International Journal of Clinical Case Reports, 2025, Vol.15, No.6, 259-270 http://medscipublisher.com/index.php/ijccr 267 by using proteomics technology. These new markers can help doctors determine the recovery status of the nervous system of patients within 24 hours after resuscitation. This research direction has received support from national projects, which reflects the country's emphasis on promoting precise care after cardiopulmonary resuscitation. Nursing research is also in development, with a focus on the clinical transformation of biomarker monitoring and the construction of comprehensive nursing approaches. Although high-level nursing and advanced monitoring techniques have not yet been fully popularized, some trauma centers and neurointensive care units have gradually adopted evidence-based guidelines and multidisciplinary collaboration. The huge patient base and scientific research platform provide favorable conditions for China's future clinical trials led by molecular markers and individualized care strategies. 7.3 Differences and implications between China and foreign countries Although the research goals are the same, there are still significant differences between China and foreign countries in the application of biomarkers and related nursing practices. Internationally, relying on standardized processes, advanced laboratories and new detection platforms, risk stratification can be rapidly completed and precise prognosis can be achieved (Moseby-Knappe et al., 2021; Hoiland et al., 2022; Moseby-Knappe et al., 2022). In contrast, in China, due to factors such as regional resource differences, insufficient accessibility of biomarker detection, and non-uniform monitoring processes, there is still a need to enhance the standardization and repeatability of postoperative care for cardiopulmonary resuscitation. Therefore, continuous investment in scientific research and infrastructure construction, as well as strengthening international collaboration, are of vital importance for promoting biomarker research and clinical transformation in China. In the future, detection technologies that are cost-controllable and easy to implement should be promoted in line with national conditions, and international best practices should be localized. Meanwhile, China's vast case data and research potential can also provide unique experience for global research on brain injury markers, promoting international cooperation and knowledge sharing in postoperative care after cardiopulmonary resuscitation. 8 Concluding Remarks Although some progress has been made, the wide clinical application of biomarkers in brain injury after cardiac arrest still faces many obstacles. Many studies have problems such as a small number of patients, significant differences in individual conditions, and inconsistent detection and interpretation processes, which make it very difficult to establish judgment criteria and make comparisons among different studies. In addition, commonly used markers such as neuron-specific enolase (NSE) and S100B are highly susceptible to various extracellular factors. However, new markers such as filament light chain (NfL) and glial fibrin acidic protein (GFAP) still require more research for verification and have not yet been widely adopted in ordinary laboratories. These issues indicate that we need to conduct larger-scale multi-center studies, adopt a unified approach to enhance the credibility of predictions, and better provide references for clinical treatment. Molecular monitoring has a promising application prospect in the care after cardiopulmonary resuscitation. Novel biomarkers such as calcitonin-2, angiotensinogen, and microRNA have the potential to determine the neurological recovery situation earlier and more accurately. The development of proteomics and multi-omics technologies has led to an increasing number of available biomarkers. Advances in detection technology have also made it possible to conduct rapid bedside tests, which can yield results within a few hours after resuscitation. If interpretable machine learning models are used to integrate data from multiple aspects such as electroencephalogram (EEG), electrocardiogram (ECG), and clinical symptoms, it is expected to make predictions more accurate, assist doctors in formulating more personalized and timely treatment plans for patients with cardiac arrest, and enable emergency departments to identify risk levels earlier and intervene precisely. Integrating molecular biomarkers into standard nursing procedures and intelligent early warning systems will bring tangible assistance to clinical nursing. By integrating real-time biomarker data with clinical assessment and monitoring tools, nurses can identify high-risk patients prone to secondary brain injury earlier and take timely
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