Feasibility of chest ultrasound up to 42 m underwater

After recent advancements, ultrasound has extended its applications from bedside clinical practice to wilderness medicine. Performing ultrasound scans in extreme environments can allow direct visualization of unique pathophysiological adaptations but can be technically challenging. This paper summarizes how a portable ultrasound apparatus was marinized to let scientific divers and sonographers perform ultrasound scans of the lungs underwater up to - 42 m. A metallic case protected the ultrasound apparatus inside; a frontal transparent panel with a glove allowed visualization and operation of the ultrasound by the diving sonographer. The inner pressure was equalized with environmental pressure through a compressed air tank connected with circuits similar to those used in SCUBA diving. Finally, the ultrasound probe exited the metallic case through a sealed aperture. No technical issues were reported after the first testing step and the real experiments.

Influence of Ultrasound Settings on Laboratory Vertical Artifacts

OBJECTIVE

The aim of the work described here was to analyze the relationship between the change in ultrasound (US) settings and the vertical artifacts' number, visual rating and signal intensity METHODS: An in vitro phantom consisting of a damp sponge and gelatin mix was created to simulate vertical artifacts. Furthermore, several US parameters were changed sequentially (i.e., frequency, dynamic range, line density, gain, power and image enhancement) and after image acquisition. Five US experts rated the artifacts for number and quality. In addition, a vertical artifact visual score was created to determine the higher artifact rating ("optimal") and the lower artifact rating ("suboptimal"). Comparisons were made between the tested US parameters and baseline recordings.

RESULTS

The expert intraclass correlation coefficient for the number of vertical artifacts was 0.694. The parameters had little effect on the "optimal" vertical artifacts but changed their number. Dynamic range increased the number of discernible vertical artifacts to 3 from 36 to 102 dB.

CONCLUSION

The intensity did not correlate with the visual rating score. Most of the available US parameters did not influence vertical artifacts.

Author Reply "Comment on Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care"

How to cite this article: Rajbanshi LK. Author Reply "Comment on Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care". Indian J Crit Care Med 2023;27(8):597-598.

Commentary on "Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit"

How to cite this article: Chowdhury SR, Kundu R. Commentary on "Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit." Indian J Crit Care Med 2023;27(8):596.

Precision Medicine Using Simultaneous Monitoring and Assessment with Imaging and Biomarkers to Manage Mechanical Ventilation in ARDS

Acute respiratory distress syndrome (ARDS) has a ~ 40% mortality rate with an increasing prevalence exacerbated by the COVID-19 pandemic. Mechanical ventilation is the primary means for life-saving support to buy time for lung healing in ARDS patients, however, it can also lead to ventilator-induced lung injury (VILI). Effective strategies to reduce or prevent VILI are necessary but are not currently delivered. Therefore, we aim at evaluating the current imaging technologies to visualize where pressure and volume being delivered to the lung during mechanical ventilation; and combining plasma biomarkers to guide management of mechanical ventilation. We searched PubMed and Medline using keywords and analyzed the literature, including both animal models and human studies, to examine the independent use of computed tomography (CT) to evaluate lung mechanics, electrical impedance tomography (EIT) to guide ventilation, ultrasound to monitor lung injury, and plasma biomarkers to indicate status of lung pathophysiology. This investigation has led to our proposal of the combination of imaging and biomarkers to precisely deliver mechanical ventilation to improve patient outcomes in ARDS.

Comparison of pulmonary congestion severity using artificial intelligence-assisted scoring versus clinical experts: A secondary analysis of BLUSHED-AHF

AIM

Acute decompensated heart failure (ADHF) is the leading cause of cardiovascular hospitalizations in the United States. Detecting B-lines through lung ultrasound (LUS) can enhance clinicians' prognostic and diagnostic capabilities. Artificial intelligence/machine learning (AI/ML)-based automated guidance systems may allow novice users to apply LUS to clinical care. We investigated whether an AI/ML automated LUS congestion score correlates with expert's interpretations of B-line quantification from an external patient dataset.

METHODS AND RESULTS

This was a secondary analysis from the BLUSHED-AHF study which investigated the effect of LUS-guided therapy on patients with ADHF. In BLUSHED-AHF, LUS was performed and B-lines were quantified by ultrasound operators. Two experts then separately quantified the number of B-lines per ultrasound video clip recorded. Here, an AI/ML-based lung congestion score (LCS) was calculated for all LUS clips from BLUSHED-AHF. Spearman correlation was computed between LCS and counts from each of the original three raters. A total of 3858 LUS clips were analysed on 130 patients. The LCS demonstrated good agreement with the two experts' B-line quantification score (r = 0.894, 0.882). Both experts' B-line quantification scores had significantly better agreement with the LCS than they did with the ultrasound operator's score (p < 0.005, p < 0.001).

CONCLUSION

Artificial intelligence/machine learning-based LCS correlated with expert-level B-line quantification. Future studies are needed to determine whether automated tools may assist novice users in LUS interpretation.

Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level

Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lungs has been investigated in various studies using artificial intelligence-based (AI) methods. However, an extensive analysis of state-of-the-art Convolutional Neural Network-based (CNN) models for frame-level scoring, a comparative analysis of aggregation techniques for video-level scoring, together with a thorough evaluation of the capability of these methodologies to provide a clinically valuable prognostic-level score is yet missing within the literature. In addition to that, the impact on the analysis of the posterior probability assigned by the network to the predicted frames as well as the impact of temporal downsampling of LUS data are topics not yet extensively investigated. This paper takes on these challenges by providing a benchmark analysis of methods from frame to prognostic level. For frame-level scoring, state-of-the-art deep learning models are evaluated with additional analysis of best performing model in transfer-learning settings. A novel cross-correlation based aggregation technique is proposed for video and exam-level scoring. Results showed that ResNet-18, when trained from scratch, outperformed the existing methods with an F1-Score of 0.659. The proposed aggregation method resulted in 59.51%, 63.29%, and 84.90% agreement with clinicians at the video, exam, and prognostic levels, respectively; thus, demonstrating improved performances over the state of the art. It was also found that filtering frames based on the posterior probability shows higher impact on the LUS analysis in comparison to temporal downsampling. All of these analysis were conducted over the largest standardized and clinically validated LUS dataset from COVID-19 patients.

Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit

BACKGROUND

Interpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances in the use of Artificial Intelligence (AI) to automate many ultrasound imaging analysis tasks, no AI-enabled LUS solutions have been proven to be clinically useful in ICUs, and specifically in LMICs. Therefore, we developed an AI solution that assists LUS practitioners and assessed its usefulness in  a low resource ICU.

METHODS

This was a three-phase prospective study. In the first phase, the performance of four different clinical user groups in interpreting LUS clips was assessed. In the second phase, the performance of 57 non-expert clinicians with and without the aid of a bespoke AI tool for LUS interpretation was assessed in retrospective offline clips. In the third phase, we conducted a prospective study in the ICU where 14 clinicians were asked to carry out LUS examinations in 7 patients with and without our AI tool and we interviewed the clinicians regarding the usability of the AI tool.

RESULTS

The average accuracy of beginners' LUS interpretation was 68.7% [95% CI 66.8-70.7%] compared to 72.2% [95% CI 70.0-75.6%] in intermediate, and 73.4% [95% CI 62.2-87.8%] in advanced users. Experts had an average accuracy of 95.0% [95% CI 88.2-100.0%], which was significantly better than beginners, intermediate and advanced users (p < 0.001). When supported by our AI tool for interpreting retrospectively acquired clips, the non-expert clinicians improved their performance from an average of 68.9% [95% CI 65.6-73.9%] to 82.9% [95% CI 79.1-86.7%], (p < 0.001). In prospective real-time testing, non-expert clinicians improved their baseline performance from 68.1% [95% CI 57.9-78.2%] to 93.4% [95% CI 89.0-97.8%], (p < 0.001) when using our AI tool. The time-to-interpret clips improved from a median of 12.1 s (IQR 8.5-20.6) to 5.0 s (IQR 3.5-8.8), (p < 0.001) and clinicians' median confidence level improved from 3 out of 4 to 4 out of 4 when using our AI tool.

CONCLUSIONS

AI-assisted LUS can help non-expert clinicians in an LMIC ICU improve their performance in interpreting LUS features more accurately, more quickly and more confidently.

Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit

Introduction

Spontaneous breathing trial (SBT) is always successful in mechanically ventilated patients. This study was conducted to assess the prediction of successful SBT and extubation of trachea by bedside lung ultrasound in mechanically ventilated patients.

Methodology

This was a prospective observational study for 1 year conducted at a tertiary teaching hospital ICU on 102 patients with age more than 18 years and who were mechanically ventilated for more than 24 hours. Bedside lung ultrasound was used to assess the lung ultrasound score (LUS) and lung profiles in patients who clinically met the criteria for SBT. The LUS at the beginning of SBT and 30 minutes after SBT were used to predict the successful SBT and tracheal extubation.

Result

Spontaneous breathing trial and tracheal extubation were successful in 73 (71.6%) and 57 (55.8%) of the patients. The AUC for lung ultrasound in predicting successful SBT at the beginning and 30 minutes of SBT were 0.781 (CI 95% 0.674-0.888, p < 0.001) and 0.841 (CI 95% 0.742-0.941, p < 0.001) with a cut-off value of 17.5 and 19.5, respectively. Similarly, AUC for LUS in relation to tracheal extubation was 0.786 (CI 95% 0.694-0.879, p < 0.001) and 0.841(CI 95% 0.756-0.925, p < 0.001) at 0 and 30 minutes. About 57.5% of the patients with A profiles tolerated successful SBT while 48.3% of the patients having C profile had failed SBT (p < 0.001). COPD, lung ultrasound, higher SOFA score, and longer duration of mechanical ventilation had a statistically significant negative correlation with successful SBT.

Conclusion

Lower LUS and A profiles lung ultrasound are associated with more successful weaning and tracheal extubation in mechanically ventilated patients.

How to cite this article

Rajbanshi LK, Bajracharya A, Devkota D. Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit. Indian J Crit Care Med 2023;27(7):482-487.

Pneumothorax detection with thoracic ultrasound as the method of choice in interventional pulmonology - A retrospective single-center analysis and experience

BACKGROUND

Recent studies have shown that thoracic ultrasound (TUS) is not inferior to chest radiography (CR) in detecting pneumothorax (PTX). It is unclear if adopting TUS can reduce the number of CR in the daily clinical routine. This retrospective study investigates the utilization of post-interventional CR and TUS for PTX detection after the introduction of TUS as the method of choice in an interventional pulmonology unit.

METHODS

All interventions with CR or TUS for ruling out PTX performed in the Pneumology Department of the University Hospital Halle (Germany) 2014 to 2020 were included. The documented TUS and CR performed before (period A) and after the introduction of TUS as the method of choice (period B), as well as the number of diagnosed and missed PTX were recorded.

RESULTS

The study included 754 interventions (110 in period A and 644 in period B). The proportion of CR decreased from 98.2% (n = 108) to 25.8% (n = 166) (p < 0.001). During period B, a total of 29 (4.5%) PTX were diagnosed. Of these, 28 (96.6%) were detected on initial imaging (14 by CR, 14 by TUS ). One PTX (0.2%) was initially missed by TUS, none by CR. Confirmatory investigations were ordered more frequently after TUS (21 of 478, 4.4%) than after CR (3 of 166, 1.8%).

CONCLUSION

The use of TUS in interventional pulmonology can effectively reduce the number of CR and thus save resources. However, CR may still be favored in specific circumstances or if pre-existing conditions limit sonographic findings.

Machine Learning Algorithm Detection of Confluent B-Lines

OBJECTIVE

B-lines are a ring-down artifact of lung ultrasound that arise with increased alveolar water in conditions such as pulmonary edema and infectious pneumonitis. Confluent B-line presence may signify a different level of pathology compared with single B-lines. Existing algorithms aimed at B-line counting do not distinguish between single and confluent B-lines. The objective of this study was to test a machine learning algorithm for confluent B-line identification.

METHODS

This study used a subset of 416 clips from 157 subjects, previously acquired in a prospective study enrolling adults with shortness of breath at two academic medical centers, using a hand-held tablet and a 14-zone protocol. After exclusions, random sampling generated a total of 416 clips (146 curvilinear, 150 sector and 120 linear) for review. A group of five experts in point-of-care ultrasound blindly evaluated the clips for presence/absence of confluent B-lines. Ground truth was defined as majority agreement among the experts and used for comparison with the algorithm.

RESULTS

Confluent B-lines were present in 206 of 416 clips (49.5%). Sensitivity and specificity of confluent B-line detection by algorithm compared with expert determination were 83% (95% confidence interval [CI]: 0.77-0.88) and 92% (95% CI: 0.88-0.96). Sensitivity and specificity did not statistically differ between transducers. Agreement between algorithm and expert for confluent B-lines measured by unweighted κ was 0.75 (95% CI: 0.69-0.81) for the overall set.

CONCLUSION

The confluent B-line detection algorithm had high sensitivity and specificity for detection of confluent B-lines in lung ultrasound point-of-care clips, compared with expert determination.

Mechanical power normalized to aerated lung predicts noninvasive ventilation failure and death and contributes to the benefits of proning in COVID-19 hypoxemic respiratory failure

Background

Concern exists that noninvasive ventilation (NIV) may promote ventilation-induced lung injury(VILI) and worsen outcome in acute hypoxemic respiratory failure (AHRF). Different individual ventilatory variables have been proposed to predict clinical outcomes, with inconsistent results.Mechanical power (MP), a measure of the energy transfer rate from the ventilator to the respiratory system during mechanical ventilation, might provide solutions for this issue in the framework of predictive, preventive and personalized medicine (PPPM). We explored (1) the impact of ventilator-delivered MP normalized to well-aerated lung (MP_WAL) on physio-anatomical and clinical responses to NIV in COVID-19-related AHRF and (2) the effect of prone position(PP) on MP_WAL.

Methods

We analyzed 216 noninvasively ventilated COVID-19 patients (108 patients receiving PP + NIV and 108 propensity score-matched patients receiving supine NIV) with moderate-to-severe(paO2/FiO2 ratio < 200) AHRF enrolled in the PRO-NIV controlled non-randomized study (ISRCTN23016116).Quantification of differentially aerated lung volumes by lung ultrasonography (LUS) was validated against CT scans. Respiratory parameters were hourly recorded, ABG were performed 1 h after each postural change. Time-weighed average values of ventilatory variables, including MP_WAL, and gas exchange parameters (paO2/FiO2 ratio, dead space indices) were calculated for each ventilatory session. LUS and circulating biomarkers were assessed daily.

Results

Compared with supine position, PP was associated with a 34% MP_WAL reduction, attributable largely to an absolute MP reduction and secondly to an enhanced lung reaeration.Patients receiving a high MP_WAL during the 1^st 24 h of NIV [MP_WAL(day 1)] had higher 28-d NIV failure (HR = 4.33,95%CI:3.09 - 5.98) and death (HR = 5.17,95%CI: 3.01 - 7.35) risks than those receiving a low MP_WAL(day 1).In Cox multivariate analyses, MP_WAL(day 1) remained independently associated with 28-d NIV failure (HR = 1.68,95%CI:1.15-2.41) and death (HR = 1.69,95%CI:1.22-2.32).MP_WAL(day 1) outperformed other power measures and ventilatory variables as predictor of 28-d NIV failure (AUROC = 0.89;95%CI:0.85-0.93) and death (AUROC = 0.89;95%CI:0.85-0.94).MP_WAL(day 1) predicted also gas exchange, ultrasonographic and inflammatory biomarker responses, as markers of VILI, on linear multivariate analysis.

Conclusions

In the framework of PPPM, early bedside MP_WAL calculation may provide added value to predict response to NIV and guide subsequent therapeutic choices i.e. prone position adoption during NIV or upgrading to invasive ventilation, to reduce hazardous MP_WAL delivery, prevent VILI progression and improve clinical outcomes in COVID-19-related AHRF.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00325-5.

Determinants of point-of-care ultrasound lung sliding amplitude in mechanically ventilated patients

BACKGROUND

Although lung sliding seen by point-of-care ultrasound (POCUS) is known to be affected to varying degrees by different physiologic and pathologic processes, it is typically only reported qualitatively in the critical care setting. Lung sliding amplitude quantitatively expresses the amount of pleural movement seen by POCUS but its determinants in mechanically ventilated patients are largely unknown.

METHODS

This was a single-center, prospective, observational pilot study examining 40 hemithoraces in 20 adult patients receiving mechanical ventilation. Each subject had lung sliding amplitude measured in both B-mode and by pulsed wave Doppler at their bilateral lung apices and bases. Differences in lung sliding amplitude were correlated with anatomical location (apex vs base) as well as physiologic parameters including positive end expiratory pressure (PEEP), driving pressure, tidal volume and the ratio of arterial partial pressure of oxygen (PaO₂) to fraction of inspired oxygen (FiO₂).

RESULTS

POCUS lung sliding amplitude was significantly lower at the lung apex compared to the lung base in both B-mode (3.6 ± 2.0 mm vs 8.6 ± 4.3 mm; p < 0.001) and the pulsed wave Doppler mode (10.3 ± 4.6 cm/s vs 13.9 ± 5.5 cm/s; p < 0.001) corresponding to expected distribution of ventilation to the lung bases. Inter-rater reliability of B-mode measurements was excellent (ICC = 0.91) and distance traversed in B-mode had a significant positive correlation with pleural line velocity (r² = 0.32; p < 0.001). There was a non-statistically significant trend towards lower lung sliding amplitude for PEEP ≥ 10 cmH₂O, as well as for driving pressure ≥ 15 cmH₂O in both ultrasound modes.

CONCLUSION

POCUS lung sliding amplitude was significantly lower at the lung apex than the lung base in mechanically ventilated patients. This was true when using both B-mode and pulsed wave Doppler. Lung sliding amplitude did not correlate with PEEP, driving pressure, tidal volume or PaO₂:FiO₂ ratio. Our findings suggest that lung sliding amplitude can be quantified in mechanically ventilated patients in a physiologically predictable way and with high inter-rater reliability. A better understanding of POCUS derived lung sliding amplitude and its determinants may aid in the more accurate diagnosis of lung pathologies, including pneumothorax, and could serve as a means of further reducing radiation exposure and improving outcomes in critically ill patients.

Prognostic value of the early lung ultrasound B-line score for postoperative pulmonary insufficiency in patients undergoing thoracic surgery: an observational study

BACKGROUND

Postoperative pulmonary insufficiency (PPI) is an important contributor to morbidity and mortality after thoracic surgery. Lung ultrasound is a reliable tool for assessing respiratory function. We sought to determine the clinical value of the early lung ultrasound B-line score for predicting changes in pulmonary function after thoracic surgery.

METHODS

Eighty-nine patients undergoing elective lung surgery were included in this study. The B-line score was determined 30 min after removal of the endotracheal tube, and the PaO2/FiO2 ratio was recorded 30 min after extubation and on the third postoperative day. Patients were divided into normal (PaO2/FiO2 ≥ 300) and PPI (PaO2/FiO2 < 300) groups according to their PaO2/FiO2 ratios. A multivariate logistic regression model was used to identify independent predictors of postoperative pulmonary insufficiency. Receiver operating characteristic (ROC) analysis was performed for significantly correlated variables.

RESULTS

Eighty-nine patients undergoing elective lung surgery were included in this study. We evaluated 69 patients in the normal group and 20 in the PPI group. Patients conforming to NYHA class 3 at administration were significantly more represented in the PPI group (5.8 and 55%; p < 0.001). B-line scores were significantly higher in the PPI group than in the normal group (16; IQR 13-21 vs. 7; IQR 5-10; p < 0.001). The B-line score was an independent risk factor (OR = 1.349 95% CI 1.154-1.578; p < 0.001), and its best cutoff value for predicting PPI was 12 (sensitivity: 77.5%; specificity: 66.7%).

CONCLUSIONS

Lung ultrasound B-line scores 30 min after extubation are effective in predicting early PPI in patients undergoing thoracic surgery. Trial registration This study was registered with the Chinese Clinical Trials Registry (ChiCTR2000040374).

CORONA (COre ultRasOund of covid in iNtensive care and Acute medicine) study: National service evaluation of lung and heart ultrasound in intensive care patients with suspected or proven COVID-19

BACKGROUND

Combined Lung Ultrasound (LUS) and Focused UltraSound for Intensive Care heart (FUSIC Heart - formerly Focused Intensive Care Echocardiography, FICE) can aid diagnosis, risk stratification and management in COVID-19. However, data on its application and results are limited to small studies in varying countries and hospitals. This United Kingdom (UK) national service evaluation study assessed how combined LUS and FUSIC Heart were used in COVID-19 Intensive Care Unit (ICU) patients during the first wave of the pandemic.

METHOD

Twelve trusts across the UK registered for this prospective study. LUS and FUSIC Heart data were obtained, using a standardised data set including scoring of abnormalities, between 1st February 2020 to 30th July 2020. The scans were performed by intensivists with FUSIC Lung and Heart competency as a minimum standard. Data was anonymised locally prior to transfer to a central database.

RESULTS

372 studies were performed on 265 patients. There was a small but significant relationship between LUS score >8 and 30-day mortality (OR 1.8). Progression of score was associated with an increase in 30-day mortality (OR 1.2). 30-day mortality was increased in patients with right ventricular (RV) dysfunction (49.4% vs 29.2%). Severity of LUS score correlated with RV dysfunction (p < 0.05). Change in management occurred in 65% of patients following a combined scan.

CONCLUSIONS

In COVID-19 patients, there is an association between lung ultrasound score severity, RV dysfunction and mortality identifiable by combined LUS and FUSIC Heart. The use of 12-point LUS scanning resulted in similar risk score to 6-point imaging in the majority of cases. Our findings suggest that serial combined LUS and FUSIC Heart on COVID-19 ICU patients may aid in clinical decision making and prognostication.

Lung ultrasound description of a newborn with bronchial atresia: A case report

Introduction

Congenital pulmonary malformations are a heterogeneous group of embryological alterations at different stages of lung development, the most frequent being the congenital malformation of the airway. Lung ultrasound is a very useful tool in neonatal intensive care units, providing great value for differential diagnosis, as well as therapeutic response or early detection of complications.

Case Report

The case is a newborn of 38weeks' gestation who was followed by prenatal ultrasound control for suspected adenomatous cystic malformation type III in the left lung from week 22. She did not present complications during pregnancy. The study of Genetics and serological test were negative. She was born by urgent caesarean section due to breech presentation without requiring resuscitation, weighing 2.915 g. She was admitted to the Unit for study, remaining stable throughout her stay, with a normal physical examination. Atelectasis of the left upper lobe was appreciated by chest X-ray. Pulmonary ultrasound on the second day of life showed signs of consolidation in the left posterosuperior field with air bronchogram, without other alterations. In subsequent ultrasound controls, an interstitial infiltrate was observed in the left posterosuperior region, compatible with progressive aeration of the area, which was maintained until 1 month of life. The computed tomographic scan performed at 6months of age shows hyperlucency and increased volume in the left upper lobe with slight hypovascularization, accompanied by paramediastinal subsegmental atelectasis. There was a hypodense image at the hilar level. These findings were compatible with bronchial atresia, later confirmed by fiberoptic bronchoscopy. At 18months of age, surgical intervention was performed.

Discussion and Conclusion

We present the first case of bronchial atresia diagnosed by LUS, thus adding new images to the very scarce literature currently available.

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.

A new non-invasive index for the prediction of endotracheal intubation in patients with SARS COVID-19 infection, in the emergency department, pilot study

BACKGROUND

In the current context of the SARS COVID-19 pandemic, where the main cause of death is respiratory failure, and since early recognition would allow timely measures to be implemented and probably improve outcomes, it is important to have tools that allow the emergency room to predict quickly and without the use of large resources which will need invasive mechanical ventilation. This study proposes using a new predictive index of noninvasive characteristics, based on the relationship between oxygenation and work of breathing measured by ultrasound-assessed diaphragmatic function, for the need for invasive mechanical ventilation in patients with SARS-COV2 infection who are admitted to the emergency department.

METHODS

A prospective predictive cohort study was performed, collecting all patients admitted to the emergency room with respiratory failure (not severe or in imminent respiratory arrest) and a confirmed diagnosis of SARS-CoV-2 pneumonia. Diaphragmatic excursion measurements were taken within the first 24 h after admission to the department. The relationship between diaphragmatic excursion and SAFI was calculated, establishing the ultrasound diaphragmatic excursion So2/FiO2 index (U.D.E.S.I). The index's performance was determined by analysis of sensitivity, specificity, and area under the curve (AUC).

RESULTS

This pilot study analyzed the first 100 patients enrolled and found in-hospital mortality of 19%, all patients who died required mechanical ventilation, the right index showed a specificity of 82.4% with a sensitivity of 76.9%, likewise for the left index an overall specificity of 90.5% with a sensitivity of 65.3% was found. The ideal cut-off point for the right index is 1.485, and for the left index, the threshold point was 1.856. AUC of the right index is 0.798 (0.676-0.920) and of the left index 0.793 (0.674-0.911), when comparing them no significant differences were found between these values p = 0.871.

CONCLUSION

The relationship of So2/FiO2 and diaphragm excursion measured by both right and left ultrasound could predict the need for mechanical ventilation of the patient with COVID-19 pneumonia in the emergency room and could constitute a valuable tool since it uses noninvasive parameters and is easily applicable at the patient's bedside. However, a more extensive study is needed to validate these preliminary results.

Trajectory and correlates of pulmonary congestion by lung ultrasound in patients with acute myocardial infarction: insights from PARADISE-MI

AIM

PARADISE-MI examined the efficacy of sacubitril/valsartan in acute myocardial infarction (AMI) complicated by reduced left ventricular ejection fraction (LVEF), pulmonary congestion, or both. We sought to assess the trajectory of pulmonary congestion using lung ultrasound (LUS) and its association with cardiac structure and function in a pre-specified substudy.

METHODS AND RESULTS

Patients without prior heart failure (HF) underwent eight-zone LUS and echocardiography at baseline (±2 days of randomization) and after 8 months. B-lines were quantified offline, blinded to treatment, clinical findings, time point, and outcomes. Among 152 patients (median age 65, 32% women, mean LVEF 41%), B-lines were detectable in 87% at baseline [median B-line count: 4 (interquartile range 2-8)]. Among 115 patients with LUS data at baseline and follow-up, B-lines decreased significantly from baseline (mean ± standard deviation: -1.6 ± 7.3; P = 0.018). The proportion of patients without pulmonary congestion at follow-up was significantly higher in those with fewer B-lines at baseline. Adjusted for baseline, B-lines at follow-up were on average 6 (95% confidence interval: 3-9) higher in patients who experienced an intercurrent HF event vs. those who did not (P = 0.001). A greater number of B-lines at baseline was associated with larger left atrial size, higher E/e' and E/A ratios, greater degree of mitral regurgitation, worse right ventricular systolic function, and higher tricuspid regurgitation velocity (P-trend <0.05 for all).

CONCLUSION

In this AMI cohort, B-lines, indicating pulmonary congestion, were common at baseline and, on average, decreased significantly from baseline to follow-up. Worse pulmonary congestion was associated with prognostically important echocardiographic markers.

Clinical performance of lung ultrasound in predicting time-dependent changes in lung aeration in ARDS patients

To evaluate whether lung ultrasound is reliable bedside tool to monitor changes of lung aeration at the early and late stages of ARDS. LUS was performed in ARDS patients that underwent at least two consecutive CT scan at ICU admission and at least 1 week after admission. Twelve fields were evaluated and graded from 0 (normal) to 3 (consolidation). Changes of LUS score in twelve fields (ΔLUStot) and in four ventral (ΔLUSV), intermediate (ΔLUSI) and dorsal (ΔLUSD) zones were calculated at each time points. Three categories were described: Improve (ΔLUS < 0), Equal (ΔLUS = 0) or Worse (ΔLUS > 0). LUS scores were correlated with total changes in lung CT aeration (ΔCTair) and with normally, poorly and not aerated regions (ΔCTnorm, ΔCTpoor and ΔCTnot, respectively). Eleven patients were enrolled. ΔLUStot had significant correlation with ΔCTair (r = - 0.74, p < 0.01). ΔLUSV, ΔLUSI and ΔLUSD showed significant correlations with ΔCTair (r = - 0.66, r = - 0.69, r = - 0.63, respectively; p < 0.05). Compared to Equal, Improve and Worse categories had significantly higher (p < 0.01) and lower (p < 0.05) ΔCTair values, respectively. Compared to Equal, Improve and Worse categories had lower (p < 0.01) and higher (p < 0.01) ΔCTnot values, respectively. LUS score had a good correlation with lung CT in detecting changes of lung aeration.

Point of care ultrasound impact in acute heart failure hospitalization: A retrospective cohort study

BACKGROUND

Acute decompensated heart failure (ADHF) is one of the most frequent causes of emergency department (ED) visits. Point-of-Care Ultrasound (POCUS) is a reliable, easy-to-use, and available tool for an accurate diagnosis of ADHF. We aimed to analyze the impact of introducing POCUS as an additional tool to clinical standard diagnosis in clinical times of hospitalized heart failure patients.

METHODS

Retrospective cohort study comparing patients consulting to ED for heart failure acute decompensation previous to the rutinary use of POCUS versus patients who received an ultrasound-guided diagnosis at entrance. Ultrasound evaluation was additional to standard diagnosis (which included natriuretic peptides, images, etc). Cumulative incidence functions were calculated for time to treatment, time to disposition decision, and time to discharge. We used a flexible parametric model for estimate the time ratio (TR) in order to reflect the effect of POCUS.

RESULTS

A total of 149 patients were included. The most frequent comorbid condition was hypertension (71.8%) followed by type 2 diabetes (36.2%). B type natriuretic peptide (BNP) was over 500 ng/ml. Most patients had Stevenson B profile (83.9%) at admission. In the cumulative incidence model (Fig. A), the TR (time ratio) for the outcome time to treatment was 1.539 (CI 95% 0.88 to 2.69). The TR for the outcome time to disposition decision was 0.665 (CI 95% 0.48 to 0.99). The TR for the outcome time to discharge (hospital length of stay) was 0.663 (CI 95% 0.49 to 0.90).

CONCLUSION

In our study, the introduction of POCUS to ADHF patients decreases time to disposition decision and total length of hospital stay. Conversely, time to treatment augments. There is need for the evaluation of ultrasound as an intervention in clinical trials to confirm these findings.

Long-term lung ultrasound follow-up in patients after COVID-19 pneumonia hospitalization: A prospective comparative study with chest computed tomography

During COVID-19 pandemic, lung ultrasound (LUS) proved to be of great value in the diagnosis and monitoring of patients with pneumonia. However, limited data exist regarding its use to assess aeration changes during follow-up (FU). Our study aims to prospectively evaluate 232 subjects who underwent a 3-month-FU program after hospitalization for COVID-19 at the University Hospital of Pisa. The goals were to assess the usefulness of standardized LUS compared with the gold standard chest computed tomography (CT) to evaluate aeration changes and to verify LUS and CT agreement at FU. Patients underwent in the same day a standardized 16-areas LUS and high-resolution chest CT reported by expert radiologists, assigning interpretative codes. Based on observations distribution, LUS score cut-offs of 3 and 7 were selected, corresponding to the 50th and 75th percentile, respectively. Patients with LUS scores above both these thresholds were older and with longer hospital stay. Patients with a LUS score ≥3 had more comorbidities. LUS and chest CT showed a high agreement in identifying residual pathological findings, using both cut-off scores of 3 (OR 14,7; CL 3,6-64,5, Sensitivity 91%, Specificity 49%) and 7 (OR 5,8; CL 2,3-14,3, Sensitivity 65%, Specificity 79%). Our data suggest that LUS is very sensitive in identifying pathological findings at FU after a hospitalization for COVID-19 pneumonia, compared to CT. Given its low cost and safety, LUS could replace CT in selected cases, such as in contexts with limited resources or it could be used as a gate-keeper examination before more advanced techniques.

Effect of lung ultrasound-guided fluid deresuscitation on duration of ventilation in intensive care unit patients (CONFIDENCE): protocol for a multicentre randomised controlled trial

BACKGROUND

Fluid therapy is a common intervention in critically ill patients. It is increasingly recognised that deresuscitation is an essential part of fluid therapy and delayed deresuscitation is associated with longer invasive ventilation and length of intensive care unit (ICU) stay. However, optimal timing and rate of deresuscitation remain unclear. Lung ultrasound (LUS) may be used to identify fluid overload. We hypothesise that daily LUS-guided deresuscitation is superior to deresuscitation without LUS in critically ill patients expected to undergo invasive ventilation for more than 24 h in terms of ventilator free-days and being alive at day 28.

METHODS

The "effect of lung ultrasound-guided fluid deresuscitation on duration of ventilation in intensive care unit patients" (CONFIDENCE) is a national, multicentre, open-label, randomised controlled trial (RCT) in adult critically ill patients that are expected to be invasively ventilated for at least 24 h. Patients with conditions that preclude a negative fluid balance or LUS examination are excluded. CONFIDENCE will operate in 10 ICUs in the Netherlands and enrol 1000 patients. After hemodynamic stabilisation, patients assigned to the intervention will receive daily LUS with fluid balance recommendations. Subjects in the control arm are deresuscitated at the physician's discretion without the use of LUS. The primary endpoint is the number of ventilator-free days and being alive at day 28. Secondary endpoints include the duration of invasive ventilation; 28-day mortality; 90-day mortality; ICU, in hospital and total length of stay; cumulative fluid balance on days 1-7 after randomisation and on days 1-7 after start of LUS examination; mean serum lactate on days 1-7; the incidence of reintubations, chest drain placement, atrial fibrillation, kidney injury (KDIGO stadium ≥ 2) and hypernatremia; the use of invasive hemodynamic monitoring, and chest-X-ray; and quality of life at day 28.

DISCUSSION

The CONFIDENCE trial is the first RCT comparing the effect of LUS-guided deresuscitation to routine care in invasively ventilated ICU patients. If proven effective, LUS-guided deresuscitation could improve outcomes in some of the most vulnerable and resource-intensive patients in a manner that is non-invasive, easy to perform, and well-implementable.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05188092. Registered since January 12, 2022.

Education in Focused Lung Ultrasound Using Gamified Immersive Virtual Reality: A Randomized Controlled Study

Focused lung ultrasound (FLUS) has high diagnostic accuracy in many common conditions seen in a variety of emergency settings. Competencies are essential for diagnostic success and patient safety but can be challenging to acquire in clinical environments. Immersive virtual reality (IVR) offers an interactive risk-free learning environment and is progressing as an educational tool. First, this study explored the educational impact of novice FLUS users participating in a gamified or non-gamified IVR training module in FLUS by comparing test scores using a test with proven validity evidence. Second, the learning effect was assessed by comparing scores of each group with known test scores of novices, intermediates and experienced users in FLUS. A total of 48 participants were included: 24 received gamified and 24 received non-gamified IVR training. No significant difference was found between gamified (mean = 15.5 points) and non-gamified (mean = 15.2 points), indicating that chosen gamification elements for our setup did not affect learning outcome (p = 0.66). The mean scores of both groups did not significantly differ from those of known intermediate users in FLUS (gamified p = 0.63, non-gamified p = 0.24), indicating that both IVR modules could be used as unsupervised out-of-hospital training for novice trainees in FLUS.

Point-of-Care Ultrasound: A Moving Picture Is Worth a Thousand Tests

The effective utilization of point-of-care ultrasound may decrease the utilization of conventional diagnostic modalities. This review describes the various pathologies that can be effectively and rapidly identified with point-of-care cardiac, lung, abdominal, vascular airway, and ocular ultrasonography.