Unravelling the skillset of point-of-care ultrasound: a systematic review

BACKGROUND

The increasing number of physicians that are trained in point-of-care ultrasound (POCUS) warrants critical evaluation and improvement of current training methods. Performing POCUS is a complex task and it is unknown which (neuro)cognitive mechanisms are most important in competence development of this skill. This systematic review was conducted to identify determinants of POCUS competence development that can be used to optimize POCUS training.

METHODS

PubMed, Web of Science, Cochrane Library, Emcare, PsycINFO and ERIC databases were searched for studies measuring ultrasound (US) skills and aptitude. The papers were divided into three categories: "Relevant knowledge", "Psychomotor ability" and 'Visuospatial ability'. The 'Relevant knowledge' category was further subdivided in 'image interpretation', 'technical aspects' and 'general cognitive abilities'. Visuospatial ability was subdivided in visuospatial subcategories based on the Cattell-Horn-Carroll (CHC) Model of Intelligence v2.2, which includes visuospatial manipulation and visuospatial perception. Post-hoc, a meta-analysis was performed to calculate pooled correlations.

RESULTS

26 papers were selected for inclusion in the review. 15 reported on relevant knowledge with a pooled coefficient of determination of 0.26. Four papers reported on psychomotor abilities, one reported a significant relationship with POCUS competence. 13 papers reported on visuospatial abilities, the pooled coefficient of determination was 0.16.

CONCLUSION

There was a lot of heterogeneity in methods to assess possible determinants of POCUS competence and POCUS competence acquisition. This makes it difficult to draw strong conclusions on which determinants should be part of a framework to improve POCUS education. However, we identified two determinants of POCUS competence development: relevant knowledge and visuospatial ability. The content of relevant knowledge could not be retrieved in more depth. For visuospatial ability we used the CHC model as theoretical framework to analyze this skill. We could not point out psychomotor ability as a determinant of POCUS competence.

Machine learning algorithm using publicly available echo database for simplified “visual estimation” of left ventricular ejection fraction

BACKGROUND

Left ventricular ejection fraction calculation automation typically requires complex algorithms and is dependent of optimal visualization and tracing of endocardial borders. This significantly limits usability in bedside clinical applications, where ultrasound automation is needed most.

AIM

To create a simple deep learning (DL) regression-type algorithm to visually estimate left ventricular (LV) ejection fraction (EF) from a public database of actual patient echo examinations and compare results to echocardiography laboratory EF calculations.

METHODS

A simple DL architecture previously proven to perform well on ultrasound image analysis, VGG16, was utilized as a base architecture running within a long short term memory algorithm for sequential image (video) analysis. After obtaining permission to use the Stanford EchoNet-Dynamic database, researchers randomly removed approximately 15% of the approximately 10036 echo apical 4-chamber videos for later performance testing. All database echo examinations were read as part of comprehensive echocardiography study performance and were coupled with EF, end systolic and diastolic volumes, key frames and coordinates for LV endocardial tracing in csv file. To better reflect point-of-care ultrasound (POCUS) clinical settings and time pressure, the algorithm was trained on echo video correlated with calculated ejection fraction without incorporating additional volume, measurement and coordinate data. Seventy percent of the original data was used for algorithm training and 15% for validation during training. The previously randomly separated 15% (1263 echo videos) was used for algorithm performance testing after training completion. Given the inherent variability of echo EF measurement and field standards for evaluating algorithm accuracy, mean absolute error (MAE) and root mean square error (RMSE) calculations were made on algorithm EF results compared to Echo Lab calculated EF. Bland-Atlman calculation was also performed. MAE for skilled echocardiographers has been established to range from 4% to 5%.

RESULTS

The DL algorithm visually estimated EF had a MAE of 8.08% (95%CI 7.60 to 8.55) suggesting good performance compared to highly skill humans. The RMSE was 11.98 and correlation of 0.348.

CONCLUSION

This experimental simplified DL algorithm showed promise and proved reasonably accurate at visually estimating LV EF from short real time echo video clips. Less burdensome than complex DL approaches used for EF calculation, such an approach may be more optimal for POCUS settings once improved upon by future research and development.

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.

Fasting does not guarantee empty stomach in the intensive care unit: A prospective ultrasonographic evaluation (The NUTRIGUS study)

BACKGROUND

In the intensive care unit (ICU), a fasting period is usually respected to avoid gastric aspiration during airway management procedures. Since there are no recognised guidelines, intensive care physicians balance the aspiration risk with the negative consequences of underfeeding. Our objective was to determine the impact of fasting on gastric emptying in critically ill patients by using gastric ultrasound.

MATERIAL AND METHODS

Among the 112 patients that met the inclusion criteria, 100 patients were analysed. Gastric ultrasonography was performed immediately before extubation. Patients with either 1/ an absence of visualised gastric content (qualitative evaluation) or 2/ a gastric volume < 1.5 mll/kg in case of clear fluid gastric content (quantitative evaluation) were classified as having an empty stomach.

MAIN FINDINGS

In our study, twenty-six (26%) patients had a full stomach at the time of extubation. The incidence of full stomach was not significantly different between patients who fasted < 6 h or patients who fasted ≥ 6 h. Among the 57 patients receiving enteral nutrition (EN) within the last 48 h, there was no correlation between the duration of EN interruption and the GAA. The absence of EN was not associated with an empty stomach.

CONCLUSION

At the time of extubation, the incidence of full stomach was high and not associated with the fasting characteristics (duration/absence of EN). Our results support the notions that fasting before airway management procedures is not a universal paradigm and that gastric ultrasound might represent a useful tool in the tailoring process. CLINICALTRIALS.GOV: NCT04245878.

The Pediatric Difficult Airway: Updates and Innovations

Children have unique characteristics that make them particularly vulnerable to perioperative adverse events. Skilled airway management is a cornerstone of high-quality anesthetic management. The use of hybrid airway techniques is a critical tool for the pediatric anesthesiologist. Point-of-care ultrasonography has an expanding role in airway management, from preoperative assessment of airway pathology and gastric contents to confirmation of tracheal intubation and identification of the cricothyroid membrane. The exciting fields of 3-dimensional printing, artificial intelligence, and machine learning are areas of innovation that will transform pediatric difficult airway management in years to come.

Internal medicine residents' point-of-care ultrasound skills and need assessment and the role of medical school training

Introduction: Point-of-care-ultrasound (POCUS) as a useful bedside tool is growing. Few studies have examined residents' attitude towards POCUS or compared POCUS image interpretation skills between residents with and without POCUS training in medical school. Material and Methods: We distributed an anonymous survey and image interpretation test to assess residents' attitude towards POCUS, confidence, and skills in interpreting POCUS images and videos. Using independent samples t-tests, we compared mean confidence levels and test scores between residents with and without prior POCUS training. Results: Fifty-two residents responded to survey (response rate 68%) and 59 took the image interpretation test (77%). Most residents (90%) reported being interested in POCUS. Residents with prior POCUS training (n=13) were either PGY-1 (9) or PGY-2 (4). No PGY-3 resident had prior training. Most residents (83%) thought POCUS could be extremely useful in the inpatient setting compared to 29% for outpatient setting. PGY-1 residents with prior training had a higher mean confidence level than PGY-1 residents without prior training, but the difference was not statistically significant (3.26 vs 2.64; p=0.08). PGY-1 with prior training had a mean confidence level that was close to that of PGY-3 residents. PGY-1 residents with prior training scored significantly higher than PGY-1 residents without prior training in image interpretation test (10.25 vs 7; p=0.01). Residents felt most confident in interpreting inferior vena cava images (mean 3.7; max. 5), which also had the highest score in image interpretation test (correct response rate of 88%). Conclusion: Our residents seem very interested in POCUS. PGY-1 residents with prior POCUS training in medical school seem to have higher confidence in their POCUS skills than PGY-1 residents without prior training and outperformed them in image interpretation test. The study is very instructive in building our future POCUS curriculum for residents.

Transcranial Doppler ultrasound in neurocritical care

Multimodality monitoring is a common practice in caring for neurocritically ill patients, and consists mainly in clinical assessment, intracranial pressure monitoring and using several imaging methods. Of these imaging methods, transcranial Doppler (TCD) is an interesting tool that provides a non-invasive, portable and radiation-free way to assess cerebral circulation and diagnose and follow-up (duplex method) intracranial mass-occupying lesions, such as hematomas and midline shift. This article reviews the basics of TCD applied to neurocritical care patients, offering a rationale for its use as well as tips for practitioners.

Typhoid intestinal perforation: Point-of-care ultrasound as a diagnostic tool in a rural Ugandan Hospital

Introduction

Point-of-care ultrasound (POCUS) in resource-limited areas has demonstrated utility in the hands of physicians and may be useful for non-physician providers to learn as well.

Case Report

An 11 year old male presented with abdominal pain and diffuse abdominal tenderness to a remote Emergency Centre (EC). An Emergency Care Practitioner, a non-physician emergency care provider with limited ultrasound training, used bedside ultrasonography and alerted the on-call surgeon of complex intraperitoneal fluid representing perforated typhoid, which expedited the patient’s care.

Discussion

There is scant literature involving cases of non-physician use of POCUS, particularly in the emergency care setting. This case demonstrates the potential benefits of training these providers in POCUS.