of acute respiratory distress syndrome were independent risk factors for residual CT abnormalities at 1 year (odds ratios = 15.9, 18.9, and 43.9, respectively; P < .001 for each comparison). In 53 participants with residual CT abnormalities at 12 months, reticular lesions (41 of 53 participants [77%]) and bronchial dilation (39 of 53 participants [74%]) were observed at discharge and were persistent in 28 (53%) and 24 (45%) of the 53 participants, respectively.

Conclusion

One year after COVID-19 diagnosis, chest CT scans showed abnormal findings in 53 of the 209 study participants (25%), with 28 of the 209 participants (13%) showing subpleural reticular or cystic lesions. Older participants with severe COVID-19 or acute respiratory distress syndrome were more likely to develop lung sequelae that persisted at 1 year.

© RSNA, 2021

Online supplemental material is available for this article.

See also the editorial by Lee and Wi et al in this issue.

Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index

INTRODUCTION

The assessment of disease severity and the prediction of clinical outcomes at early disease stages can contribute to decreased mortality in patients with Coronavirus disease 2019 (COVID-19). This study was conducted to develop and validate a multivariable risk prediction model for mortality with using a combination of computed tomography severity score (CT-SS), national early warning score (NEWS), and quick sequential (sepsis-related) organ failure assessment (qSOFA) in COVID-19 patients.

METHODS

We retrospectively collected medical data from 655 adult COVID-19 patients admitted to our hospital between July and November 2020. Data on demographics, clinical characteristics, and laboratory and radiological findings measured as part of standard care at admission were used to calculate NEWS, qSOFA score, CT-SS, peripheral perfusion index (PPI) and shock index (SI). Logistic regression and Cox proportional hazard models were used to predict mortality, which was our primary outcome. The predictive accuracy of distinct scoring systems was evaluated by the receiver-operating characteristic (ROC) curve analysis.

RESULTS

The median age was 50.0 years [333 males (50.8%), 322 females (49.2%)]. Higher NEWS and SI was associated with time-to-death within 90-days, whereas higher age, CT-SS and lower PPI were significantly associated with time-to-death within both 14 days and 90 days in the adjusted Cox regression model. The CT-SS predicted different mortality risk levels within each stratum of NEWS and qSOFA and improved the discrimination of mortality prediction models. Combining CT-SS with NEWS score yielded more accurate 14 days (DBA: -0.048, p = 0.002) and 90 days (DBA: -0.066, p < 0.001) mortality prediction.

CONCLUSION

Combining severity tools such as CT-SS, NEWS and qSOFA improves the accuracy of predicting mortality in patients with COVID-19. Inclusion of these tools in decision strategies might provide early detection of high-risk groups, avoid delayed medical attention, and improve patient outcomes.

Olfactory dysfunction and coronavirus disease 2019 severity: a prospective cohort study

Objective

The primary goal of this study was to evaluate the association between olfactory dysfunction or taste impairment and disease severity and radiological findings in coronavirus disease-2019. The secondary goal was to assess the prevalence, severity and course of olfactory dysfunction or taste impairment in patients with coronavirus disease 2019.

Method

This prospective observational cohort study evaluated patients hospitalised with coronavirus disease 2019 between April 1 and 1 May 2020. Olfactory dysfunction and taste impairment were evaluated by two questionnaires. Chest computed tomography findings and coronavirus disease-2019 severity were assessed.

Results

Among 133 patients, 23.3 per cent and 30.8 per cent experienced olfactory dysfunction and taste impairment, respectively, and 17.2 per cent experienced both. The mean age was 56.03 years, and 64.7 per cent were male and 35.3 per cent were female. No statistically significant association was found between olfactory dysfunction (p = 0.706) and taste impairment (p = 0.35) with either disease severity or chest computed tomography grading.

Conclusion

Olfactory dysfunction or taste impairment does not have prognostic importance in patients with coronavirus disease 2019.

Clinical and CT findings of adenovirus pneumonia in immunocompetent adults

INTRODUCTION

Adenovirus pneumonia is not uncommon in children and immunocompromised patients. However, the study of the clinical and computed tomography (CT) characteristics of Adenovirus pneumonia in immunocompetent adults is still limited.

OBJECTIVE

The objective of this study was to retrospectively observe the clinical and CT characteristics as well as their dynamic change of Adenovirus pneumonia in immunocompetent adults.

METHODS

Twenty patients (18 males, median age, 36 years old) with Adenovirus pneumonia were retrospectively included from January 2018 to December 2019. Clinical information and chest CT at admission of all patients were reviewed. Twelve patients underwent serial CT scans, and the temporal changes of CT findings were summarized. Pneumonia severity index (PSI) was calculated according to clinical information.

RESULTS

The median time interval from illness onset to admission was 6 days (interquartile range [IQR], 5-7.5 days). The clinical characteristics included the high fever (39.2 ± 0.8°C) with the normal white blood cell count, the decreased lymphocyte, and elevated C-reactive protein. Ten cases complicated with mycoplasma infection at admission. Thirteen patients were mechanically ventilated, and two patients died during hospitalization. Consolidation was a predominant pattern found during the first 2 weeks and then resolved to minimal consolidation after the fourth week. There was no significant correlation between CT score and PSI score (r = 0.15, p = 0.41).

CONCLUSIONS

Predominant radiological finding of Adenovirus pneumonia was consolidation. Multilobular involvement, higher CT scores, and pleural effusion were found in more severe patients. The abnormal opacity peaked in 2 weeks of illness onset and gradually resolved after the third week. The temporal changes of radiological score are consistent with clinical findings.

Does COVID-19 pneumonia signify secondary organizing pneumonia?: A narrative review comparing the similarities between these two distinct entities

Multiple observational studies have described the similarities between COVID-19 pneumonia and organizing pneumonia (OP). These two entities clinically manifest with mild and subacute respiratory symptoms, often with a delayed diagnosis due to the atypical ARDS and silent hypoxemia presentation. Radiological features are often indistinguishable between the two. With the increase in antemortem lung biopsies and autopsies being performed, more histopathological findings of OP and its variant, acute fibrinous and organizing pneumonia (AFOP), are being diagnosed. These entities are known complications of viral infections as a delayed immunological process, explaining the favorable response to corticosteroids. Clinicians should be vigilant to diagnose this under-recognized entity of secondary OP in people with COVID-19 when clinical deterioration occurs, especially with compatible radiologic findings and recent cessation of corticosteroids. Despite the proven benefits of corticosteroids in treating COVID-19, treatment approaches can be more effective as OP often requires higher doses and a more prolonged therapy duration for remission and preventing relapses. The purpose of our narrative review is to compare the similarities between COVID-19 pneumonia and OP, emphasizing the clinical, radiological, and histopathological features based on the evidence available in the literature.

One-year follow-up of chest CT findings in patients after SARS-CoV-2 infection

BACKGROUND

Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge.

METHODS

A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated.

RESULTS

A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0-2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older (p = 0.01), with higher rate in current smokers (p = 0.04), higher rate in hypertensives (p = 0.05), lower SaO2 (p = 0.004), and higher prevalence of secondary bacterial infections during acute phase (p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01-1.15, p = 0.02). Pulmonary functions of total lung capacity (p = 0.008) and residual volume (p < 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores.

CONCLUSION

During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.

Therapeutic and diagnostic targeting of fibrosis in metabolic, proliferative and viral disorders

Fibrosis is a common denominator in many pathologies and crucially affects disease progression, drug delivery efficiency and therapy outcome. We here summarize therapeutic and diagnostic strategies for fibrosis targeting in atherosclerosis and cardiac disease, cancer, diabetes, liver diseases and viral infections. We address various anti-fibrotic targets, ranging from cells and genes to metabolites and proteins, primarily focusing on fibrosis-promoting features that are conserved among the different diseases. We discuss how anti-fibrotic therapies have progressed over the years, and how nanomedicine formulations can potentiate anti-fibrotic treatment efficacy. From a diagnostic point of view, we discuss how medical imaging can be employed to facilitate the diagnosis, staging and treatment monitoring of fibrotic disorders. Altogether, this comprehensive overview serves as a basis for developing individualized and improved treatment strategies for patients suffering from fibrosis-associated pathologies.

Follow-up chest radiographic findings in patients with MERS-CoV after recovery

PURPOSE

To evaluate the follow-up chest radiographic findings in patients with Middle East respiratory syndrome coronavirus (MERS-CoV) who were discharged from the hospital following improved clinical symptoms.

MATERIALS AND METHODS

Thirty-six consecutive patients (9 men, 27 women; age range 21-73 years, mean ± SD 42.5 ± 14.5 years) with confirmed MERS-CoV underwent follow-up chest radiographs after recovery from MERS-CoV. The 36 chest radiographs were obtained at 32 to 230 days with a median follow-up of 43 days. The reviewers systemically evaluated the follow-up chest radiographs from 36 patients for lung parenchymal, airway, pleural, hilar and mediastinal abnormalities. Lung parenchyma and airways were assessed for consolidation, ground-glass opacity (GGO), nodular opacity and reticular opacity (i.e., fibrosis). Follow-up chest radiographs were also evaluated for pleural thickening, pleural effusion, pneumothorax and lymphadenopathy. Patients were categorized into two groups: group 1 (no evidence of lung fibrosis) and group 2 (chest radiographic evidence of lung fibrosis) for comparative analysis. Patient demographics, length of ventilations days, number of intensive care unit (ICU) admission days, chest radiographic score, chest radiographic deterioration pattern (Types 1-4) and peak lactate dehydrogenase level were compared between the two groups using the student t-test, Mann-Whitney U test and Fisher's exact test.

RESULTS

Follow-up chest radiographs were normal in 23 out of 36 (64%) patients. Among the patients with abnormal chest radiographs (13/36, 36%), the following were found: lung fibrosis in 12 (33%) patients GGO in 2 (5.5%) patients, and pleural thickening in 2 (5.5%) patients. Patients with lung fibrosis had significantly greater number of ICU admission days (19 ± 8.7 days; P value = 0.001), older age (50.6 ± 12.6 years; P value = 0.02), higher chest radiographic scores [10 (0-15.3); P value = 0.04] and higher peak lactate dehydrogenase levels (315-370 U/L; P value = 0.001) when compared to patients without lung fibrosis.

CONCLUSION

Lung fibrosis may develop in a substantial number of patients who have recovered from Middle East respiratory syndrome coronavirus (MERS-CoV). Significantly greater number of ICU admission days, older age, higher chest radiographic scores, chest radiographic deterioration patterns and peak lactate dehydrogenase levels were noted in the patients with lung fibrosis on follow-up chest radiographs after recovery from MERS-CoV.

Pattern and Age Distribution of COVID-19 on Pulmonary Computed Tomography

BACKGROUND

COVID-19 has emerged recently and has become a global concern. Computed tomography (CT) plays a vital role in the diagnosis.

OBJECTIVES

To characterize the pulmonary CT findings and distributions of COVID-19 infection in regard to different age groups.

METHODS

Chest CT scan of 104 symptomatic patients with COVID-19 infection from 7 Iraqi isolation centers were retrospectively analyzed between March 10th to April 5th, 2020. Patients were sub-classified according to their ages into three groups (young adult:20-39 years, middle age:40-59 years, and old age:60-90 years).

RESULTS

The most common findings were ground-glass opacities (GGO) (92.3%, followed by consolidation (27.9%), bronchovascular thickening (15.4%), and crazy-paving (12.5%). Less commonly, there were tree-in-bud (6.7%), pulmonary nodules (5.8%), bronchiectasis (3.8%), pleural effusion (1.9%), and cavitation (1%). There were no hallo signs, reversed hallo signs, and mediastinal lymphadenopathy. Pulmonary changes were unilateral in 16.7% and bilateral in 83.3%, central in 14.6%, peripheral in 57.3%, and diffuse (central and peripheral) in 28.1%. Most cases showed multi- lobar changes (70.8%), while the lower lobe was more commonly involved (17.7%) than the middle lobe/lingula (8.3%) and upper lobe (3.1%). In unilateral involvement, changes were more on the right (68.8%) than the left (31.2%) side. Compared with middle and old age groups, young adult patients showed significantly lesser frequency of consolidation (17% vs. 13.3% and 37%), diffuse changes 28.1% (14.2% vs. 35.3% and 40.5%), bilateral disease (71.4% vs. 94.1% and 85.2%), and multi-lobar involvement (51.4% vs. 82.4% and 81.4%) respectively.

CONCLUSION

Bilateral and peripheral GGO were the most frequent findings with the right and lower lobar predilection. The pattern and the distribution of CT changes seem to be age-specific.

Association between NT-proBNP Level and the Severity of COVID-19 Pneumonia

In this study, we investigated the association between the plasma NT-proBNP level at admission and the severity of COVID-19 pneumonia. For this retrospective, single-centre cohort study, we enrolled consecutive patients from February 9 to March 4, 2020, in a COVID-19 ward of Hubei General Hospital (East Branch) in Wuhan, which is a government-assigned centre for COVID-19 treatment. Diagnosis was confirmed by microbiological and radiographic findings following the interim guidance of the World Health Organization (WHO). A total of 91 (92.9%) patients were finally included in this study. The median age of the patients was 61 years (IQR, 47–69), and 39 (43.0%) of them were male. Two cases of death were reported (2.3%). Twenty-three patients (25.3%) had NT-proBNP levels above 300 pg/ml. Higher NT-proBNP levels were associated with worse PSI and CT scores. The natural logarithm of the NT-proBNP level was positively correlated with the PSI and CT scores (PSI score: r_S = 0.396, P=0.001; CT score: r_S = 0.440, P < 0.001). Patients with NT-proBNP ≥300 pg/ml showed a potential risk for higher mortality than patients with NT-proBNP <300 pg/ml (mortality rate, 8.7% vs. 0%; P=0.062). The plasma NT-proBNP level of COVID-19 patients was significantly related to the severity of pneumonia.