International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 90-97 http://medscipublisher.com/index.php/ijccr 91 2 Rapid Assessment Tools in Nursing Care 2.1 Commonly used rapid assessment tools for CVA Rapid assessment tools are critical in the early identification and management of cerebrovascular accidents (CVA). Two of the most commonly used tools in prehospital settings are the Cincinnati Prehospital Stroke Scale (CPSS) and the Los Angeles Prehospital Stroke Screen (LAPSS). These tools are designed to quickly assess the likelihood of a stroke based on specific clinical criteria, enabling prompt and appropriate emergency care (Roh and Kim, 2012). The CPSS focuses on facial droop, arm drift, and speech abnormalities, while the LAPSS includes additional criteria such as age, history of seizures, and blood glucose levels to improve diagnostic accuracy. 2.2 Criteria for effective rapid assessment tools Effective rapid assessment tools for CVA must meet several criteria to ensure they are both practical and reliable in clinical settings. Firstly, they should have high sensitivity and specificity to accurately identify stroke patients and minimize false positives. Secondly, the tools should be easy to use and require minimal training, allowing for quick application by healthcare providers in emergency situations. Thirdly, they should be validated through extensive clinical trials and real-world use to ensure their effectiveness across diverse patient populations (Moon et al., 2016). Additionally, these tools should integrate seamlessly with existing clinical workflows and electronic medical records to facilitate timely decision-making and treatment. 2.3 Recent developments in rapid assessment tools Recent advancements in rapid assessment tools for CVA have focused on incorporating technology and artificial intelligence (AI) to enhance diagnostic accuracy and efficiency. For instance, AI-powered software such as RAPID™ has been developed to analyze CT perfusion data and assess cerebrovascular reserve (CVR) in patients with cranio-cervical arterial stenoses and occlusions (Alsrouji et al., 2023). This software automates the processing of imaging data, reducing the potential for human error and allowing for more precise identification of abnormal CVR. However, studies have shown that while AI tools like RAPID™ offer innovative solutions, they may still have limitations in sensitivity compared to traditional methods like Vitrea™. Continuous research and development are necessary to refine these tools and establish reliable thresholds that correlate better with clinical outcomes. 3 Impact of Rapid Assessment Tools on Patient Outcomes 3.1 Early detection and diagnosis Rapid assessment tools have significantly enhanced the early detection and diagnosis of acute cerebrovascular accidents (ACAs). For instance, the use of convolutional neural networks (CNNs) in stroke triage has shown high accuracy in segmenting cerebrovascular structures and detecting occlusions, which is crucial for early intervention (Figure 1) (Deshpande et al., 2023). The CNN model achieved a segmentation accuracy of 94%, with a sensitivity and specificity of 92% and 94%, respectively, for stroke detection. Similarly, computer-aided diagnosis (CAD) systems for traumatic brain injury (TBI) have been developed to facilitate early and accurate detection of intracranial hematomas and other complications, which are critical for timely management and improved outcomes (Vidhya et al., 2021). Near-infrared spectroscopy (NIRS) has also emerged as a promising tool for continuous bedside monitoring of cerebrovascular physiology, aiding in the early identification of new brain injuries and clinical deterioration (Thomas et al., 2023). 3.2 Improvement in treatment response time The implementation of rapid assessment tools has been instrumental in reducing the time to treatment for patients with ACAs. A systematic review of next-generation point-of-care stroke diagnostic technologies highlighted several novel devices, such as portable MRI and EEG-based diagnostics, which have shown promise in facilitating rapid stroke diagnosis and thereby shortening the time to treatment (Shahrestani et al., 2021). Additionally, systems-based physical assessments conducted by nurses have been shown to reduce delays in activating rapid response teams, thereby improving the timeliness of interventions. This initiative decreased the delay in rapid response team activation from 11.7 hours to 9.6 hours, significantly enhancing the response time to patient deterioration (Hamlin et al., 2023).
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