中华护理杂志 ›› 2021, Vol. 56 ›› Issue (10): 1445-1452.DOI: 10.3761/j.issn.0254-1769.2021.10.001

• 论著 •    下一篇

ICU后综合征患者症状特征的潜在类别分析

何曼曼(),江智霞(),张芳,李晓娟,胡汝均   

  1. 563000 遵义市 遵义医科大学附属医院重症监护室(何曼曼,李晓娟),急诊科(胡汝均);贵州护理职业技术学院院长办公室(江智霞);遵义医科大学护理学院(张芳)
  • 收稿日期:2021-01-14 出版日期:2021-10-15 发布日期:2021-10-19
  • 通讯作者:
  • 作者简介:何曼曼:女,硕士,护师,E-mail: 773985858@qq.com
  • 基金资助:
    2020年贵州省护理学会科研课题(gzsh1xhkt 2020-34)

Latent class analysis of symptom characteristics in patients with post-intensive care syndrome

HE Manman(),JIANG Zhixia(),ZHANG Fang,LI Xiaojuan,HU Rujun   

  1. Intensive Care Unit,Affiliated Hospital of Zunyi Medical University,Zunyi,563000,China
  • Received:2021-01-14 Online:2021-10-15 Published:2021-10-19

摘要:

目的 探讨ICU后综合征(post-intensive care syndrome,PICS)患者症状特征的潜在类别并分析各类别患者在人口学特征和疾病特征上的差异。 方法 采用便利抽样法,于2019年8月16日—2020年1月16日、2020年6月8日—2020年10月30日选取贵州省某三级甲等医院综合ICU的患者作为调查对象。患者转出ICU 1个月时,采用PICS相关症状评估量表对其进行电话随访。对PICS患者的症状特征进行潜在类别分析,并通过单因素分析和多项分类Logistic回归识别其潜在类别的影响因素。 结果 共纳入299例ICU患者,其中165例(55.18%)出现PICS症状。PICS患者的症状特征分为3个潜在类别,分别为“疲劳-睡眠障碍组”(44.24%)、“焦虑组”(16.97%)、“症状高发组”(38.79%)。“症状高发组”与“疲劳-睡眠障碍组”比较,PICS患者的急性生理与慢性健康状况评分Ⅱ(Acute Physiology and Chronic Health Evaluation Ⅱ,APACHE Ⅱ)越高归于“疲劳-睡眠障碍组”的概率越小(OR=0.882,P=0.001),无呼吸系统疾病史和无气管切开归于“疲劳-睡眠障碍组”的概率较大(OR=5.443,P=0.048;OR=4.015,P=0.006);“症状高发组”与“焦虑组”比较,PICS患者的APACHE Ⅱ越高归于“焦虑组”的概率越小(OR=0.903,P=0.027),年龄<50岁归于“焦虑组”的概率较大(OR=3.392,P=0.025);“疲劳-睡眠障碍组”与“焦虑组”比较,年龄<50岁的PICS患者归于“焦虑组”的概率较大(OR=4.422,P=0.005)。结论 PICS患者的症状特征存在异质性,可分为3个潜在类别。高APACHE Ⅱ、有呼吸系统疾病史和气管切开的PICS患者归为“症状高发组”的概率较大,年龄<50岁的PICS患者归为“焦虑组”的概率较大。临床医护人员应关注PICS患者症状特征的异质性,对不同类别的患者给予针对性的干预措施。

关键词: 重症监护病房, ICU后综合征, 潜在类别分析, 影响因素, 护理

Abstract:

Objective To explore the latent classes of symptom characteristics of post-intensive care syndrome(PICS)patients and to analyze the differences in demographic and disease characteristics of patients among different classes. Methods According to the inclusion and exclusion criteria,patients in the general ICU of a tertiary hospital in Guizhou were selected as the research subjects from August 16,2019 to January 16,2020,and from June 8,2020 to October 30,2020 by using convenient sampling method. Patients were followed up by telephone after being transferred out of ICU for 1 month to assess their PICS-related symptoms. Latent class analysis(LCA)was used to explore the latent classes of the symptom characteristics of PICS patients. Single factor analysis and multiple logistic regression were used to identify the influencing factors of the latent classes of PICS. Results A total of 299 samples were obtained and PICS occurred in 165 patients(55.18%). The symptom characteristics of PICS could be divided into 3 latent classes,which were named as “fatigue-sleep disorder group”(44.24%),“anxiety group”(16.97%),and “high symptom group”(38.79%). Compared “high symptom group” with “fatigue-sleep disorder group”,the higher acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score was,the less likely it was to be classified as “fatigue-sleep disorder group”(OR=0.882,P=0.001),and the more likely it was to be classified as “fatigue-sleep disorder group” without respiratory disease history or tracheotomy(OR=5.443,P=0.048;OR=4.015,P=0.006). Compared “high symptom group” with “anxiety group”,the higher APACHE Ⅱ score was Less likely to be classified to be “anxiety group”(OR=0.903,P=0.027),and patients younger than 50 years old were more likely to be classified as “anxiety group”(OR=3.392,P=0.025). Compared with “fatigue-sleep disorder group”,patients with age younger than 50 years were more likely to be classified as “anxiety group”(OR=4.422,P=0.005). Conclusion The symptomatic characteristics of PICS are heterogeneous and can be divided into 3 latent classes. Patients with a high APACHE II score,a history of respiratory disease,and a tracheotomy were more likely to be classified as “high symptom group”,while those younger than 50 were more likely to be classified as “anxiety group”. It is suggested that the clinical staff should pay attention to the heterogeneity of PICS individual symptom characteristics and give targeted intervention measures to different classes of patients.

Key words: Intensive Care Unit, Post-Intensive Care Syndrome, Latent Class Analysis, Influencing Factors, Nursing Care