Analysis of the characteristics and influencing factors of post-intensive care syndrome risk trajectory in critically ill patients

doi:10.3761/j.issn.0254-1769.2026.15.009

Abstract

Abstract:

Objective To explore the course of post-intensive care syndrome in critically ill patients，analyze the influencing factors，and provide theoretical bases for clinical implementation of precise management. Methods By using the convenience sampling method，357 patients who were transferred out of the ICU of a tertiary grade A hospital in Guizhou Province from December 2024 to July 2025 were selected for the questionnaire survey. The baseline survey was conducted using the general information questionnaire，Richards-Campbell sleep questionnaire，and Barthel Index. The Health Aging Brain Care Monitoring Questionnaire（Mixed Version） was used to assess the risk level of ICU post-syndrome at 3 time points：1 week（T1），1 month（T2），and 3 months（T3） after the pa-tients were transferred out of the ICU. The latent class growth model was used to identify the potential classes of post-intensive care syndrome risk in critically ill patients，and the multivariate Logistic regression was used to ana-lyze the influencing factors of the potential classes. Results A total of 301 patients completed all 3 follow-ups. The development trajectory of post-intensive care syndrome presented 4 types，including slow recovery trajectory（24.25%），rapid recovery trajectory（44.19%），risk increasing trajectory（6.64%），and persistent high-risk trajectory（24.92%）. Logistic regression analysis showed that the length of ICU post-hospitalization，personality traits，marital status，Barthel Index score，Acute Physiology and Chronic Health Evaluation Ⅱ（APACHE Ⅱ） score，presence of infection，presence of internal environment disorder，and early activities were independent influencing factors for the potential categories of post-intensive care syndrome risk trajectory in critically ill patients（P<0.05）. Conclusion The post-intensive care syndrome in critically ill patients shows different change trajectories. Healthcare professionals should pay attention to the risk assessment of the post-intensive care syndrome in patients who have a longer ICU stay，a higher APACHE Ⅱ score，an Barthel Index score of 21~59，introverted personality，being unmarried/divorced/widowed，presence of infections and internal environment disorders，and lack of early activities. They should also implement precise interventions as early as possible based on the possible influencing factors.

Key words: Critically Ill Patients, Post-Intensive Care Syndrome, Analysis of Influencing Factors, Trajectory, Latent Category Growth Model, Nursing Care

摘要：

目的探讨重症患者ICU后综合征的变化轨迹并分析其影响因素，为临床开展精准化管理提供依据。方法采用便利抽样法，选取2024年12月至2025年7月贵州省某三级甲等医院ICU转出的357例患者进行问卷调查。采用一般资料调查表、理查兹-坎贝尔睡眠量表、巴氏指数进行基线调查，使用健康老化大脑护理监测问卷（混合版）于患者转出ICU后1周（T1）、1个月（T2）、3个月（T3）3个时间点评估其ICU后综合征风险水平。运用潜类别增长模型识别重症患者ICU后综合征风险轨迹的潜在类别，使用多元Logistic回归分析其影响因素。结果共301例患者完成3次随访，其ICU后综合征发展轨迹存在4种类别：缓慢恢复轨迹（24.25%）、快速恢复轨迹（44.19%）、风险递增轨迹（6.64%）、持续高风险轨迹（24.92%）。多元Logistic回归分析显示，出ICU后住院时间、性格特征、婚姻状况、巴氏指数评分、急性生理与慢性健康状况Ⅱ评分、是否感染、是否内环境紊乱及是否早期活动是重症患者ICU后综合征风险轨迹潜在类别的独立影响因素（P<0.05）。结论重症患者ICU后综合征呈现不同的变化轨迹，医护人员应重视出ICU后住院时间长、急性生理与慢性健康状况Ⅱ评分高、巴氏指数评分为21~59分、性格内向、未婚/离异/丧偶、存在感染、内环境紊乱、未进行早期活动的重症患者ICU后综合征的风险评估，并针对其可能的影响因素尽早实施精准干预。

关键词: 重症患者, ICU后综合征, 影响因素分析, 轨迹, 潜类别增长模型, 护理

LIU Yan, YAO Li, WANG Yinhua, WANG Tingrui, LI Qinqin. Analysis of the characteristics and influencing factors of post-intensive care syndrome risk trajectory in critically ill patients[J]. Chinese Journal of Nursing, 2026, 61(15): 2076-2084.

刘焱, 姚丽, 王银花, 王庭瑞, 李钦钦. 重症患者ICU后综合征变化轨迹及影响因素分析[J]. 中华护理杂志, 2026, 61(15): 2076-2084.

Figures/Tables 4

Table 1 General characteristics and single factor analysis of influencing factors of post-intensive care syndrome trajectory type in critically ill patients

Table 2 Model fitting results of post-intensive care syndrome in critically ill patients（n=301）

Figure 1 Trajectory diagram of post-intensive care syndrome development for critically ill patients

Table 3 Multiple logistic regression analysis of post-intensive care syndrome trajectory category in critically ill patients（n=301）

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