Literature DB >> 15917980

Mortality prediction in critical care for acute stroke: Severity of illness-score or coma-scale?

René Handschu1, Mathias Haslbeck, Alexandra Hartmann, Andreas Fellgiebel, Peter Kolominsky-Rabas, Dietmar Schneider, Jörg Berrouschot, Frank Erbguth, Udo Reulbach.   

Abstract

BACKGROUND AND
PURPOSE: The use of early prognostic data provided by various scores in critically ill stroke patients remains unclear. We tested the performance of the Simplified Acute Physiology Score (SAPS) II in prediction of mortality of acute stroke patients in the NeuroCriticalCareUnit (NCCU).
METHODS: During one year every patient admitted to the NCCUs at 2 University hospitals for cerebral ischemia (CI) or intracerebral hemorrhage (ICH) and intubated was included in this study. Data for SAPS (I)/II and the Glasgow Coma Scale (GCS) were collected, and mortality at 10 days, 90 days and 1 year was determined. Prognostic performance of all scores was tested by calculation of receiver operating curve (ROC) and by Cox regression analysis.
RESULTS: 90 patients were included in the study, 49 with ICH and 41 with CI. Mortality after 10 days was 32.2%, after 3 months 58.9% and after 1 year 67.8%. Compared by their area under curve the predictive values were overall quite good for both SAPS (I) (0.77) and SAPS II (0.77) as well as GCS. Motor subscore was equal to total GCS (0.75 vs. 0.73). In Cox regression models all three scores were independent predictors of fatal outcome.
CONCLUSION: SAPS II and SAPS (I) but also the GCS are valuable tools for prediction of short and long-term mortality in acute stroke patients treated in NCCU. The GCS as a predictor for mortality in stroke patients could be further simplified by using its subscore "best motor response" alone.

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Year:  2005        PMID: 15917980     DOI: 10.1007/s00415-005-0853-5

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   4.849


  24 in total

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  11 in total

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3.  [Long short-term memory and Logistic regression for mortality risk prediction of intensive care unit patients with stroke].

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