Delirium prediction in the intensive care unit: comparison of two delirium prediction models

被引:51
|
作者
Wassenaar, Annelies [1 ]
Schoonhoven, Lisette [2 ,3 ,4 ]
Devlin, John W. [5 ,6 ]
van Haren, Frank M. P. [7 ,8 ,9 ]
Slooter, Arjen J. C. [10 ,11 ]
Jorens, Philippe G. [12 ]
van der Jagt, Mathieu [13 ]
Simons, Koen S. [14 ]
Egerod, Ingrid [15 ]
Burry, Lisa D. [16 ,17 ]
Beishuizen, Albertus [18 ]
Matos, Joaquim [19 ]
Donders, A. Rogier T. [20 ]
Pickkers, Peter [1 ,21 ]
van den Boogaard, Mark [1 ]
机构
[1] Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Intens Care Med, Med Ctr, POB 9101, NL-6500 HB Nijmegen, Netherlands
[2] Univ Southampton, Fac Hlth Sci, Southampton, Hants, England
[3] Univ Southampton, Natl Inst Hlth Res Collaborat Leadership Appl Hlt, Southampton, Hants, England
[4] Radboud Univ Nijmegen, Sci Inst Qual Healthcare, Radboud Inst Hlth Sci, Med Ctr, Nijmegen, Netherlands
[5] Northeastern Univ, Sch Pharm, Boston, MA 02115 USA
[6] Tufts Med Ctr, Div Pulm Crit Care & Sleep Med, Boston, MA USA
[7] Canberra Hosp, Intens Care Unit, Canberra, ACT, Australia
[8] Univ Canberra, Fac Hlth, Canberra, ACT, Australia
[9] Australian Natl Univ, Coll Hlth & Med, Canberra, ACT, Australia
[10] Univ Med Ctr Utrecht, Dept Intens Care Med, Utrecht, Netherlands
[11] Univ Med Ctr Utrecht, Brain Ctr Rudolf Magnus, Utrecht, Netherlands
[12] Univ Antwerp, Univ Antwerp Hosp, Dept Crit Care Med, Antwerp, Belgium
[13] Erasmus MC, Dept Intens Care, Rotterdam, Netherlands
[14] Jeroen Bosch Ziekenhuis, Dept Intens Care Med, sHertogenbosch, Netherlands
[15] Univ Copenhagen, Intens Care Unit, Rigshosp, Copenhagen, Denmark
[16] Univ Toronto, Leslie Dan Fac Pharm, Toronto, ON, Canada
[17] Mt Sinai Hosp, Sinai Hlth Syst, Toronto, ON, Canada
[18] Med Spectrum Twente, Dept Intens Care, Enschede, Netherlands
[19] Hosp Espirito Santo, Dept Intens Care Med, Evora, Portugal
[20] Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Hlth Evidence, Med Ctr, Nijmegen, Netherlands
[21] Radboud Univ Nijmegen, Med Ctr, Radboud Inst Mol Life Sci, Radboud Ctr Infect Dis, Nijmegen, Netherlands
来源
CRITICAL CARE | 2018年 / 22卷
关键词
Adult; Clinical prediction; Critical illness; Delirium; Intensive care unit; CRITICALLY-ILL PATIENTS; MECHANICALLY VENTILATED PATIENTS; CONFUSION ASSESSMENT METHOD; EXTERNAL VALIDATION; PROGNOSTIC MODEL; ABCDEF BUNDLE; ICU; SEDATION; RELIABILITY; VALIDITY;
D O I
10.1186/s13054-018-2037-6
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background: Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. Methods: This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h. Results: In total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71-0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66-0.71)) (z score of -2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible. Conclusions: While both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Delirium prediction in the intensive care unit: comparison of two delirium prediction models
    Annelies Wassenaar
    Lisette Schoonhoven
    John W. Devlin
    Frank M. P. van Haren
    Arjen J. C. Slooter
    Philippe G. Jorens
    Mathieu van der Jagt
    Koen S. Simons
    Ingrid Egerod
    Lisa D. Burry
    Albertus Beishuizen
    Joaquim Matos
    A. Rogier T. Donders
    Peter Pickkers
    Mark van den Boogaard
    [J]. Critical Care, 22
  • [2] External validation and comparison of two delirium prediction models in patients admitted to the cardiac intensive care unit
    Kim, Sung Eun
    Ko, Ryoung-Eun
    Na, Soo Jin
    Chung, Chi Ryang
    Choi, Ki Hong
    Kim, Darae
    Park, Taek Kyu
    Lee, Joo Myung
    Song, Young Bin
    Choi, Jin-Oh
    Hahn, Joo-Yong
    Choi, Seung-Hyuk
    Gwon, Hyeon-Cheol
    Yang, Jeong Hoon
    [J]. FRONTIERS IN CARDIOVASCULAR MEDICINE, 2022, 9
  • [3] Delirium prediction in the intensive care unit: a temporal approach
    Lucini, Filipe R.
    Fiest, Kirsten M.
    Stelfox, Henry T.
    Lee, Joon
    [J]. 42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 5527 - 5530
  • [4] MACHINE LEARNING PREDICTION OF INTENSIVE CARE UNIT DELIRIUM
    Gong, Kirby
    Lu, Ryan
    Bergamaschi, Teya
    Sanyal, Akaash
    Guo, Joanna
    Kim, Hanbiehn
    Stevens, Robert
    [J]. CRITICAL CARE MEDICINE, 2021, 49 (01) : 14 - 14
  • [5] Delirium risk prediction models for intensive care unit patients: A systematic review
    Chen, Junshan
    Yu, Jintian
    Zhang, Aiqin
    [J]. INTENSIVE AND CRITICAL CARE NURSING, 2020, 60
  • [6] Development and Validation of Simplified Delirium Prediction Model in Intensive Care Unit
    Kim, Min-Kyeong
    Oh, Jooyoung
    Kim, Jae-Jin
    Park, Jin Young
    [J]. FRONTIERS IN PSYCHIATRY, 2022, 13
  • [7] Automatic delirium prediction system in a Korean surgical intensive care unit
    Oh, Suk-Hwa
    Park, Eun-Ju
    Jin, Yinji
    Piao, Jinshi
    Lee, Sun-Mi
    [J]. NURSING IN CRITICAL CARE, 2014, 19 (06) : 281 - 291
  • [8] Machine learning for the prediction of delirium in elderly intensive care unit patients
    Ma, Rui
    Zhao, Jin
    Wen, Ziying
    Qin, Yunlong
    Yu, Zixian
    Yuan, Jinguo
    Zhang, Yumeng
    Wang, Anjing
    Li, Cui
    Li, Huan
    Chen, Yang
    Han, Fengxia
    Zhao, Yueru
    Sun, Shiren
    Ning, Xiaoxuan
    [J]. EUROPEAN GERIATRIC MEDICINE, 2024,
  • [9] Validation of the Prediction of Delirium for Intensive Care model to predict subsyndromal delirium
    Azuma, Kazunari
    Mishima, Shiro
    Shimoyama, Keiichiro
    Ishii, Yuri
    Ueda, Yasuhiro
    Sakurai, Masako
    Morinaga, Kentaro
    Fujikawa, Tsubasa
    Oda, Jun
    [J]. ACUTE MEDICINE & SURGERY, 2019, 6 (01): : 54 - 59
  • [10] Machine Learning for Intensive Care Delirium Prediction
    Gong, Kirby D.
    Lu, Ryan
    Bergamaschi, Teya
    Sanyal, Akaash
    Guo, Joanna
    Kim, Han
    Stevens, Robert D.
    [J]. ANESTHESIA AND ANALGESIA, 2021, 132 (5S_SUPPL): : 590 - 593