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

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http://hdl.handle.net/10138/313606

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HEALICS Consortium , Keuning , B E , Kaufmann , T , Wiersema , R , Pettilä , V & van der Horst , I C C 2020 , ' Mortality prediction models in the adult critically ill : A scoping review ' , Acta Anaesthesiologica Scandinavica , vol. 64 , no. 4 , pp. 424-442 . https://doi.org/10.1111/aas.13527

Title: Mortality prediction models in the adult critically ill : A scoping review
Author: Keuning, Britt E.; Kaufmann, Thomas; Wiersema, Renske; Granholm, Anders; Pettilä, Ville; Moller, Morten Hylander; Christiansen, Christian Fynbo; Forte, Jose Castela; Snieder, Harold; Keus, Frederik; Pleijhuis, Rick G.; van der Horst, Iwan C. C.
Contributor: University of Helsinki, HUS Perioperative, Intensive Care and Pain Medicine
Date: 2020-04
Number of pages: 19
Belongs to series: Acta Anaesthesiologica Scandinavica
ISSN: 0001-5172
URI: http://hdl.handle.net/10138/313606
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.
Subject: 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
3126 Surgery, anesthesiology, intensive care, radiology
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