Publication

Mortality prediction models in the adult critically ill: A scoping review

HEALICS Consortium, Keuning, B. E., Kaufmann, T., Wiersema, R., Granholm, A., Pettila, V., Moller, M. H., Christiansen, C. F., Forte, J. C., Snieder, H., Keus, F., Pleijhuis, R. G. & van der Horst, I. C. C., 26-Dec-2019, In : Acta Anaesthesiologica Scandinavica. 19 p.

Research output: Contribution to journalReview articleAcademicpeer-review

APA

HEALICS Consortium, Keuning, B. E., Kaufmann, T., Wiersema, R., Granholm, A., Pettila, V., Moller, M. H., Christiansen, C. F., Forte, J. C., Snieder, H., Keus, F., Pleijhuis, R. G., & van der Horst, I. C. C. (2019). Mortality prediction models in the adult critically ill: A scoping review. Acta Anaesthesiologica Scandinavica. https://doi.org/10.1111/aas.13527

Author

HEALICS Consortium ; Keuning, Britt E. ; Kaufmann, Thomas ; Wiersema, Renske ; Granholm, Anders ; Pettila, Ville ; Moller, Morten Hylander ; Christiansen, Christian Fynbo ; Forte, Jose Castela ; Snieder, Harold ; Keus, Frederik ; Pleijhuis, Rick G. ; van der Horst, Iwan C. C. / Mortality prediction models in the adult critically ill : A scoping review. In: Acta Anaesthesiologica Scandinavica. 2019.

Harvard

HEALICS Consortium, Keuning, BE, Kaufmann, T, Wiersema, R, Granholm, A, Pettila, V, Moller, MH, Christiansen, CF, Forte, JC, Snieder, H, Keus, F, Pleijhuis, RG & van der Horst, ICC 2019, 'Mortality prediction models in the adult critically ill: A scoping review', Acta Anaesthesiologica Scandinavica. https://doi.org/10.1111/aas.13527

Standard

Mortality prediction models in the adult critically ill : A scoping review. / HEALICS Consortium; Keuning, Britt E.; Kaufmann, Thomas; Wiersema, Renske; Granholm, Anders; Pettila, Ville; Moller, Morten Hylander; Christiansen, Christian Fynbo; Forte, Jose Castela; Snieder, Harold; Keus, Frederik; Pleijhuis, Rick G.; van der Horst, Iwan C. C.

In: Acta Anaesthesiologica Scandinavica, 26.12.2019.

Research output: Contribution to journalReview articleAcademicpeer-review

Vancouver

HEALICS Consortium, Keuning BE, Kaufmann T, Wiersema R, Granholm A, Pettila V et al. Mortality prediction models in the adult critically ill: A scoping review. Acta Anaesthesiologica Scandinavica. 2019 Dec 26. https://doi.org/10.1111/aas.13527


BibTeX

@article{5e196b95c9f8426c8d020d8eb66078ad,
title = "Mortality prediction models in the adult critically ill: A scoping review",
abstract = "Background Mortality prediction models are applied in the intensive care unit (ICU) to stratify patients into different risk categories and to facilitate benchmarking. To ensure that the correct prediction models are applied for these purposes, the best performing models must be identified. As a first step, we aimed to establish a systematic review of mortality prediction models in critically ill patients. Methods Mortality prediction models were searched in four databases using the following criteria: developed for use in adult ICU patients in high-income countries, with mortality as primary or secondary outcome. Characteristics and performance measures of the models were summarized. Performance was presented in terms of discrimination, calibration and overall performance measures presented in the original publication. Results In total, 43 mortality prediction models were included in the final analysis. In all, 15 models were only internally validated (35%), 13 externally (30%) and 10 (23%) were both internally and externally validated by the original researchers. Discrimination was assessed in 42 models (98%). Commonly used calibration measures were the Hosmer-Lemeshow test (60%) and the calibration plot (28%). Calibration was not assessed in 11 models (26%). Overall performance was assessed in the Brier score (19%) and the Nagelkerke's R-2 (4.7%). Conclusions Mortality prediction models have varying methodology, and validation and performance of individual models differ. External validation by the original researchers is often lacking and head-to-head comparisons are urgently needed to identify the best performing mortality prediction models for guiding clinical care and research in different settings and populations.",
keywords = "critical care, intensive care unit, mortality prediction model, performance, risk prediction, scoping review, INTENSIVE-CARE-UNIT, NEW-ZEALAND RISK, HOSPITAL MORTALITY, SAPS-II, PROGNOSTIC MODEL, ACUTE PHYSIOLOGY, ICU PATIENTS, INTERNAL VALIDATION, PROBABILITY-MODELS, APACHE-II",
author = "{HEALICS Consortium} and Keuning, {Britt E.} and Thomas Kaufmann and Renske Wiersema and Anders Granholm and Ville Pettila and Moller, {Morten Hylander} and Christiansen, {Christian Fynbo} and Forte, {Jose Castela} and Harold Snieder and Frederik Keus and Pleijhuis, {Rick G.} and {van der Horst}, {Iwan C. C.}",
year = "2019",
month = dec,
day = "26",
doi = "10.1111/aas.13527",
language = "English",
journal = "Acta Anaesthesiologica Scandinavica",
issn = "0001-5172",
publisher = "Wiley",

}

RIS

TY - JOUR

T1 - Mortality prediction models in the adult critically ill

T2 - A scoping review

AU - HEALICS Consortium

AU - Keuning, Britt E.

AU - Kaufmann, Thomas

AU - Wiersema, Renske

AU - Granholm, Anders

AU - Pettila, Ville

AU - Moller, Morten Hylander

AU - Christiansen, Christian Fynbo

AU - Forte, Jose Castela

AU - Snieder, Harold

AU - Keus, Frederik

AU - Pleijhuis, Rick G.

AU - van der Horst, Iwan C. C.

PY - 2019/12/26

Y1 - 2019/12/26

N2 - Background Mortality prediction models are applied in the intensive care unit (ICU) to stratify patients into different risk categories and to facilitate benchmarking. To ensure that the correct prediction models are applied for these purposes, the best performing models must be identified. As a first step, we aimed to establish a systematic review of mortality prediction models in critically ill patients. Methods Mortality prediction models were searched in four databases using the following criteria: developed for use in adult ICU patients in high-income countries, with mortality as primary or secondary outcome. Characteristics and performance measures of the models were summarized. Performance was presented in terms of discrimination, calibration and overall performance measures presented in the original publication. Results In total, 43 mortality prediction models were included in the final analysis. In all, 15 models were only internally validated (35%), 13 externally (30%) and 10 (23%) were both internally and externally validated by the original researchers. Discrimination was assessed in 42 models (98%). Commonly used calibration measures were the Hosmer-Lemeshow test (60%) and the calibration plot (28%). Calibration was not assessed in 11 models (26%). Overall performance was assessed in the Brier score (19%) and the Nagelkerke's R-2 (4.7%). Conclusions Mortality prediction models have varying methodology, and validation and performance of individual models differ. External validation by the original researchers is often lacking and head-to-head comparisons are urgently needed to identify the best performing mortality prediction models for guiding clinical care and research in different settings and populations.

AB - Background Mortality prediction models are applied in the intensive care unit (ICU) to stratify patients into different risk categories and to facilitate benchmarking. To ensure that the correct prediction models are applied for these purposes, the best performing models must be identified. As a first step, we aimed to establish a systematic review of mortality prediction models in critically ill patients. Methods Mortality prediction models were searched in four databases using the following criteria: developed for use in adult ICU patients in high-income countries, with mortality as primary or secondary outcome. Characteristics and performance measures of the models were summarized. Performance was presented in terms of discrimination, calibration and overall performance measures presented in the original publication. Results In total, 43 mortality prediction models were included in the final analysis. In all, 15 models were only internally validated (35%), 13 externally (30%) and 10 (23%) were both internally and externally validated by the original researchers. Discrimination was assessed in 42 models (98%). Commonly used calibration measures were the Hosmer-Lemeshow test (60%) and the calibration plot (28%). Calibration was not assessed in 11 models (26%). Overall performance was assessed in the Brier score (19%) and the Nagelkerke's R-2 (4.7%). Conclusions Mortality prediction models have varying methodology, and validation and performance of individual models differ. External validation by the original researchers is often lacking and head-to-head comparisons are urgently needed to identify the best performing mortality prediction models for guiding clinical care and research in different settings and populations.

KW - critical care

KW - intensive care unit

KW - mortality prediction model

KW - performance

KW - risk prediction

KW - scoping review

KW - INTENSIVE-CARE-UNIT

KW - NEW-ZEALAND RISK

KW - HOSPITAL MORTALITY

KW - SAPS-II

KW - PROGNOSTIC MODEL

KW - ACUTE PHYSIOLOGY

KW - ICU PATIENTS

KW - INTERNAL VALIDATION

KW - PROBABILITY-MODELS

KW - APACHE-II

U2 - 10.1111/aas.13527

DO - 10.1111/aas.13527

M3 - Review article

JO - Acta Anaesthesiologica Scandinavica

JF - Acta Anaesthesiologica Scandinavica

SN - 0001-5172

ER -

ID: 110138739