Factors Associated With Emergency Department Length of Stay and In-hospital Mortality in Intracerebral Hemorrhage Patients

Artificial Intelligence in Emergency Radiology: Where Are We Going?

Emergency Radiology is a unique branch of imaging, as rapidity in the diagnosis and management of different pathologies is essential to saving patients' lives. Artificial Intelligence (AI) has many potential applications in emergency radiology: firstly, image acquisition can be facilitated by reducing acquisition times through automatic positioning and minimizing artifacts with AI-based reconstruction systems to optimize image quality, even in critical patients; secondly, it enables an efficient workflow (AI algorithms integrated with RIS-PACS workflow), by analyzing the characteristics and images of patients, detecting high-priority examinations and patients with emergent critical findings. Different machine and deep learning algorithms have been trained for the automated detection of different types of emergency disorders (e.g., intracranial hemorrhage, bone fractures, pneumonia), to help radiologists to detect relevant findings. AI-based smart reporting, summarizing patients' clinical data, and analyzing the grading of the imaging abnormalities, can provide an objective indicator of the disease's severity, resulting in quick and optimized treatment planning. In this review, we provide an overview of the different AI tools available in emergency radiology, to keep radiologists up to date on the current technological evolution in this field.

Observation on the Effect of Solution-Focused Approach Combined with Family Involvement in WeChat Platform Management on Inpatients with Intracerebral Hemorrhage

Objective. To explore the effect of the solution-focused approach combined with family involvement in the WeChat platform management on inpatients with intracerebral hemorrhage (ICH). Methods. A total of 80 ICH patients hospitalized in our hospital from June 2018 to June 2021 were split into the control group (CG) and the study group (SG) according to the clinical nursing modes, with 40 cases in each group. Both groups received routine intervention, while SG additionally received the solution-focused approach combined with family involvement in the WeChat platform management to compare the self-care ability, psychological status, and hope levels between the two groups after intervention. Results. No significant differences in general data were observed between the two groups ( $P>0.05$ ). The SAS and SDS scores before intervention showed mild depression and anxiety in both groups, which improved after intervention. In addition, the SAS and SDS scores after intervention were remarkably lower in SG than in CG ( $P<0.05$ ). After intervention, the scores of ICH-related knowledge, self-care skills, self-care responsibility, and rehabilitation knowledge in SG were notably higher compared with CG ( $P<0.05$ ). After intervention, the Herth scores of both groups increased, with a higher score in SG than in CG ( $P<0.05$ ). After intervention, SG had higher quality of life (QOL) scores in general health, physiological function, physiological role, body pain, vitality, social function, emotional role, and physiological health than CG ( $P<0.05$ ). Conclusion. The implementation of the solution-focused approach combined with family involvement in the WeChat platform management for ICH inpatients can effectively improve their psychological status, enhance their self-care ability and hope levels, promote body recovery, and improve their QOL after intervention.