LU Xuefei, ZHANG Xiaoyu, CAO Zhijie, et al. Summary of integrated evidence on key predictive factors for early identification of sepsis in emergency department based on clinical decision-making processJ. Chin J Nosocomiol, 2026, 36(19): 1-6. DOI: 10.11816/cn.ni.2026-260791
Citation: LU Xuefei, ZHANG Xiaoyu, CAO Zhijie, et al. Summary of integrated evidence on key predictive factors for early identification of sepsis in emergency department based on clinical decision-making processJ. Chin J Nosocomiol, 2026, 36(19): 1-6. DOI: 10.11816/cn.ni.2026-260791

Summary of integrated evidence on key predictive factors for early identification of sepsis in emergency department based on clinical decision-making process

  • OBJECTIVE To integrate the best evidence on key predictive factors for the early identification of sepsis in the emergency department, and to develop an evidence integration framework based on the clinical decision-making process.
    METHODS A systematic search was conducted in guideline repositories such as BMJ Best Practice, JBI, NICE, as well as Chinese and English databases including PubMed, Embase, Cochrane Library and China National Knowledge Infrastructure. Relevant guidelines, expert consensus and systematic reviews on the early identification of sepsis in the emergency department published from the inception of the databases to Aug. 31, 2025, were collected. Four researchers independently performed literature screening, quality assessment and evidence extraction. The search period extended from the inception of the databases to Aug. 31, 2025.
    RESULTS A total of 10 articles were included. Through integrated analysis of the extracted evidence, a decision-making framework for the early identification of sepsis in the emergency department consisting of three sequential stages was developed: (1) Rapid screening and triage stage: focusing on rapidly obtainable bedside indicators and high-risk factors, during which the National Early Warning Score (NEWS) was recommended for screening high-risk patients. (2) Preliminary assessment and diagnostic verification stage: integrating key laboratory indicators, such as blood lactate, procalcitonin and C-reactive protein, to support diagnosis and severity stratification. (3) Dynamic monitoring and prognosis determination stage: incorporating treatment-related variables, such as timing of antibiotic initiation and fluid resuscitation response, to shift the focus to treatment response and prognosis assessment. This framework clarified the core objectives and key predictive factors at each decision-making stage.
    CONCLUSION The evidence integration framework developed in this study, based on the clinical decision-making process, systematically maps scattered evidence on predictive factors to sequential clinical decision-making stages, providing a structured pathway for practitioners in the emergency department to implement standardized assessments.
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