Point-of-Care Lung Ultrasound Findings in Patients with COVID-19 Pneumonia

Transfer of POCUS Skills of Anesthesia Trainees from the Simulation Laboratory to Clinical Practice: A Follow-Up Pilot Evaluation After ABC US Protocol Training

Background/objectives: Point-of-care ultrasound (POCUS) in the intensive care unit (ICU) has gained much attention in the last few years as an alternative to the classic ways of assessing and diagnosing life-threatening conditions in critical patients. During the COVID-19 pandemic, we proposed a POCUS protocol based on the airway, breathing, and circulation (ABC) approach to quickly evaluate and diagnose life-threatening diseases in critical patients with acute respiratory failure and shock, and later, we used it as a curriculum to teach POCUS to anesthesia and intensive care trainees. Methods: We developed an evaluation protocol where evaluators with experience in POCUS in critically ill patients had to assess the trainee's ultrasound scan; this was based on the ABC protocol taught in the simulation laboratory and applied in a clinical setting at the bedside. Results: Statistically significant differences were observed in some categories evaluated regarding independence and diagnosis. Conclusion: Initial POCUS simulation-based training using an ABC POCUS protocol (that demonstrated good results in the simulation laboratory) is useful when transferring US skills to the bedside and is applicable in daily clinical practice with good results in terms of operator independence.

Lung Ultrasound in Predicting Outcomes in Patients with COVID-19 Treated with Extracorporeal Membrane Oxygenation

Pulmonary involvement due to SARS-CoV-2 infection can lead to acute respiratory distress syndrome in patients with COVID-19. Consequently, pulmonary imaging is crucial for management of COVID-19. This study aimed to evaluate the prognostic value of lung ultrasound (LUS) with a handheld ultrasound device (HHUD) in patients with COVID-19 treated with extracorporeal membrane oxygenation (ECMO). Therefore, patients underwent LUS with a HHUD every two days until they were either discharged from the intensive care unit or died. The study was conducted at the University Hospital of Bonn's anesthesiological intensive care ward from December 2020 to August 2021. A total of 33 patients (median [IQR]: 56.0 [53-60.5] years) were included. A high LUS score was associated with a decreased P/F ratio (repeated measures correlation [rmcorr]: -0.26; 95% CI: -0.34, -0.15; p < 0.001), increased extravascular lung water, defined as fluid accumulation in the pulmonary interstitium and alveoli (rmcorr: 0.11; 95% CI: 0.01, 0.20; p = 0.030), deteriorated electrolyte status (base excess: rmcorr: 0.14; 95% CI: 0.05, 0.24; p = 0.004; pH: rmcorr: 0.12; 95% CI: 0.03, 0.21; p = 0.001), and decreased pulmonary compliance (rmcorr: -0.10; 95% CI: -0.20, -0.01; p = 0.034). The maximum LUS score was lower in survivors (median difference [md]: -0.35; 95% CI: -0.55, -0.06; p = 0.006). A cutoff value for non-survival was calculated at a LUS score of 2.63. At the time of maximum LUS score, P/F ratio (md: 1.97; 95% CI: 1.12, 2.76; p < 0.001) and pulmonary compliance (md: 18.67; 95% CI: 3.33, 37.15; p = 0.018) were higher in surviving patients. In conclusion, LUS with a HHUD enables continuous evaluation of cardiopulmonary function in COVID-19 patients receiving ECMO support therapy and provides prognostic value in determining the patients' likelihood of survival.

A Review of Crucial Radiological Investigations in the Management of COVID-19 Cases

Chest X-ray, chest CT, and lung ultrasound are the most common radiological interventions used in the diagnosis and management of coronavirus disease 2019 (COVID-19) patients. The purpose of this literature review, which was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, is to determine which radiological investigation is crucial for that purpose. PubMed, Medline, American Journal of Radiology (AJR), Public Library of Science (PLOS), Elsevier, National Center for Biotechnology Information (NCBI), and ScienceDirect were explored. Seventy-two articles were reviewed for potential inclusion, including 50 discussing chest CT, 15 discussing chest X-ray, five discussing lung ultrasound, and two discussing COVID-19 epidemiology. The reported sensitivities and specificities for chest CT ranged from 64 to 98% and 25 to 88%, respectively. The reported sensitivities and specificities for chest X-rays ranged from 33 to 89% and 11.1 to 88.9%, respectively. The reported sensitivities and specificities for lung ultrasound ranged from 93 to 96.8% and 21.3 to 95%, respectively. The most common findings on chest CT include ground glass opacities and consolidation. The most common findings on chest X-rays include opacities, consolidation, and pleural effusion. The data indicate that chest CT is the most effective radiological tool for the diagnosis and management of COVID-19 patients. The authors support the continued use of reverse transcription polymerase chain reaction (RT-PCR), along with physical examination and contact history, for such diagnosis. Chest CT could be more appropriate in emergency situations when quick triage of patients is necessary before RT-PCR results are available. CT can also be used to visualize the progression of COVID-19 pneumonia and to identify potential false positive RT-PCR results. Chest X-ray and lung ultrasound are acceptable in situations where chest CT is unavailable or contraindicated.

Emergency Department Point-Of-Care Echocardiography and Lung Ultrasound in Predicting COVID-19 Severity

OBJECTIVES

We sought to determine if point-of-care ultrasound (POCUS) performed on patients with COVID-19 in the emergency department (ED) can help predict disease course, severity, or identify complications.

METHODS

This was a retrospective cohort study of adult ED patients who tested positive for COVID-19 at hospital admission or within 2 weeks of presentation and received heart or lung POCUS. Clips were reviewed for presence of decreased left ventricular ejection fraction (LVEF), right ventricular dilation, presence of B-lines, and pleural line abnormalities. Patients with worsening hypoxemic respiratory failure or shock requiring higher level of care and patients who expired were considered to have developed severe COVID-19. Regression analysis was performed to determine if there was a correlation between ED POCUS findings and development of severe COVID-19.

RESULTS

A total of 155 patients met study criteria; 148 patients had documented cardiac views and 116 patients had documented lung views (113 with both). Mean age was 66.5 years old (±18.6) and 53% of subjects were female. Subjects with decreased LVEF that was not previously documented had increased odds of having severe COVID during their hospitalization compared to those with old or no dysfunction (OR 5.66, 95% CI: 1.55-19.95, P = .08). The presence of pleural line abnormalities was also predictive for development of severe COVID (OR 2.68, 95% CI: 1.04-6.92, P = .04).

CONCLUSION

POCUS findings of previously unidentified decreased LVEF and pleural line abnormalities in patients with COVID-19 evaluated in the ED were correlated to a more severe clinical course and worse prognosis.

Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees

COVID-19 raised the need for automatic medical diagnosis, to increase the physicians' efficiency in managing the pandemic. Among all the techniques for evaluating the status of the lungs of a patient with COVID-19, lung ultrasound (LUS) offers several advantages: portability, cost-effectiveness, safety. Several works approached the automatic detection of LUS imaging patterns related COVID-19 by using deep neural networks (DNNs). However, the decision processes based on DNNs are not fully explainable, which generally results in a lack of trust from physicians. This, in turn, slows down the adoption of such systems. In this work, we use two previously built DNNs as feature extractors at the frame level, and automatically synthesize, by means of an evolutionary algorithm, a decision tree (DT) that aggregates in an interpretable way the predictions made by the DNNs, returning the severity of the patients' conditions according to a LUS score of prognostic value. Our results show that our approach performs comparably or better than previously reported aggregation techniques based on an empiric combination of frame-level predictions made by DNNs. Furthermore, when we analyze the evolved DTs, we discover properties about the DNNs used as feature extractors. We make our data publicly available for further development and reproducibility.

Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia

Our automated deep learning-based approach identifies consolidation/collapse in LUS images to aid in the identification of late stages of COVID-19 induced pneumonia, where consolidation/collapse is one of the possible associated pathologies. A common challenge in training such models is that annotating each frame of an ultrasound video requires high labelling effort. This effort in practice becomes prohibitive for large ultrasound datasets. To understand the impact of various degrees of labelling precision, we compare labelling strategies to train fully supervised models (frame-based method, higher labelling effort) and inaccurately supervised models (video-based methods, lower labelling effort), both of which yield binary predictions for LUS videos on a frame-by-frame level. We moreover introduce a novel sampled quaternary method which randomly samples only 10% of the LUS video frames and subsequently assigns (ordinal) categorical labels to all frames in the video based on the fraction of positively annotated samples. This method outperformed the inaccurately supervised video-based method and more surprisingly, the supervised frame-based approach with respect to metrics such as precision-recall area under curve (PR-AUC) and F1 score, despite being a form of inaccurate learning. We argue that our video-based method is more robust with respect to label noise and mitigates overfitting in a manner similar to label smoothing. The algorithm was trained using a ten-fold cross validation, which resulted in a PR-AUC score of 73% and an accuracy of 89%. While the efficacy of our classifier using the sampled quaternary method significantly lowers the labelling effort, it must be verified on a larger consolidation/collapse dataset, our proposed classifier using the sampled quaternary video-based method is clinically comparable with trained experts' performance.

Lung Ultrasound in COVID-19 and Post-COVID-19 Patients, an Evidence-Based Approach

OBJECTIVES

Worldwide, lung ultrasound (LUS) was utilized to assess coronavirus disease 2019 (COVID-19) patients. Often, imaging protocols were however defined arbitrarily and not following an evidence-based approach. Moreover, extensive studies on LUS in post-COVID-19 patients are currently lacking. This study analyses the impact of different LUS imaging protocols on the evaluation of COVID-19 and post-COVID-19 LUS data.

METHODS

LUS data from 220 patients were collected, 100 COVID-19 positive and 120 post-COVID-19. A validated and standardized imaging protocol based on 14 scanning areas and a 4-level scoring system was implemented. We utilized this dataset to compare the capability of 5 imaging protocols, respectively based on 4, 8, 10, 12, and 14 scanning areas, to intercept the most important LUS findings. This to evaluate the optimal trade-off between a time-efficient imaging protocol and an accurate LUS examination. We also performed a longitudinal study, aimed at investigating how to eventually simplify the protocol during follow-up. Additionally, we present results on the agreement between AI models and LUS experts with respect to LUS data evaluation.

RESULTS

A 12-areas protocol emerges as the optimal trade-off, for both COVID-19 and post-COVID-19 patients. For what concerns follow-up studies, it appears not to be possible to reduce the number of scanning areas. Finally, COVID-19 and post-COVID-19 LUS data seem to show differences capable to confuse AI models that were not trained on post-COVID-19 data, supporting the hypothesis of the existence of LUS patterns specific to post-COVID-19 patients.

CONCLUSIONS

A 12-areas acquisition protocol is recommended for both COVID-19 and post-COVID-19 patients, also during follow-up.

Lung Ultrasound for Pleural Line Abnormalities, Confluent B-Lines, and Consolidation: Expert Reproducibility and a Method of Standardization

OBJECTIVES

Discrete B-lines have clear definitions, but confluent B-lines, consolidations, and pleural line abnormalities are less well defined. We proposed definitions for these and determined their reproducibility using COVID-19 patient images obtained with phased array probes.

METHODS

Two raters collaborated to refine definitions, analyzing disagreements on 107 derivation scans from 10 patients. Refined definitions were used by those raters and an independent rater on 1260 validation scans from 105 patients. Reliability was evaluated using intraclass correlation coefficients (ICC) or Cohen's kappa.

RESULTS

The agreement was excellent between collaborating raters for B-line abnormalities, ICC = 0.97 (95% confidence interval [CI] 0.97-0.98) and pleural line to consolidation abnormalities, ICC = 0.90 (95% CI 0.87-0.92). The independent rater's agreement for B-line abnormalities was excellent, ICC = 0.97 (95% CI 0.96-0.97) and for pleural line to consolidation was good, ICC = 0.88 (95% CI 0.84-0.91). Agreement just on pleural line abnormalities was weak (collaborators, κ = 0.54, 95% CI 0.48-0.60; independent, κ = 0.54, 95% CI 0.49-0.59).

CONCLUSION

With proposed definitions or via collaboration, overall agreement on confluent B-lines and pleural line to consolidation abnormalities was robust. Pleural line abnormality agreement itself was persistently weak and caution should be used interpreting pleural line abnormalities with only a phased array probe.

Multiclass Classification of Chest X-Ray Images for the Prediction of COVID-19 Using Capsule Network

It is critical to establish a reliable method for detecting people infected with COVID-19 since the pandemic has numerous harmful consequences worldwide. If the patient is infected with COVID-19, a chest X-ray can be used to determine this. In this work, an X-ray showing a COVID-19 infection is classified by the capsule neural network model we trained to recognise. 6310 chest X-ray pictures were used to train the models, separated into three categories: normal, pneumonia, and COVID-19. This work is considered an improved deep learning model for the classification of COVID-19 disease through X-ray images. Viewpoint invariance, fewer parameters, and better generalisation are some of the advantages of CapsNet compared with the classic convolutional neural network (CNN) models. The proposed model has achieved an accuracy greater than 95% during the model's training, which is better than the other state-of-the-art algorithms. Furthermore, to aid in detecting COVID-19 in a chest X-ray, the model could provide extra information.

Asthma and risk of infection, hospitalization, ICU admission and mortality from COVID-19: Systematic review and meta-analysis

OBJECTIVE

As COVID-19 spreads across the world, there are concerns that people with asthma are at a higher risk of acquiring the disease, or of poorer outcomes. This systematic review aimed to summarize evidence on the risk of infection, severe illness and death from COVID-19 in people with asthma.

DATA SOURCES AND STUDY SELECTION

A comprehensive search of electronic databases including preprint repositories and WHO COVID-19 database was conducted (until 26 May 2020). Studies reporting COVID-19 in people with asthma were included. For binary outcomes, we performed Sidik-Jonkman random effects meta-analysis. We explored quantitative heterogeneity by subgroup analyses, meta regression and evaluating the I2 statistic.

RESULTS

Fifty-seven studies with an overall sample size of 587 280 were included. The prevalence of asthma among those infected with COVID-19 was 7.46% (95% CI = 6.25-8.67). Non-severe asthma was more common than severe asthma (9.61% vs. 4.13%). Pooled analysis showed a 14% risk ratio reduction in acquiring COVID-19 (95% CI = 0.80-0.94; p < 0.0001) and 13% reduction in hospitalization with COVID-19 (95% CI = 0.77-0.99, p = 0.03) for people with asthma compared with those without. There was no significant difference in the combined risk of requiring admission to ICU and/or receiving mechanical ventilation for people with asthma (RR = 0.87 95% CI = 0.94-1.37; p = 0.19) and risk of death from COVID-19 (RR = 0.87; 95% CI = 0.68-1.10; p = 0.25).

CONCLUSION

The findings from this study suggest that the prevalence of people with asthma among COVID-19 patients is similar to the global prevalence of asthma. The overall findings suggest that people with asthma have a lower risk than those without asthma for acquiring COVID-19 and have similar clinical outcomes.

Egyptian Consensus on the Role of Lung Ultrasonography During the Coronavirus Disease 2019 Pandemic

BACKGROUND & AIMS

Coronavirus disease 2019 (COVID-19) is a global health problem, presenting with symptoms ranging from mild nonspecific symptoms to serious pneumonia. Early screening techniques are essential in the diagnosis and assessment of disease progression. This consensus was designed to clarify the role of lung ultrasonography versus other imaging modalities in the COVID-19 pandemic.

METHODS

A multidisciplinary team consisting of experts from different specialties (ie, pulmonary diseases, infectious diseases, intensive care unit and emergency medicine, radiology, and public health) who deal with patients with COVID-19 from different geographical areas was classified into task groups to review the literatures from different databases and generate 10 statements. The final consensus statements were based on expert physically panelists' discussion held in Cairo July 2021 followed by electric voting for each statement.

RESULTS

The statements were electronically voted to be either "agree," "not agree," or "neutral." For a statement to be accepted to the consensus, it should have 80% agreement.

CONCLUSION

Lung ultrasonography is a rapid and useful tool, which can be performed at bedside and overcomes computed tomography limitations, for screening and monitoring patients with COVID-19 with an accepted accuracy rate.

Severe Acute Respiratory Syndrome by SARS-CoV-2 Infection or Other Etiologic Agents Among Brazilian Indigenous Population: An Observational Study from the First Year of Coronavirus Disease (COVID)-19 Pandemic

Background

Indigenous peoples are vulnerable to pandemics, including to the coronavirus disease (COVID)-19, since it causes high mortality and specially, the loss of elderly Indigenous individuals.

Methods

The epidemiological data of severe acute respiratory syndrome (SARS) by SARS-CoV-2 infection or other etiologic agents (OEA) among Brazilian Indigenous peoples during the first year of COVID-19 pandemic was obtained from a Brazilian Ministry of Health open-access database to perform an observational study. Considering only Indigenous individuals diagnosed with SARS by COVID-19, the epidemiology data were also evaluated as risk of death. The type of sample collection for virus screening, demographic profile, clinical symptoms, comorbidities, and clinical evolution were evaluated. The primary outcome was considered the death in the Brazilian Indigenous individuals and the secondary outcome, the characteristics of Brazilian Indigenous infected by SARS-CoV-2 or OEA, as the need for intensive care unit admission or the need for mechanical ventilation support. The statistical analysis was done using Logistic Regression Model. Alpha of 0.05.

Findings

A total of 3,122 cases of Indigenous individuals with SARS in Brazil were reported during the first year of the COVID-19 pandemic. Of these, 1,994 were diagnosed with COVID-19 and 730/1,816 (40.2%) of them died. The death rate among individuals with SARS-CoV-2 was three-fold increased when compared to the group of individuals with OEA. Several symptoms (myalgia, loss of smell, and sore throat) and comorbidities (cardiopathy, systemic arterial hypertension, and diabetes mellitus) were more prevalent in the COVID-19 group when compared to Indigenous individuals with OEA. Similar profile was observed considering the risk of death among the Indigenous individuals with COVID-19 who presented several symptoms (oxygen saturation <95%, dyspnea, and respiratory distress) and comorbidities (renal disorders, cardiopathy, and diabetes mellitus). The multivariate analysis was significant in differentiating between the COVID-19-positive and non-COVID-19 patients [X²₍₇₎=65.187; P-value<0.001]. Among the patients’ features, the following contributed in relation to the diagnosis of COVID-19: age [≥43 years-old [y.o.]; OR=1.984 (95%CI=1.480-2.658)]; loss of smell [OR=2.373 (95%CI=1.461-3.854)]; presence of previous respiratory disorders [OR=0.487; 95%CI=0.287-0.824)]; and fever [OR=1.445 (95%CI=1.082-1.929)]. Also, the multivariate analysis was able to predict the risk of death [X²₍₉₎=293.694; P-value<0.001]. Among the patients’ features, the following contributed in relation to the risk of death: male gender [OR=1.507 (95%CI=1.010-2.250)]; age [≥60 y.o.; OR=3.377 (95%CI=2.292-4.974)]; the need for ventilatory support [invasive mechanical ventilation; OR=24.050 (95%CI=12.584-45.962) and non-invasive mechanical ventilation; OR=2.249 (95%CI=1.378-3.671)]; dyspnea [OR=2.053 (95%CI=1.196-3.522)]; oxygen saturation <95% [OR=1.691 (95%CI=1.050-2.723)]; myalgia [OR=0.423 (95%CI=0.191-0.937)]; and the presence of kidney disorders [OR=3.135 (95%CI=1.144-8.539)].

Interpretation

The Brazilian Indigenous peoples are in a vulnerable situation during the COVID-19 pandemic and presented an increased risk of death due to COVID-19. Several factors were associated with enhanced risk of death, as male sex, older age (≥60 y.o.), and need for ventilatory support; also, other factors might help to differentiate SARS by COVID-19 or by OEA, as older age (≥43 y.o.), loss of smell, and fever.

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo (Foundation for Research Support of the State of São Paulo; #2021/05810-7).

Review of Machine Learning in Lung Ultrasound in COVID-19 Pandemic

Ultrasound imaging of the lung has played an important role in managing patients with COVID-19-associated pneumonia and acute respiratory distress syndrome (ARDS). During the COVID-19 pandemic, lung ultrasound (LUS) or point-of-care ultrasound (POCUS) has been a popular diagnostic tool due to its unique imaging capability and logistical advantages over chest X-ray and CT. Pneumonia/ARDS is associated with the sonographic appearances of pleural line irregularities and B-line artefacts, which are caused by interstitial thickening and inflammation, and increase in number with severity. Artificial intelligence (AI), particularly machine learning, is increasingly used as a critical tool that assists clinicians in LUS image reading and COVID-19 decision making. We conducted a systematic review from academic databases (PubMed and Google Scholar) and preprints on arXiv or TechRxiv of the state-of-the-art machine learning technologies for LUS images in COVID-19 diagnosis. Openly accessible LUS datasets are listed. Various machine learning architectures have been employed to evaluate LUS and showed high performance. This paper will summarize the current development of AI for COVID-19 management and the outlook for emerging trends of combining AI-based LUS with robotics, telehealth, and other techniques.

Ultrasound findings of lung ultrasonography in COVID-19: A systematic review

PURPOSE

To identify the defining lung ultrasound (LUS) findings of COVID-19, and establish its association to the initial severity of the disease and prognostic outcomes.

METHOD

Systematic review was conducted according to the PRISMA guidelines. We queried PubMed, Embase, Web of Science, Cochrane Database and Scopus using the terms ((coronavirus) OR (covid-19) OR (sars AND cov AND 2) OR (2019-nCoV)) AND (("lung ultrasound") OR (LUS)), from 31st of December 2019 to 31st of January 2021. PCR-confirmed cases of SARS-CoV-2 infection, obtained from original studies with at least 10 participants 18 years old or older, were included. Risk of bias and applicability was evaluated with QUADAS-2.

RESULTS

We found 1333 articles, from which 66 articles were included, with a pooled population of 4687 patients. The most examined findings were at least 3 B-lines, confluent B-lines, subpleural consolidation, pleural effusion and bilateral or unilateral distribution. B-lines, its confluent presentation and pleural abnormalities are the most frequent findings. LUS score was higher in intensive care unit (ICU) patients and emergency department (ED), and it was associated with a higher risk of developing unfavorable outcomes (death, ICU admission or need for mechanical ventilation). LUS findings and/or the LUS score had a good negative predictive value in the diagnosis of COVID-19 compared to RT-PCR.

CONCLUSIONS

The most frequent ultrasound findings of COVID-19 are B-lines and pleural abnormalities. High LUS score is associated with developing unfavorable outcomes. The inclusion of pleural effusion in the LUS score and the standardisation of the imaging protocol in COVID-19 LUS remains to be defined.

Edge Detection Algorithm-Based Lung Ultrasound in Evaluation of Efficacy of High-Flow Oxygen Therapy on Critical Lung Injury

The study focused on the therapeutic effects of high-flow oxygen therapy on patients with critical lung injury using edge detection-based ultrasound images. Firstly, the traditional Canny edge detection algorithm was improved, and the optimal threshold was obtained by optimizing the median filter and combining Otsu algorithm and threshold iteration method. Then, the optimized algorithm was compared with the traditional Canny edge detection algorithm and applied to process the lung ultrasound images of 120 cases of critical lung injury, to compare the efficacy of high-flow oxygen therapy and the traditional oxygen therapy. It was found that the peak signal-to-noise ratio (PSNR) (20.34~31.3), edge intensity value (17.89~27.34), and edge detection effect of the improved Canny algorithm were better than the traditional Canny algorithm (15.2~28.61, 9.44~18.56). The failure rate of extubation (4.1%), reintubation rate (0.8%), comfort (2.38 ± 0.15 points), dry humidity score (1.07 ± 0.21 points), antibiotic use (7.41 ± 0.74 days), and hospital stay (8.66 ± 1.02 days) in the experimental group were significantly lower than the corresponding indexes in the control group (11.7%, 5%, 4.25 ± 0.26 minutes, 4.94 ± 0.78 minutes, 19.29 ± 1.7 days, and 27.49 ± 2.22 days), and the difference was statistically significant (P < 0.05). In the experimental group, within 48 hours after extubation, the respiratory rate (RR), heart rate (HR), arterial partial pressure of carbon dioxide (PaCO2), and HCO3 - were significantly lower than those of the control group; and the values of transcutaneous oxygen saturation (SpO2), mean arterial pressure (MAP), arterial partial pressure of oxygen (PaO2), and pH were significantly higher than the control group, and the difference was statistically significant (P < 0.05). In conclusion, the algorithm in this study is superior to the traditional Canny algorithm, and the high-flow oxygen therapy can reduce the failure rate of extubation, strengthen patient comfort, improve the degree of gas humidification, stabilize the respiratory function and circulatory system, and shorten the time of antibiotic use and hospital stay.

Role of Point of Care Ultrasonography in Patients with COVID-19 Associated Acute Kidney Injury

The severe acute respiratory virus covariate-2 (SARS CoV-2) that causes Corona Virus Disease 2019 (COVID-19) has affected more than 194 million people worldwide and has attributed to or caused more than 4 million deaths. Acute kidney injury (AKI) is a common complication of COVID-19. Point of care ultrasonography (POCUS) can be a useful tool for the nephrologist. POCUS can be used to elucidate the cause of kidney disease and then also help to manage volume status. Here, we review pearls and pitfalls of using POCUS to manage COVID-19 associated AKI with special attention to kidney, lung, and cardiac ultrasound.

Recent ultrasound advancements for the manipulation of nanobiomaterials and nanoformulations for drug delivery

Recent advances in ultrasound (US) have shown its great potential in biomedical applications as diagnostic and therapeutic tools. The coupling of US-assisted drug delivery systems with nanobiomaterials possessing tailor-made functions has been shown to remove the limitations of conventional drug delivery systems. The low-frequency US has significantly enhanced the targeted drug delivery effect and efficacy, reducing limitations posed by conventional treatments such as a limited therapeutic window. The acoustic cavitation effect induced by the US-mediated microbubbles (MBs) has been reported to replace drugs in certain acute diseases such as ischemic stroke. This review briefly discusses the US principles, with particular attention to the recent advancements in drug delivery applications. Furthermore, US-assisted drug delivery coupled with nanobiomaterials to treat different diseases (cancer, neurodegenerative disease, diabetes, thrombosis, and COVID-19) are discussed in detail. Finally, this review covers the future perspectives and challenges on the applications of US-mediated nanobiomaterials.

Lung Ultrasound Severity Index: Development and Usefulness in Patients with Suspected SARS-Cov-2 Pneumonia-A Prospective Study

Coronavirus disease 2019 (COVID-19) has spread across the world with a strong impact on populations and health systems. Lung ultrasound is increasingly employed in clinical practice but a standard approach and data on the accuracy of lung ultrasound are still needed. Our study's objective was to evaluate lung ultrasound diagnostic and prognostic characteristics in patients with suspected COVID-19. We conducted a monocentric, prospective, observational study. Patients with respiratory distress and suspected COVID-19 consecutively admitted to the Emergency Medicine Unit were enrolled. Lung ultrasound examinations were performed blindly to clinical data. Outcomes were diagnosis of COVID-19 pneumonia and in-hospital mortality. One hundred fifty-nine patients were included in our study; 66% were males and 63.5% had a final diagnosis of COVID-19. COVID-19 patients had a higher mortality rate (18.8% vs. 6.9%, p = 0.04) and Lung Ultrasound Severity Index (16.14 [8.71] vs. 10.08 [8.92], p < 0.001) compared with non-COVID-19 patients. This model proved able to distinguish between positive and negative cases with an area under the receiver operating characteristic (AUROC) equal to 0.72 (95% confidence interval [CI]: 0.64-0.78) and to predict in-hospital mortality with an AUROC equal to 0.81 (95% CI: 0.74-0.86) in the whole population and an AUROC equal to 0.76 (95% CI: 0.66-0.84) in COVID-19 patients. The Lung Ultrasound Severity Index can be a useful tool in diagnosing COVID-19 in patients with a high pretest probability of having the disease and to identify, among them, those with a worse prognosis.

Diagnostic imaging in COVID-19 pneumonia: a literature review

In December 2019 in Wuhan (China), a bat-origin coronavirus (2019-nCoV), also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified, and the World Health Organization named the related disease COVID-19. Its most severe manifestations are pneumonia, systemic and pulmonary thromboembolism, acute respiratory distress syndrome (ARDS), and respiratory failure. A swab test is considered the gold standard for the diagnosis of COVID-19 despite the high number of false negatives. Radiologists play a crucial role in the rapid identification and early diagnosis of pulmonary involvement. Lung ultrasound (LUS) and computed tomography (CT) have a high sensitivity in detecting pulmonary interstitial involvement. LUS is a low-cost and radiation-free method, which allows a bedside approach and needs disinfection of only a small contact area, so it could be particularly useful during triage and in intensive care units (ICUs). High-resolution computed tomography (HRCT) is particularly useful in evaluating disease progression or resolution, being able to identify even the smallest changes.

The Role and Challenges of Clinical Imaging During COVID-19 Outbreak

Objective:

The Radiology department played a crucial role in detecting and following up with the COVID-19 disease during the pandemic. The purpose of this review was to highlight and discuss the role of each imaging modality, in the radiology department, that can help in the current pandemic and to determine the challenges faced by staff and how to overcome them.

Materials and Methods:

A literature search was performed using different databases, including PubMed, Google scholar, and the college electronic library to access 2020 published related articles.

Results:

A chest computed tomogram (CT) was found to be superior to a chest radiograph, with regards to the early detection of COVID-19. Utilizing lung point of care ultrasound (POCUS) with pediatric patients, demonstrated excellent sensitivity and specificity, compared to a chest radiography. In addition, lung ultrasound (LUS) showed a high correlation with the disease severity assessed with CT. However, magnetic resonance imaging (MRI) has some limiting factors with regard to its clinical utilization, due to signal loss. The reported challenges that the radiology department faced were mainly related to infection control, staff workload, and the training of students.

Conclusion:

The choice of an imaging modality to provide a COVID-19 diagnosis is debatable. It depends on several factors that should be carefully considered, such as disease stage, mobility of the patient, and ease of applying infection control procedures. The pros and cons of each imaging modality were highlighted, as part of this review. To control the spread of the infection, precautionary measures such as the use of portable radiographic equipment and the use of personal protective equipment (PPE) must be implemented.

Applicability of lung ultrasound in COVID-19 diagnosis and evaluation of the disease progression: A systematic review

INTRODUCTION

The COVID-19 pandemic originated in China and within about 4 months affected individuals all over the world. One of the limitations to the management of the COVID-19 is the diagnostic imaging to evaluate lung impairment and the patients' clinical evolution, mainly, in more severe cases that require admission into the intensive care unit. Among image examinations, lung ultrasound (LU) might be a useful tool to employ in the treatment of such patients.

METHODS

A survey was carried out on PubMed to locate studies using the descriptors: ((Lung ultrasound OR ultrasound OR lung ultrasonography OR lung US) AND (coronavirus disease-19 OR coronavirus disease OR corona virus OR COVID-19 OR COVID19 OR SARS-CoV-2)). The period covered by the search was November 2019 to October 2020 and the papers selected reported LU in COVID-19.

RESULTS

Forty-three studies were selected to produce this systematic review. The main LU findings referred to the presence of focal, multifocal and/or confluent B lines and the presence of pleural irregularities.

CONCLUSIONS

The use of LU in the evaluation of patients with COVID-19 should be encouraged due to its intrinsic characteristics; a low cost, radiation free, practical method, with easy to sanitize equipment, which facilitates structural evaluation of lung damage caused by SARS-CoV-2. With the increase in the number of studies and the use of ultrasound scans, LU has been shown as a useful tool to evaluate progression, therapeutic response and follow-up of pulmonary disease in the patients with COVID-19.

Lung Ultrasound for Identification of Patients Requiring Invasive Mechanical Ventilation in COVID-19

OBJECTIVES

Indication for invasive mechanical ventilation in COVID-19 pneumonia has been a major challenge. This study aimed to evaluate if lung ultrasound (LUS) can assist identification of requirement of invasive mechanical ventilation in moderate to severe COVID-19 pneumonia.

MATERIALS AND METHODS

Between April 23 and November 12, 2020, hospitalized patients with moderate to severe COVID-19 (oxygen demand ≥4 L/min) were included consecutively. Lung ultrasound was performed daily until invasive mechanical ventilation (IMV-group) or spontaneous recovery (non-IMV-group). Clinical parameters and lung ultrasound findings were compared between groups, at intubation (IMV-group) and highest oxygen demand (non-IMV-group). A reference group with oxygen demand <4 L/min was examined at hospital admission.

RESULTS

Altogether 72 patients were included: 50 study patients (IMV-group, n = 23; non-IMV-group, n = 27) and 22 reference patients. LUS-score correlated to oxygen demand (SpO₂ /FiO₂ -ratio) (r = 0.728; p < .0001) and was higher in the IMV-group compared to the non-IMV-group (20.0 versus 18.0; p = .026). Based on receiver operating characteristic analysis, a LUS-score of 19.5 was identified as cut-off for requirement of invasive mechanical ventilation (area under the curve 0.68; sensitivity 56%, specificity 74%). In 6 patients, LUS identified critical coexisting conditions. Respiratory rate and oxygenation index ((SpO₂ /FiO₂ )/respiratory rate) ≥4.88 identified no requirement of invasive mechanical ventilation with a positive predictive value of 87% and negative predictive value of 100%.

CONCLUSIONS

LUS-score had only a moderate diagnostic value for requirement of invasive mechanical ventilation in moderate to severe COVID-19. However, LUS proved valuable as complement to respiratory parameters in guidance of disease severity and identifying critical coexisting conditions.

Prediction Accuracy of Serial Lung Ultrasound in COVID-19 Hospitalized Patients (Pred-Echovid Study)

The value of serial lung ultrasound (LUS) in patients with COVID-19 is not well defined. In this multicenter prospective observational study, we aimed to assess the prognostic accuracy of serial LUS in patients admitted to hospital due to COVID-19. The serial LUS protocol included two examinations (0–48 h and 72–96 h after admission) using a 10-zones sequence, and a 0 to 5 severity score. Primary combined endpoint was death or the need for invasive mechanical ventilation. Calibration (Hosmer–Lemeshow test and calibration curves), and discrimination power (area under the ROC curve) of both ultrasound exams (SCORE1 and 2), and their difference (DIFFERENTIAL-SCORE) were performed. A total of 469 patients (54.2% women, median age 60 years) were included. The primary endpoint occurred in 51 patients (10.9%). Probability risk tertiles of SCORE1 and SCORE2 (0–11 points, 12–24 points, and ≥25 points) obtained a high calibration. SCORE-2 showed a higher discrimination power than SCORE-1 (AUC 0.72 (0.58–0.85) vs. 0.61 (0.52–0.7)). The DIFFERENTIAL-SCORE showed a higher discrimination power than SCORE-1 and SCORE-2 (AUC 0.78 (0.66–0.9)). An algorithm for clinical decision-making is proposed. Serial lung ultrasound performing two examinations during the first days of hospitalization is an accurate strategy for predicting clinical deterioration of patients with COVID-19.

Comparing lung ultrasound: extensive versus short in COVID-19 (CLUES): a multicentre, observational study at the emergency department

BACKGROUND

Bedside lung ultrasound (LUS) is an affordable diagnostic tool that could contribute to identifying COVID-19 pneumonia. Different LUS protocols are currently used at the emergency department (ED) and there is a need to know their diagnostic accuracy.

DESIGN

A multicentre, prospective, observational study, to compare the diagnostic accuracy of three commonly used LUS protocols in identifying COVID-19 pneumonia at the ED.

SETTING/PATIENTS

Adult patients with suspected COVID-19 at the ED, in whom we prospectively performed 12-zone LUS and SARS-CoV-2 reverse transcription PCR.

MEASUREMENTS

We assessed diagnostic accuracy for three different ultrasound protocols using both PCR and final diagnosis as a reference standard.

RESULTS

Between 19 March 2020 and 4 May 2020, 202 patients were included. Sensitivity, specificity and negative predictive value compared with PCR for 12-zone LUS were 91.4% (95% CI 84.4 to 96.0), 83.5% (95% CI 74.6 to 90.3) and 90.0% (95% CI 82.7 to 94.4). For 8-zone and 6-zone protocols, these results were 79.7 (95% CI 69.9 to 87.6), 69.0% (95% CI 59.6 to 77.4) and 81.3% (95% CI 73.8 to 87.0) versus 89.9% (95% CI 81.7 to 95.3), 57.5% (95% CI 47.9 to 66.8) and 87.8% (95% CI 79.2 to 93.2). Negative likelihood ratios for 12, 8 and 6 zones were 0.1, 0.3 and 0.2, respectively. Compared with the final diagnosis specificity increased to 83.5% (95% CI 74.6 to 90.3), 78.4% (95% CI 68.8 to 86.1) and 65.0% (95% CI 54.6 to 74.4), respectively, while the negative likelihood ratios were 0.1, 0.2 and 0.16.

CONCLUSION

Identifying COVID-19 pneumonia at the ED can be aided by bedside LUS. The more efficient 6-zone protocol is an excellent screening tool, while the 12-zone protocol is more specific and gives a general impression on lung involvement.

TRIAL REGISTRATION NUMBER

NL8497.

A New Lung Ultrasound Protocol Able to Predict Worsening in Patients Affected by Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia

OBJECTIVES

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can generate severe pneumonia associated with high mortality. A bedside lung ultrasound (LUS) examination has been shown to have a potential role in this setting. The purpose of this study was to evaluate the potential prognostic value of a new LUS protocol (evaluation of 14 anatomic landmarks, with graded scores of 0-3) in patients with SARS-CoV-2 pneumonia and the association of LUS patterns with clinical or laboratory findings.

METHODS

A cohort of 52 consecutive patients with laboratory-confirmed SARS-CoV-2 underwent LUS examinations on admission in an internal medicine ward and before their discharge. A total LUS score as the sum of the scores at each explored area was computed. We investigated the association between the LUS score and clinical worsening, defined as a combination of high-flow oxygen support, intensive care unit admission, or 30-day mortality as the primary end point.

RESULTS

Twenty (39%) patients showed a worse outcome during the observation period; the mean LUS scores ± SDs were 20.4 ± 8.5 and 29.2 ± 7.3 in patients without and with worsening, respectively (P < .001). In a multivariable analysis, adjusted for comorbidities (>2), age (>65 years), sex (male), and body mass index (≥25 kg/m² ), the association between the LUS score and worsening (odds ratio, 1.17; 95% confidence interval, 1.05 to 1.29; P = .003) was confirmed, with good discrimination of the model (area under the receiver operating characteristic curve, 0.82). A median LUS score higher than 24 was associated with an almost 6-fold increase in the odds of worsening (odds ratio, 5.67; 95% confidence interval, 1.29 to 24.8; P = .021).

CONCLUSIONS

Lung ultrasound can represent an effective tool for monitoring and stratifying the prognosis of patients with SARS-CoV-2 pulmonary involvement.

Medical imaging and computational image analysis in COVID-19 diagnosis: A review

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough, and chronic fatigue, amongst others. The disease may be asymptomatic in some patients in the early stages, which can lead to increased transmission of the disease to others. This study attempts to review papers on the role of imaging and medical image computing in COVID-19 diagnosis. For this purpose, PubMed, Scopus and Google Scholar were searched to find related studies until the middle of 2021. The contribution of this study is four-fold: 1) to use as a tutorial of the field for both clinicians and technologists, 2) to comprehensively review the characteristics of COVID-19 as presented in medical images, 3) to examine automated artificial intelligence-based approaches for COVID-19 diagnosis, 4) to express the research limitations in this field and the methods used to overcome them. Using machine learning-based methods can diagnose the disease with high accuracy from medical images and reduce time, cost and error of diagnostic procedure. It is recommended to collect bulk imaging data from patients in the shortest possible time to improve the performance of COVID-19 automated diagnostic methods.

Pulmonary Ultrasound in the Diagnosis and Monitoring of Coronavirus Disease (COVID-19): A Systematic Review

The goal of this review was to systematize the evidence on pulmonary ultrasound (PU) use in diagnosis, monitorization or hospital discharge criteria for patients with coronavirus disease 2019 (COVID-19). Evidence on the use of PU for diagnosis and monitorization of or as hospital discharge criteria for COVID-19 patients confirmed to have COVID-19 by reverse transcription polymerase chain reaction (RT-PCR) between December 1, 2019 and July 5, 2020 was compared with evidence obtained with thoracic radiography (TR), chest computed tomography (CT) and RT-PCR. The type of study, motives for use of PU, population, type of transducer and protocol, results of PU and quantitative or qualitative correlation with TR and/or chest CT and/or RT-PCR were evaluated. A total of 28 articles comprising 418 patients were involved. The average age was 50 y (standard deviation: 25.1 y), and there were 395 adults and 23 children. One hundred forty-three were women, 13 of whom were pregnant. The most frequent result was diffuse, coalescent and confluent B-lines. The plural line was irregular, interrupted or thickened. The presence of subpleural consolidation was noduliform, lobar or multilobar. There was good qualitative correlation between TR and chest CT and a quantitative correlation with chest CT of r = 0.65 (p < 0.001). Forty-four patients were evaluated only with PU. PU is a useful tool for diagnosis and monitorization and as criteria for hospital discharge for patients with COVID-19.

Comparison Between Lung Ultrasound and Computed Tomographic Findings in Patients With COVID-19 Pneumonia

OBJECTIVES

The aim of this study was to describe findings from lung ultrasound (LUS) and computed tomography (CT) in health professionals with coronavirus disease 2019 pneumonia and to evaluate the associations of the findings of both tests.

METHODS

This cross-sectional observational study evaluated 45 health professionals who were initially seen in screening tents and had a diagnosis of coronavirus disease 2019 as confirmed by a reverse transcription polymerase chain reaction and lung involvement diagnosed by LUS. Subsequently, these individuals were admitted to the hospital, where chest CT was performed. Aeration scores were obtained for the LUS examinations based on the following findings: more than 2 B-lines, coalescent B-lines, and subpleural consolidations. A subjective assessment of the extent of lung disease on CT was performed on the basis of the percentage of lung parenchyma involvement as follows: 25% or less, 25% to 50%, and greater than 50%.

RESULTS

Regarding LUS signs, more than 2 B-lines, coalescent B-lines, and subpleural consolidations were present in 73.3%, 68.2%, and 24.4% of cases, respectively. The main findings on CT were ground glass opacities, a crazy-paving pattern, and consolidations (66.7%, 20%, and 20% of cases); 17.8% of cases had examinations without abnormalities. Patients with more than 2 B-lines on LUS had more ground glass opacity areas on CT (P = .0007), whereas patients with subpleural consolidations on LUS had more consolidations on CT (P < .0001). In addition, patients with higher LUS aeration scores had more extensive disease on CT (P < .0001).

CONCLUSIONS

Lung ultrasound can detect lung injury even in the presence of normal CT results. There are associations between the abnormalities detected by both methods, and a relationship also exists between LUS aeration scores and the disease extent on CT.

Epidemiological and clinical characteristics of cancer patients with COVID-19: A systematic review and meta-analysis of global data

There are minimal data regarding the prevalence of cancer in patients with coronavirus disease 2019 (COVID-19), as well as the incidence of severe illness and rate of mortality in COVID-19 patients with cancer. PubMed, Embase, Cochrane Library, and Web of Science were systematically searched, from database inception to July 15, 2020, for studies of patients with COVID-19 that included information regarding comorbid cancer. In total, 109 eligible global studies were included in this systematic review. Ninety studies with 94,845 COVID-19 patients, among which 4106 exhibited comorbid cancer, were included in the meta-analysis regarding prevalence of comorbid cancer. Twenty-three studies with 71,969 COVID-19 patients, among which 4351 with comorbid cancer had severe illness or death, were included in the meta-analysis. The overall prevalence of cancer among COVID-19 patients was 0.07 (95% CI 0.05-0.09). The cancer prevalence in COVID-19 patients was higher in Europe (0.22, 95% CI 0.17-0.28) than in the Asia-Pacific region (0.04, 95% CI 0.03-0.06) or North America (0.05, 95% CI 0.04-0.06). The cancer prevalence in COVID-19 patients aged >60 years was 0.10 (95% CI 0.07-0.14), while the prevalence among patients aged ≤60 years was 0.05 (95% CI 0.03-0.06). The pooled prevalence of severe illness among COVID-19 patients with cancer was 0.34 (95% CI 0.26-0.42) and the pooled mortality rate of COVID-19 patients with cancer was 0.20 (95% CI 0.16-0.25). Pooled incidences of severe illness among COVID-19 patients with cancer from Asia Pacific, Europe, and North America were 0.38 (95% CI 0.24-0.52), 0.39 (95% CI 0.25-0.53), and 0.26 (95% CI 0.20-0.31), respectively; pooled mortality rates from the Asia-Pacific region, Europe, and North America were 0.17 (95% CI 0.10-0.24), 0.26 (95% CI 0.18-0.35), and 0.19 (95% CI 0.13-0.25), respectively.

Coronavirus Disease 2019 in Children

Since its appearance in Wuhan in mid-December 2019, acute respiratory syndrome coronavirus 2 (SARS-CoV-2) related 19 coronavirus disease (COVID-19) has spread dramatically worldwide. It soon became apparent that the incidence of pediatric COVID-19 was much lower than the adult form. Morbidity in children is characterized by a variable clinical presentation and course. Symptoms are similar to those of other acute respiratory viral infections, the upper airways being more affected than the lower airways. Thus far, over 90% of children who tested positive for the virus presented mild or moderate symptoms and signs. Most children were asymptomatic, and only a few cases were severe, unlike in the adult population. Deaths have been rare and occurred mainly in children with underlying morbidity. Factors as reduced angiotensin-converting enzyme receptor expression, increased activation of the interferon-related innate immune response, and trained immunity have been implicated in the relative resistance to COVID-19 in children, however the underlying pathogenesis and mechanism of action remain to be established. While at the pandemic outbreak, mild respiratory manifestations were the most frequently described symptoms in children, subsequent reports suggested that the clinical course of COVID-19 is more complex than initially thought. Thanks to the experience acquired in adults, the diagnosis of pediatric SARS-CoV-2 infection has improved with time. Data on the treatment of children are sparse, however, several antiviral trials are ongoing. The purpose of this narrative review is to summarize current understanding of pediatric SARS-CoV-2 infection and provide more accurate information for healthcare workers and improve the care of patients.

Lung Assessment with Point-of-Care Ultrasound in Respiratory Coronavirus Disease (COVID-19): A Prospective Cohort Study

Lung ultrasound (LUS) has shown promising diagnostic potential in different pulmonary conditions. We evaluated the diagnostic accuracy of LUS for pulmonary COVID-19. In this prospective cohort study at a Swiss tertiary care center, patients hospitalized with suspected COVID-19 were scanned using a 12-zone protocol. Association of a summation score (0-36 points) with the final diagnosis was tested using the area under the receiver operating characteristic curve and sensitivity and specificity at different cutoff points. Of the 49 participants, 11 (22%) were later diagnosed with COVID-19. LUS score showed excellent diagnostic performance, with an odds ratio of 1.30 per point (95% confidence interval [CI], 1.09-1.54, p = 0.003) and an area under the curve of 0.85 (95% CI, 0.71-0.99). At a cutoff of 8/36 points, 10 of 11 participants later diagnosed with COVID-19 were correctly predicted (sensitivity 91%, 95% CI, 59%-100%), and 29 of the 38 who were not diagnosed with COVID-19 were correctly ruled out (specificity 76%, 95% CI, 60%-89%). LUS demonstrated promising discriminatory potential in people hospitalized with suspected COVID-19.

Lung Ultrasound Patterns and Clinical-Laboratory Correlates during COVID-19 Pneumonia: A Retrospective Study from North East Italy

Background and Aim. Lung ultrasound (LUS) is a convenient imaging modality in the setting of coronavirus disease-19 (COVID-19) because it is easily available, can be performed bedside and repeated over time. We herein examined LUS patterns in relation to disease severity and disease stage among patients with COVID-19 pneumonia. Methods. We performed a retrospective case series analysis of patients with confirmed SARS-CoV-2 infection who were admitted to the hospital because of pneumonia. We recorded history, clinical parameters and medications. LUS was performed and scored in a standardized fashion by experienced operators, with evaluation of up to 12 lung fields, reporting especially on B-lines and consolidations. Results. We included 96 patients, 58.3% men, with a mean age of 65.9 years. Patients with a high-risk quick COVID-19 severity index (qCSI) were older and had worse outcomes, especially for the need for high-flow oxygen. B-lines and consolidations were located mainly in the lower posterior lung fields. LUS patterns for B-lines and consolidations were significantly worse in all lung fields among patients with high versus low qCSI. B-lines and consolidations were worse in the intermediate disease stage, from day 7 to 13 after onset of symptoms. While consolidations correlated more with inflammatory biomarkers, B-lines correlated more with end-organ damage, including extrapulmonary involvement. Conclusions. LUS patterns provide a comprehensive evaluation of patients with COVID-19 pneumonia that correlated with severity and dynamically reflect disease stage. LUS patterns may reflect different pathophysiological processes related to inflammation or tissue damage; consolidations may represent a more specific sign of localized disease, whereas B-lines seem to be also dependent upon generalized illness due to SARS-CoV-2 infection.

Low Sensitivity of Admission Lung US Compared to Chest CT for Diagnosis of Lung Involvement in a Cohort of 82 Patients with COVID-19 Pneumonia

Background and Objectives: The potential role of lung ultrasound (LUS) in characterizing lung involvement in Coronavirus disease 2019 (COVID-19) is still debated. The aim of the study was to estimate sensitivity of admission LUS for the detection of SARS-CoV-2 lung involvement using Chest-CT (Computed Tomography) as reference standard in order to assess LUS usefulness in ruling out COVID-19 pneumonia in the Emergency Department (ED). Methods: Eighty-two patients with confirmed COVID-19 and signs of lung involvement on Chest-CT were consecutively admitted to our hospital and recruited in the study. Chest-CT and LUS examination were concurrently performed within the first 6-12h from admission. Sensitivity of LUS was calculated using CT findings as a reference standard. Results: Global LUS sensitivity in detecting COVID-19 pulmonary lesions was 52%. LUS sensitivity ranged from 8% in case of focal and sporadic ground-glass opacities (mild disease), to 52% for a crazy-paving pattern (moderate disease) and up to 100% in case of extensive subpleural consolidations (severe disease), although LUS was not always able to detect all the consolidations assessed at Chest-CT. LUS sensitivity was higher in detecting a typical Chest-CT pattern (60%) and abnormalities showing a middle-lower zone predominance (79%). Conclusions: As admission LUS may result falsely negative in most cases, it should not be considered as a reliable imaging tool in ruling out COVID-19 pneumonia in patients presenting in ED. It may at least represent an expanded clinical evaluation that needs integration with other diagnostic tests (e.g., nasopharyngeal swab, Chest-CT).

Comparison of Lung Ultrasound versus Chest X-ray for Detection of Pulmonary Infiltrates in COVID-19

Point-of-care lung ultrasound (LUS) is an attractive alternative to chest X-ray (CXR), but its diagnostic accuracy compared to CXR has not been well studied in coronavirus disease 2019 (COVID-19) patients. We conducted a prospective observational study to assess the correlation between LUS and CXR findings in COVID-19 patients. Ninety-six patients with a clinical diagnosis of COVID-19 underwent an LUS exam and CXR upon presentation. Physicians blinded to the CXR findings performed all LUS exams. Detection of pulmonary infiltrates by CXR versus LUS was compared between patients categorized as suspected or confirmed COVID-19 based on reverse transcriptase-polymerase chain reaction. Sensitivities and correlation by Kappa statistic were calculated between LUS and CXR. LUS detected pulmonary infiltrates more often than CXR in both suspected and confirmed COVID-19 subjects. The most common LUS abnormalities were discrete B-lines, confluent B-lines, and small subpleural consolidations. Most important, LUS detected unilateral or bilateral pulmonary infiltrates in 55% of subjects with a normal CXR. Substantial agreement was demonstrated between LUS and CXR for normal, unilateral or bilateral findings (Κ = 0.48 (95% CI 0.34 to 0.63)). In patients with suspected or confirmed COVID-19, LUS detected pulmonary infiltrates more often than CXR, including more than half of the patients with a normal CXR.

Current understanding of the impact of COVID-19 on gastrointestinal disease: Challenges and openings

The novel coronavirus disease-2019 (COVID-19) is caused by a positive-sense single-stranded RNA virus which belongs to the Coronaviridae family. In March 2019 the World Health Organization declared that COVID-19 was a pandemic. COVID-19 patients typically have a fever, dry cough, dyspnea, fatigue, and anosmia. Some patients also report gastrointestinal (GI) symptoms, including diarrhea, nausea, vomiting, and abdominal pain, as well as liver enzyme abnormalities. Surprisingly, many studies have found severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA in rectal swabs and stool specimens of asymptomatic COVID-19 patients. In addition, viral receptor angiotensin-converting enzyme 2 and transmembrane protease serine-type 2, were also found to be highly expressed in gastrointestinal epithelial cells of the intestinal mucosa. Furthermore, SARS-CoV-2 can dynamically infect and replicate in both GI and liver cells. Taken together these results indicate that the GI tract is a potential target of SARS-CoV-2. Therefore, the present review summarizes the vital information available to date on COVID-19 and its impact on GI aspects.

Point-of-Care Lung Ultrasound for COVID-19: Findings and Prognostic Implications From 105 Consecutive Patients

Background:

The prognostic value of point-of-care lung ultrasound has not been evaluated in a large cohort of patients with COVID-19 admitted to general medicine ward in the United States. The aim of this study was to describe lung ultrasound findings and their prognostic value in patients with COVID-19 admitted to internal medicine ward.

Method:

This prospective observational study consecutively enrolled 105 hospitalized participants with COVID-19 at 2 tertiary care centers. Ultrasound was performed in 12 lung zones within 24 hours of admission. Findings were assessed relative to 4 outcomes: intensive care unit (ICU) need, need for intensive respiratory support, length of stay, and death.

Results:

We detected abnormalities in 92% (97/105) of participants. The common findings were confluent B-lines (92%), non-homogenous pleural lines (78%), and consolidations (54%). Large confluent B-lines, consolidations, bilateral involvement, and any abnormality in ≥ 6 areas were associated with a longer hospitalization and need for intensive respiratory support. Large confluent B-lines and bilateral involvement were also associated with ICU stay. A total lung ultrasound score <5 had a negative predictive value of 100% for the need of intensive respiratory support. A higher total lung ultrasound score was associated with ICU need (median total 18 in the ICU group vs. 11 non-ICU, p = 0.004), a hospitalization ≥ 9d (15 vs 10, p = 0.016) and need for intensive respiratory support (18 vs. 8.5, P < 0.001).

Conclusions:

Most patients hospitalized with COVID-19 had lung ultrasound abnormalities on admission and a higher lung ultrasound score was associated with worse clinical outcomes except death. A low total lung ultrasound score (<5) had a negative predictive value of 100% for the need of intensive respiratory support. Point-of-care ultrasound can aid in the risk stratification for patients with COVID-19 admitted to general wards.

Point-of-care ultrasound in the COVID-19 era: A scoping review

In the midst of the COVID-19 pandemic, unprecedented pressure has been added to healthcare systems around the globe. Imaging is a crucial component in the management of COVID-19 patients. Point-of-care ultrasound (POCUS) such as hand-carried ultrasound emerges in the COVID-19 era as a tool that can simplify the imaging process of COVID-19 patients, and potentially reduce the strain on healthcare providers and healthcare resources. The preliminary evidence available suggests an increasing role of POCUS in diagnosing, monitoring, and risk-stratifying COVID-19 patients. This scoping review aims to delineate the challenges in imaging COVID-19 patients, discuss the cardiopulmonary complications of COVID-19 and their respective sonographic findings, and summarize the current data and recommendations available. There is currently a critical gap in knowledge in the role of POCUS in the COVID-19 era. Nonetheless, it is crucial to summarize the current preliminary data available in order to help fill this gap in knowledge for future studies.

Pragmatic Recommendations for the Use of Diagnostic Testing and Prognostic Models in Hospitalized Patients with Severe COVID-19 in Low- and Middle-Income Countries

Management of patients with severe or critical COVID-19 is mainly modeled after care of patients with severe pneumonia or acute respiratory distress syndrome from other causes. These models are based on evidence that primarily originates from investigations in high-income countries, but it may be impractical to apply these recommendations to resource-restricted settings in low- and middle-income countries (LMICs). We report on a set of pragmatic recommendations for microbiology and laboratory testing, imaging, and the use of diagnostic and prognostic models in patients with severe COVID-19 in LMICs. For diagnostic testing, where reverse transcription-PCR (RT-PCR) testing is available and affordable, we recommend using RT-PCR of the upper or lower respiratory specimens and suggest using lower respiratory samples for patients suspected of having COVID-19 but have negative RT-PCR results for upper respiratory tract samples. We recommend that a positive RT-PCR from any anatomical source be considered confirmatory for SARS-CoV-2 infection, but, because false-negative testing can occur, recommend that a negative RT-PCR does not definitively rule out active infection if the patient has high suspicion for COVID-19. We suggest against using serologic assays for the detection of active or past SARS-CoV-2 infection, until there is better evidence for its usefulness. Where available, we recommend the use of point-of-care antigen-detecting rapid diagnostic testing for SARS-CoV-2 infection as an alternative to RT-PCR, only if strict quality control measures are guaranteed. For laboratory testing, we recommend a baseline white blood cell differential platelet count and hemoglobin, creatinine, and liver function tests and suggest a baseline C-reactive protein, lactate dehydrogenase, troponin, prothrombin time (or other coagulation test), and D-dimer, where such testing capabilities are available. For imaging, where availability of standard thoracic imaging is limited, we suggest using lung ultrasound to identify patients with possible COVID-19, but recommend against its use to exclude COVID-19. We suggest using lung ultrasound in combination with clinical parameters to monitor progress of the disease and responses to therapy in COVID-19 patients. We currently suggest against using diagnostic and prognostic models as these models require extensive laboratory testing and imaging, which often are limited in LMICs.

COVID-19 Dentistry-Related Aspects: A Literature Overview

A new coronavirus (Sars-CoV-2) was detected in China at the end of 2019 and has since caused a worldwide pandemic. This virus is responsible for an acute respiratory syndrome (COVID-19), distinguished by a potentially lethal interstitial bilateral pneumonia. Because Sars-CoV-2 is highly infective through airborne contamination, the high infection risk in the dental environment is a serious problem for both professional practitioners and patients. This literature overview provides a description of the clinical aspects of COVID-19 and its transmission, while supplying valuable information regarding protection and prevention measures.

Utility of Lung Ultrasound in Decision-making to Prioritize Hospital Admission for COVID-19 Patients: A Developing Country Perspective

BACKGROUND AND AIMS

In the midst of this pandemic, planning the prioritization of hospital admissions for patients affected with COVID-19 should be of prime concern, particularly in healthcare settings with limited resources. Thus, in this study, we aimed to develop a novel approach to triage COVID-19 patients and attempt to prioritize their hospital admission using Lung Ultrasonography (LUS). The efficacy of LUS in triaging suspected COVID-19 patients and assessing the severity of COVID-19 pneumonia was evaluated; the findings were then compared with those obtained by chest computed tomography (CT).

METHODS

This multicenter, cross-sectional study comprised 243 COVID-19 patients who presented to the emergency department in 3 major university hospitals in Egypt. LUS was performed by an experienced emergency or chest physician, according to the local protocol of each hospital. Demographic, clinical, and laboratory data were then collected from each patient. Each patient was subjected to chest CT scans and LUS.

RESULTS

The mean age of the 243 patients was 46.7 ± 10.4 years. Ground-glass opacity, subpleural consolidation, translobar consolidation, and crazy paving were reported in the chest CT scans of 54.3%, 15.2%, 11.1%, and 8.6% of the patients, respectively. B-line artifacts were observed in 81.1% of the patients (confluent pattern, 18.9%). The LUS findings completely coincided with the CT findings (Kappa agreement value, 0.77) in 197 patients (81.1%) and offered a diagnostic sensitivity of 74%, diagnostic specificity of 97.9%, positive predictive value of 90.2%, and negative predictive value of 93.6% for the COVID-19 patients. Following the addition of O2 saturation to the lung imaging findings, the ultrasound method was able to demonstrate 100% sensitivity and specificity in accurately differentiating between severe and non-severe lung diseases.

CONCLUSION

LUS with oxygen saturation might prove to be effective in prioritizing the hospital admission of COVID-19 patients, particularly in healthcare settings with limited resources.

Role of lung ultrasonography in the diagnosis of COVID-19 patients admitted to the emergency department

Introduction

In this study, the use of lung ultrasonography (LUS) to diagnosis lung findings was evaluated in patients with suspected COVID-19 who were admitted to the emergency department (ED).

Methods

This observational clinical study was conducted in the ED of the Ankara City Hospital during the period April 1–30, 2020. Patients who were admitted to the ED were triaged as COVID-19 infected and who agreed to undergo LUS/LCT (lung computed tomography) were included in the study.

Results

Included in the study were 40 patients who had been prediagnosed with COVID-19. Pneumonia was detected with LCT in 32 (80%) patients, while the LUS examination identified pneumonia in 23 patients. The most common finding in LCT was ground-glass opacity (n = 29, 90.6%). Of the 23 patients with pneumonia findings in LUS, 15 (65.2%) had direct consolidation. Among the 32 patients who were found to have pneumonia as a result of LCT, 20 (62.5%) had signs of pneumonia on LUS examination, and 12 had no signs of pneumonia. In addition, 3 patients showed no signs of pneumonia with LCT, but they were misdiagnosed with pneumonia by LUS. The sensitivity of LUS in the diagnosis of pneumonia in the COVID-19 patients was 62.5%, while its specificity was 62.5%. In addition, its positive predictive value was 87.0%, and its negative predictive value was 29.4%.

Conclusion

LUS may also be used in the diagnosis of pneumonia in COVID-19 patients because it is a valuable and accessible bedside diagnostic tool.

Electronic supplementary material

The online version of this article (10.1007/s10049-020-00807-3) shows RT-PCR results of patients with a definitive diagnosis of COVID-19 by lung computed tomography and patients with pneumonia detected by lung ultrasonography.

The article and additional material are available at www.springermedizin.de. Please enter the title of the article in the search field. You will find the additional material under “Ergänzende Inhalte” in the article.

Serum Interleukin-6 Concentrations and the Severity of COVID-19 Pneumonia: A Retrospective Study at a Single Center in Bengbu City, Anhui Province, China, in January and February 2020

Background

At present, the relationships among COVID-19 disease progression, patient prognosis, and immune status are unclear. This single-center retrospective study evaluated the correlation between serum interleukin-6 (IL-6) levels at admission with the severity of COVID-19 pneumonia, as determined by admission to the intensive Care Unit (ICU).

Material/Methods

Patients admitted to The First Affiliated Hospital of Bengbu Medical College in Bengbu City, Anhui Province, China, in January and February 2020 for COVID-19 pneumonia were enrolled in this study. COVID-19 infection was confirmed by the detection of SARS-CoV-2 nucleic acid in throat swab samples using real-time fluorescent reverse transcription PCR. Serum IL-6 concentrations at admission were measured by ELISA. Correlations between serum IL-6 concentrations and ICU admission due to the development of severe COVID-19 pneumonia were evaluated.

Results

This study enrolled 68 patients with novel coronavirus pneumonia. IL-6 concentrations were significantly higher in patients with more severe than less severe COVID-19 pneumonia. Eight of 40 patients with severe COVID-19 pneumonia became critically ill and required ICU admission. IL-6 concentrations were significantly higher in patients with severe COVID-19 pneumonia who were than who were not treated in the ICU. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.816 (P<0.01), indicating that IL-6 was prognostic of disease severity in patients with COVID-19 pneumonia.

Conclusions

Serum IL-6 concentration is closely associated with the severity of COVID-19. Continuous monitoring of IL-6 has clinical value in evaluating patient condition.

The utility of lung ultrasound in COVID-19: A systematic scoping review

Introduction

Lung ultrasound (LUS) has an established evidence base and has proven useful in previous viral epidemics. An understanding of the utility of LUS in COVID-19 is crucial to determine its most suitable role based on local circumstances.

Method

Online databases, specialist websites and social media platforms were searched to identify studies that explore the utility of LUS in COVID-19. Case reports and recommendations were excluded.

Findings

In total, 33 studies were identified which represent a rapidly expanding evidence base for LUS in COVID-19. The quality of the included studies was relatively low; however, LUS certainly appears to be a highly sensitive and fairly specific test for COVID-19 in all ages and in pregnancy.

Discussion

There may be LUS findings and patterns that are relatively specific to COVID-19; however, specificity may also be influenced by factors such as disease severity, pre-existing lung disease, operator experience, disease prevalence and the reference standard.

Conclusion

LUS is almost certainly more sensitive than chest radiograph for COVID-19 and has several advantages over computed tomography and real-time polymerase chain reaction. High-quality research is needed into various aspects of LUS including: diagnostic accuracy in undifferentiated patients; triage and prognostication; monitoring progression and guiding interventions; the persistence of residual LUS findings; inter-observer agreement and the role of contrast-enhanced LUS.

Changes in lung ultrasound of symptomatic healthcare professionals with COVID-19 pneumonia and their association with clinical findings

PURPOSE

To evaluate ultrasound signs of coronavirus disease-19 (COVID-19) pneumonia in symptomatic healthcare professionals and to correlate those changes with clinical findings.

METHODS

All patients underwent real-time polymerase chain reaction (RT-PCR), lung ultrasound (LUS) and clinical evaluation on the same day. In each of the 12 areas evaluated in the LUS, the LUS signs were scored to generate the aeration score.

RESULTS

A total of 409 participants had positive PCR, with a median age of 41 (35-51) years. All participants had clinical symptoms, with cough in 84.1%, fever in 69.7%, and dyspnea in 36.2% of cases. In the LUS, 72.6% of participants had B-lines >2, 36.2% had coalescent B-lines, and 8.06% had subpleural consolidations. The median aeration score was 3 (2-7). The aeration score differed significantly regarding the presence of cough (P = .002), fever (P = .001), and dyspnea (P < .0001). The finding of subpleural consolidations in the LUS showed significant differences between participants with or without dyspnea (P < .0001).

CONCLUSIONS

In healthcare professionals with COVID-19, LUS plays a key role in the characterization of lung involvement. Although B-lines are the most common ultrasound sign, subpleural consolidations are those that most impact the respiratory condition.

Case Report: Lung Ultrasound for the Guidance of Adjunctive Therapies in Two Invasively Ventilated Patients with COVID-19

Two patients with respiratory failure due to confirmed COVID-19 were examined using bedside lung ultrasound (LUS) shortly after intubation and start of invasive ventilation. In the first patient, LUS revealed extensive atelectatic areas. A recruitment maneuver was applied, resulting in some reaeration of areas that showed atelectasis, and some improvement in oxygenation was observed. Oxygenation improved further with the use of prone positioning. In the second patient, LUS showed diffuse abnormalities without atelectatic areas, and ventilation proceeded without a recruitment maneuver but with prone positioning. These two cases illustrate how LUS could be useful in identifying different lung morphologies early after the start of invasive ventilation and help decide on adjunctive therapies. This has possible implications for ventilator management in resource-limited settings, with limited availability of chest computed tomography and blood gas analyzers. Tailoring invasive ventilation based on LUS findings early after the start of invasive ventilation is feasible, but this should be further evaluated in future studies.

Lung Ultrasound May Support Diagnosis and Monitoring of COVID-19 Pneumonia

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) is characterized by severe pneumonia and/or acute respiratory distress syndrome in about 20% of infected patients. Computed tomography (CT) is the routine imaging technique for diagnosis and monitoring of COVID-19 pneumonia. Chest CT has high sensitivity for diagnosis of COVID-19, but is not universally available, requires an infected or unstable patient to be moved to the radiology unit with potential exposure of several people, necessitates proper sanification of the CT room after use and is underutilized in children and pregnant women because of concerns over radiation exposure. The increasing frequency of confirmed COVID-19 cases is striking, and new sensitive diagnostic tools are needed to guide clinical practice. Lung ultrasound (LUS) is an emerging non-invasive bedside technique that is used to diagnose interstitial lung syndrome through evaluation and quantitation of the number of B-lines, pleural irregularities and nodules or consolidations. In patients with COVID-19 pneumonia, LUS reveals a typical pattern of diffuse interstitial lung syndrome, characterized by multiple or confluent bilateral B-lines with spared areas, thickening of the pleural line with pleural line irregularity and peripheral consolidations. LUS has been found to be a promising tool for the diagnosis of COVID-19 pneumonia, and LUS findings correlate fairly with those of chest CT scan. Compared with CT, LUS has several other advantages, such as lack of exposure to radiation, bedside repeatability during follow-up, low cost and easier application in low-resource settings. Consequently, LUS may decrease utilization of conventional diagnostic imaging resources (CT scan and chest X-ray). LUS may help in early diagnosis, therapeutic decisions and follow-up monitoring of COVID-19 pneumonia, particularly in the critical care setting and in pregnant women, children and patients in areas with high rates of community transmission.

Lung ultrasound in early SARS-CoV-2 pneumonia and the LUS-CoV criteria

There is a scarcity of data on lung ultrasound (LUS) in SARS-CoV-2 pneumonia. As with many other pulmonary conditions, ultrasound may be a better diagnostic tool than routine chest radiography. In an era where computed tomography scanning is deferred because of the potential for cross-contamination, we evaluated the ability of LUS to detect a pattern of lung injury in SARS-CoV-2 pneumonia. A limited anterolateral LUS was performed to limit time spent in isolation rooms by ultrasound operators. We chose to use a hand-held ultrasound device due to portability and superior confidence in infection control. Both linear and phased array probes were used to obtain images of the pleura and lung. Of 69 patients who had lung ultrasound images saved and were included in the analysis, 36 were positive for SARS-CoV-2. Multifocal confluent B-lines, pleural irregularities, and the absence of moderate or large pleural effusions were the predominant pattern observed in most (86%) of SARS-CoV-2–positive patients. We evaluated the accuracy of the above criteria (LUS-CoV) and report a high sensitivity (91%) and specificity (86%) for SARS-CoV-2 pneumonia. In conclusion, a characteristic sonographic pattern of multifocal confluent B-lines with irregular pleural markings was seen on LUS in patients with SARS-CoV-2 pneumonia.

The Role of the Lung Ultrasound in Coronavirus Disease 2019: A Systematic Review

The coronavirus disease 2019 (COVID-19) pandemic has now infected six million people and is responsible for nearly four hundred thousand deaths. We review the potential role of the lung ultrasound to evaluate its benefits and potential roles to compare it to the current gold standard of computed tomography. A literature search was carried out utilizing electronic search engines and databases with COVID-19. Keywords related to the lung ultrasound (LUS) were used to refine this search - only the relevant articles found are cited. This review showed that there exists a strong correlation between the CT and LUS scan in COVID-19. Prominent features include the vertical B-lines, thicker pleural lines, and subpleural consolidation. Potential roles include reducing transmission between health-care workers and monitoring the progress of the disease. However, the current research is scarce compared to well-established imaging modalities, and as such, there is a necessity for more research to confirm the findings of this review.