重症监护病房转出后患者早期症状网络分析

doi:10.3969/j.issn.1674-8115.2024.06.008

上海交通大学学报（医学版） ›› 2024, Vol. 44 ›› Issue (6): 733-740.doi: 10.3969/j.issn.1674-8115.2024.06.008

重症监护病房转出后患者早期症状网络分析

董冉¹(), 余倩², 台瑞², 杨富², 方芳²()

^1.上海交通大学护理学院，上海 200025
^2.上海交通大学医学院附属第一人民医院护理部，上海 200080

收稿日期:2023-12-15 接受日期:2024-03-01 出版日期:2024-06-28 发布日期:2024-06-18
通讯作者: 方芳 E-mail:random5126@126.com;fang_fang0604@163.com
作者简介:董冉（1998—），女，硕士生；电子信箱：random5126@126.com。
基金资助:
上海交通大学医学院护理学科建设项目(SJTUHLXK2021);上海申康医院发展中心技术规范化管理和推广项目(SHDC22022219)

Early symptom network analysis of patients after transfer from intensive care unit

DONG Ran¹(), YU Qian², TAI Rui², YANG Fu², FANG Fang²()

^1.School of Nursing, Shanghai Jiao Tong University, Shanghai 200025, China
^2.Department of Nursing, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China

Received:2023-12-15 Accepted:2024-03-01 Online:2024-06-28 Published:2024-06-18
Contact: FANG Fang E-mail:random5126@126.com;fang_fang0604@163.com
Supported by:
Nursing Development Program of Shanghai Jiao Tong University School of Medicine(SJTUHLXK2021);Standardized Technology Management and Promotion Project of Shanghai Hospital Development Center(SHDC22022219)

摘要/Abstract

摘要：

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。

关键词: 危重症, 症状管理, 网络分析, 重症监护病房, 过渡期护理

Abstract:

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.

Key words: critical illness, symptom management, network analysis, intensive care unit (ICU), transitional care

中图分类号:

R473.5

董冉, 余倩, 台瑞, 杨富, 方芳. 重症监护病房转出后患者早期症状网络分析[J]. 上海交通大学学报（医学版）, 2024, 44(6): 733-740.

DONG Ran, YU Qian, TAI Rui, YANG Fu, FANG Fang. Early symptom network analysis of patients after transfer from intensive care unit[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2024, 44(6): 733-740.

图/表 5

表1 302例ICU后患者的早期症状发生情况和可预测性

Tab 1 Early symptoms and predictability of 302 post-ICU patients

Symptom and manifestation	Incidence/n(%)	Item No.	R²
Sleep disturbance	246 (81.5)
Sleep depth		R1	0.660
Time to fall asleep		R2	0.627
Wake up in the night		R3	0.677
Sleep after waking up		R4	0.688
Overall sleep quality		R5	0.734
Anxiety	50 (16.6)
Tense or wound up		A1	0.513
Afraid of upcoming awful things		A2	0.627
Worrying thoughts		A3	0.696
Can sit at ease		A4	0.575
Feel restless		A5	0.635
Sudden panic		A6	0.602
Butterflies in stomach		A7	0.541
Depression	113 (37.4)
Enjoy something		D1	0.722
Laugh on funny thing		D2	0.738
Feel cheerful		D3	0.758
Not interested in appearance		D4	0.610
Look forward with enjoyment		D5	0.718
Feel slowed down		D6	0.650
Read or enjoy other entertainment		D7	0.646
Fatigue	167 (55.3)
Motivation is lower when fatigued		F1	0.698
Exercise brings on my fatigue		F2	0.818
Easily fatigued		F3	0.820
Interferes with physical function		F4	0.857
Causes frequent problems		F5	0.817
Prevents sustained physical function		F6	0.811
Troubles with duties and responsibilities		F7	0.814
Most disabling symptom		F8	0.828
Interferes with work, family or social life		F9	0.810
Sleep-affected pain	71 (23.5)
Pain numeric rating		P	0.346

图1 总体、综合ICU和CCU患者转入普通病房后早期症状的GLASSO网络图Note：A, B, and C are symptom networks of overall, mixed ICU and CCU patients, respectively. The thicker the edges, the stronger the correlation; blue edges represent positive correlations while the red ones represent negative correlations. In order to highlight the symptom network of overall ICU patients, spring distribution was adopted in A. Circle distribution was adopted in B and C to describe the comparison between subgroup networks.

Fig 1 GLASSO networks of early symptoms in overall, mixed ICU, and CCU patients after transfer to common wards

图2 ICU后患者早期症状网络的中心性指标

Fig 2 Node centralities of post-ICU patients' early symptom network

图3 ICU后患者早期症状网络桥梁强度

Fig 3 Bridge strengths of all nodes in post-ICU patients' early symptom network

图4 ICU后患者早期症状网络中心性指标的相关稳定性

Fig 4 Stability of centralities in post-ICU patients' early symptom network

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重症监护病房转出后患者早期症状网络分析

Early symptom network analysis of patients after transfer from intensive care unit

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