Emergent Comprehensive Imaging of the Major Trauma Patient: A New Paradigm for Improved Clinical Decision-Making

On the edge of decision-making in trauma care: A focus group study on radiographers' experiences of interprofessional collaboration

INTRODUCTION

The temporary trauma teams in trauma alerts consist of a diverse group of unique professionals requiring interprofessional collaboration and coordination to achieve efficient, high-quality care. The uncertain situation and complex care environment impose high demands on team dynamics such as individual attitudes and team behaviours. Within interprofessional teams, interaction and coordination reflect the collective success of collaboration and the achievement of goals. Interactions with radiographers have increased in trauma teams given computed tomography's prominent role in providing crucial knowledge for decision-making in trauma care. This study aimed to explore radiographers' experiences of interprofessional collaboration during trauma alerts.

METHOD

The study was designed with focus group methodology, including 17 radiographers participating in five focus groups, analysed with an inductive focus group analysis.

RESULTS

An overarching theme, "On the edge of decision-making", emerged along with three sub-themes: "Feeling included requires acknowledgement", "Exclusion precludes shared knowledge", and "Experience and mutual awareness facilitate team interaction".

CONCLUSIONS

Interprofessional collaboration from the radiographer's perspective within trauma teams requires a sense of inclusion and the ability to interact with the team. Exclusion from vital decision-making obstructs radiographers' comprehension of situations and thereby the interdependence in interprofessional collaboration.

IMPLICATIONS FOR PRACTICE

Common platforms are needed for knowledge sharing and team practices, including radiographers' areas of responsibility and relational coordination to foster interprofessional relationships. Through these means interdependence through awareness and shared knowledge can be facilitated on trauma teams.

CT-based diagnostic algorithm to identify bowel and/or mesenteric injury in patients with blunt abdominal trauma

OBJECTIVES

To develop a CT-based algorithm and evaluate its performance for the diagnosis of blunt bowel and/or mesenteric injury (BBMI) in patients with blunt abdominal trauma.

METHODS

This retrospective study included a training cohort of 79 patients (29 with BBMI and 50 patients with blunt abdominal trauma without BBMI) and a validation cohort of 37 patients (13 patients with BBMI and 24 patients with blunt abdominal trauma without BBMI). CT examinations were blindly analyzed by two independent radiologists. For each CT sign, the kappa value, sensitivity, specificity, and accuracy were calculated. A diagnostic algorithm was built using a recursive partitioning model on the training cohort, and its performances were assessed on the validation cohort.

RESULTS

CT signs with kappa value > 0.6 were extraluminal gas, hemoperitoneum, no or moderate bowel wall enhancement, and solid organ injury. CT signs yielding best accuracies in the training cohort were extraluminal gas (98%; 95% CI: 91-100), bowel wall defect (97%; 95% CI: 91-100), irregularity of mesenteric vessels (97%; 95% CI: 90-99), and mesenteric vessel extravasation (97%; 95% CI: 90-99). Using a recursive partitioning model, a decision tree algorithm including extraluminal gas and no/moderate bowel wall enhancement was built, achieving 86% sensitivity (95% CI: 74-99) and 96% specificity (95% CI: 91-100) in the training cohort and 92% sensitivity (95% CI: 78-97) and 88% specificity (95% CI: 74-100) in the validation cohort for the diagnosis of BBMI.

CONCLUSIONS

An effective diagnostic algorithm was built to identify BBMI in patients with blunt abdominal trauma using only extraluminal gas and no/moderate bowel wall enhancement on CT examination.

KEY POINTS

• A CT diagnostic algorithm that included extraluminal gas and no/moderate bowel wall enhancement was built for the diagnosis of surgical blunt bowel and/or mesenteric injury. • A decision tree combining only two reproducible CT signs has high diagnostic performance for the diagnosis of surgical blunt bowel and/or mesenteric injury.

Toward Building Surge Capacity: Potentially Effective Spatial Configurations in Emergency Departments

BACKGROUND

Emergency departments (EDs) have been struggling with overcrowding issues for years. Some spatial configurations have been proposed to improve ED performance in facing overcrowding. Despite similarities with mass casualty incidents (MCIs), when demand for care exceeds the capacity, little is documented about the application of the proposed configurations during MCIs to improve surge capacity.

OBJECTIVES

We aimed to explore the potential of spatial configurations that have been proposed to handle ED overcrowding in daily operations so as to improve surge capacity during MCIs.

METHODS

Using an online Likert-scale survey, 11 spatial design strategies were rated by ED care teams in terms of their potential to improve surge capacity during MCIs.

RESULTS

Responses from 72 participants revealed that establishing an in-house lab was perceived as the most potential strategy, followed by rapid care area, internal waiting rooms, and in-house imaging. In contrast, separate entrance and exit doors, as well as decentralized nurse stations, were perceived as the least potential strategies but also exhibited the most variance in response. Respondents' comments implied that their choice of in-house ancillary services was primarily to improve communication and to reduce turnaround time and risk of errors. Their choice of rapid care and internal waiting areas related to improved flexibility.

CONCLUSIONS

Understanding clinicians' perspectives on potentially effective spatial configurations aids in implementing balanced strategies to better equip EDs to handle overcrowding in daily operations and manage surges during MCIs.

Comparison of detection of trauma-related injuries using combined "all-in-one" fused images and conventionally reconstructed images in acute trauma CT

OBJECTIVES

To compare the accuracy of lesion detection of trauma-related injuries using combined "all-in-one" fused (AIO) and conventionally reconstructed images (CR) in acute trauma CT.

METHODS

In this retrospective study, trauma CT of 66 patients (median age 47 years, range 18-96 years; 20 female (30.3%)) were read using AIO and CR. Images were independently reviewed by 4 blinded radiologists (two residents and two consultants) for trauma-related injuries in 22 regions. Sub-analyses were performed to analyze the influence of experience (residents vs. consultants) and body region (chest, abdomen, skeletal structures) on lesion detection. Paired t-test was used to compare the accuracy of lesion detection. The effect size was calculated (Cohen's d). Linear mixed-effects model with patients as the fixed effect and random forest models were used to investigate the effect of experience, reconstruction/image processing, and body region on lesion detection.

RESULTS

Reading time of residents was significantly faster using AIO (AIO: 266 ± 72 s, CR: 318 ± 113 s; p < 0.001; d = 0.46) while no significant difference was observed in the accuracy of lesion detection (AIO: 93.5 ± 6.0%, CR: 94.6 ± 6.0% p = 0.092; d =  - 0.21). Reading time of consultants showed no significant difference (AIO: 283 ± 82 s, CR: 274 ± 95 s; p = 0.067; d = 0.16). Accuracy was significantly higher using CR; however, the difference and effect size were very small (AIO 95.1 ± 4.9%, CR: 97.3 ± 3.7%, p = 0.002; d =  - 0.39). The linear mixed-effects model showed only minor effect of image processing/reconstruction for lesion detection.

CONCLUSIONS

Residents at the emergency department might benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT.

KEY POINTS

• Image fusion techniques decrease the reading time of acute trauma CT without sacrificing diagnostic accuracy.

Volumetric Markers of Body Composition May Improve Personalized Prediction of Major Arterial Bleeding After Pelvic Fracture: A Secondary Analysis of the Baltimore CT Prediction Model Cohort

METHODS

This work is a retrospective secondary analysis of a single institution cohort used in the development of the Baltimore CT prediction model. The cohort includes 115 consecutive patients that underwent admission contrast-enhanced CT of the abdomen and pelvis for blunt trauma with pelvic ring disruption followed by conventional angiography. Major arterial injury requiring angioembolization served as the outcome variable. Angioembolization was required in 73/115 patients (63% of the cohort). Average age was 46.9 years (±SD 20.4). Body composition measurements were determined as 2-dimensional (2D) or 3-dimensional (3D) parameters and included mid-L3 trabecular bone attenuation, abdominal visceral fat area or volume, and percent muscle fat fraction (as a marker of sarcopenia) measured using segmentation and histogram analysis.

RESULTS

Models incorporating 2D (Model B) or 3D markers (model C) of body composition showed improvement over the original Baltimore model (model A) in all parameters of performance, quality, and fit (area under the receiver-operating curve [AUC], Akaike information criterion, Brier score, Hosmer-Lemeshow test, and adjusted-R2). Area under the receiver-operating curve increased from 0.83 (A), to 0.86 (B), and 0.88 (C). The greatest improvement was seen with 3D parameters.

CONCLUSION

Once automated, quantitative visualization tools providing "free" 3D body composition information can be expected to improve personalized precision diagnostics, outcome prediction, and decision support in patients with bleeding pelvic fractures.