Mortality prediction models in the adult critically ill: A scoping review
| Autor: | Christian Fynbo Christiansen, Morten Hylander Møller, Rick G. Pleijhuis, Ville Pettilä, Iwan C. C. van der Horst, Britt E Keuning, Harold Snieder, Renske Wiersema, Thomas Kaufmann, Anders Granholm, José Castela Forte, Frederik Keus |
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| Rok vydání: | 2019 |
| Předmět: |
Adult
Male INTENSIVE-CARE-UNIT NEW-ZEALAND RISK SAPS-II Calibration (statistics) APACHE-II Critical Illness ICU PATIENTS intensive care unit Risk Assessment Severity of Illness Index law.invention 03 medical and health sciences risk prediction 0302 clinical medicine PROBABILITY-MODELS law Statistics HOSPITAL MORTALITY Medicine Humans 030212 general & internal medicine Models Statistical APACHE II business.industry Critically ill ACUTE PHYSIOLOGY INTERNAL VALIDATION 030208 emergency & critical care medicine General Medicine Benchmarking Middle Aged Intensive care unit 3. Good health PROGNOSTIC MODEL critical care Intensive Care Units Anesthesiology and Pain Medicine Brier score SAPS II mortality prediction model Female scoping review business Predictive modelling performance |
| Zdroj: | Keuning, B E, Kaufmann, T, Wiersema, R, Granholm, A, Pettilä, V, Møller, M H, Christiansen, C F, Castela Forte, J, Snieder, H, Keus, F, Pleijhuis, R G, van der Horst, I C C & HEALICS consortium 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 Keuning, B E, Kaufmann, T, Wiersema, R, Granholm, A, Pettilä, V, Møller, M H, Christiansen, C F, Castela Forte, J, Snieder, H, Keus, F, Pleijhuis, R G, van der Horst, I C & HEALICS consortium 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 |
| ISSN: | 1399-6576 |
| DOI: | 10.1111/aas.13527 |
| Popis: | 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. Fifteen 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 R2 (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. |
| Databáze: | OpenAIRE |
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