Cargando…

Development and validation of a predictive score for ICU delirium in critically ill patients

BACKGROUND: The incidence of delirium in intensive care unit (ICU) patients is high and associated with a poor prognosis. We validated the risk factors of delirium to identify relevant early and predictive clinical indicators and developed an optimized model. METHODS: In the derivation cohort, 223 p...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Huijuan, Yuan, Jing, Chen, Qun, Cao, Yingya, Wang, Zhen, Lu, Weihua, Bao, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863543/
https://www.ncbi.nlm.nih.gov/pubmed/33546592
http://dx.doi.org/10.1186/s12871-021-01259-z
_version_ 1783647516236972032
author Zhang, Huijuan
Yuan, Jing
Chen, Qun
Cao, Yingya
Wang, Zhen
Lu, Weihua
Bao, Juan
author_facet Zhang, Huijuan
Yuan, Jing
Chen, Qun
Cao, Yingya
Wang, Zhen
Lu, Weihua
Bao, Juan
author_sort Zhang, Huijuan
collection PubMed
description BACKGROUND: The incidence of delirium in intensive care unit (ICU) patients is high and associated with a poor prognosis. We validated the risk factors of delirium to identify relevant early and predictive clinical indicators and developed an optimized model. METHODS: In the derivation cohort, 223 patients were assigned to two groups (with or without delirium) based on the CAM-ICU results. Multivariate logistic regression analysis was conducted to identify independent risk predictors, and the accuracy of the predictors was then validated in a prospective cohort of 81 patients. RESULTS: A total of 304 patients were included: 223 in the derivation group and 81 in the validation group, 64(21.1%)developed delirium. The model consisted of six predictors assessed at ICU admission: history of hypertension (RR = 4.367; P = 0.020), hypoxaemia (RR = 3.382; P = 0.018), use of benzodiazepines (RR = 5.503; P = 0.013), deep sedation (RR = 3.339; P = 0.048), sepsis (RR = 3.480; P = 0.018) and mechanical ventilation (RR = 3.547; P = 0.037). The mathematical model predicted ICU delirium with an accuracy of 0.862 (P < 0.001) in the derivation cohort and 0.739 (P < 0.001) in the validation cohort. No significant difference was found between the predicted and observed cases of ICU delirium in the validation cohort (P > 0.05). CONCLUSIONS: Patients’ risk of delirium can be predicted at admission using the early prediction score, allowing the implementation of early preventive interventions aimed to reduce the incidence and severity of ICU delirium.
format Online
Article
Text
id pubmed-7863543
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-78635432021-02-08 Development and validation of a predictive score for ICU delirium in critically ill patients Zhang, Huijuan Yuan, Jing Chen, Qun Cao, Yingya Wang, Zhen Lu, Weihua Bao, Juan BMC Anesthesiol Research Article BACKGROUND: The incidence of delirium in intensive care unit (ICU) patients is high and associated with a poor prognosis. We validated the risk factors of delirium to identify relevant early and predictive clinical indicators and developed an optimized model. METHODS: In the derivation cohort, 223 patients were assigned to two groups (with or without delirium) based on the CAM-ICU results. Multivariate logistic regression analysis was conducted to identify independent risk predictors, and the accuracy of the predictors was then validated in a prospective cohort of 81 patients. RESULTS: A total of 304 patients were included: 223 in the derivation group and 81 in the validation group, 64(21.1%)developed delirium. The model consisted of six predictors assessed at ICU admission: history of hypertension (RR = 4.367; P = 0.020), hypoxaemia (RR = 3.382; P = 0.018), use of benzodiazepines (RR = 5.503; P = 0.013), deep sedation (RR = 3.339; P = 0.048), sepsis (RR = 3.480; P = 0.018) and mechanical ventilation (RR = 3.547; P = 0.037). The mathematical model predicted ICU delirium with an accuracy of 0.862 (P < 0.001) in the derivation cohort and 0.739 (P < 0.001) in the validation cohort. No significant difference was found between the predicted and observed cases of ICU delirium in the validation cohort (P > 0.05). CONCLUSIONS: Patients’ risk of delirium can be predicted at admission using the early prediction score, allowing the implementation of early preventive interventions aimed to reduce the incidence and severity of ICU delirium. BioMed Central 2021-02-05 /pmc/articles/PMC7863543/ /pubmed/33546592 http://dx.doi.org/10.1186/s12871-021-01259-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Zhang, Huijuan
Yuan, Jing
Chen, Qun
Cao, Yingya
Wang, Zhen
Lu, Weihua
Bao, Juan
Development and validation of a predictive score for ICU delirium in critically ill patients
title Development and validation of a predictive score for ICU delirium in critically ill patients
title_full Development and validation of a predictive score for ICU delirium in critically ill patients
title_fullStr Development and validation of a predictive score for ICU delirium in critically ill patients
title_full_unstemmed Development and validation of a predictive score for ICU delirium in critically ill patients
title_short Development and validation of a predictive score for ICU delirium in critically ill patients
title_sort development and validation of a predictive score for icu delirium in critically ill patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863543/
https://www.ncbi.nlm.nih.gov/pubmed/33546592
http://dx.doi.org/10.1186/s12871-021-01259-z
work_keys_str_mv AT zhanghuijuan developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT yuanjing developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT chenqun developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT caoyingya developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT wangzhen developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT luweihua developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients
AT baojuan developmentandvalidationofapredictivescoreforicudeliriumincriticallyillpatients