Lung ultrasound is associated with distinct clinical phenotypes in COVID-19 ARDS: A retrospective observational study.

BACKGROUND: ARDS is a heterogeneous syndrome with distinct clinical phenotypes. Here we investigate whether the presence or absence of large pulmonary ultrasonographic consolidations can categorize COVID-19 ARDS patients requiring mechanical ventilation into distinct clinical phenotypes. METHODS: This is a retrospective study performed in a tertiary-level intensive care unit in Israel between April and September 2020. Data collected included lung ultrasound (LUS) findings, respiratory parameters, and treatment interventions. The primary outcome was a composite of three ARDS interventions: prone positioning, high PEEP, or a high dose of inhaled nitric oxide. RESULTS: A total of 128 LUS scans were conducted among 23 patients. The mean age was 65 and about two-thirds were males. 81 scans identified large consolidation and were classified as "C-type", and 47 scans showed multiple B-lines with no or small consolidation and were classified as "B-type". The presence of a "C-type" study had 2.5 times increased chance of receiving the composite primary outcome of advanced ARDS interventions despite similar SOFA scores, Pao2/FiO2 ratio, and markers of disease severity (OR = 2.49, %95CI 1.40-4.44). CONCLUSION: The presence of a "C-type" profile with LUS consolidation potentially represents a distinct COVID-19 ARDS subphenotype that is more likely to require aggressive ARDS interventions. Further studies are required to validate this phenotype in a larger cohort and determine causality, diagnostic, and treatment responses.

Self-learning of cardiac ultrasound by medical students: can augmented online training improve and maintain manual POCUS skills over time?

BACKGROUND: The use of cardiac point of care ultra-sound is rapidly growing and so is the demand for quality POCUS teaching. POCUS teaching is usually conducted in small groups requiring much space and equipment. This study attempts to test whether providing access to an E-learning module as an adjunct to a cardiac POCUS course can increase students' image acquisition skills. This will show POCUS teaching can improve significantly without having to invest a significant amount of resources. METHODS: Medical students (N = 125) were divided into two groups and had undergone a hands-on Cardiac POCUS course before their internal clerkship. During the clerkship, members of both groups got to practice their POCUS skills in the internal wards. One group was provided with accounts to a cardiac POCUS teaching E-learning platform (eMedical Academy©). After limited time for self- practice, both groups underwent a pre-validated ultrasound examination. The two groups' test results were then compared for each POCUS view and for the total exam score. RESULTS: The E-learning group performed significantly better than the course-only group in the 6-min exam total score, and at acquiring the following views: parasternal long axis view, apical four-chamber view, and the inferior vena cava view. CONCLUSION: E-learning platforms can be an efficient tool for improving cardiac POCUS teaching and maintaining POCUS skills. Using it as a supplement to a hands-on course provides better POCUS skills without the need of extra hands-on teaching.

A Comparison of Online Self-Training and Standard Bedside Training in Lung Ultrasonography for Medical Students.

PURPOSE: Point-of-care ultrasonography (POCUS) is increasingly integrated into medical education. Traditionally taught at the bedside using a hands-on approach, POCUS is limited by cost, time, faculty availability, and access to POCUS resources. With the recent transition to digitalization in medical education, the authors compare lung POCUS performance and pathology identification among medical students to examine whether using an online, self-learning lung POCUS module is noninferior to traditional bedside, faculty-led lung POCUS training. METHOD: This study assessed the performance of 51 medical students from August to October 2021 on an elearning lung POCUS course with traditional bedside training and no training. POCUS students were scored on use of a simulator to identify pathologies, ability to identify lung ultrasonographic pathological clips, and scanning technique. RESULTS: The elearning group had a significantly higher median (interquartile range [IQR]) total test score (15/18 [10.5-16] vs. 12/18 [9-13]; P = .03) and scanning technique score (5/5 [4-5] vs. 4/5 [3-4]; P = .03) compared with the standard curriculum group. The median (IQR) accuracy in the clip segment of the examination was 7.5 of 10 (4-9) in the self-learning group and 6 of 10 (4-7) in the standard curriculum group ( P = .18). The median (IQR) grade on the simulator segment of the examination was 2 of 3 (2-3) in the self-learning group and 2 of 3 (1-2) in the standard curriculum group ( P = .06). CONCLUSIONS: This study suggests that self-directed elearning of lung POCUS is at least noninferior to bedside teaching and possibly even a superior method of learning lung POCUS. This teaching method POCUS is feasible for medical students to learn lung ultrasonography and has potential to complement or augment the traditional learning process or eliminate or lessen the requirement for bedside teaching by reaching a larger audience while minimizing costs and human resources.

Severity of a Vipera palaestinae envenomation objective findings associated with a complicated hospitalization course following a Vipera palaestinae bite.

The most common snake in Israel, responsible for most snakebites is Vipera palaestinae (VP). Envenomation signs and symptoms vary from local manifestations to systemic reactions that may end with death. Antivenom treatment, given to high-risk patients, reduces complications and mortality but carries risks. As of now, there is no standardized protocol for adults bitten by VP based on objective clinical and laboratory findings. We conducted A retrospective analysis of 159 patients admitted to two large tertiary care institutions in the center (Hadassah University Medical Center) and south (Soroka University Medical Center) of Israel with Vipera palaestinae bites during 1990-2017. Epidemiological and clinical data were extracted, and the patients were divided into two groups based on hospitalization time (over or under 48 h). 159 patients were included in this study. The average hospitalization time was 66.1 h, with 49.7% of patients admitted over 48 h. The main factors that statistically correlated with a longer hospitalization time were: Male gender, lower extremity bite, platelets lower than 150 K at presentation, leukocyte count of over 10 K at presentation and elevated D-Dimer levels. This study provides factors which are associated with a severe VP envenomation. These clinical or laboratory findings (along with accompanying clinical symptoms) are associated with a higher risk of a prolonged hospitalization with more complications and may require a more intensive treatment and monitoring.

Artificial Intelligence (AI) versus POCUS Expert: A Validation Study of Three Automatic AI-Based, Real-Time, Hemodynamic Echocardiographic Assessment Tools.

BACKGROUND: Point Of Care Ultra-Sound (POCUS) is an operator dependent modality. POCUS examinations usually include 'Eyeballing' the inspected anatomical structure without conducting accurate measurements due to complexity and insufficient time. Automatic real time measuring tools can make accurate measurements fast and simple and dramatically increase examination reliability while saving the operator much time and effort. In this study we aim to assess three automatic tools which are integrated into the Venue™ device by GE: the automatic ejection fraction, velocity time integral, and inferior vena cava tools in comparison to the gold standard-an examination by a POCUS expert. METHODS: A separate study was conducted for each of the three automatic tools. In each study, cardiac views were acquired by a POCUS expert. Relevant measurements were taken by both an auto tool and a POCUS expert who was blinded to the auto tool's measurement. The agreement between the POCUS expert and the auto tool was measured for both the measurements and the image quality using a Cohen's Kappa test. RESULTS: All three tools have shown good agreement with the POCUS expert for high quality views: auto LVEF (0.498; p < 0.001), auto IVC (0.536; p = 0.009), and the auto VTI (0.655; p = 0.024). Auto VTI has also shown a good agreement for medium quality clips (0.914; p < 0.001). Image quality agreement was significant for the auto EF and auto IVC tools. CONCLUSIONS: The Venue™ show a high agreement with a POCUS expert for high quality views. This shows that auto tools can provide reliable real time assistance in performing accurate measurements, but do not reduce the need of a good image acquisition technique.