Yang Xia, Jiang Zhixia, Chen Fang, Zhang Xia, Yuan Xiaoli, Yang Yi, Xu Nan, Li Sijing
School of Nursing, Zunyi Medical University, Zunyi, China.
Guizhou Nursing Vocational College, Guiyang, Guizhou, China
BMJ Open. 2025 Aug 12;15(8):e094232. doi: 10.1136/bmjopen-2024-094232.
Delirium is a prevalent neuropsychiatric disorder in the intensive care unit (ICU), associated with poorer health outcomes, including extended duration of mechanical ventilation, prolonged ICU stays, and persistent or long-term cognitive impairment. Substantial evidence has indicated that the frequency, duration and severity of delirium during hospitalisation are significant risk factors for cognitive dysfunction in patients after ICU discharge. While existing studies have investigated the association between ICU delirium and subsequent cognitive outcomes, their analytical approaches have predominantly employed conventional longitudinal methods. Such methodological constraints impede the detection of clinically meaningful heterogeneous patient populations and the comprehensive evaluation of subgroup-specific determinants. The Latent Growth Curve Model (LGCM) and the Latent Class Growth Model (LCGM) serve as statistical tools capable of delineating the trajectory of cognitive change following delirium, along with identifying subgroups exhibiting distinct patterns of change. These methods may uncover clinically significant subtypes that were previously unrecognised. Therefore, this study aims to employ LGCM and LCGM to analyse the trajectory of cognitive level and risk factors in patients with delirium in the ICU one year after transfer.
This prospective study aims to investigate the 1-year trajectory of cognitive changes in ICU patients with delirium. It is planned to recruit 250 participants and gather comprehensive data, including general demographics, disease-related information and scores from the Mini-Mental State Examination, Hospital Anxiety and Depression Scale and the Pittsburgh Sleep Quality Index. All data will be collected at the following time points: on the day of ICU transfer, 1 month post-transfer, 3 months post-transfer, 6 months post-transfer and 1 year post-transfer. Ultimately, we will employ LGCM and LCGM to analyse the trajectory of cognitive changes and identify potential subgroups, while conducting logistic regression analysis to explore risk factors. The results of this study will provide a theoretical framework for the clinical implementation of precision nursing interventions within this demographic, aiming to prevent or mitigate cognitive decline and improve patients' quality of life.
Ethical approval was obtained from the ethics committee of Guizhou Nursing Vocational College (ethical approval number: gzhlllscb-2024-09-01). The findings of this study will be disseminated on a national and international scale through the publication of scholarly articles in research journals.
NCT06674603.
谵妄是重症监护病房（ICU）中一种常见的神经精神障碍，与较差的健康结局相关，包括机械通气时间延长、ICU住院时间延长以及持续性或长期认知障碍。大量证据表明，住院期间谵妄的发生频率、持续时间和严重程度是ICU出院患者认知功能障碍的重要危险因素。虽然现有研究调查了ICU谵妄与随后认知结局之间的关联，但其分析方法主要采用传统的纵向方法。这种方法学上的限制阻碍了对具有临床意义的异质患者群体的检测以及对亚组特异性决定因素的全面评估。潜在增长曲线模型（LGCM）和潜在类别增长模型（LCGM）是能够描绘谵妄后认知变化轨迹以及识别表现出不同变化模式亚组的统计工具。这些方法可能会揭示以前未被认识到的具有临床意义的亚型。因此，本研究旨在采用LGCM和LCGM分析ICU谵妄患者转出后一年的认知水平轨迹及危险因素。
本前瞻性研究旨在调查ICU谵妄患者1年的认知变化轨迹。计划招募250名参与者并收集全面数据，包括一般人口统计学信息、疾病相关信息以及简易精神状态检查表、医院焦虑抑郁量表和匹兹堡睡眠质量指数的评分。所有数据将在以下时间点收集：ICU转出当天、转出后1个月、转出后3个月、转出后6个月和转出后1年。最终，我们将采用LGCM和LCGM分析认知变化轨迹并识别潜在亚组，同时进行逻辑回归分析以探索危险因素。本研究结果将为该人群精准护理干预的临床实施提供理论框架，旨在预防或减轻认知衰退并改善患者生活质量。
获得了贵州护理职业学院伦理委员会的伦理批准（伦理批准号：gzhlllscb - 2024 - 09 - 01）。本研究结果将通过在研究期刊上发表学术文章在国内和国际范围内进行传播。
NCT06674603。
