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

Associations of early changes in lung ultrasound aeration scores and mortality in invasively ventilated patients: a post hoc analysis

BACKGROUND

Lung ultrasound (LUS) in an emerging technique used in the intensive care unit (ICU). The derivative LUS aeration score has been shown to have associations with mortality in invasively ventilated patients. This study assessed the predictive value of baseline and early changes in LUS aeration scores in critically ill invasively ventilated patients with and without ARDS (Acute Respiratory Distress Syndrome) on 30- and 90-day mortality.

METHODS

This is a post hoc analysis of a multicenter prospective observational cohort study, which included patients admitted to the ICU with an expected duration of ventilation for at least 24 h. We restricted participation to patients who underwent a 12-region LUS exam at baseline and had the primary endpoint (30-day mortality) available. Logistic regression was used to analyze the primary and secondary endpoints. The analysis was performed for the complete patient cohort and for predefined subgroups (ARDS and no ARDS).

RESULTS

A total of 442 patients were included, of whom 245 had a second LUS exam. The baseline LUS aeration score was not associated with mortality (1.02 (95% CI: 0.99 - 1.06), p = 0.143). This finding was not different in patients with and in patients without ARDS. Early deterioration of the LUS score was associated with mortality (2.09 (95% CI: 1.01 - 4.3), p = 0.046) in patients without ARDS, but not in patients with ARDS or in the complete patient cohort.

CONCLUSION

In this cohort of critically ill invasively ventilated patients, the baseline LUS aeration score was not associated with 30- and 90-day mortality. An early change in the LUS aeration score was associated with mortality, but only in patients without ARDS.

TRIAL REGISTRATION

ClinicalTrials.gov, ID NCT04482621.

The Role of POCUS to Face COVID-19: A Narrative Review

COVID-19 has been a challenging outbreak to face, with millions of deaths among the globe. Acute respiratory failure due to interstitial pneumonia was the leading cause of death other than prothrombotic activation and complications. Lung ultrasound (LUS) and point-of-care ultrasound (POCUS) are widely used not only to triage, to identify, and to monitor lungs involvement but also to assess hemodynamic status and thrombotic and hemorrhagic complications, mainly in critically ill patients. POCUS has gained growing consideration due to its bedside utilization, reliability, and reproducibility even in emergency settings especially in unstable patients. In this narrative review, we aim to describe LUS and POCUS utilization in COVID-19 infection based on the literature found on this topic. We reported the LUS patterns of COVID-19 pulmonary infection, the diagnostic accuracy with respect to CT lung scan, its prognostic value, the variety of scores and protocols proposed, and the utilization of POCUS to investigate the extra-lung complications.

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.

Point-of-care ultrasound use in COVID-19: a narrative review

Background and Objective

The coronavirus disease 2019 (COVID-19) pandemic that began in early 2020 resulted in significant mortality from respiratory tract infections. Existing imaging modalities such as chest X-ray (CXR) lacks sensitivity in its diagnosis while computed tomography (CT) scan carries risks of radiation and contamination. Point-of-care ultrasound (POCUS) has the advantage of bedside testing with higher diagnostic accuracy. We aim to describe the various applications of POCUS for patients with suspected severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in the emergency department (ED) and intensive care unit (ICU).

Methods

We performed literature search on the use of POCUS in the diagnosis and management of COVID-19 in MEDLINE, Embase and Scopus databases using the following search terms: "ultrasonography", "ultrasound", "COVID-19", "SARS-CoV-2", "SARS-CoV-2 variants", "emergency services", "emergency department" and "intensive care units". Search was performed independently by two reviewers with any discrepancy adjudicated by a third member.

Key Content and Findings

Lung POCUS in patients with COVID-19 shows different ultrasonographic features from pulmonary oedema, bacterial pneumonia, and other viral pneumonia, thus useful in differentiating between these conditions. It is more sensitive than CXR, and more accessible and widely available than CT scan. POCUS can be used to diagnose COVID-19 pneumonia, screen for COVID-19-related pulmonary and extrapulmonary complications, and guide management of ICU patients, such as timing of ventilator weaning based on lung POCUS findings.

Conclusions

POCUS is a useful and rapid point-of-care modality that can be used to aid in diagnosis, management, and risk stratification of COVID-19 patients in different healthcare settings.

Comparison Between Lung Ultrasonography Score in the Emergency Department and Clinical Outcomes of Patients With or With Suspected COVID-19: An Observational Multicentric Study

OBJECTIVE

Chest CT is the reference test for assessing pulmonary injury in suspected or diagnosed COVID-19 with signs of clinical severity. This study aimed to evaluate the association of a lung ultrasonography score and unfavorable clinical evolution at 28 days.

METHODS

The eChoVid is a multicentric study based on routinely collected data that was conducted in 8 emergency units in France; patients were included between March 19, 2020 and April 28, 2020 and underwent lung ultrasonography, a short clinical assessment by 2 emergency physicians blinded to each other's assessment, and chest CT. Lung ultrasonography consisted of scoring lesions from 0 to 3 in 8 chest zones, thus defining a global score (GS) of severity from 0 to 24. The primary outcome was the association of lung damage severity as assessed by the GS at day 0 and patient status at 28 days. Secondary outcomes were comparing the performance between GS and CT scan and the performance between a new trainee physician and an ultrasonography expert in scores.

RESULTS

For the 328 patients analyzed, the GS showed good performance in predicting clinical worsening at 28 days (area under the receiver operating characteristic curve [AUC] 0.83, sensitivity 84.2%, specificity 76.4%). The GS showed good performance in predicting the CT severity assessment (AUC 0.84, sensitivity 77.2%, specificity 83.7%).

CONCLUSION

A lung ultrasonography GS is a simple tool that can be used in the emergency department to predict unfavorable assessment at 28 days in patients with COVID-19.

The role of ultrasound in predicting non-invasive ventilation outcomes: a systematic review

Purpose

To systematically review and compare ultrasonographic methods and their utility in predicting non-invasive ventilation (NIV) outcomes.

Methods

A systematic review was performed using the PubMed, Medline, Embase, and Cochrane databases from January 2015 to March 2023. The search terms included the following: ultrasound, diaphragm, lung, prediction, non-invasive, ventilation, and outcomes. The inclusion criteria were prospective cohort studies on adult patients requiring non-invasive ventilation in the emergency department or inpatient setting.

Results

Fifteen studies were analyzed, which comprised of 1,307 patients (n = 942 for lung ultrasound score studies; n = 365 patients for diaphragm dysfunction studies). Lung ultrasound scores (LUS) greater than 18 were associated with NIV failure with a sensitivity 62-90.5% and specificity 60-91.9%. Similarly, a diaphragm thickening fraction (DTF) of less than 20% was also associated with NIV failure with a sensitivity 80-84.6% and specificity 76.3-91.5%.

Conclusion

Predicting NIV failure can be difficult by routine initial clinical impression and diagnostic work up. This systematic review emphasizes the importance of using lung and diaphragm ultrasound, in particular the lung ultrasound score and diaphragm thickening fraction respectively, to accurately predict NIV failure, including the need for ICU-level of care, requiring invasive mechanical ventilation, and resulting in higher rates of mortality.

Make It Less Complex: Autoencoder for Speckle Noise Removal-Application to Breast and Lung Ultrasound

Ultrasound (US) imaging is used in the diagnosis and monitoring of COVID-19 and breast cancer. The presence of Speckle Noise (SN) is a downside to its usage since it decreases lesion conspicuity. Filters can be used to remove SN, but they involve time-consuming computation and parameter tuning. Several researchers have been developing complex Deep Learning (DL) models (150,000-500,000 parameters) for the removal of simulated added SN, without focusing on the real-world application of removing naturally occurring SN from original US images. Here, a simpler (<30,000 parameters) Convolutional Neural Network Autoencoder (CNN-AE) to remove SN from US images of the breast and lung is proposed. In order to do so, simulated SN was added to such US images, considering four different noise levels (σ = 0.05, 0.1, 0.2, 0.5). The original US images (N = 1227, breast + lung) were given as targets, while the noised US images served as the input. The Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to compare the output of the CNN-AE and of the Median and Lee filters with the original US images. The CNN-AE outperformed the use of these classic filters for every noise level. To see how well the model removed naturally occurring SN from the original US images and to test its real-world applicability, a CNN model that differentiates malignant from benign breast lesions was developed. Several inputs were used to train the model (original, CNN-AE denoised, filter denoised, and noised US images). The use of the original US images resulted in the highest Matthews Correlation Coefficient (MCC) and accuracy values, while for sensitivity and negative predicted values, the CNN-AE-denoised US images (for higher σ values) achieved the best results. Our results demonstrate that the application of a simpler DL model for SN removal results in fewer misclassifications of malignant breast lesions in comparison to the use of original US images and the application of the Median filter. This shows that the use of a less-complex model and the focus on clinical practice applicability are relevant and should be considered in future studies.

Lung ultrasound score severity cut-off points in COVID-19 pneumonia. A systematic review and validating cohort

OBJECTIVES

Our purpose was to establish different cut-off points based on the lung ultrasound score (LUS) to classify COVID-19 pneumonia severity.

METHODS

Initially, we conducted a systematic review among previously proposed LUS cut-off points. Then, these results were validated by a single-centre prospective cohort study of adult patients with confirmed SARS-CoV-2 infection. Studied variables were poor outcome (ventilation support, intensive care unit admission or 28-days mortality) and 28-days mortality.

RESULTS

From 510 articles, 11 articles were included. Among the cut-off points proposed in the articles included, only the LUS>15 cut-off point could be validated for its original endpoint, demonstrating also the strongest relation with poor outcome (odds ratio [OR]=3.636, confidence interval [CI] 1.411-9.374). Regarding our cohort, 127 patients were admitted. In these patients, LUS was statistically associated with poor outcome (OR=1.303, CI 1.137-1.493), and with 28-days mortality (OR=1.024, CI 1.006-1.042). LUS>15 showed the best diagnostic performance when choosing a single cut-off point in our cohort (area under the curve 0.650). LUS≤7 showed high sensitivity to rule out poor outcome (0.89, CI 0.695-0.955), while LUS>20 revealed high specificity to predict poor outcome (0.86, CI 0.776-0.917).

CONCLUSIONS

LUS is a good predictor of poor outcome and 28-days mortality in COVID-19. LUS≤7 cut-off point is associated with mild pneumonia, LUS 8-20 with moderate pneumonia and ≥20 with severe pneumonia. If a single cut-off point were used, LUS>15 would be the point which better discriminates mild from severe disease.

Lung ultrasound score severity cut-off points in COVID-19 pneumonia. A systematic review and validating cohort

Objectives

Our purpose was to establish different cut-off points based on the lung ultrasound score (LUS) to classify COVID-19 pneumonia severity.

Methods

Initially, we conducted a systematic review among previously proposed LUS cut-off points. Then, these results were validated by a single-centre prospective cohort study of adult patients with confirmed SARS-CoV-2 infection. Studied variables were poor outcome (ventilation support, intensive care unit admission or 28-days mortality) and 28-days mortality.

Results

From 510 articles, 11 articles were included. Among the cut-off points proposed in the articles included, only the LUS > 15 cut-off point could be validated for its original endpoint, demonstrating also the strongest relation with poor outcome (odds ratio [OR] = 3.636, confidence interval [CI] 1.411-9.374). Regarding our cohort, 127 patients were admitted. In these patients, LUS was statistically associated with poor outcome (OR = 1.303, CI 1.137-1.493), and with 28-days mortality (OR = 1.024, CI 1.006-1.042). LUS > 15 showed the best diagnostic performance when choosing a single cut-off point in our cohort (area under the curve 0.650). LUS ≤ 7 showed high sensitivity to rule out poor outcome (0.89, CI 0.695-0.955), while LUS > 20 revealed high specificity to predict poor outcome (0.86, CI 0.776-0.917).

Conclusions

LUS is a good predictor of poor outcome and 28-days mortality in COVID-19. LUS ≤ 7 cut-off point is associated with mild pneumonia, LUS 8-20 with moderate pneumonia and ≥20 with severe pneumonia. If a single cut-off point were used, LUS > 15 would be the point which better discriminates mild from severe disease.

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.

Pulmonary hypertension at admission predicts ICU mortality in elderly critically ill with severe COVID-19 pneumonia: retrospective cohort study

BACKGROUND

Point-of-care ultrasound (POCUS) is a useful diagnostic tool for non-invasive assessment of critically ill patients. Mortality of elderly patients with COVID-19 pneumonia is high and there is still scarcity of definitive predictors. Aim of our study was to assess the prediction value of combined lung and heart POCUS data on mortality of elderly critically ill patients with severe COVID-19 pneumonia.

METHODS

This was a retrospective observational study. Data of patients older than 70 years, with severe COVID-19 pneumonia admitted to mixed 25-bed, level 3, intensive care unit (ICU) was analyzed retrospectively. POCUS was performed at admission; our parameters of interest were pulmonary artery systolic pressure (PASP) and presence of diffuse B-line pattern (B-pattern) on lung ultrasound.

RESULTS

Between October 2020 and March 2021, 117 patients aged 70 years or more (average age 77 ± 5 years) were included. Average length of ICU stay was 10.7 ± 8.9 days. High-flow oxygenation, non-invasive ventilation and invasive mechanical ventilation were at some point used to support 36/117 (31%), 39/117 (33%) and 75/117 (64%) patients respectively. ICU mortality was 50.9%. ICU stay was shorter in survivors (8.8 ± 8.3 vs 12.6 ± 9.3 days, p = 0.02). PASP was lower in ICU survivors (32.5 ± 9.8 vs. 40.4 ± 14.3 mmHg, p = 0.024). B-pattern was more often detected in non-survivors (35/59 (59%) vs. 19/58 (33%), p = 0.005). PASP and B-pattern at admission, and also mechanical ventilation and development of VAP, were univariate predictors of mortality. PASP at admission was an independent predictor of ICU (OR 1.061, 95%CI 1.003-1.124, p = 0.039) and hospital (OR 1.073, 95%CI 1.003-1.146, p = 0.039) mortality.

CONCLUSIONS

Pulmonary artery systolic pressure at admission is an independent predictor of ICU and hospital mortality of elderly patients with severe COVID-19 pneumonia.

Reliability and clinical correlations of semi-quantitative lung ultrasound on BLUE points in COVID-19 mechanically ventilated patients: The 'BLUE-LUSS'-A feasibility clinical study

INTRODUCTION

Bedside lung ultrasound has gained a key role in each segment of the treatment chain during the COVID-19 pandemic. During the diagnostic assessment of the critically ill patients in ICUs, it is highly important to maximize the amount and quality of gathered information while minimizing unnecessary interventions (e.g. moving/rotating the patient). Another major factor is to reduce the risk of infection and the workload of the staff.

OBJECTIVES

To serve these significant issues we constructed a feasibility study, in which we used a single-operator technique without moving the patient, only assessing the easily achievable lung regions at conventional BLUE points. We hypothesized that calculating this 'BLUE lung ultrasound score' (BLUE-LUSS) is a reasonable clinical tool. Furthermore, we used both longitudinal and transverse scans to measure their reliability and assessed the interobserver variability as well.

METHODS

University Intensive Care Unit based, single-center, prospective, observational study was performed on 24 consecutive SARS-CoV2 RT-PCR positive, mechanically ventilated critically ill patients. Altogether 400 loops were recorded, rated and assessed off-line by 4 independent intensive care specialists (each 7+ years of LUS experience).

RESULTS

Intraclass correlation values indicated good reliability for transversal and longitudinal qLUSS scores, while we detected excellent interrater agreement of both cLUSS calculation methods. All of our LUS scores correlated inversely and significantly to the P/F values. Best correlation was achieved in the case of longitudinal qLUSS (r = -0.55, p = 0.0119).

CONCLUSION

Summarized score of BLUE-LUSS can be an important, easy-to-perform adjunct tool for assessing and quantifying lung pathology in critically ill ventilated patients at bedside, especially for the P/F ratio. The best agreement for the P/F ratio can be achieved with the longitudinal scans. Regarding these findings, assessing BLUE-points can be extended with the BLUE-LUSS for daily routine using both transverse and longitudinal views.

Current Advances in Lung Ultrasound in COVID-19 Critically Ill Patients: A Narrative Review

Lung ultrasound (LUS) has a relatively recent democratization due to the better availability and training of physicians, especially in intensive care units. LUS is a relatively cheap and easy-to-learn and -use bedside technique that evaluates pulmonary morphology when using simple algorithms. During the global COVID-19 pandemic, LUS was found to be an accurate tool to quickly diagnose, triage and monitor patients with COVID-19 pneumonia. This paper aims to provide a comprehensive review of LUS use during the COVID-19 pandemic. The first section of our work defines the technique, the practical approach and the semeiotic signs of LUS examination. The second section exposed the COVID-19 pattern in LUS examination and the difference between the differential diagnosis patterns and the well-correlation found with computer tomography scan findings. In the third section, we described the utility of LUS in the management of COVID-19 patients, allowing an early diagnosis and triage in the emergency department, as the monitoring of pneumonia course (pneumonia progression, alveolar recruitment, mechanical ventilation weaning) and detection of secondary complications (pneumothorax, superinfection). Moreover, we describe the usefulness of LUS as a marker of the prognosis of COVID-19 pneumonia in the fourth section. Finally, the 5th part is focused on describing the interest of the LUS, as a non-ionized technique, in the management of pregnant COVID-19 women.

Applicability of lung ultrasound in the assessment of COVID-19 pneumonia: Diagnostic accuracy and clinical correlations

BACKGROUND

The purpose of this study was to assess the diagnostic accuracy of lung ultrasound (LUS) in determining the severity of coronavirus disease 2019 (COVID-19) pneumonia compared with thoracic computed tomography (CT) and establish the correlations between LUS score, inflammatory markers, and percutaneous oxygen saturation (SpO₂).

METHODS

This prospective observational study, conducted at Târgu-Mureș Pulmonology Clinic included 78 patients with confirmed severe acute respiratory syndrome coronavirus-2 infection via nasopharyngeal real-time-polymerase chain reaction (RT-PCR) (30 were excluded). Enrolled patients underwent CT, LUS, and blood tests on admission. Lung involvement was evaluated in 16 thoracic areas, using AB₁ B₂ C (letters represent LUS pattern) scores ranging 0-48.

RESULTS

LUS revealed bilateral B-lines (97.8%), pleural irregularities with thickening/discontinuity (75%), and subpleural consolidations (70.8%). Uncommon sonographic patterns were alveolar consolidations with bronchogram (33%) and pleural effusion (2%). LUS score cutoff values of ≤14 and > 22 predicted mild COVID-19 (sensitivity [Se] = 84.6%; area under the curve [AUC] = 0.72; P = 0.002) and severe COVID-19 (Se = 50%, specificity (Sp) = 91.2%, AUC = 0.69; P = 0.02), respectively, and values > 29 predicted the patients' transfer to the intensive care unit (Se = 80%, Sp = 97.7%). LUS score positively correlated with CT score (r = 0.41; P = 0.003) and increased with the decrease of SpO₂ (r = -0.49; P = 0.003), with lymphocytes decline (r = -0.52; P = 0.0001). Patients with consolidation patterns had higher ferritin and C-reactive protein than those with B-line patterns (P = 0.01; P = 0.03).

CONCLUSIONS

LUS is a useful, non-invasive and effective tool for diagnosis, monitoring evolution, and prognostic stratification of COVID-19 patients.

Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study

The clinical utility of point-of-care lung ultrasound (LUS) among hospitalized patients with COVID-19 is unclear.

DESIGN

Prospective cohort study.

SETTING

A large tertiary care center in Maryland, between April 2020 and September 2021.

PATIENTS

Hospitalized adults (≥ 18 yr old) with positive severe acute respiratory syndrome coronavirus 2 reverse transcriptase-polymerase chain reaction results.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

All patients were scanned using a standardized protocol including 12 lung zones and followed to determine clinical outcomes until hospital discharge and vital status at 28 days. Ultrasounds were independently reviewed for lung and pleural line artifacts and abnormalities, and the mean LUS Score (mLUSS) (ranging from 0 to 3) across lung zones was determined. The primary outcome was time to ICU-level care, defined as high-flow oxygen, noninvasive, or invasive mechanical ventilation, within 28 days of the initial ultrasound. Cox proportional hazards regression models adjusted for age and sex were fit for mLUSS and each ultrasound covariate. A total of 264 participants were enrolled in the study; the median age was 61 years and 114 participants (43.2%) were female. The median mLUSS was 1.0 (interquartile range, 0.5-1.3). Following enrollment, 27 participants (10.0%) went on to require ICU-level care, and 14 (5.3%) subsequently died by 28 days. Each increase in mLUSS at enrollment was associated with disease progression to ICU-level care (adjusted hazard ratio [aHR], 3.61; 95% CI, 1.27-10.2) and 28-day mortality (aHR, 3.10; 95% CI, 1.29-7.50). Pleural line abnormalities were independently associated with disease progression to death (aHR, 20.93; CI, 3.33-131.30).

CONCLUSIONS

Participants with a mLUSS greater than or equal to 1 or pleural line changes on LUS had an increased likelihood of subsequent requirement of high-flow oxygen or greater. LUS is a promising tool for assessing risk of COVID-19 progression at the bedside.

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.

Rapid 8-Zone Lung Ultrasound Protocol is Comparable to a Full 12-Zone Protocol for Outcome Prediction in Hospitalized COVID-19 Patients

OBJECTIVES

Safety precautions limit the clinical assessment of hospitalized Coronavirus disease 2019 (COVID-19) patients. The minimal exposure required to perform lung ultrasound (LUS) paired with its high accuracy, reproducibility, and availability make it an attractive solution for initial assessment of COVID-19 patients. We aim to evaluate whether the association between sonographic findings and clinical outcomes among COVID 19 patients is comparable between the validated 12-zone protocol and a shorter, 8-zone protocol, in which the posterior lung regions are omitted.

METHODS

One hundred and one COVID-19 patients hospitalized in a dedicated COVID-19 ward in a tertiary referral hospital were examined upon admission and scored by 2 LUS protocols. The association between the scores and a composite outcome consisting of death, transfer to the intensive care unit (ICU) or initiation of invasive or noninvasive mechanical ventilation was estimated and compared.

RESULTS

LUS scores in both the 8- and the 12-zone protocols were associated with the composite outcome during hospitalization (hazard ratio [HR] 1.21 [1.03-1.42, P = .022] and HR 1.13 [1.01-1.27, P = .037], respectively). The observed difference in the discriminatory ROC-AUC values for the 8- and 12-zone scores was not significant (0.767 and 0.754 [P = .647], respectively).

CONCLUSION

A short 8-zone LUS protocol is as accurate as the previously validated, 12-zone protocol for prognostication of clinical deterioration in nonventilated COVID-19 patients.

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.

Importance of Lung Ultrasound Follow-Up in Patients Who Had Recovered from Coronavirus Disease 2019: Results from a Prospective Study

There is growing evidence regarding the imaging findings of coronavirus disease 2019 (COVID-19) in lung ultrasounds, however, their role in predicting the prognosis has yet to be explored. Our objective was to assess the usefulness of lung ultrasound in the short-term follow-up (1 and 3 months) of patients with SARS-CoV-2 pneumonia, and to describe the progression of the most relevant lung ultrasound findings. We conducted a prospective, longitudinal and observational study performed in patients with confirmed COVID-19 who underwent a lung ultrasound examination during hospitalization and repeated it 1 and 3 months after hospital discharge. A total of 96 patients were enrolled. In the initial ultrasound, bilateral involvement was present in 100% of the patients with mild, moderate or severe ARDS. The most affected lung area was the posteroinferior (93.8%) followed by the lateral (88.7%). Subpleural consolidations were present in 68% of the patients and consolidations larger than 1 cm in 24%. One month after the initial study, only 20.8% had complete resolution on lung ultrasound. This percentage rose to 68.7% at 3 months. Residual lesions were observed in a significant percentage of patients who recovered from moderate or severe ARDS (32.4% and 61.5%, respectively). In conclusion, lung injury associated with COVID-19 might take time to resolve. The findings in this report support the use of lung ultrasound in the short-term follow-up of patients recovered from COVID-19, as a radiation-sparing, easy to use, novel care path worth exploring.

Association of Lung Ultrasound Score with Mortality and Severity of COVID-19: A Meta-Analysis and Trial Sequential Analysis

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread all over the world. Lung ultrasound (LUS) has emerged as a useful tool for diagnosing many respiratory diseases. The prognostic role of LUS in COVID-19 patients has not yet been established.

METHODS

Several databases were searched on 09 April 2021. The difference in LUS score between the death and survival groups, and the relationship between LUS score and COVID-19 severity were both assessed.

RESULTS

The LUS score was significantly higher in the death group compared with the survival group (weighted mean difference (WMD) = 8.21, 95% CI: 4.74-11.67, P < 0.001), which was confirmed by trial sequential analysis. Those with mild/moderate, severe and critical COVID-19 had a progressively higher LUS score (critical vs. severe: WMD = 8.78, 95% CI: 4.17-13.38; P < 0.001; critical vs. mild/moderate/severe: WMD = 10.00, 95% CI: 6.83-13.17, P < 0.001; severe vs. moderate: WMD = 5.96, 95% CI: 3.48-8.44, P < 0.001; severe vs. mild/moderate: WMD = 7.31, 95% CI: 4.45-10.17, P < 0.001).

CONCLUSIONS

The LUS score was associated with mortality and severity of COVID-19. The LUS score might be a risk stratification tool for COVID-19 patients.