Skip to main content
Top
Published in: Critical Care 1/2018

Open Access 01-12-2018 | Research

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

Authors: 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

Published in: Critical Care | Issue 1/2018

Login to get access

Abstract

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.

Trial registration

ClinicalTrials.gov, NCT02518646. Registered on 21 July 2015.
Appendix
Available only for authorised users
Literature
1.
go back to reference APA. Diagnostic and statistical manual of mental disorders, fifth edition. 5th ed. Washington, D.C.: American Psychiatric Association (APA); 2013. APA. Diagnostic and statistical manual of mental disorders, fifth edition. 5th ed. Washington, D.C.: American Psychiatric Association (APA); 2013.
2.
go back to reference Milbrandt EB, Deppen S, Harrison PL, et al. Costs associated with delirium in mechanically ventilated patients. Crit Care Med. 2004;32(4):955–62.CrossRefPubMed Milbrandt EB, Deppen S, Harrison PL, et al. Costs associated with delirium in mechanically ventilated patients. Crit Care Med. 2004;32(4):955–62.CrossRefPubMed
3.
4.
go back to reference Mistraletti G, Pelosi P, Mantovani ES, Berardino M, Gregoretti C. Delirium: clinical approach and prevention. Best Pract Res Clin Anaesthesiol. 2012;26(3):311–26.CrossRefPubMed Mistraletti G, Pelosi P, Mantovani ES, Berardino M, Gregoretti C. Delirium: clinical approach and prevention. Best Pract Res Clin Anaesthesiol. 2012;26(3):311–26.CrossRefPubMed
5.
go back to reference Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19(4):453–73.CrossRefPubMed Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19(4):453–73.CrossRefPubMed
6.
go back to reference Giannini A, Garrouste-Orgeas M, Latour JM. What’s new in ICU visiting policies: can we continue to keep the doors closed? Intensive Care Med. 2014;40(5):730–3.CrossRefPubMed Giannini A, Garrouste-Orgeas M, Latour JM. What’s new in ICU visiting policies: can we continue to keep the doors closed? Intensive Care Med. 2014;40(5):730–3.CrossRefPubMed
8.
go back to reference Morandi A, Piva S, Ely EW, et al. Worldwide survey of the “Assessing Pain, Both Spontaneous Awakening and Breathing Trials, Choice of Drugs, Delirium Monitoring/Management, Early Exercise/Mobility, and Family Empowerment” (ABCDEF) bundle. Crit Care Med. 2017;45(11):e1111–22.CrossRefPubMed Morandi A, Piva S, Ely EW, et al. Worldwide survey of the “Assessing Pain, Both Spontaneous Awakening and Breathing Trials, Choice of Drugs, Delirium Monitoring/Management, Early Exercise/Mobility, and Family Empowerment” (ABCDEF) bundle. Crit Care Med. 2017;45(11):e1111–22.CrossRefPubMed
9.
go back to reference van den Boogaard M, Pickkers P, Slooter AJ, et al. Development and validation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for intensive care patients: observational multicentre study. BMJ. 2012;344:e420.CrossRefPubMedPubMedCentral van den Boogaard M, Pickkers P, Slooter AJ, et al. Development and validation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for intensive care patients: observational multicentre study. BMJ. 2012;344:e420.CrossRefPubMedPubMedCentral
10.
go back to reference van den Boogaard M, Schoonhoven L, Maseda E, et al. Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study. Intensive Care Med. 2014;40(3):361–9.CrossRefPubMed van den Boogaard M, Schoonhoven L, Maseda E, et al. Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study. Intensive Care Med. 2014;40(3):361–9.CrossRefPubMed
11.
go back to reference Wassenaar A, van den Boogaard M, van Achterberg T, et al. Multinational development and validation of an early prediction model for delirium in ICU patients. Intensive Care Med. 2015;41(6):1048–56.CrossRefPubMedPubMedCentral Wassenaar A, van den Boogaard M, van Achterberg T, et al. Multinational development and validation of an early prediction model for delirium in ICU patients. Intensive Care Med. 2015;41(6):1048–56.CrossRefPubMedPubMedCentral
12.
go back to reference Ely EW, Shintani A, Truman B, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA. 2004;291(14):1753–62.CrossRefPubMed Ely EW, Shintani A, Truman B, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA. 2004;291(14):1753–62.CrossRefPubMed
13.
go back to reference Serafim RB, Dutra MF, Saddy F, et al. Delirium in postoperative nonventilated intensive care patients: risk factors and outcomes. Ann Intensive Care. 2012;2(1):51.CrossRefPubMedPubMedCentral Serafim RB, Dutra MF, Saddy F, et al. Delirium in postoperative nonventilated intensive care patients: risk factors and outcomes. Ann Intensive Care. 2012;2(1):51.CrossRefPubMedPubMedCentral
14.
go back to reference Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ. 2009;338:b375.CrossRefPubMed Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ. 2009;338:b375.CrossRefPubMed
15.
go back to reference Castor Electronic Data Capture. Amsterdam, the Netherlands: Ciwit BV; 2017. Castor Electronic Data Capture. Amsterdam, the Netherlands: Ciwit BV; 2017.
16.
go back to reference Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818–29.CrossRefPubMed Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818–29.CrossRefPubMed
17.
go back to reference Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707–10.CrossRefPubMed Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707–10.CrossRefPubMed
18.
go back to reference 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). JAMA. 2001;286(21):2703–10.CrossRefPubMed 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). JAMA. 2001;286(21):2703–10.CrossRefPubMed
19.
go back to reference Bergeron N, Dubois MJ, Dumont M, Dial S, Skrobik Y. Intensive Care Delirium Screening Checklist: evaluation of a new screening tool. Intensive Care Med. 2001;27(5):859–64.CrossRefPubMed Bergeron N, Dubois MJ, Dumont M, Dial S, Skrobik Y. Intensive Care Delirium Screening Checklist: evaluation of a new screening tool. Intensive Care Med. 2001;27(5):859–64.CrossRefPubMed
20.
go back to reference Moons KG, Kengne AP, Woodward M, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart. 2012;98(9):683–90.CrossRefPubMed Moons KG, Kengne AP, Woodward M, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart. 2012;98(9):683–90.CrossRefPubMed
21.
go back to reference Riker RR, Picard JT, Fraser GL. Prospective evaluation of the Sedation-Agitation Scale for adult critically ill patients. Crit Care Med. 1999;27(7):1325–9.CrossRefPubMed Riker RR, Picard JT, Fraser GL. Prospective evaluation of the Sedation-Agitation Scale for adult critically ill patients. Crit Care Med. 1999;27(7):1325–9.CrossRefPubMed
22.
go back to reference Sessler CN, Gosnell MS, Grap MJ, et al. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166(10):1338–44.CrossRefPubMed Sessler CN, Gosnell MS, Grap MJ, et al. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166(10):1338–44.CrossRefPubMed
23.
go back to reference van Eijk MM, van den Boogaard M, van Marum RJ, et al. Routine use of the confusion assessment method for the intensive care unit: a multicenter study. Am J Respir Crit Care Med. 2011;184(3):340–4.CrossRefPubMed van Eijk MM, van den Boogaard M, van Marum RJ, et al. Routine use of the confusion assessment method for the intensive care unit: a multicenter study. Am J Respir Crit Care Med. 2011;184(3):340–4.CrossRefPubMed
24.
go back to reference Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2016;35(2):214–26.CrossRefPubMed Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2016;35(2):214–26.CrossRefPubMed
25.
go back to reference Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. New York: Springer Science+Business Media; 2009.CrossRef Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. New York: Springer Science+Business Media; 2009.CrossRef
26.
go back to reference Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology. 1983;148(3):839–43.CrossRefPubMed Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology. 1983;148(3):839–43.CrossRefPubMed
28.
go back to reference Grol R, Wensing M. What drives change? Barriers to and incentives for achieving evidence-based practice. Med J Aust. 2004;180(6 Suppl):S57–60.PubMed Grol R, Wensing M. What drives change? Barriers to and incentives for achieving evidence-based practice. Med J Aust. 2004;180(6 Suppl):S57–60.PubMed
29.
go back to reference Grol R, Wensing M: Implementation; Effective improvement of patient care. (In Dutch: Implementatie; Effectieve Verbeteringen Van Patiëntenzorg. Amsterdam: Bohn Stafleu en van Loghum; 2016. Grol R, Wensing M: Implementation; Effective improvement of patient care. (In Dutch: Implementatie; Effectieve Verbeteringen Van Patiëntenzorg. Amsterdam: Bohn Stafleu en van Loghum; 2016.
30.
go back to reference Barr J, Fraser GL, Puntillo K, et al. Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med. 2013;41(1):263–306.CrossRefPubMed Barr J, Fraser GL, Puntillo K, et al. Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med. 2013;41(1):263–306.CrossRefPubMed
32.
go back to reference Siddiqi N. Predicting delirium: time to use delirium risk scores in routine practice? Age Ageing. 2016;45(1):9–10.CrossRefPubMed Siddiqi N. Predicting delirium: time to use delirium risk scores in routine practice? Age Ageing. 2016;45(1):9–10.CrossRefPubMed
33.
go back to reference Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605.CrossRefPubMed Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605.CrossRefPubMed
34.
go back to reference Siontis GC, Tzoulaki I, Castaldi PJ, Ioannidis JP. External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination. J Clin Epidemiol. 2015;68(1):25–34.CrossRefPubMed Siontis GC, Tzoulaki I, Castaldi PJ, Ioannidis JP. External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination. J Clin Epidemiol. 2015;68(1):25–34.CrossRefPubMed
35.
go back to reference Lee A, Mu JL, Joynt GM, et al. Risk prediction models for delirium in the intensive care unit after cardiac surgery: a systematic review and independent external validation. Br J Anaesth. 2017;118(3):391–9.CrossRefPubMed Lee A, Mu JL, Joynt GM, et al. Risk prediction models for delirium in the intensive care unit after cardiac surgery: a systematic review and independent external validation. Br J Anaesth. 2017;118(3):391–9.CrossRefPubMed
36.
go back to reference van den Boogaard M, Schoonhoven L, van der Hoeven JG, van Achterberg T, Pickkers P. Incidence and short-term consequences of delirium in critically ill patients: a prospective observational cohort study. Int J Nurs Stud. 2012;49(7):775–83.CrossRefPubMed van den Boogaard M, Schoonhoven L, van der Hoeven JG, van Achterberg T, Pickkers P. Incidence and short-term consequences of delirium in critically ill patients: a prospective observational cohort study. Int J Nurs Stud. 2012;49(7):775–83.CrossRefPubMed
37.
go back to reference Peterson JF, Pun BT, Dittus RS, et al. Delirium and its motoric subtypes: a study of 614 critically ill patients. J Am Geriatr Soc. 2006;54(3):479–84.CrossRefPubMed Peterson JF, Pun BT, Dittus RS, et al. Delirium and its motoric subtypes: a study of 614 critically ill patients. J Am Geriatr Soc. 2006;54(3):479–84.CrossRefPubMed
38.
go back to reference Woien H, Balsliemke S, Stubhaug A. The incidence of delirium in Norwegian intensive care units; deep sedation makes assessment difficult. Acta Anaesthesiol Scand. 2013;57(3):294–302.CrossRefPubMed Woien H, Balsliemke S, Stubhaug A. The incidence of delirium in Norwegian intensive care units; deep sedation makes assessment difficult. Acta Anaesthesiol Scand. 2013;57(3):294–302.CrossRefPubMed
40.
go back to reference Dykema J, Jones NR, Piche T, Stevenson J. Surveying clinicians by web: current issues in design and administration. Eval Health Prof. 2013;36(3):352–81.CrossRefPubMed Dykema J, Jones NR, Piche T, Stevenson J. Surveying clinicians by web: current issues in design and administration. Eval Health Prof. 2013;36(3):352–81.CrossRefPubMed
41.
go back to reference Moons KG, Altman DG, Vergouwe Y, Royston P. Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ. 2009;338:b606.CrossRefPubMed Moons KG, Altman DG, Vergouwe Y, Royston P. Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ. 2009;338:b606.CrossRefPubMed
42.
go back to reference Gusmao-Flores D, Salluh JI, Chalhub RA, Quarantini LC. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) for the diagnosis of delirium: a systematic review and meta-analysis of clinical studies. Crit Care. 2012;16(4):R115.CrossRefPubMedPubMedCentral Gusmao-Flores D, Salluh JI, Chalhub RA, Quarantini LC. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) for the diagnosis of delirium: a systematic review and meta-analysis of clinical studies. Crit Care. 2012;16(4):R115.CrossRefPubMedPubMedCentral
Metadata
Title
Delirium prediction in the intensive care unit: comparison of two delirium prediction models
Authors
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
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Critical Care / Issue 1/2018
Electronic ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-018-2037-6

Other articles of this Issue 1/2018

Critical Care 1/2018 Go to the issue