Lung ultrasound findings in patients with COVID-19 pneumonia

Application and internal validation of lung ultrasound score in COVID-19 setting: The ECOVITA observational study

BACKGROUND

The severe acute respiratory syndrome Coronarovirus-2 associated still causes a significant number of deaths and hospitalizations mainly by the development of respiratory failure. We aim to validate lung ultrasound score in order to predict mortality and the severity of the clinical course related to the need of respiratory support.

METHODS

In this prospective multicenter hospital-based cohort study, all adult patients with diagnosis of SARS-CoV-2 infection, performed by real-time reverse transcription polymerase chain reaction were included. Upon admission, all patients underwent blood gas analysis and lung ultrasound by expert operators. The acquisition of ultrasound scan was performed on 12 peculiar anatomic landmarks of the chest. Lung ultrasound findings were classified according to a scoring method, ranging 0 to 3: Score 0: normal A-lines. Score 1: multiple separated B-lines. Score 2: coalescent B-lines, alteration of pleural line. Score 3: consolidation area.

RESULTS

One thousand and seven patients were included in statistical analysis (male 62.4 %, mean age 66.3). Oxygen support was needed in 811 (80.5 %) patients. The median ultrasound score was 24 and the risk of having more invasive respiratory support increased in relation to higher values score computed. Lung ultrasound score showed negative strong correlation (rho: -0.71) with the P/F ratio and a significant association with in-hospital mortality (OR 1.11, 95 %CI 1.07-1.14; p < 0.001), even after adjustment with the following variables (age, sex, P/F ratio, SpO2, lactate, hypertension, chronic renal failure, diabetes, and obesity).

CONCLUSIONS

The novelty of this research corroborates and validates the 12-field lung ultrasound score as tool for predicting mortality and severity clinical course in COVID-19 patients. Baseline lung ultrasound score was associated with in-hospital mortality and requirement of intensive respiratory support and predict the risk of IOT among COVID-19 patients.

Nuts and bolts of lung ultrasound: utility, scanning techniques, protocols, and findings in common pathologies

Point of Care ultrasound (POCUS) of the lungs, also known as lung ultrasound (LUS), has emerged as a technique that allows for the diagnosis of many respiratory pathologies with greater accuracy and speed compared to conventional techniques such as chest x-ray and auscultation. The goal of this narrative review is to provide a simple and practical approach to LUS for critical care, pulmonary, and anesthesia providers, as well as respiratory therapists and other health care providers to be able to implement this technique into their clinical practice. In this review, we will discuss the basic physics of LUS, provide a hands-on scanning technique, describe LUS findings seen in normal and pathological conditions (such as mainstem intubation, pneumothorax, atelectasis, pneumonia, aspiration, COPD exacerbation, cardiogenic pulmonary edema, ARDS, and pleural effusion) and also review the training necessary to achieve competence in LUS.

Knowledge fused latent representation from lung ultrasound examination for COVID-19 pneumonia severity assessment

COVID-19 pneumonia severity assessment is of great clinical importance, and lung ultrasound (LUS) plays a crucial role in aiding the severity assessment of COVID-19 pneumonia due to its safety and portability. However, its reliance on qualitative and subjective observations by clinicians is a limitation. Moreover, LUS images often exhibit significant heterogeneity, emphasizing the need for more quantitative assessment methods. In this paper, we propose a knowledge fused latent representation framework tailored for COVID-19 pneumonia severity assessment using LUS examinations. The framework transforms the LUS examination into latent representation and extracts knowledge from regions labeled by clinicians to improve accuracy. To fuse the knowledge into the latent representation, we employ a knowledge fusion with latent representation (KFLR) model. This model significantly reduces errors compared to approaches that lack prior knowledge integration. Experimental results demonstrate the effectiveness of our method, achieving high accuracy of 96.4 % and 87.4 % for binary-level and four-level COVID-19 pneumonia severity assessments, respectively. It is worth noting that only a limited number of studies have reported accuracy for clinically valuable exam level assessments, and our method surpass existing methods in this context. These findings highlight the potential of the proposed framework for monitoring disease progression and patient stratification in COVID-19 pneumonia cases.

Detection of COVID-19 features in lung ultrasound images using deep neural networks

BACKGROUND

Deep neural networks (DNNs) to detect COVID-19 features in lung ultrasound B-mode images have primarily relied on either in vivo or simulated images as training data. However, in vivo images suffer from limited access to required manual labeling of thousands of training image examples, and simulated images can suffer from poor generalizability to in vivo images due to domain differences. We address these limitations and identify the best training strategy.

METHODS

We investigated in vivo COVID-19 feature detection with DNNs trained on our carefully simulated datasets (40,000 images), publicly available in vivo datasets (174 images), in vivo datasets curated by our team (958 images), and a combination of simulated and internal or external in vivo datasets. Seven DNN training strategies were tested on in vivo B-mode images from COVID-19 patients.

RESULTS

Here, we show that Dice similarity coefficients (DSCs) between ground truth and DNN predictions are maximized when simulated data are mixed with external in vivo data and tested on internal in vivo data (i.e., 0.482 ± 0.211), compared with using only simulated B-mode image training data (i.e., 0.464 ± 0.230) or only external in vivo B-mode training data (i.e., 0.407 ± 0.177). Additional maximization is achieved when a separate subset of the internal in vivo B-mode images are included in the training dataset, with the greatest maximization of DSC (and minimization of required training time, or epochs) obtained after mixing simulated data with internal and external in vivo data during training, then testing on the held-out subset of the internal in vivo dataset (i.e., 0.735 ± 0.187).

CONCLUSIONS

DNNs trained with simulated and in vivo data are promising alternatives to training with only real or only simulated data when segmenting in vivo COVID-19 lung ultrasound features.

Role of Imaging in Diagnosis and Management of COVID-19: Evidence-Based Approaches

Imaging has been demonstrated to play a crucial role in both the diagnosis and management of COVID-19. Depending on resources, pre-test probability, and risk factors for severe disease progression, real-time polymerase chain reaction (RT-PCR) testing may be followed by chest radiography (CXR) or chest computed tomography (CT) to further aid in diagnosis or excluding COVID-19 disease. SARS-CoV-2 has been shown not only to pathologically impact the pulmonary system, but also the cardiovascular, gastrointestinal, and neurological systems to name a few. Imaging has again proven useful in further investigating and managing extrapulmonary disease, with the use of echocardiogram, CT angiography of the cardiovascular and cerebrovascular structures, MRI of the brain, as well as ultrasound of the abdomen and CT of the abdomen and pelvis proving particularly useful. Research in artificial intelligence and its application in the diagnosis of COVID-19 and disease severity prediction is underway, and point-of-care ultrasound is an emerging bedside technique that may allow for more efficient and timely diagnosis of COVID-19.

Fully Automatic Dual-Probe Lung Ultrasound Scanning Robot for Screening Triage

Two-dimensional lung ultrasound (LUS) has widely emerged as a rapid and noninvasive imaging tool for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, image differences will be magnified due to changes in ultrasound (US) imaging experience, such as US probe attitude control and force control, which will directly affect the diagnosis results. In addition, the risk of virus transmission between sonographer and patients is increased due to frequent physical contact. In this study, a fully automatic dual-probe US scanning robot for the acquisition of LUS images is proposed and developed. Furthermore, the trajectory was optimized based on the velocity look-ahead strategy, the stability of contact force of the system and the scanning efficiency were improved by 24.13% and 29.46%, respectively. Also, the control ability of the contact force of robotic automatic scanning was 34.14 times higher than that of traditional manual scanning, which significantly improves the smoothness of scanning. Importantly, there was no significant difference in image quality obtained by robotic automatic scanning and manual scanning. Furthermore, the scanning time for a single person is less than 4 min, which greatly improves the efficiency of screening triage of group COVID-19 diagnosis and suspected patients and reduces the risk of virus exposure and spread.

Serial lung ultrasound in monitoring viral pneumonia: the lesson learned from COVID-19

Background

Lung ultrasound (LUS) has proven to be useful in the evaluation of lung involvement in COVID-19. However, its effectiveness for predicting the risk of severe disease is still up for debate. The aim of the study was to establish the prognostic accuracy of serial LUS examinations in the prediction of clinical deterioration in hospitalised patients with COVID-19.

Methods

Prospective single-centre cohort study of patients hospitalised for COVID-19. The study protocol consisted of a LUS examination within 24 h from admission and a follow-up examination on day 3 of hospitalisation. Lung involvement was evaluated by a 14-area LUS score. The primary end-point was the ability of LUS to predict clinical deterioration defined as need for intensive respiratory support with high-flow oxygen or invasive mechanical ventilation.

Results

200 patients were included and 35 (17.5%) of them reached the primary end-point and were transferred to the intensive care unit (ICU). The LUS score at admission had been significantly higher in the ICU group than in the non-ICU group (22 (interquartile range (IQR) 20-26) versus 12 (IQR 8-15)). A LUS score at admission ≥17 was shown to be the best cut-off point to discriminate patients at risk of deterioration (area under the curve (AUC) 0.95). The absence of progression in LUS score on day 3 significantly increased the prediction accuracy by ruling out deterioration with a negative predictive value of 99.29%.

Conclusion

Serial LUS is a reliable tool in predicting the risk of respiratory deterioration in patients hospitalised due to COVID-19 pneumonia. LUS could be further implemented in the future for risk stratification of viral pneumonia.

A cross-sectional study factors associated with resilience among medical staff in radiology departments during COVID-19, Riyadh, Kingdom of Saudi Arabia

OBJECTIVES

This study aims to assess the level of resilience of medical workers in radiology departments in Riyadh, Kingdom of Saudi Arabia, during the COVID-19 outbreak and to explore associated factors.

SETTING

Medical staff, including nurses, technicians, radiology specialists and physicians, working in radiology departments at government hospitals in Riyadh, Saudi Arabia during the COVID-19 outbreak.

DESIGN

A cross-sectional study.

PARTICIPANTS

The study was conducted among 375 medical workers in radiology departments in Riyadh, Kingdom of Saudi Arabia. The data collection took place from 15 February 2022 to 31 March 2022.

RESULTS

The total resilience score was 29.37±6.760 and the scores of each dimension showed that the higher mean score was observed in the domain of 'flexibility', while the lowest was observed in 'maintaining attention under stress'. Pearson's correlation analysis showed that there was a significant negative correlation between resilience and perceived stress (r=-0.498, p<0.001). Finally, based on multiple linear regression analysis, factors affecting resilience among participants are the availability of psychological hotline (available, B=2.604, p<0.050), knowledge of COVID-19 protective measures (part of understanding, B=-5.283, p<0.001), availability of adequate protective materials (partial shortage, B=-2.237, p<0.050), stress (B=-0.837, p<0.001) and education (postgraduate, B=-1.812, p<0.050).

CONCLUSIONS

This study sheds light on the level of resilience and the factors that contribute to resilience in radiology medical staff. Moderate levels of resilience call for health administrators to focus on developing strategies that can effectively help cope with workplace adversities.

Assessment of lung injury severity using ultrasound in critically ill COVID-19 patients in resource limited settings

BACKGROUND

Lung ultrasound is a non-invasive tool available at the bedside for the assessment of critically ill patients. The objective of this study was to evaluate the usefulness of lung ultrasound in assessing the severity of SARS-CoV-2 infection in critically-ill patients in a low-income setting.

METHODS

We conducted a 12-month observational study in a university hospital intensive care unit (ICU) in Mali, on patients admitted for COVID-19 as diagnosed by a positive polymerase chain reaction for SARS-CoV-2 and/or typical lung computed tomography scan findings.

RESULTS

The inclusion criteria was met by 156 patients with a median age of 59 years. Almost all patients (96%) had respiratory failure at admission and many needed respiratory support (121/156, 78%). The feasibility of lung ultrasound was very good, with 1802/1872 (96%) quadrants assessed. The reproducibility was good with an intra-class correlation coefficient of elementary patterns of 0.74 (95% CI 0.65, 0.82) and a coefficient of repeatability of lung ultrasound score < 3 for an overall score of 24. Confluent B lines were the most common lesions found in patients (155/156). The overall mean ultrasound score was 23 ± 5.4, and was significantly correlated with oxygen saturation (Pearson correlation coefficient of - 0.38, p < 0.001). More than half of the patients died (86/156, 55.1%). The factors associated with mortality, as shown by multivariable analysis, were: the patients' age; number of organ failures; therapeutic anticoagulation, and lung ultrasound score.

CONCLUSION

Lung ultrasound was feasible and contributed to characterize lung injury in critically-ill COVID-19 patients in a low income setting. Lung ultrasound score was associated with oxygenation impairment and mortality.

Infectious Pneumonia and Lung Ultrasound: A Review

The application of thoracic ultrasound examination has not long been developed because ultrasound's interaction with the lung does not generate an anatomical image but an artifactual one. Subsequently, the evaluation of pulmonary artifacts and their correlation to specific diseases allowed the development of ultrasound semantics. Currently, pneumonia still represents one of the main causes of hospitalization and mortality. Several studies in the literature have demonstrated the ultrasound features of pneumonia. Although ultrasound cannot be considered the diagnostic gold standard for the study of all lung diseases, it has experienced an extraordinary development and growth of interest due to the SARS-CoV-2 pandemic. This review aims to provide essential information on the application of lung ultrasound to the study of infectious pneumonia and to discuss the differential diagnosis.

Surgical Science and the Evolution of Critical Care Medicine

Surgical science has driven innovation and inquiry across adult and pediatric disciplines that provide critical care regardless of location. Surgically originated but broadly applicable knowledge has been globally shared within the pages Critical Care Medicine over the last 50 years.

The use of lung ultrasound in COVID-19

This review article addresses the role of lung ultrasound in patients with coronavirus disease 2019 (COVID-19) for diagnosis and disease management. As a simple imaging procedure, lung ultrasound contributes to the early identification of patients with clinical conditions suggestive of COVID-19, supports decisions about hospital admission and informs therapeutic strategy. It can be performed in various clinical settings (primary care facilities, emergency departments, hospital wards, intensive care units), but also in outpatient settings using portable devices. The article describes typical lung ultrasound findings for COVID-19 pneumonia (interstitial pattern, pleural abnormalities and consolidations), as one component of COVID-19 diagnostic workup that otherwise includes clinical and laboratory evaluation. Advantages and limitations of lung ultrasound use in COVID-19 are described, along with equipment requirements and training needs. To infer on the use of lung ultrasound in different regions, a literature search was performed using key words "COVID-19", "lung ultrasound" and "imaging". Lung ultrasound is a noninvasive, rapid and reproducible procedure; can be performed at the point of care; requires simple sterilisation; and involves non-ionising radiation, allowing repeated exams on the same patient, with special benefit in children and pregnant women. However, physical proximity between the patient and the ultrasound operator is a limitation in the current pandemic context, emphasising the need to implement specific infection prevention and control measures. Availability of qualified staff adequately trained to perform lung ultrasound remains a major barrier to lung ultrasound utilisation. Training, advocacy and awareness rising can help build up capacities of local providers to facilitate lung ultrasound use for COVID-19 management, in particular in low- and middle-income countries.

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.

E-GCS: Detection of COVID-19 through classification by attention bottleneck residual network

Background

Recently,  the coronavirus disease 2019 (COVID-19)  has caused mortality of many people globally. Thus, there existed a need to detect this disease to prevent its further spread. Hence, the study aims to predict COVID-19 infected patients based on deep learning (DL) and image processing.

Objectives

The study intends to classify the normal and abnormal cases of COVID-19 by considering three different medical imaging modalities namely ultrasound imaging, X-ray images and CT scan images through introduced attention bottleneck residual network (AB-ResNet). It also aims to segment the abnormal infected area from normal images for localizing localising the disease infected area through the proposed edge based graph cut segmentation (E-GCS).

Methodology

AB-ResNet is used for classifying images whereas E-GCS segment the abnormal images. The study possess various advantages as it rely on DL and possess capability for accelerating the training speed of deep networks. It also enhance the network depth leading to minimum parameters, minimising the impact of vanishing gradient issue and attaining effective network performance with respect to better accuracy.

Results/Conclusion

Performance and comparative analysis is undertaken to evaluate the efficiency of the introduced system and results explores the efficiency of the proposed system in COVID-19 detection with high accuracy (99%).

Early Lung Ultrasound Findings in Patients With COVID-19 Pneumonia: A Retrospective Multicenter Study of 479 Patients

OBJECTIVES

Lung ultrasound (LUS) holds the promise of an accurate, radiation-free, and affordable diagnostic and monitoring tool in coronavirus disease 2019 (COVID-19) pneumonia. We sought to evaluate the usefulness of LUS in the diagnosis of patients with respiratory distress and suspicion of interstitial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, in comparison to other imaging modalities.

METHODS

This was a multicenter, retrospective study. LUS was performed, on Emergency Department (ED) arrival of patients presenting for possible COVID-19 evaluation, by trained emergency physicians, before undergoing conventional radiologic examination or while waiting for the report. Scans were performed using longitudinal transducer orientation of the lung regions. CXR was interpreted by radiologists staffing ED radiology. Subjects were divided into two group based on molecular test results. LUS findings were compared to COVID test results, nonlaboratory data, and other imaging for each patient. Categorical variables were expressed as percentages and continuous variables as median ± standard error.

RESULTS

A total of 479 patients were enrolled, 87% diagnosed with SARS-CoV-2 by molecular testing. COVID positive and COVID negative patients differed with respect to sex, presence of fever, and white blood cells count. Most common findings on lung point of care ultrasound (POCUS) for COVID-positive patients were B-lines, irregular pleural lines, and small consolidation. Normal chest X-ray was found in 17.89% of cases.

CONCLUSIONS

This 479 patient cohort, with COVID-19, found LUS to be noninferior to chest X-ray (CXR) for diagnostic accuracy. In this study, COVID-positive patients are most likely to show B lines and sub-pleural consolidations on LUS examination.

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 findings in hospitalized COVID-19 patients in relation to venous thromboembolic events: the ECHOVID-19 study

PURPOSE

Several studies have reported thromboembolic events to be common in severe COVID-19 cases. We sought to investigate the relationship between lung ultrasound (LUS) findings in hospitalized COVID-19 patients and the development of venous thromboembolic events (VTE).

METHODS

A total of 203 adults were included from a COVID-19 ward in this prospective multi-center study (mean age 68.6 years, 56.7% men). All patients underwent 8-zone LUS, and all ultrasound images were analyzed off-line blinded. Several LUS findings were investigated (total number of B-lines, B-line score, and LUS-scores).

RESULTS

Median time from admission to LUS examination was 4 days (IQR: 2, 8). The median number of B-lines was 12 (IQR: 8, 18), and 44 (21.7%) had a positive B-line score. During hospitalization, 17 patients developed VTE (4 deep-vein thrombosis, 15 pulmonary embolism), 12 following and 5 prior to LUS. In fully adjusted multivariable Cox models (excluding participants with VTE prior to LUS), all LUS parameters were significantly associated with VTE (total number of B-lines: HR = 1.14, 95% CI (1.03, 1.26) per 1 B-line increase), positive B-line score: HR = 9.79, 95% CI (1.87, 51.35), and LUS-score: HR = 1.51, 95% CI (1.10, 2.07), per 1-point increase). The B-line score and LUS-score remained significantly associated with VTE in sensitivity analyses.

CONCLUSION

In hospitalized COVID-19 patients, pathological LUS findings were common, and the total number of B-lines, B-line score, and LUS-score were all associated with VTE. These findings indicate that the LUS examination may be useful in risk stratification and the clinical management of COVID-19. These findings should be considered hypothesis generating.

CLINICALTRIALS

GOV ID

NCT04377035.

Seeing inside a body in motion

Adhesive ultrasound patches can provide medical imaging for patients on the go.

Bioadhesive ultrasound for long-term continuous imaging of diverse organs

Continuous imaging of internal organs over days could provide crucial information about health and diseases and enable insights into developmental biology. We report a bioadhesive ultrasound (BAUS) device that consists of a thin and rigid ultrasound probe robustly adhered to the skin via a couplant made of a soft, tough, antidehydrating, and bioadhesive hydrogel-elastomer hybrid. The BAUS device provides 48 hours of continuous imaging of diverse internal organs, including blood vessels, muscle, heart, gastrointestinal tract, diaphragm, and lung. The BAUS device could enable diagnostic and monitoring tools for various diseases.

Detection of COVID-19 in Point of Care Lung Ultrasound

The coronavirus disease 2019 (COVID-19) evolved into a global pandemic, responsible for a significant number of infections and deaths. In this scenario, point-of-care ultrasound (POCUS) has emerged as a viable and safe imaging modality. Computer vision (CV) solutions have been proposed to aid clinicians in POCUS image interpretation, namely detection/segmentation of structures and image/patient classification but relevant challenges still remain. As such, the aim of this study is to develop CV algorithms, using Deep Learning techniques, to create tools that can aid doctors in the diagnosis of viral and bacterial pneumonia (VP and BP) through POCUS exams. To do so, convolutional neural networks were designed to perform in classification tasks. The architectures chosen to build these models were the VGG16, ResNet50, DenseNet169 e MobileNetV2. Patients images were divided in three classes: healthy (HE), BP and VP (which includes COVID-19). Through a comparative study, which was based on several performance metrics, the model based on the DenseNet169 architecture was designated as the best performing model, achieving 78% average accuracy value of the five iterations of 5- Fold Cross-Validation. Given that the currently available POCUS datasets for COVID-19 are still limited, the training of the models was negatively affected by such and the models were not tested in an independent dataset. Furthermore, it was also not possible to perform lesion detection tasks. Nonetheless, in order to provide explainability and understanding of the models, Gradient-weighted Class Activation Mapping (GradCAM) were used as a tool to highlight the most relevant classification regions. Clinical relevance - Reveals the potential of POCUS to support COVID-19 screening. The results are very promising although the dataset is limite.

Radiography-based triage for COVID-19 in the Emergency Department in a Spanish cohort of patients

Background

Strategies to determine who could be safely discharged home from the Emergency Department (ED) in COVID-19 are needed to decongestion healthcare systems.

Objectives

To describe the outcomes of an ED triage system for non-severe patients with suspected COVID-19 and possible pneumonia based on chest X-ray (CXR) upon admission.

Material and methods

Retrospective, single-center study performed in Barcelona (Spain) during the COVID-19 peak in March-April 2020. Patients with COVID-19 symptoms and potential pneumonia, without respiratory insufficiency, with priority class IV-V (Andorran triage model) had a CXR upon admission. This approach tried to optimize resource use and to facilitate discharges. The results after adopting this organizational approach are reported.

Results

We included 834 patients, 53% were female. Most patients were white (66%) or Hispanic (27%). CXR showed pneumonia in 523 (62.7%). Compared to those without pneumonia, patients with pneumonia were older (55 vs 46.6 years old) and had a higher Charlson comorbidity index (1.9 vs 1.3). Patients with pneumonia were at a higher risk for a combined outcome of admission and/or death (91 vs 12%). Death rates tended to be numerically higher in the pneumonia group (10 vs 1). Among patients without pneumonia in the initial CXR, 10% reconsulted (40% of them with new pneumonia).

Conclusion

CXR identified pneumonia in a significant number of patients. Those without pneumonia were mostly discharged. Mortality among patients with an initially negative CXR was low. CXR triage for pneumonia in non-severe COVID-19 patients in the ED can be an effective strategy to optimize resource use.

Radiography-based triage for COVID-19 in the Emergency Department in a Spanish cohort of patients

BACKGROUND

Strategies to determine who could be safely discharged home from the Emergency Department (ED) in COVID-19 are needed to decongestion healthcare systems.

OBJECTIVES

To describe the outcomes of an ED triage system for non-severe patients with suspected COVID-19 and possible pneumonia based on chest X-ray (CXR) upon admission.

MATERIAL AND METHODS

Retrospective, single-center study performed in Barcelona (Spain) during the COVID-19 peak in March-April 2020. Patients with COVID-19 symptoms and potential pneumonia, without respiratory insufficiency, with priority class IV-V (Andorran triage model) had a CXR upon admission. This approach tried to optimize resource use and to facilitate discharges. The results after adopting this organizational approach are reported.

RESULTS

We included 834 patients, 53% were female. Most patients were white (66%) or Hispanic (27%). CXR showed pneumonia in 523 (62.7%). Compared to those without pneumonia, patients with pneumonia were older (55 vs 46.6 years old) and had a higher Charlson comorbidity index (1.9 vs 1.3). Patients with pneumonia were at a higher risk for a combined outcome of admission and/or death (91 vs 12%). Death rates tended to be numerically higher in the pneumonia group (10 vs 1). Among patients without pneumonia in the initial CXR, 10% reconsulted (40% of them with new pneumonia).

CONCLUSION

CXR identified pneumonia in a significant number of patients. Those without pneumonia were mostly discharged. Mortality among patients with an initially negative CXR was low. CXR triage for pneumonia in non-severe COVID-19 patients in the ED can be an effective strategy to optimize resource use.

The Role of Lung Ultrasound Monitoring in Early Detection of Ventilator-Associated Pneumonia in COVID-19 Patients: A Retrospective Observational Study

Specific lung ultrasound signs combined with clinical parameters allow for early diagnosis of ventilator-associated pneumonia in the general ICU population. This retrospective cohort study aimed to determine the accuracy of lung ultrasound monitoring for ventilator-associated pneumonia diagnosis in COVID-19 patients. Clinical (i.e., clinical pulmonary infection score) and ultrasound (i.e., presence of consolidation and a dynamic linear−arborescent air bronchogram, lung ultrasound score, ventilator-associated lung ultrasound score) data were collected on the day of the microbiological sample (pneumonia-day) and 48 h before (baseline) on 55 bronchoalveolar lavages of 33 mechanically-ventilated COVID-19 patients who were monitored daily with lung ultrasounds. A total of 26 samples in 23 patients were positive for ventilator-associated pneumonia (pneumonia cases). The onset of a dynamic linear−arborescent air bronchogram was 100% specific for ventilator-associated pneumonia. The ventilator-associated lung ultrasound score was higher in pneumonia-cases (2.5 (IQR 1.0 to 4.0) vs. 1.0 (IQR 1.0 to 1.0); p < 0.001); the lung ultrasound score increased from baseline in pneumonia-cases only (3.5 (IQR 2.0 to 6.0) vs. −1.0 (IQR −2.0 to 1.0); p = 0.0001). The area under the curve for clinical parameters, ventilator-associated pneumonia lung ultrasound score, and lung ultrasound score variations were 0.472, 0.716, and 0.800, respectively. A newly appeared dynamic linear−arborescent air bronchogram is highly specific for ventilator-associated pneumonia in COVID-19 patients. A high ventilator-associated pneumonia lung ultrasound score (or an increase in the lung ultrasound score) orients to ventilator-associated pneumonia.

Role of Lung Ultrasound in the Management of Patients with Suspected SARS-CoV-2 Infection in the Emergency Department

Background: The lung ultrasound (LUS) score has been proposed as an optimal scheme for the ultrasound study of patients with suspected/confirmed COVID-19 pneumonia. The aims of our study were to evaluate the use of lung ultrasound as a diagnostic tool for diagnosing SARS-CoV-2 pneumonia, to examine the validity of the LUS score for the diagnosis of COVID-19 pneumonia, and to correlate this score with hospitalization rate and 30-day mortality. Materials and Methods: A retrospective analysis was performed on 1460 patients who were referred to the General Emergency Department of the S. Orsola-Malpighi Hospital from April 2020 to May 2020 for symptoms suspected to indicate SARS-CoV-2 infection. The ultrasound examination was based on a common execution scheme called the LUS score, as previously described. Results and Conclusions: The LUS score was found to correlate with the degree of clinical severity and respiratory failure (paO2/FiO2 ratio and the alveolar−arterial gradient increase than expected for age). It was shown that COVID-19 patients with an LUS score of >7 require the use of oxygen support, and a value of >10 is associated with an increased risk of oro-tracheal intubation. The LUS score was found to present higher values in hospitalized patients, increasing according to the degree of care intensity. Patients who died from COVID-19 were characterized by a mean LUS score of 11 at presentation to the emergency department. An LUS score of >7.5 was found to indicate a sensitivity of 83% and a specificity of 89% for 30-day mortality in COVID-19 patients. The use of LUS seems to be an optimal first level method for pneumonia detection and risk stratification in patients with suspected SARS-CoV-2 infection.

Lung ultrasound findings following COVID-19 hospitalization: A prospective longitudinal cohort study

Background

Lung ultrasound (LUS) is a useful tool for diagnosis and monitoring in patients with active COVID-19-infection. However, less is known about the changes in LUS findings after a hospitalization for COVID-19.

Methods

In a prospective, longitudinal study in patients with COVID-19 enrolled from non-ICU hospital units, adult patients underwent 8-zone LUS and blood sampling both during the hospitalization and 2–3 months after discharge. LUS images were analyzed blinded to clinical variables and outcomes.

Results

A total of 71 patients with interpretable LUS at baseline and follow up (mean age 64 years, 61% male, 24% with acute respiratory distress syndrome (ARDS)) were included. The follow-up LUS was performed a median of 72 days after the initial LUS performed during hospitalization. At baseline, 87% had pathologic LUS findings in ≥1 zone (e.g. ≥3 B-lines, confluent B-lines or subpleural or lobar consolidation), whereas 30% had pathologic findings at follow-up (p < 0.001). The total number of B-lines and LUS score decreased significantly from hospitalization to follow-up (median 17 vs. 4, p < 0.001 and 4 vs. 0, p < 0.001, respectively). On the follow-up LUS, 28% of all patients had ≥3 B-lines in ≥1 zone, whereas in those with ARDS during the baseline hospitalization (n = 17), 47% had ≥3 B-lines in ≥1 zone.

Conclusion

LUS findings improved significantly from hospitalization to follow-up 2–3 months after discharge in COVID-19 survivors. However, persistent B-lines were frequent at follow-up, especially among those who initially had ARDS. LUS seems to be a promising method to monitor COVID-19 lung changes over time.

Clinicaltrials.gov ID

NCT04377035.

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.

Trombosis y COVID-19: revisión de alcance

La enfermedad por coronavirus COVID-19 ha generado la mayor crisis de salud pública de la era moderna. Se considera que el estado protrombótico inducido por la infección tiene una relación directa y de importancia sustancial con el daño agudo en el pulmón y con las complicaciones de la infección, incluida la muerte. Esta revisión de alcance (scoping review) resume y evalúa críticamente la evidencia sobre la relación entre la trombosis y la COVID-19, y se basa en una búsqueda bibliográfica sistemática de todos los artículos publicados hasta el 5 de mayo de 2020 e incluidos en las bases de datos PubMed, Scopus, Cochrane y Clinicaltrials.gov. Hemos incluido 26 artículos en la revisión, y hemos evaluado su calidad empleando la guía STROBE. Los principales síntomas que presentan los pacientes diagnosticados con COVID-19 son disnea, fiebre, tos, diarrea y vómitos. A nivel analítico destaca, en esta enfermedad, un aumento de dímero-D, fibrinógeno, tiempo de protrombina y linfopenia. En cuanto a las pruebas radiológicas, las técnicas más usadas para el diagnóstico de tromboembolismo pulmonar, trombosis venosa profunda y otros fenómenos trombóticos fueron la ecografía y la tomografía computarizada. Como conclusión, en la actualidad existe escasa evidencia científica con respecto a la COVID-19 y sus complicaciones trombóticas. Esta revisión resume este cuerpo de evidencia, evalúa su calidad, y ofrece conclusiones que orientan los siguientes pasos a dar en este área de investigación de enorme relevancia y crecimiento exponencial.

Quantitative Analysis of Pleural Line and B-Lines in Lung Ultrasound Images for Severity Assessment of COVID-19 Pneumonia

Specific patterns of lung ultrasound (LUS) images are used to assess the severity of coronavirus disease 2019 (COVID-19) pneumonia, while such assessment is mainly based on clinicians' qualitative and subjective observations. In this study, we quantitatively analyze the LUS images to assess the severity of COVID-19 pneumonia by characterizing the patterns related to the pleural line (PL) and B-lines (BLs). Twenty-seven patients with COVID-19 pneumonia, including 13 moderate cases, seven severe cases, and seven critical cases, are enrolled. Features related to the PL, including the thickness (TPL) and roughness of the PL (RPL), and the mean (MPLI) and standard deviation (SDPLI) of the PL intensities are extracted from the LUS images. Features related to the BLs, including the number (NBL), accumulated width (AWBL), attenuation coefficient (ACBL), and accumulated intensity (AIBL) of BLs, are also extracted. The correlations of these features with the disease severity are evaluated. The performances of the binary severe/non-severe classification are assessed for each feature and support vector machine (SVM) classifiers with various combinations of features as input. Several features, including the RPL, NBL, AWBL, and AIBL, show significant correlations with disease severity (all ). The classification performance is optimal using the SVM classifier using all the features as input (area under the receiver operating characteristic (ROC) curve = 0.96, sensitivity = 0.93, and specificity = 1). These findings demonstrate that the proposed method may be a promising tool for automatic grading diagnosis and follow-up of patients with COVID-19 pneumonia.

Lung Ultrasound Findings Associated With COVID-19 ARDS, ICU Admission, and All-Cause Mortality

BACKGROUND

As lung ultrasound (LUS) has emerged as a diagnostic tool in patients with COVID-19, we sought to investigate the association between LUS findings and the composite in-hospital outcome of ARDS incidence, ICU admission, and all-cause mortality.

METHODS

In this prospective, multi-center, observational study, adults with laboratory-confirmed SARS-CoV-2 infection were enrolled from non-ICU in-patient units. Subjects underwent an LUS evaluating a total of 8 zones. Images were analyzed off-line, blinded to clinical variables and outcomes. A LUS score was developed to integrate LUS findings: ≥ 3 B-lines corresponded to a score of 1, confluent B-lines to a score of 2, and subpleural or lobar consolidation to a score of 3. The total LUS score ranged from 0-24 per subject.

RESULTS

Among 215 enrolled subjects, 168 with LUS data and no current signs of ARDS or ICU admission (mean age 59 y, 56% male) were included. One hundred thirty-six (81%) subjects had pathologic LUS findings in ≥ 1 zone (≥ 3 B-lines, confluent B-lines, or consolidations). Markers of disease severity at baseline were higher in subjects with the composite outcome (n = 31, 18%), including higher median C-reactive protein (90 mg/L vs 55, P < .001) and procalcitonin levels (0.35 μg/L vs 0.13, P = .033) and higher supplemental oxygen requirements (median 4 L/min vs 2, P = .001). However, LUS findings and score did not differ significantly between subjects with the composite outcome and those without, and were not associated with outcomes in unadjusted and adjusted logistic regression analyses.

CONCLUSIONS

Pathologic findings on LUS were common a median of 3 d after admission in this cohort of non-ICU hospitalized subjects with COVID-19 and did not differ among subjects who experienced the composite outcome of incident ARDS, ICU admission, and all-cause mortality compared to subjects who did not. These findings should be confirmed in future investigations. The study is registered at Clinicaltrials.gov (NCT04377035).

Recent Advancements on COVID-19: A Comprehensive Review

Over the last few decades, there have been several global outbreaks of severe respiratory infections. The causes of these outbreaks were coronaviruses that had infected birds, mammals and humans. The outbreaks predominantly caused respiratory tract and gastrointestinal tract symptoms and other mild to very severe clinical signs. The current coronavirus disease-2019 (COVID-19) outbreak, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a rapidly spreading illness affecting millions of people worldwide. Among the countries most affected by the disease are the United States of America (USA), India, Brazil, and Russia, with France recording the highest infection, morbidity, and mortality rates. Since early January 2021, thousands of articles have been published on COVID-19. Most of these articles were consistent with the reports on the mode of transmission, spread, duration, and severity of the sickness. Thus, this review comprehensively discusses the most critical aspects of COVID-19, including etiology, epidemiology, pathogenesis, clinical signs, transmission, pathological changes, diagnosis, treatment, prevention and control, and vaccination.

Lung Ultrasound: A Diagnostic Leading Tool for SARS-CoV-2 Pneumonia: A Narrative Review

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global pandemic. In this context, lung ultrasound (LUS) has played an important role due to its high diagnostic sensitivity, low costs, simplicity of execution and radiation safeness. Despite computed tomography (CT) being the imaging gold standard, lung ultrasound point of care exam is essential in every situation where CT is not readily available nor applicable. The aim of our review is to highlight the considerable versatility of LUS in diagnosis, framing the therapeutic route and follow-up for SARS-CoV-2 interstitial syndrome.

Performance of a computer aided diagnosis system for SARS-CoV-2 pneumonia based on ultrasound images

Purpose

In this study we aimed to leverage deep learning to develop a computer aided diagnosis (CAD) system toward helping radiologists in the diagnosis of SARS-CoV-2 virus syndrome on Lung ultrasonography (LUS).

Method

A CAD system is developed based on a transfer learning of a residual network (ResNet) to extract features on LUS and help radiologists to distinguish SARS-CoV-2 virus syndrome from healthy and non-SARS-CoV-2 pneumonia. A publicly available LUS dataset for SARS-CoV-2 virus syndrome consisting of 3909 images has been employed. Six radiologists with different experiences participated in the experiment. A comprehensive LUS data set was constructed and employed to train and verify the proposed method. Several metrics such as accuracy, recall, precision, and F1-score, are used to evaluate the performance of the proposed CAD approach. The performances of the radiologists with and without the help of CAD are also evaluated quantitively. The p-values of the t-test shows that with the help of the CAD system, both junior and senior radiologists significantly improve their diagnosis performance on both balanced and unbalanced datasets.

Results

Experimental results indicate the proposed CAD approach and the machine features from it can significantly improve the radiologists’ performance in the SARS-CoV-2 virus syndrome diagnosis. With the help of the proposed CAD system, the junior and senior radiologists achieved F1-score values of 91.33% and 95.79% on balanced dataset and 94.20% and 96.43% on unbalanced dataset. The proposed approach is verified on an independent test dataset and reports promising performance.

Conclusions

The proposed CAD system reports promising performance in facilitating radiologists’ diagnosis SARS-CoV-2 virus syndrome and might assist the development of a fast, accessible screening method for pulmonary diseases.

Is Lung Ultrasound Helpful in COVID-19 Neonates?-A Systematic Review

Background: The SARS-CoV-2 infection has occurred in neonates, but it is a fact that radiation exposure is not recommended given their age. The aim of this review is to assess the evidence on the utility of lung ultrasound (LUS) in neonates diagnosed with COVID-19. Methods: A systematic literature review was performed so as to find a number of published studies assessing the benefits of lung ultrasound for newborns diagnosed with COVID and, in the end, to make a comparison between LUS and the other two more conventional procedures of chest X-rays or CT exam. The key terms used in the search of several databases were: “lung ultrasound”, “sonography”, “newborn”, “neonate”, and “COVID-19′. Results: In total, 447 studies were eligible for this review, and after removing the duplicates, 123 studies referring to LU were further examined, but only 7 included cases of neonates. These studies were considered for the present research paper. Conclusions: As a non-invasive, easy-to-use, and reliable method for lung lesion detection in neonates with COVID-19, lung ultrasound can be used as a useful diagnosis tool for the evaluation of COVID-19-associated lung lesions. The benefits of this method in this pandemic period are likely to arouse interest in opening new research horizons, with immediate practical applicability.

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.

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.

Role of Imaging in Diagnosis and Management of COVID-19: A Multiorgan Multimodality Imaging Review

In this pandemic of Coronavirus disease 2019 (COVID-19), a vast proportion of healthcare resources, including imaging tools, have been dedicated to the management of affected patients; yet, the frequent reports of unknown presentations and complications of disease over time have been changing the usual standard of care and resource allocation in health centers. As of now, we have witnessed multisystemic symptoms requiring the collaboration of different clinical teams in COVID-19 patients' care. Compared to previous viral pandemics, imaging modalities are now playing an essential role in the diagnosis and management of patients. This widespread utility of imaging modalities calls for a deeper understanding of potential radiologic findings in this disease and identifying the most compatible imaging protocol with safety precautions. Although initially used for respiratory tract evaluation, imaging modalities have also been used for cardiovascular, neurologic, and gastrointestinal evaluation of patients with COVID-19. In this narrative review article, we provide multimodality and multisystemic review of imaging techniques and features that can aid in the diagnosis and management of COVID-19 patients.

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.

The Role of Lung Ultrasound Before and During the COVID-19 Pandemic: A review article

Lung ultrasound [LUS] has evolved considerably over the last years. The aim of the current review is to conduct a systematic review reported from a number of studies to show the usefulness of [LUS] and point of care ultrasound for diagnosing COVID-19. A systematic search of electronic data was conducted including the national library of medicine, and the national institute of medicine, PubMed Central [PMC] to identify the articles depended on [LUS] to monitor COVID-19. This review highlights the ultrasound findings reported in articles before the pandemic [11], clinical articles before COVID-19 [14], review studies during the pandemic [27], clinical cases during the pandemic [5] and other varying aims articles. The reviewed studies revealed that ultrasound findings can be used to help in the detection and staging of the disease. The common patterns observed included irregular and thickened A-lines, multiple B-lines ranging from focal to diffuse interstitial consolidation, and pleural effusion. Sub-plural consolidation is found to be associated with the progression of the disease and its complications. Pneumothorax was not recorded for COVID-19 patients. Further improvement in the diagnostic performance of [LUS] for COVID-19 patients can be achieved by using elastography, contrast-enhanced ultrasound, and power Doppler imaging.

Arterial and venous thromboembolism in COVID-19: a study-level meta-analysis

BACKGROUND

The prevalence of venous thromboembolic event (VTE) and arterial thromboembolic event (ATE) thromboembolic events in patients with COVID-19 remains largely unknown.

METHODS

In this meta-analysis, we systematically searched for observational studies describing the prevalence of VTE and ATE in COVID-19 up to 30 September 2020.

RESULTS

We analysed findings from 102 studies (64 503 patients). The frequency of COVID-19-related VTE was 14.7% (95% CI 12.1% to 17.6%, I2=94%; 56 studies; 16 507 patients). The overall prevalence rates of pulmonary embolism (PE) and leg deep vein thrombosis were 7.8% (95% CI 6.2% to 9.4%, I2=94%; 66 studies; 23 117 patients) and 11.2% (95% CI 8.4% to 14.3%, I2=95%; 48 studies; 13 824 patients), respectively. Few were isolated subsegmental PE. The VTE prevalence was significantly higher in intensive care unit (ICU) (23.2%, 95% CI 17.5% to 29.6%, I2=92%, vs 9.0%, 95% CI 6.9% to 11.4%, I2=95%; pinteraction<0.0001) and in series systematically screening patients compared with series testing symptomatic patients (25.2% vs 12.7%, pinteraction=0.04). The frequency rates of overall ATE, acute coronary syndrome, stroke and other ATE were 3.9% (95% CI 2.0% to to 3.0%, I2=96%; 16 studies; 7939 patients), 1.6% (95% CI 1.0% to 2.2%, I2=93%; 27 studies; 40 597 patients) and 0.9% (95% CI 0.5% to 1.5%, I2=84%; 17 studies; 20 139 patients), respectively. Metaregression and subgroup analyses failed to explain heterogeneity of overall ATE. High heterogeneity limited the value of estimates.

CONCLUSIONS

Patients admitted in the ICU for severe COVID-19 had a high risk of VTE. Conversely, further studies are needed to determine the specific effects of COVID-19 on the risk of ATE or VTE in less severe forms of the disease.

Management of COVID-19 Patients in the Emergency Department

COVID-19 is an emerging disease of global public health concern. As the pandemic overwhelmed emergency departments (EDs), a restructuring of emergency care delivery became necessary in many hospitals. Furthermore, with more than 2000 papers being published each week, keeping up with ever-changing information has proven to be difficult for emergency physicians. The aim of the present review is to provide emergency physician with a summary of the current literature regarding the management of COVID-19 patients in the emergency department.

Canadian Internal Medicine Ultrasound (CIMUS) Expert Consensus Statement on the Use of Lung Ultrasound for the Assessment of Medical Inpatients With Known or Suspected Coronavirus Disease 2019

OBJECTIVES

To develop a consensus statement on the use of lung ultrasound (LUS) in the assessment of symptomatic general medical inpatients with known or suspected coronavirus disease 2019 (COVID-19).

METHODS

Our LUS expert panel consisted of 14 multidisciplinary international experts. Experts voted in 3 rounds on the strength of 26 recommendations as "strong," "weak," or "do not recommend." For recommendations that reached consensus for do not recommend, a fourth round was conducted to determine the strength of those recommendations, with 2 additional recommendations considered.

RESULTS

Of the 26 recommendations, experts reached consensus on 6 in the first round, 13 in the second, and 7 in the third. Four recommendations were removed because of redundancy. In the fourth round, experts considered 4 recommendations that reached consensus for do not recommend and 2 additional scenarios; consensus was reached for 4 of these. Our final recommendations consist of 24 consensus statements; for 2 of these, the strength of the recommendations did not reach consensus.

CONCLUSIONS

In symptomatic medical inpatients with known or suspected COVID-19, we recommend the use of LUS to: (1) support the diagnosis of pneumonitis but not diagnose COVID-19, (2) rule out concerning ultrasound features, (3) monitor patients with a change in the clinical status, and (4) avoid unnecessary additional imaging for patients whose pretest probability of an alternative or superimposed diagnosis is low. We do not recommend the use of LUS to guide admission and discharge decisions. We do not recommend routine serial LUS in patients without a change in their clinical condition.

The Use of POCUS to Manage ICU Patients With COVID-19

Since the advent of SARS-CoV-2, the virus that causes COVID-19, clinicians have had to modify how they provide high-value care while mitigating the risk of viral spread. Routine imaging studies have been discouraged due to elevated transmission risk. Patients who have been diagnosed with COVID-19 often have a protracted hospital course with progression of disease. Given the need for close follow-up of patients, we recommend the use of ultrasonography, particularly point-of-care ultrasound (POCUS), to manage patients with COVID-19 through their entire ICU course. POCUS will allow a clinician to evaluate and monitor cardiac and pulmonary function, as well as evaluate for thromboembolic disease, place an endotracheal tube, confirm central venous catheter placement, and rule out a pneumothorax. If a patient improves sufficiently to perform weaning trials, POCUS can also help evaluate readiness for ventilator liberation.

Residual Lung Injury in Patients Recovering From COVID-19 Critical Illness: A Prospective Longitudinal Point-of-Care Lung Ultrasound Study

Scarce data exist regarding the natural history of lung lesions detected on ultrasound in those who survive severe COVID-19 pneumonia.

OBJECTIVE

We performed a prospective analysis of point-of-care ultrasound (POCUS) findings in critically ill COVID-19 patients during and after hospitalization.

METHODS

We enrolled 171 COVID-19 intensive care unit patients. POCUS of the lungs was performed with phased array (2-4 MHz), convex (2-6 MHz) and linear (10-15 MHz) transducers, scanning 12 lung areas. Chest computed tomography angiography was performed to exclude suspected pulmonary embolism. Survivors were clinically and sonographically evaluated during a 4 month period for evidence of residual lung injury. Chest computed tomography angiography and echocardiography were used to exclude pulmonary hypertension (PH) and chest high-resolution-computed-tomography to exclude interstitial lung disease (ILD) in symptomatic survivors.

RESULTS

Cox regression analysis showed that lymphocytopenia (hazard ratio [HR]: 0.88, 95% confidence intervals [CI]: 0.68-0.96, p = .048), increased lactate (HR: 1.17, 95% CI: 0.94-1.46, p = 0.049), and D-dimers (HR: 1.21, 95% CI: 1.03-1.44, p = .03) were mortality predictors. Non-survivors had increased incidence of pulmonary abnormalities (B-lines, pleural line irregularities, and consolidations) compared to survivors (p < .05). During follow-up, POCUS with clinical and laboratory parameters integrated in the semi-quantitative Riyadh-Residual-Lung-Injury scale had sensitivity of 0.82 (95% CI: 0.76-0.89) and specificity of 0.91 (95% CI: 0.94-0.95) in predicting ILD. The prevalence of PH and ILD (non-specific-interstitial-pneumonia) was 7% and 11.8%, respectively.

CONCLUSION

POCUS showed ability to monitor the evolution of severe COVID-19 pneumonia after hospital discharge, supporting its integration in clinical predictive models of residual lung injury.

Lungensonographie bei COVID‑19

Die medizinische Versorgung von Patienten, die im Zusammenhang mit der pandemischen Coronaviruserkrankung 2019 („coronavirus disease 2019“, COVID-19) erkrankt sind, stellt für die staatlichen Gesundheitssysteme weltweit eine große Herausforderung dar. Das Virus mit dem Namen „severe acute respiratory syndrome coronavirus 2“ (SARS-CoV-2) zeigt eine hohe Organspezifität zu den unteren Atemwegen. Da bislang weder eine wirksame Therapie noch Impfung gegen das Virus existieren, kommt der diagnostischen Früherkennung eine große Bedeutung zu. Durch den spezifischen Aspekt der überwiegend im peripheren Lungenparenchym beginnenden Infektion ist die Lungensonographie als bildgebende Diagnostikmethode geeignet, Verdachtsfälle bereits im Frühstadium der Erkrankung als solche zu identifizieren. Serielle Ultraschalluntersuchungen an Patienten mit bestätigter Infektion können bettseitig und zeitnah Veränderungen im betroffenen Lungengewebe nachweisen. Dieser Artikel fasst das diagnostische Potenzial der Lungensonographie im Hinblick auf Screening und therapeutische Entscheidungsfindung bei Patienten mit vermuteter oder bestätigter SARS-CoV-2-Pneumonie zusammen.

Prevalence and significance of pulmonary disease on lung ultrasonography in outpatients with SARS-CoV-2 infection

BACKGROUND

The majority of patients with SARS-CoV-2 infection are diagnosed and managed as outpatients; however, little is known about the burden of pulmonary disease in this setting. Lung ultrasound (LUS) is a convenient tool for detection of COVID-19 pneumonia. Identifying SARS-CoV-2 infected outpatients with pulmonary disease may be important for early risk stratification.

OBJECTIVES

To investigate the prevalence, natural history and clinical significance of pulmonary disease in outpatients with SARS-CoV-2.

METHODS

SARS-CoV-2 PCR positive outpatients (CV(+)) were assessed with LUS to identify the presence of interstitial pneumonia. Studies were considered positive based on the presence of B-lines, pleural irregularity and consolidations. A subset of patients underwent longitudinal examinations. Correlations between LUS findings and patient symptoms, demographics, comorbidities and clinical outcomes over 8 weeks were evaluated.

RESULTS

102 CV(+) patients underwent LUS with 42 (41%) demonstrating pulmonary involvement. Baseline LUS severity scores correlated with shortness of breath on multivariate analysis. Of the CV(+) patients followed longitudinally, a majority showed improvement or resolution in LUS findings after 1-2 weeks. Only one patient in the CV(+) cohort was briefly hospitalised, and no patient died or required mechanical ventilation.

CONCLUSION

We found a high prevalence of LUS findings in outpatients with SARS-CoV-2 infection. Given the pervasiveness of pulmonary disease across a broad spectrum of LUS severity scores and lack of adverse outcomes, our findings suggest that LUS may not be a useful as a risk stratification tool in SARS-CoV-2 in the general outpatient population.

Lung Ultrasound Can Predict the Clinical Course and Severity of COVID-19 Disease

Coronavirus disease 2019 (COVID-19) compromises the lung in large numbers of people. The development of minimally invasive methods to determine the severity of pulmonary extension is desired. This study aimed to describe the characteristics of sequential lung ultrasound and to test the prognostic usefulness of this exam in a group of patients admitted to the hospital with COVID-19. We prospectively evaluated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection admitted to our hospital between April and August 2020. Bedside lung ultrasound exams were performed at three time points: at inclusion in the study, after 48 h and on the seventh day of follow-up. Lung ultrasound scores were quantified according to the aeration loss in each of eight zones scanned. Sixty-six participants were included: 42 (63.6%) in the intensive care unit and 24 (36.3%) in the ward. Lung ultrasound scores were higher in participants admitted to the intensive care unit than in those admitted to the ward at the time of inclusion (16 [13-17] vs. 10 [4-14], p < 0.001), after 48 h (15.5 [13-17] vs. 12.5 [8.2-14.7], p = 0.001) and on the seventh day (16 [14-17] vs. 7 [4.5-13.7], p < 0.001) respectively. Lung ultrasound score measured at the time of inclusion in the study was independently associated with the need for admission to the intensive care unit (odds ratio = 1.480; 95% confidence interval, 1.093-2.004; p = 0.011) adjusted by the Sequential Organ Failure Assessment score.