Retrospective analysis of eFAST ultrasounds performed on trauma activations at an academic level-1 trauma center

Implementation of an eFAST guideline and teaching to improve documentation practices and saving of ultrasound images

OBJECTIVES

To investigate whether implementation of a hospital-based Extended Focused Assessment with Sonography in Trauma (eFAST) guideline and teaching improved documentation and saving of images.

METHODS

A retrospective cohort study was conducted on trauma patients aged ≥16 years presenting to St Vincent's Hospital Sydney Emergency Department over two, three-month periods in 2023.

RESULTS

Guideline and teaching implementation resulted in statistically significant improvement in documentation on the Trauma Response Form, 85% (113/133) to 93% (120/129), odds ratio (OR) 2.4 (95% confidence interval [CI] = 1.03-5.40), P = 0.04, and images saved, 4% (5/133) to 21% (27/129), OR 6.7 (95% CI = 2.5-18.2), P < 0.001.

CONCLUSIONS

Developing an eFAST Standard of Care Guideline and education was associated with improvements in documentation and saving of images to ultrasound machines.

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults

Abdominal ultrasonography has become an integral component of the evaluation of trauma patients. Internal hemorrhage can be rapidly diagnosed by finding free fluid with point-of-care ultrasound (POCUS) and expedite decisions to perform lifesaving interventions. However, the widespread clinical application of ultrasound is limited by the expertise required for image interpretation. This study aimed to develop a deep learning algorithm to identify the presence and location of hemoperitoneum on POCUS to assist novice clinicians in accurate interpretation of the Focused Assessment with Sonography in Trauma (FAST) exam. We analyzed right upper quadrant (RUQ) FAST exams obtained from 94 adult patients (44 confirmed hemoperitoneum) using the YoloV3 object detection algorithm. Exams were partitioned via fivefold stratified sampling for training, validation, and hold-out testing. We assessed each exam image-by-image using YoloV3 and determined hemoperitoneum presence for the exam using the detection with highest confidence score. We determined the detection threshold as the score that maximizes the geometric mean of sensitivity and specificity over the validation set. The algorithm had 95% sensitivity, 94% specificity, 95% accuracy, and 97% AUC over the test set, significantly outperforming three recent methods. The algorithm also exhibited strength in localization, while the detected box sizes varied with a 56% IOU averaged over positive cases. Image processing demonstrated only 57-ms latency, which is adequate for real-time use at the bedside. These results suggest that a deep learning algorithm can rapidly and accurately identify the presence and location of free fluid in the RUQ of the FAST exam in adult patients with hemoperitoneum.

Quality assessment of point-of-care ultrasound reports for patients at the emergency department treated by internists

BACKGROUND

POCUS (point-of-care ultrasound) is an important diagnostic tool for several medical specialties. To provide safe patient care, the quality of this exam should be as high as possible. This includes solid documentation with a written report and the availability of images for review. However, international guidelines or publications about this quality assessment and its application in clinical practice are scarce.

METHODS

We designed a criteria-checklist to evaluate the quality of POCUS examinations. This checklist was made based on international guidelines and protocols and was validated by a Dutch expert group using the nominal group technique (NGT). All POCUS exams in general internal medicine patients documented between August 2019 and November 2020 in our ED were evaluated using this checklist.

RESULTS

A total of 169 exams were included. In general, the compliance for most important criteria was high, but not optimal. A clinical question or indication for the POCUS exam was stated in 75.7% of cases. The completeness of all standard views differed per indication, but was lower when more than one standard view was required. Labels were provided in 83.5% of the saved images, while 90.8% of all examinations showed a written conclusion.

CONCLUSIONS

Our research showed that the overall quality of documentation varies with regard to several important criteria. Suboptimal compliance of documentation may have adverse effects on patient safety. We have developed a checklist which can be used to improve POCUS documentation.

Point-of-Care Ultrasound in the Pediatric Intensive Care Unit

Ultrasonography has been widely used in medicine for decades but often by specific users such as cardiologists, obstetricians, and radiologists. In the last several years, the use of this imaging modality has moved to the bedside, with clinicians performing and interpreting focused point of care ultrasonography to aid in immediate assessment and management of their patients. The growth of point of care ultrasonography has been facilitated by advancement in ultrasound-related technology and emerging studies and protocols demonstrating its utility in clinical practice. However, considerable challenges remain before this modality can be adopted across the spectrum of disciplines, primarily as it relates to training, competency, and standardization of usage. This review outlines the history, current state, challenges and the future direction of point of care ultrasonography specifically in the field of pediatric critical care medicine.

eFAST exam errors at a level 1 trauma center: A retrospective cohort study

OBJECTIVES

Extended Focused Assessment with Sonography for Trauma (eFAST) ultrasound exams are central to the care of the unstable trauma patient. We examined six years of eFAST quality assurance data to identify the most common reasons for false positive and false negative eFAST exams.

METHODS

This was an observational, retrospective cohort study of trauma activation patients evaluated in an urban, academic Level 1 trauma center. All eFAST exams that were identified as false positive or false negative exams compared with computed tomography (CT) imaging were included.

RESULTS

4860 eFAST exams were performed on trauma patients. 1450 (29.8%) were undocumented, technically limited, or incomplete (missing images). Of the 3410 remaining exams, 180 (5.27%) were true positive and 3128 (91.7%) were true negative. 27 (0.79%) exams were identified as false positive and 75 (2.19%) were identified as false negative. Of the false positive scans, 7 had no CT scan and 8 had correct real-time trauma paper documentation of eFAST exam results when compared to CT and were excluded, leaving 12 false positive scans. Of the false negative scans, 11 were excluded for concordant documentation in real-time trauma room paper documentation, 20 were excluded for no CT scan, and 2 were excluded as incomplete, leaving 42 false negative scans. Pelvic fluid, double-line sign, pericardial fat pad, and the thoracic portion of the eFAST exam were the most common source of errors.

CONCLUSION

The eFAST exams in trauma activation patients are highly accurate. Unfortunately poor documentation and technically limited/incomplete studies represent 29.8% of our eFAST exams. Pelvic fluid, double-line sign, pericardial fat pad, and the thoracic portion of the eFAST exam are the most common source of errors.

Does shifting to professional emergency department staffing affect the decision for chest radiography?

BACKGROUND

The study aims to determine whether shifting to professional emergency department (ED) teams leads to a higher rate of radiologic workup.

METHODS

We retrospectively analyzed a total of 2,000 patients presenting to the ED of a tertiary teaching hospital in two time periods: group 1 (G1) comprised 1,000 consecutive patients enrolled from December 21, 2012 to January 5, 2013 (all patients were examined by an internal medicine specialist); group 2 (G2) comprised 1,000 consecutive patients enrolled from December 21, 2018 to January 3, 2019 (all patients were examined by an emergency physician).

RESULTS

The chest X-ray (CXR) was performed in 40.6% of all patients. There was no difference in the frequency of CXR (38.9% in G1 vs. 42.3% in G2, P=0.152). More CXRs were performed in G2 patients older than 65 years, in female patients older than 65 years, in patients presenting during the evening and night shifts or off-hours, in patients with a history of malignancy, in patients with gastrointestinal bleeding, and in patients with bradycardia, but fewer in patients presenting with arrhythmia. No difference in the rates of pathological CXR was found (47.3% in G1 vs. 52.2% in G2, P=0.186). Compared with G2, higher sensitivity and specificity were obtained for the binary logistic regression model predicting pathological findings in G1.

CONCLUSIONS

Shifting to professional ED teams does not increase radiologic workup. By implementing deliberate usage of ultrasound, some self-governing procedures, case-oriented investigations, and center-specific recommendations, unnecessary radiologic workup can be avoided. Professional ED teams could lead to a higher standard of emergency care.

Risk factors and predictive model of adrenocortical insufficiency in patients with traumatic brain injury

BACKGROUND

Neuroendocrine dysfunction after traumatic brain injury (TBI) has received increased attention due to its impact on the recovery of neural function. The purpose of this study is to investigate the incidence and risk factors of adrenocortical insufficiency (AI) after TBI to reveal independent predictors and build a prediction model of AI after TBI.

METHODS

Enrolled patients were grouped into the AI and non-AI groups. Fourteen preset impact factors were recorded. Patients were regrouped according to each impact factor as a categorical variable. Univariate and multiple logistic regression analyses were performed to screen the related independent risk factors of AI after TBI and develop the predictive model.

RESULTS

A total of 108 patients were recruited, of whom 34 (31.5%) patients had AI. Nine factors (age, Glasgow Coma Scale [GCS] score on admission, mean arterial pressure [MAP], urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, diffuse axonal injury [DAI], and skull base fracture) were probably related to AI after TBI. Three factors (urinary volume [X ₄], serum sodium level [X ₅], and DAI [X ₈]) were independent variables, based on which a prediction model was developed (logit P= -3.552+2.583X ₄+2.235X ₅+2.269X ₈).

CONCLUSIONS

The incidence of AI after TBI is high. Factors such as age, GCS score, MAP, urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, DAI, and skull base fracture are probably related to AI after TBI. Urinary volume, serum sodium level, and DAI are the independent predictors of AI after TBI.