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Updated: Jul 11, 2025
A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
Published on: August 18, 2015
Predicting 30-day mortality in intensive care unit patients with ischaemic stroke or intracerebral haemorrhage
Mariëlle K van Valburg1, Fabian Termorshuizen, Bart F Geerts
1From the Department of Intensive Care Medicine, University Medical Center Utrecht, Utrecht University, Utrecht (MKvV, AJCS), Department of Anaesthesiology, Intensive Care and Pain Medicine, Amphia Hospital, Breda (MKvV), National Intensive Care Evaluation Foundation, Amsterdam University Medical Center (FT, SB, MSA), Department of Medical Informatics, Amsterdam University Medical Center, Amsterdam (FT, SB), Healthplus.ai BV, Amsterdam (BFG), Department of Intensive Care Medicine, Radboud University Medical Center, Nijmegen (WFA), Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen (WMvdB), Department of Intensive Care, Amsterdam University Medical Center, Amsterdam (JH), Department of Intensive Care Medicine, and Academy for Postgraduate Training, Maastricht University Medical Center (WNKAvM), School of Health Professions Education, Maastricht University, Maastricht (WNKAvM), the UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands (AJCS), Department of Neurology, UZ Brussel and Vrije Universiteit Brussel, Brussels, Belgium (AJCS), Department of Neurology, Leiden University Medical Center, Leiden (MJHW), Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen (MJHW), Department of Clinical Epidemiology, Leiden University Medical Center (BS, MSA), Department of Intensive Care, Leiden University Medical Center, Leiden, the Netherlands (MSA).
Background:
Stroke patients admitted to an intensive care unit (ICU) follow a particular survival pattern with a high short-term mortality, but if they survive the first 30 days, a relatively favourable subsequent survival is observed.
Objectives:
The development and validation of two prognostic models predicting 30-day mortality for ICU patients with ischaemic stroke and for ICU patients with intracerebral haemorrhage (ICH), analysed separately, based on parameters readily available within 24 h after ICU admission, and with comparison with the existing Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) model.
Design:
Observational cohort study.
Setting:
All 85 ICUs participating in the Dutch National Intensive Care Evaluation database.
Patients:
All adult patients with ischaemic stroke or ICH admitted to these ICUs between 2010 and 2019.
Main Outcome Measures:
Models were developed using logistic regressions and compared with the existing APACHE-IV model. Predictive performance was assessed using ROC curves, calibration plots and Brier scores.
Results:
We enrolled 14 303 patients with stroke admitted to ICU: 8422 with ischaemic stroke and 5881 with ICH. Thirty-day mortality was 27% in patients with ischaemic stroke and 41% in patients with ICH. Important factors predicting 30-day mortality in both ischaemic stroke and ICH were age, lowest Glasgow Coma Scale (GCS) score in the first 24 h, acute physiological disturbance (measured using the Acute Physiology Score) and the application of mechanical ventilation. Both prognostic models showed high discrimination with an AUC 0.85 [95% confidence interval (CI), 0.84 to 0.87] for patients with ischaemic stroke and 0.85 (0.83 to 0.86) in ICH. Calibration plots and Brier scores indicated an overall good fit and good predictive performance. The APACHE-IV model predicting 30-day mortality showed similar performance with an AUC of 0.86 (95% CI, 0.85 to 0.87) in ischaemic stroke and 0.87 (0.86 to 0.89) in ICH.
Conclusion:
We developed and validated two prognostic models for patients with ischaemic stroke and ICH separately with a high discrimination and good calibration to predict 30-day mortality within 24 h after ICU admission.
Trial Registration:
Trial registration: Dutch Trial Registry ( https://www.trialregister.nl/ ); identifier: NTR7438.
