目的·构建成人重症监护病房（intensive care unit，ICU）患者转出后（ICU后患者）的早期症状网络；辨别网络中的核心症状和桥梁症状，对比综合ICU和心脏监护病房（coronary care unit，CCU）2个亚组的症状网络，分析症状的发生情况。方法·于2022年12月—2023年8月，从上海交通大学医学院附属第一人民医院综合ICU和CCU转入普通病房3 d（±48 h）的成人患者中方便抽样328例。采用患者一般情况和临床资料调查表、症状调查问卷（由医院焦虑抑郁量表、疲劳严重程度量表、理查兹-坎贝尔睡眠量表、疼痛数字评分法组成）对患者进行调查。基于Spearman相关性分析和GLASSO算法构建同期症状网络，计算网络的中心性指标，对比亚组症状网络的差异，并进行网络的边线准确性和中心性指标稳定性检验。结果·共收集有效问卷302份，问卷有效率92.1%。中心性指标计算结果显示，ICU后患者的早期症状网络中，强度最高的是“感到振奋和愉快”（r_S=1.145），紧密性最高的是“对以往感兴趣的事情仍然有兴趣”（r_C=1.851×10^-3），预期影响最高的是“疲劳影响体能”（r_E=1.143）。桥梁强度前3位的是“心中充满烦恼”（r_b=10.392）、“对以往感兴趣的事情仍然有兴趣”（r_b=10.359）和疼痛（r_b=10.221）。综合ICU和CCU患者转入普通病房后的早期症状网络在网络结构（M=0.289）和整体连接强度（GS_综合ICU=13.876，GS_CCU=13.838；S=0.039）上差异无统计学意义；对比亚组的中心性指标，除5个症状表现的强度和预期影响差异有统计学意义（均P<0.05）外，其他指标间差异均无统计学意义。ICU后患者早期症状网络的边线准确性和中心性指标稳定性良好。结论·成人ICU后患者早期的核心症状为焦虑和抑郁，疼痛是桥梁症状之一。综合ICU和CCU患者转出后的早期症状发生情况差异不大。医护人员要关注ICU后患者早期的不适症状，针对性开展干预以提升患者的舒适体验，促进其康复进程。

Objective ·To establish the early symptom network of adult intensive care unit (ICU) patients after transfer (post-ICU patients), identify the core symptoms and bridge symptoms, compare the symptom networks of two subgroups, i.e. mixed ICU and coronary care unit (CCU), and analyze the occurrence of symptoms. Methods ·From December 2022 to August 2023, a total of 328 adult patients transferred to wards from mixed ICU and CCU of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine were selected by convenience sampling. The general situation and clinical data questionnaire, and symptom questionnaires (including Hospital Anxiety and Depression Scale, Fatigue Severity Scale, Richards-Campbell Sleep Questionnaire, and Pain Numeric Rating Scale) were used. Based on Spearman correlation analysis and GLASSO algorithm, contemporaneous symptom network was built, and centrality indices and differences between subgroup symptom networks were computed. The edge accuracy and the stability of centrality indices of the network were tested. Results ·A total of 302 valid questionnaires were collected, and the effective rate was 92.1%. The results of the centrality indices computations showed that in the early symptom network of post-ICU patients, the highest strength was “feel cheerful” (r_S=1.145), the highest closeness was “enjoy something” (r_C=1.851×10^-3), and the highest expected influence was “（fatigue） interferes with physical function” (r_E=1.143). The top three highest bridge strengths of symptoms were “worrying thoughts” (r_b=10.392), “enjoy something” (r_b=10.359), and pain (r_b=10.221). There were no significant differences in network structure (M=0.289) and overall connection strength (GS_{mixed ICU}=13.876, GS_CCU=13.838; S=0.039) of the early symptom networks between mixed ICU and CCU patients after being transferred to wards. When comparing the centrality indices, apart from the strength and expected influence of five symptoms showing statistically significant differences (all P<0.05), other indices were not significantly different. The edge accuracy and the stability of centrality indices in the early symptom network of post-ICU patients were fine. Conclusion ·Anxiety and depression are the core symptoms of adult post-ICU patients, and pain is one of the bridge symptoms. There is no significant difference in the incidence of early symptoms between mixed ICU and CCU patients after being transferred out. Medical care personnel should pay attention to the discomfort symptoms of post-ICU patients, and carry out targeted interventions to improve patients' comfort and promote the rehabilitation process.