Guangnan Liu MM , Zhen Li MM , Hui Zhang PhD , Jinbang Liu BS , Chengwu Yang BS , Haoyu Bi BS , Zhining Yang MM , Yu Sheng PhD
{"title":"应用健康老化脑保健监测仪对重症监护室转诊患者重症监护后综合征的潜在特征分类及影响因素:一项多中心队列研究","authors":"Guangnan Liu MM , Zhen Li MM , Hui Zhang PhD , Jinbang Liu BS , Chengwu Yang BS , Haoyu Bi BS , Zhining Yang MM , Yu Sheng PhD","doi":"10.1016/j.aucc.2025.101313","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Post–intensive care syndrome (PICS) significantly impacts intensive care unit (ICU)–transferred patients, causing long-term physical, cognitive, and psychological consequences. However, personalised interventions targeting the full spectrum of symptoms in these patients remain limited. Current mainstream PICS assessment methods involve multiple scales, which can be complex, whereas the Healthy Aging Brain Care Monitor offers a more streamlined approach for evaluating the full range of symptoms in ICU-transferred patients; thus, its application in this population requires further exploration.</div></div><div><h3>Objectives</h3><div>The objectives of this study were to classify the severity of PICS symptoms in ICU-transferred patients using the Healthy Aging Brain Care Monitor and to identify influencing factors associated with different PICS severity categories.</div></div><div><h3>Methods</h3><div>A cohort study was conducted at four tertiary hospitals in Beijing from January to December 2023, enrolling ICU-transferred patients. Data were collected using paper-based questionnaires, and a latent profile analysis was performed using Mplus 8.3 (Muthén & Muthén, Los Angeles, CA, USA) to classify PICS severity. Differences between groups were analysed using chi-squared tests, Kruskal–Wallis tests, and logistic regression.</div></div><div><h3>Results</h3><div>The latent profile analysis identified three categories of PICS symptoms: “mild PICS group” (48.95%), “moderate PICS group” (28.69%), and “severe PICS group” (22.36%). Logistic regression analysis showed that factors such as education level (primary school or below, odds ratio [OR] = 3.129, 95% confidence interval [CI]: 1.182–6.985), Acute Physiology and Chronic Health Evaluation II score (OR = 1.100, 95% CI: 1.016–1.190), Sequential Organ Failure Assessment score (OR = 1.312, 95% CI: 1.110–1.552), and Hospital Anxiety and Depression Scale for depression score (OR = 1.721, 95% CI: 1.220–2.426) significantly influenced the likelihood of severe PICS symptoms.</div></div><div><h3>Conclusions</h3><div>The study revealed distinct PICS severity profiles in ICU-transferred patients, emphasising the significant role of baseline health, anxiety, and department of transfer in determining symptom severity. These findings highlight the potential for personalised, targeted interventions based on these profiles. Future research should explore how these factors interact and their causal relationships to better tailor interventions for improving recovery and quality of life post ICU discharge.</div></div>","PeriodicalId":51239,"journal":{"name":"Australian Critical Care","volume":"38 6","pages":"Article 101313"},"PeriodicalIF":2.7000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of the healthy aging brain care monitor for latent profile classification and influencing factors of post–intensive care syndrome in intensive care unit–transferred patients: A multicentre cohort study\",\"authors\":\"Guangnan Liu MM , Zhen Li MM , Hui Zhang PhD , Jinbang Liu BS , Chengwu Yang BS , Haoyu Bi BS , Zhining Yang MM , Yu Sheng PhD\",\"doi\":\"10.1016/j.aucc.2025.101313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Post–intensive care syndrome (PICS) significantly impacts intensive care unit (ICU)–transferred patients, causing long-term physical, cognitive, and psychological consequences. However, personalised interventions targeting the full spectrum of symptoms in these patients remain limited. Current mainstream PICS assessment methods involve multiple scales, which can be complex, whereas the Healthy Aging Brain Care Monitor offers a more streamlined approach for evaluating the full range of symptoms in ICU-transferred patients; thus, its application in this population requires further exploration.</div></div><div><h3>Objectives</h3><div>The objectives of this study were to classify the severity of PICS symptoms in ICU-transferred patients using the Healthy Aging Brain Care Monitor and to identify influencing factors associated with different PICS severity categories.</div></div><div><h3>Methods</h3><div>A cohort study was conducted at four tertiary hospitals in Beijing from January to December 2023, enrolling ICU-transferred patients. Data were collected using paper-based questionnaires, and a latent profile analysis was performed using Mplus 8.3 (Muthén & Muthén, Los Angeles, CA, USA) to classify PICS severity. Differences between groups were analysed using chi-squared tests, Kruskal–Wallis tests, and logistic regression.</div></div><div><h3>Results</h3><div>The latent profile analysis identified three categories of PICS symptoms: “mild PICS group” (48.95%), “moderate PICS group” (28.69%), and “severe PICS group” (22.36%). Logistic regression analysis showed that factors such as education level (primary school or below, odds ratio [OR] = 3.129, 95% confidence interval [CI]: 1.182–6.985), Acute Physiology and Chronic Health Evaluation II score (OR = 1.100, 95% CI: 1.016–1.190), Sequential Organ Failure Assessment score (OR = 1.312, 95% CI: 1.110–1.552), and Hospital Anxiety and Depression Scale for depression score (OR = 1.721, 95% CI: 1.220–2.426) significantly influenced the likelihood of severe PICS symptoms.</div></div><div><h3>Conclusions</h3><div>The study revealed distinct PICS severity profiles in ICU-transferred patients, emphasising the significant role of baseline health, anxiety, and department of transfer in determining symptom severity. These findings highlight the potential for personalised, targeted interventions based on these profiles. Future research should explore how these factors interact and their causal relationships to better tailor interventions for improving recovery and quality of life post ICU discharge.</div></div>\",\"PeriodicalId\":51239,\"journal\":{\"name\":\"Australian Critical Care\",\"volume\":\"38 6\",\"pages\":\"Article 101313\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Australian Critical Care\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1036731425001432\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CRITICAL CARE MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian Critical Care","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1036731425001432","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
Application of the healthy aging brain care monitor for latent profile classification and influencing factors of post–intensive care syndrome in intensive care unit–transferred patients: A multicentre cohort study
Background
Post–intensive care syndrome (PICS) significantly impacts intensive care unit (ICU)–transferred patients, causing long-term physical, cognitive, and psychological consequences. However, personalised interventions targeting the full spectrum of symptoms in these patients remain limited. Current mainstream PICS assessment methods involve multiple scales, which can be complex, whereas the Healthy Aging Brain Care Monitor offers a more streamlined approach for evaluating the full range of symptoms in ICU-transferred patients; thus, its application in this population requires further exploration.
Objectives
The objectives of this study were to classify the severity of PICS symptoms in ICU-transferred patients using the Healthy Aging Brain Care Monitor and to identify influencing factors associated with different PICS severity categories.
Methods
A cohort study was conducted at four tertiary hospitals in Beijing from January to December 2023, enrolling ICU-transferred patients. Data were collected using paper-based questionnaires, and a latent profile analysis was performed using Mplus 8.3 (Muthén & Muthén, Los Angeles, CA, USA) to classify PICS severity. Differences between groups were analysed using chi-squared tests, Kruskal–Wallis tests, and logistic regression.
Results
The latent profile analysis identified three categories of PICS symptoms: “mild PICS group” (48.95%), “moderate PICS group” (28.69%), and “severe PICS group” (22.36%). Logistic regression analysis showed that factors such as education level (primary school or below, odds ratio [OR] = 3.129, 95% confidence interval [CI]: 1.182–6.985), Acute Physiology and Chronic Health Evaluation II score (OR = 1.100, 95% CI: 1.016–1.190), Sequential Organ Failure Assessment score (OR = 1.312, 95% CI: 1.110–1.552), and Hospital Anxiety and Depression Scale for depression score (OR = 1.721, 95% CI: 1.220–2.426) significantly influenced the likelihood of severe PICS symptoms.
Conclusions
The study revealed distinct PICS severity profiles in ICU-transferred patients, emphasising the significant role of baseline health, anxiety, and department of transfer in determining symptom severity. These findings highlight the potential for personalised, targeted interventions based on these profiles. Future research should explore how these factors interact and their causal relationships to better tailor interventions for improving recovery and quality of life post ICU discharge.
期刊介绍:
Australian Critical Care is the official journal of the Australian College of Critical Care Nurses (ACCCN). It is a bi-monthly peer-reviewed journal, providing clinically relevant research, reviews and articles of interest to the critical care community. Australian Critical Care publishes peer-reviewed scholarly papers that report research findings, research-based reviews, discussion papers and commentaries which are of interest to an international readership of critical care practitioners, educators, administrators and researchers. Interprofessional articles are welcomed.