| Literature DB >> 27838806 |
Gianni Turcato1, Gianfranco Cervellin2, Manuel Cappellari3, Antonio Bonora1, Massimo Zannoni1, Paolo Bovi3, Giorgio Ricci1, Giuseppe Lippi4.
Abstract
The availability of prediction tools for risk stratification after acute stroke is seen as a valuable perspective for tailored clinical management. This retrospective study was aimed to identify significant predictors of poor outcome in patients presenting with acute ischemic stroke, which could then be used for constructing a prediction model. The study population consisted of 837 patients admitted to the Stoke Unit of University Hospital of Verona (Italy) for acute ischemic stroke within 12 h of symptoms onset. In multivariate analysis, age, use of thrombolysis, red blood cell distribution width (RDW) and NIHSS score at admission were found to be significant predictors of 3-month functional decline. A nomogram constructed by integrating these four variables exhibited an area under the curve of 0.832 for predicting functional impairment. The >80% risk cut-off derived from the nomogram was associated with 0.91 positive predictive value, whereas a risk probability <10% displayed 0.93 negative predictive value for predicting functional impairment. These results demonstrate that a prediction tool integrating some important clinical, laboratory and demographic variables may enable an efficient risk stratification of poor outcome after acute stroke.Entities:
Keywords: Cerebral ischemia; Nomogram; Outcome; Prediction; Red blood cell distribution width; Stroke
Mesh:
Year: 2017 PMID: 27838806 DOI: 10.1007/s11239-016-1456-y
Source DB: PubMed Journal: J Thromb Thrombolysis ISSN: 0929-5305 Impact factor: 2.300