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Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study

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Abstract

Purpose

Recalibration and determining discriminative power, internationally, of the existing delirium prediction model (PRE-DELIRIC) for intensive care patients.

Methods

A prospective multicenter cohort study was performed in eight intensive care units (ICUs) in six countries. The ten predictors (age, APACHE-II, urgent and admission category, infection, coma, sedation, morphine use, urea level, metabolic acidosis) were collected within 24 h after ICU admission. The confusion assessment method for the intensive care unit (CAM-ICU) was used to identify ICU delirium. CAM-ICU screening compliance and inter-rater reliability measurements were used to secure the quality of the data.

Results

A total of 2,852 adult ICU patients were screened of which 1,824 (64 %) were eligible for the study. Main reasons for exclusion were length of stay <1 day (19.1 %) and sustained coma (4.1 %). CAM-ICU compliance was mean (SD) 82 ± 16 % and inter-rater reliability 0.87 ± 0.17. The median delirium incidence was 22.5 % (IQR 12.8–36.6 %). Although the incidence of all ten predictors differed significantly between centers, the area under the receiver operating characteristic (AUROC) curve of the eight participating centers remained good: 0.77 (95 % CI 0.74–0.79). The linear predictor and intercept of the prediction rule were adjusted and resulted in improved re-calibration of the PRE-DELIRIC model.

Conclusions

In this multinational study, we recalibrated the PRE-DELIRIC model. Despite differences in the incidence of predictors between the centers in the different countries, the performance of the PRE-DELIRIC-model remained good. Following validation of the PRE-DELIRIC model, it may facilitate implementation of strategies to prevent delirium and aid improvements in delirium management of ICU patients.

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Acknowledgments

The authors would like to thank Amanda McCairn and Sue Dowling (research nurses, Whiston Hospital), Anna Schandl (PhD student, Karolinska University Hospital, Stockholm) Lena James and Rod Hurford (Princess Alexandra Hospital, Brisbane, Australia) Walter Verbrugghe, Petra Vertongen (MD/staff member and data management, Antwerp University Hospital, Belgium) for their help in collecting the patient data.

Conflicts of interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

  1. Department of Intensive Care Medicine, Radboud University Medical Center, P.O. 6101 Internal Post 710, 6500 HB, Nijmegen, The Netherlands

    M. van den Boogaard, J. G. van der Hoeven & P. Pickkers

  2. Scientific Institute for Quality of Healthcare, Radboud University Medical Center, Nijmegen, The Netherlands

    L. Schoonhoven

  3. Faculty of Health Sciences, University of Southampton, Southampton, UK

    L. Schoonhoven

  4. Department of Intensive Care Medicine, Hospital Universitario La Paz, Madrid, Spain

    E. Maseda

  5. Anaesthetic Department, Medway Maritime Hospital, Kent, UK

    C. Plowright

  6. Ward 4E (Critical Care), Whiston Hospital, Prescot, UK

    C. Jones

  7. Department of Anesthesiology and Intensive Care Medicine, Charité—Universitaetsmedizin Berlin, Berlin, Germany

    A. Luetz

  8. Departments of Anesthesiology, Surgical Services and Intensive Care Medicine, Physiology and Pharmacology, Karolinska Institute, Karolinska University Hospital Solna, Stockholm, Sweden

    P. V. Sackey

  9. Department of Critical Care Medicine, Antwerp University Hospital, University of Antwerp, Edegem (Antwerp), Belgium

    P. G. Jorens

  10. Intensive Care Unit, Princess Alexandra Hospital, Brisbane, Australia

    L. M. Aitken

  11. NHMRC Center for Research Excellence, Center for Health Practice Innovation, Griffith Health Institute, Griffith University, Brisbane, Australia

    L. M. Aitken

  12. Department of Intensive Care, Canberra Hospital, Canberra, Australia

    F. M. P. van Haren

  13. Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands

    R. Donders

Authors
  1. M. van den Boogaard
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  2. L. Schoonhoven
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  3. E. Maseda
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  4. C. Plowright
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  5. C. Jones
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  6. A. Luetz
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  7. P. V. Sackey
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  8. P. G. Jorens
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  9. L. M. Aitken
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  10. F. M. P. van Haren
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  11. R. Donders
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  12. J. G. van der Hoeven
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  13. P. Pickkers
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Corresponding author

Correspondence to M. van den Boogaard.

Additional information

Take-home message The delirium prediction model for ICU patients (PRE-DELIRIC) is relevant for recognizing patients’ delirium risk in order to take preventive measures. In this multinational study, we recalibrated the PRE-DELIRIC model. Despite differences in the incidence of predictors between the centers in the different countries the performance of the PRE-DELIRIC-model remained good. Following validation of the PRE-DELIRIC model it may facilitate implementation of strategies to prevent delirium and aid improvements in delirium management of ICU patients.

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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 40, 361–369 (2014). https://doi.org/10.1007/s00134-013-3202-7

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  • DOI: https://doi.org/10.1007/s00134-013-3202-7

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