Welcome to visit Zhongnan Medical Journal Press Series journal website!

Development trajectory and risk factors of delirium in ICU patients

Published on Sep. 30, 2024Total Views: 101 timesTotal Downloads: 39 timesDownloadMobile

Author: SUN Shanshan 1 TAO Lei 1 ZHONG Mingming 1 TIAN Jinhui 2 WANG Min 1 ZHANG Zhigang 1, 3

Affiliation: 1. School of Nursing, Lanzhou university, Lanzhou 730011, China 2. Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China 3. Department of Intensive Care Medicine, The First Hospital of Lanzhou University, Lanzhou 730030, China

Keywords: Intensive care unit Delirium Risk factors Latent class growth model Development trajectory

DOI: 10.12173/j.issn.1004-5511.202405097

Reference: Sun SS, Tao L, Zhong MM, Tian JH, Wang M, Zhang ZG. Development trajectory and risk factors of delirium in ICU patients[J]. Yixue Xinzhi Zazhi, 2024, 34(9):978-988. DOI: 10.12173/j.issn.1004-5511.202405097.[Article in Chinese]

  • Abstract
  • Full-text
  • References
Abstract

Objective  To explore the different trajectories and risk factors of delirium in ICU patients, and to provide theoretical basis for delirium management.

Methods  From March 2023 to December 2023, ICU patients from The First Hospital of Lanzhou University were selected by convenient sampling method. Baseline and delirium assessments were performed at 24 hours (T1) after admission to the ICU using the general data questionnaire, Confusion Assessment Method of Intensive Care Unit (CAM-ICU), and Confusion Assessment Method for the Intensive Care Unit-7 (CAM-ICU-7), Richmond Agitation-Sedation Scale (RASS). Patients who developed delirium were continuously monitored at day 2, 3, 4, and 5 (T2-T5) time points after admission using RASS, CAM-ICU, and CAM-ICU-7. The latent class growth model was used to identify the category of delirium trajectory, and the influencing factors of different categories were analyzed.

Results  269 ICU patients were included, of which 126 patients experienced delirium and 102 patients with delirium participated in the whole 5 times of investigation, the incidence of delirium in ICU patients was 42.86%. The potential category growth model showed that the model with 3 subgroups fitted best. The 3 subgroups were named as the persistent delirium group(30.4%), the high-risk declining group(29.4%), and the low-risk rising group(40.2%). The univariate analysis showed that gender, type of sedatives and RASS score at different time points influenced the development trajectory of delirium (P<0.05). Multiple Logistic regression analysis showed that compared with the persistent delirium group, gender and type of sedatives were the main predictors of developing delirium in ICU patients into the high-risk declining group. Compared with the persistent delirium group, the predictors of ICU patients developing into the low-risk elevated group were T1 and T5 time point RASS scores.

Conclusions  There is population heterogeneity in the development trajectory of delirium in ICU patients, which can be divided into 3 potential categories. Gender, type of sedation use, and RASS score are influential factors in the latent category of delirium development trajectory in ICU patients. The medical staff should conduct personalized delirium management for ICU patients according to different delirium change trajectories.

Full-text
Please download the PDF version to read the full text: download
References

1.Battle DE. Diagnostic and statistical manual of mental disorders (DSM)[J]. Codas, 2013, 25(2): 191-202. DOI: 10.1590/s2317-17822013000200017.

2.Rasheed AM, Amirah M, Abdallah M, et al. Delirium incidence and risk factors in adult critically Ill patients in Saudi Arabia[J]. J Emerg Trauma Shock, 2019, 12(1): 30-34. DOI: 10.4103/JETS.JETS_91_18.

3.孙丹丹, 王瑞, 芦秀燕, 等. ICU患者谵妄持续时间及其影响因素的研究[J]. 中华护理杂志, 2017, 52(10): 1168-1172. [Sun DD, Wang R, Lu XY, et al. Analysis of duration of ICU delirium and its influencing factors[J]. Chinese Journal of Nursing, 2017, 52(10): 1168-1172.] DOI: 10.3761/j.issn.0254-1769.2017.10.003.

4.Krewulak KD, Stelfox HT, Leigh JP, et al. Incidence and prevalence of delirium subtypes in an adult ICU: a systematic review and Meta-analysis[J]. Crit Care Med, 2018, 46(12): 2029-2035. DOI: 10.1097/CCM.0000000000003402.

5.Salluh JI, Wang H, Schneider EB, et al. Outcome of delirium in critically ill patients: systematic review and Meta-analysis[J]. BMJ, 2015, 350: h2538. DOI: 10.1136/bmj.h2538.

6.Fan H, Ji M, Huang J, et al. Development and validation of a dynamic delirium prediction rule in patients admitted to the intensive care units (DYNAMIC-ICU): a prospective cohort study[J]. Int J Nurs Stud, 2019, 93: 64-73. DOI: 10.1016/j.ijnurstu.2018.10.008.

7.Mesa P, Previgliano IJ, Altez S, et al. Delirium in a Latin American intensive care unit. A prospective cohort study of mechanically ventilated patients[J]. Rev Bras Ter Intensiva, 2017, 29(3): 337-345. DOI: 10.5935/0103-507X.20170058.

8.Estrup S, Kjer CKW, Poulsen LM, et al. Delirium and effect of circadian light in the intensive care unit: a retrospective cohort study[J]. Acta Anaesthesiol Scand, 2018, 62(3): 367-375. DOI: 10.1111/aas.13037.

9.Ordóñez-Velasco LM, Hernández-Leiva E. Factors associated with delirium after cardiac surgery: a prospective cohort study[J]. Ann Card Anaesth, 2021, 24(2): 183-189. DOI: 10.4103/aca.ACA_43_20.

10.Marquetand J, Bode L, Fuchs S, et al. Risk factors for delirium are different in the very old: a comparative one-year prospective cohort study of 5,831 patients[J]. Front Psychiatry, 2021, 12: 655087. DOI: 10.3389/fpsyt.2021.655087.

11.Yang J, Zhou Y, Kang Y, et al. Risk factors of delirium in sequential sedation patients in intensive care units[J]. Biomed Res Int, 2017, 2017: 3539872. DOI: 10.1155/2017/3539872.

12.倪平, 陈京立, 刘娜. 护理研究中量性研究的样本量估计[J]. 中华护理杂志, 2010, 45(4): 378-380. [Ni P, Chen JL, Liu N. The sample size estimation hi quantitative nursing research[J]. Chinese Journal of Nursing, 2010, 45(4): 378-380.] DOI: 1310.3761/j.issn.0254-1769. 2010.04.037.

13.Ely EW, Truman B, Shintani A, et al. Monitoring sedation status over time in ICU patients: reliability and validity of the Richmond Agitation-Sedation Scale (RASS)[J]. JAMA, 2003, 289(22): 2983-2991. DOI: 10.1001/jama.289.22. 2983.

14.Inouye SK, van Dyck CH, Alessi CA, et al. Clarifying confusion: the confusion assessment method. A new method for detection of delirium[J]. Ann Intern Med, 1990, 113(12): 941-948. DOI: 10.7326/0003-4819-113-12-941.

15.Ely EW, Margolin R, Francis J, et al. Evaluation of delirium in critically ill patients: validation of the confusion assessment method for the intensive care unit (CAM-ICU)[J]. Crit Care Med, 2001, 29(7): 1370-1379. DOI: 10.1097/00003246-200107000-00012.

16.Ely EW, Inouye SK, Bernard GR, et al. Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU)[J]. JAMA, 2001, 286(21): 2703-2710. DOI: 10.1001/jama.286.21.2703.

17.Ho MH, Montgomery A, Traynor V, et al. Diagnostic performance of delirium assessment tools in critically ill patients: a systematic review and Meta-analysis[J]. Worldviews Evid Based Nurs, 2020, 17(4): 301-310. DOI: 10.1111/wvn.12462.

18.邹姮婧. 中文版CAM-ICU的信度效度检验及与其他量表的比较[D]. 武汉:华中科技大学, 2012. [Zou HJ. Reliability and validity test of the Chinese version of CAM-ICU and comparison with other scales[D]. Wuhan: Huazhong University of Science and Technology, 2012.] DOI: 10.7666/d.D231674.

19.Khan BA, Perkins AJ, Gao S, et al. The confusion assessment method for the ICU-7 delirium severity scale: a novel delirium severity instrument for use in the ICU[J]. Crit Care Med, 2017, 45(5): 851-857. DOI: 10.1097/CCM. 0000000000002368.

20.李鑫, 李奇, 孙建华, 等. ICU意识模糊评估表-7量化项目的汉化及信效度检验[J]. 护士进修杂志, 2022, 37(10): 865-869. [Li X, Li Q, Sun JH, et al. The Chinese version of scored items and reliability and validity test of the confusion assessment method for the intensive care unit-7[J]. Journal of Nurses Training, 2022, 37(10): 865-869.] DOI: 10.16821/j.cnki.hsjx.2022.10.001.

21.汤铂, 王小亭, 陈文劲, 等. 重症患者谵妄管理专家共识[J]. 中华内科杂志, 2019, 58(2): 108-118. [Tang B, Wang XT, Chen WJ, et al. Severe disease expert inpatient deliriummanagement consensus[J]. Inner China Journal of Science, 2019, 58 (2): 108-118.] DOI: 10.3760/cma .j.issn.0578-1426. 2019.02.007.

22.Hughes CG, Boncyk CS, Culley DJ, et al. American society for enhanced recovery and perioperative quality initiative joint consensus statement on postoperative delirium prevention[J]. Anesth Analg, 2020, 130(6): 1572-1590. DOI: 10.1213/ANE.0000000000004641.

23.Shehabi Y, Riker RR, Bokesch PM, et al. Delirium duration and mortality in lightly sedated, mechanically ventilated intensive care patients[J]. Crit Care Med, 2010, 38(12): 2311-2318. DOI: 10.1097/CCM.0b013e3181f85759.

24.Green C, Bonavia W, Toh C, et al. Prediction of ICU delirium: validation of current delirium predictive models in routine clinical practice[J]. Crit Care Med, 2019, 47(3): 428-435. DOI: 10.1097/CCM.0000000000003577.

25.王孟成. 潜变量建模与Mplus应用·基础篇[M]. 重庆:重庆大学出版社, 2014. [Wang MC. Latent variable modeling and mplus application·basic part[M]. Chongqing: Chongqing University Press, 2014.]

26.冯国双, 于石成, 刘世炜. 轨迹分析模型在追踪数据分析中的应用[J]. 中国预防医学杂志, 2014, 15(3): 292-295. [Feng GS, Yu SC, Liu SW. Application of trajectory analysis model in tracking data analysis[J]. China Preventive Medicine, 2014, 15(3): 292-295.] DOI: 10.16506/j.1009-6639.2014.03.009.

27.蔡伟. 基于潜分类增长模型孕期血压轨迹和胎盘源性标志物的子痫前期预测——社区前瞻性队列研究[D]. 天津:天津医科大学, 2018. [Cai W. Prediction of preeclampsia based on latent growth model of blood pressure locus and placenta-derived markers during pregnancy[D]. Tianjin: Tianjin Medical University, 2018.]

28.Lindroth H, Khan BA, Carpenter JS, et al. Delirium severity trajectories and outcomes in ICU patients. Defining a dynamic symptom phenotype[J]. Ann Am Thorac Soc, 2020, 17(9): 1094-1103. DOI: 10.1513/AnnalsATS. 201910-764OC.

29.Sylvestre MP, McCusker J, Cole M, et al. Classification of patterns of delirium severity scores over time in an elderly population[J]. Int Psychogeriatr, 2006, 18(4): 667-680. DOI: 10.1017/S1041610206003334.

30.Fan H, Ji M, Huang J, et al. Development and validation of a dynamic delirium prediction rule in patients admitted to the intensive care units (DYNAMIC-ICU): a prospective cohort study[J]. Int J Nurs Stud, 2019, 93: 64-73. DOI: 10.1016/j.ijnurstu.2018.10.008.

31.Wansrisuthon W, Ratta-Apha W, Thongchot L, et al. Accuracy of diagnosis and international classification of diseases; tenth revision coding for alcohol dependence, alcohol withdrawal, and alcohol-withdrawal delirium among inpatients at a university hospital[J]. J Addict Med, 2017, 11(3): 241-242. DOI: 10.1097/ADM.0000000000000307.

32.Suzuki S, Brown CM, Dela Cruz CD, et al. Timing of estrogen therapy after ovariectomy dictates the efficacy of its neuroprotective and antiinflammatory actions[J]. Proc Natl Acad Sci USA, 2007, 104(14): 6013-6018. DOI: 10.1073/pnas.0610394104.

33.Palakshappa JA, Hough CL. How we prevent and treat delirium in the ICU[J]. Chest, 2021, 160(4): 1326-1334. DOI: 10.1016/j.chest.2021.06.002.

34.Day E, Daly C. Clinical management of the alcohol withdrawal syndrome[J]. Addiction, 2022, 117(3): 804-814. DOI: 10.1111/add.15647.

35.李雪梅, 王欣琦, 徐励, 等. 脑肿瘤术后ICU患者谵妄亚型的危险因素分析[J]. 解放军护理杂志, 2022, 39(5): 13-17. [Li XM, Wang XQ, Xu L, et al. Analysis the risk factors of delirium subtypes in ICU patients after brain tumor surgery[J]. Military Nursing, 2022, 39(5): 13-17.] DOI: 10.3969/j.issn.1008-9993.2022.05.004.

36.Burry LD, Cheng W, Williamson DR, et al. Pharmacological and non-pharmacological interventions to prevent delirium in critically ill patients: a systematic review and network Meta-analysis[J]. Intensive Care Med, 2021, 47(9): 943-960. DOI: 10.1007/s00134-021-06490-3.

37.李文萍, 邓平洋, 杨林, 等. 右美托咪定用于ICU机械通气患者的快速卫生技术评估[J]. 药物流行病学杂志, 2024, 33(4): 441-448. [Li WP, Deng PY, Yang L, et al. Dexmedetomidine for sedation in the ICU patients on mechanical ventilation:a rapid health technology assessment[J]. Chinese Journal of Pharmacoepidemiology, 2019, 33(4):441-448.] DOI: 10.12173/j.issn. 1005-0698.202311046.

38.蒋玲洁, 岳伟岗, 王盛均, 等. 非药物干预比较改善ICU患者睡眠质量效果的网状Meta分析[J]. 中国循证医学杂志, 2020, 20(4): 403-411. [Jiang LJ, Yue WG, Wang SJ, et al. Efficacy of non-pharmacological interventions to improve sleep quality in ICU patients: a network Meta-analysis[J]. Chinese Journal of Evidence-Based Medicine, 2020, 20(4): 403-411.] DOI: 10.7507/1672-2531.201907084.