Analysis of potential categories and influencing factors of fatigue trajectories in post-intensive care syndrome patients

doi:10.3761/j.issn.0254-1769.2022.03.003

Abstract

Abstract:

Objective To explore the potential trajectory categories of fatigue degree in patients with post-intensive care syndrome（PICS）,and to analyze the influence of patient demographic data and disease-related data on the potential categories of fatigue trajectory. Methods A convenient sampling method was used to select patients hospitalized in general ICU ward of a tertiary hospital in Guizhou Province from January 2020 to September,and the demographic and disease-related data of patients was collected. The fatigue degree of the patients was evaluated at 1 week（T1）,1 month（T2） and 3 months（T3） after ICU discharge. The growth mixture model was used to identify the potential trajectory category. Logistic regression analysis was used to analyze the prediction factors of trajectory category. Results 556 research subjects were initially enrolled,and 300 of them developed PICS. 4 types of fatigue trajectories were identified in these patients,and they were sustained fatigue group（19.00%）,increased fatigue group（6.00%）,fatigue remission group（27.67%）and non-fatigue group（47.33%）. Logistic regression analysis showed that high APACHE Ⅱ score,advanced age and history of respiratory diseases were independent predictors of fatigue trajectory categories. Conclusion The degree of fatigue in patients with PICS shows different trajectories. Medical staff should pay attention to the evaluation and intervention of fatigue in patients with high APACHE Ⅱ scores,advanced age,and history of respiratory diseases.

Key words: Critical Illness, Intensive Care Units, Fatigue, Root Cause Analysis, Latent Class Analysis, Nursing Care

摘要：

目的探讨ICU后综合征患者疲劳轨迹的潜在类别,分析患者人口学资料和疾病相关资料对其疲劳轨迹潜在类别的影响。方法采用便利抽样法,选取2020年1月—9月于贵州省某三级甲等医院综合ICU住院的患者作为调查对象,收集患者人口学及疾病相关资料。分别在患者转出ICU后1周、1个月、3个月时评估患者的疲劳程度,使用增长混合模型识别其疲劳轨迹的潜在类别,采用Logistic回归分析潜在类别的影响因素。结果初步纳入556例ICU转出患者,其中300例发生ICU后综合征,其疲劳程度存在4种轨迹,分别为持续疲劳（19.00%）、疲劳升高（6.00%）、疲劳缓解（27.67%）、无疲劳（47.33%）。Logistic回归分析显示,急性生理与慢性健康状况评分Ⅱ（Acute Physiology and Chronic Health Evaluation Ⅱ,APACHE Ⅱ）、年龄、是否有呼吸系统疾病史是ICU后综合征患者疲劳轨迹潜在类别的独立影响因素（P<0.05）。结论 ICU后综合征患者疲劳程度呈现不同的变化轨迹,医护人员应重视APACHE Ⅱ高、高龄、有呼吸系统疾病史患者疲劳程度的评估和干预。

关键词: 危重病, 重症监护病房, 疲劳, 影响因素分析, 潜在类别分析, 护理

ZHANG Xiying, JIANG Zhixia, LIU Qilan, HE Manman, ZHANG Fang, XIANG Qianling, HU Rujun. Analysis of potential categories and influencing factors of fatigue trajectories in post-intensive care syndrome patients[J]. Chinese Journal of Nursing, 2022, 57(3): 272-278.

张习莹, 江智霞, 刘其兰, 何曼曼, 张芳, 向黔灵, 胡汝均. ICU后综合征患者疲劳轨迹的潜在类别及影响因素分析[J]. 中华护理杂志, 2022, 57(3): 272-278.

Figures/Tables 3

References 31

[1]	Needham DM, Davidson J, Cohen H, et al. Improving long-term outcomes after discharge from intensive care unit:report from a stakeholders’ conference[J]. Crit Care Med, 2012,40(2):502-509. DOI PMID
[2]	Lee M, Kang J, Jeong YJ. Risk factors for post-intensive care syndrome:a systematic review and meta-analysis[J]. Aust Crit Care, 2020,33(3):287-294. DOI URL
[3]	Bower JE, Wiley J, Petersen L, et al. Fatigue after breast cancer treatment:biobehavioral predictors of fatigue trajectories[J]. Health Psychol, 2018,37(11):1025-1034. DOI URL
[4]	Cajanding RJ. Causes,assessment and management of fatigue in critically ill patients[J]. Br J Nurs, 2017,26(21):1176-1181. DOI PMID
[5]	Neufeld KJ, Leoutsakos JS, Yan HJ, et al. Fatigue symptoms during the first year following ARDS[J]. Chest, 2020,158(3):999-1007. DOI PMID
[6]	何曼曼, 江智霞, 王颖, 等. 成人ICU转出患者健康相关生活质量的研究进展[J]. 中华护理杂志, 2021,56(1):148-154.
	He MM, Jiang ZX, Wang Y, et al. Research progress on health-related quality of life in adult ICU discharged patients[J]. Chin J Nurs, 2021,56(1):148-154.
[7]	Nedergaard HK, Haberlandt T, Reichmann PD, et al. Patients’ opinions on outcomes following critical illness[J]. Acta Anaesthesiol Scand, 2018,62(4):531-539. DOI PMID
[8]	Wintermann GB, Rosendahl J, Weidner K, et al. Self-reported fatigue following intensive care of chronically critically ill patients:a prospective cohort study[J]. J Intensive Care, 2018,6:27.
[9]	肖健, 叶玲珑, 方亚. 增长混合模型在健康轨迹研究中的应用进展[J]. 中国卫生统计, 2020,37(4):637-640.
	Xiao J, Ye LL, Fang Y. Application progress of growth mixture model in health trajectory research[J]. Chin J Heal Stat, 2020,37(4):637-640.
[10]	陈峰. 医用多元统计分析方法[M]. 北京: 中国统计出版社, 2000: 12.
	Chen F. Multivariate statistical analysis for medical use[M]. Beijing: China Statistics Press, 2000: 12.
[11]	李若祎, 应巧燕, 刘桂英, 等. 院内及院外功能锻炼对ICU后综合征患者影响的研究进展[J]. 中华护理杂志, 2018,53(11):1328-1332.
	Li RY, Ying QY, Liu GY, et al. Research progress of functional exercise in and out of hospital for post-intensive care syndrome[J]. Chin J Nurs, 2018,53(11):1328-1332.
[12]	韦秀霞, 张秀伟, 彭剑英, 等. 国外ICU后综合征的研究现状[J]. 中华护理杂志, 2016,51(1):84-89.
	Wei XX, Zhang XW, Peng JY, et al. Current status of research on post-intensive care syndrome abroad[J]. Chin J Nurs, 2016,51(1):84-89.
[13]	周小炫. 中文版简易智能精神状态检查量表在脑卒中患者中的信效度初步研究[D]. 福州:福建中医药大学, 2015.
	Zhou XX. A preliminary study of the validity and reliability of the Chinese version of Mini-mental State Examination in stroke patients[D]. Fuzhou:Fujian University of Traditional Chinese Medicine, 2015.
[14]	孙振晓, 刘化学, 焦林瑛, 等. 医院焦虑抑郁量表的信度及效度研究[J]. 中华临床医师杂志(电子版), 2017,11(2):198-201.
	Sun ZX, Liu HX, Jiao LY, et al. Reliability and validity of Hospital Anxiety and Depression Scale[J]. Chin J Clin Electron Ed, 2017,11(2):198-201.
[15]	黄国平, 张亚林, 向慧, 等. 事件影响量表-修订版(IES-R)在女性犯人中的信度、效度分析[J]. 中国心理卫生杂志, 2006,20(1):28-31.
	Huang GP, Zhang YL, Xiang H, et al. The Chinese version of the Impact of Event Scale-revised:reliability and validity[J]. Chin Ment Heal J, 2006,20(1):28-31.
[16]	Garrouste-Orgeas M, Flahault C, Vinatier I, et al. Effect of an ICU diary on posttraumatic stress disorder symptoms among patients receiving mechanical ventilation:a randomized clinical trial[J]. JAMA, 2019,322(3):229-239. DOI PMID
[17]	侯东哲, 张颖, 巫嘉陵, 等. 中文版Barthel指数的信度与效度研究[J]. 临床荟萃, 2012,27(3):219-221.
	Hou DZ, Zhang Y, Wu JL, et al. Study on reliability and validity of Chinese version of Barthel Index[J]. Clin Focus, 2012,27(3):219-221.
[18]	路桃影, 李艳, 夏萍, 等. 匹兹堡睡眠质量指数的信度及效度分析[J]. 重庆医学, 2014,43(3):260-263.
	Lu TY, Li Y, Xia P, et al. Analysis on reliability and validity of the Pittsburgh Sleep Quality Index[J]. Chongqing Med, 2014,43(3):260-263.
[19]	Schwartz JE, Jandorf L, Krupp LB. The measurement of fatigue:a new instrument[J]. J Psychosom Res, 1993,37(7):753-762. PMID
[20]	王孟成, 邓俏文, 毕向阳, 等. 分类精确性指数Entropy在潜剖面分析中的表现:一项蒙特卡罗模拟研究[J]. 心理学报, 2017,49(11):1473-1482.
	Wang MC, Deng QW, Bi XY, et al. Performance of the entropy as an index of classification accuracy in latent profile analysis:a Monte Carlo simulation study[J]. Acta Psychol Sin, 2017,49(11):1473-1482.
[21]	Müller F, Tuinman MA, Janse M, et al. Clinically distinct trajectories of fatigue and their longitudinal relationship with the disturbance of personal goals following a cancer diagnosis[J]. Br J Health Psychol, 2017,22(3):627-643. DOI URL
[22]	Langerud AK, Rustøen T, Småstuen MC, et al. Intensive care survivor-reported symptoms:a longitudinal study of survivors’ symptoms[J]. Nurs Crit Care, 2018,23(1):48-54. DOI URL
[23]	Whisenant M, Wong B, Mitchell SA, et al. Distinct trajectories of fatigue and sleep disturbance in women receiving chemotherapy for breast cancer[J]. Oncol Nurs Forum, 2017,44(6):739-750. To examine self-reported severity of fatigue and disturbed sleep experienced daily by women with breast cancer during multiple cycles of chemotherapy, exploring potential classes of women experiencing similar symptom trajectories. .In a secondary analysis, classes of women experiencing similar patterns of fatigue and disturbed sleep were identified. .Oncology clinics in the United States. .166 women with breast cancer receiving chemotherapy.  .Severity scores were self-reported daily using an automated system. Classes of fatigue and disturbed sleep severity were identified using latent growth mixture modeling. .Fatigue, disturbed sleep, age, stage of disease, education, employment, marital status, chemotherapy regimen, hours lying down, and missed work. .Three fatigue classes were identified.Patterns of symptom trajectories for fatigue and disturbed sleep were distinguished by baseline symptom severity. .Identification of women at risk for fatigue and disturbed sleep may allow clinicians to intensify symptom management. DOI PMID
[24]	Picariello F, Norton S, Moss-Morris R, et al. A prospective study of fatigue trajectories among in-centre haemodialysis patients[J]. Br J Health Psychol, 2020,25(1):61-88. DOI PMID
[25]	King J, O’Neill B, Ramsay P, et al. Identifying patients’ support needs following critical illness:a scoping review of the qualitative literature[J]. Crit Care, 2019,23(1):187. DOI URL
[26]	Genç F, Karadağ S, Kılıç Akça N, et al. The effect of aromatherapy on sleep quality and fatigue level of the elderly:a randomized controlled study[J]. Holist Nurs Pract, 2020,34(3):155-162. DOI URL
[27]	Hosey MM, Needham DM, Kudchadkar SR. Fatigue in critical care survivors:multidisciplinary and self-management strategies[J]. Anaesthesia, 2021,76(9):1163-1166. DOI PMID
[28]	Goërtz YMJ, Spruit MA, van’t Hul AJ, et al. Fatigue is highly prevalent in patients with COPD and correlates poorly with the degree of airflow limitation[J]. Ther Adv Respir Dis, 2019,13(1):1-13.
[29]	Yang Y, Li QQ, Mao J, et al. Fatigue and health-related quality of life among patients with chronic obstructive pulmonary disease in China[J]. Clin Respir J, 2020,14(2):109-115. DOI URL
[30]	Spadaro S, Capuzzo M, Valpiani G, et al. Fatigue in intensive care survivors one year after discharge[J]. Health Qual Life Outcomes, 2016,14(1):148. DOI URL
[31]	叶小健, 庄一渝, 陈香萍, 等. ICU后综合征的干预研究现状[J]. 中华护理杂志, 2015,50(11):1369-1374.
	Ye XJ, Zhuang YY, Chen XP, et al. Current status of intervention research on post-intensive care syndrome[J]. Chin J Nurs, 2015,50(11):1369-1374.