Literature DB >> 23632975

External validation of the SEDAN score for prediction of intracerebral hemorrhage in stroke thrombolysis.

Michael V Mazya1, Paolo Bovi, José Castillo, Dalius Jatuzis, Adam Kobayashi, Nils Wahlgren, Niaz Ahmed.   

Abstract

BACKGROUND AND
PURPOSE: The SEDAN score is a prediction rule for assessment of the risk of symptomatic intracerebral hemorrhage (SICH) per the European Cooperative Acute Stroke Study (ECASS) II definition in patients with acute ischemic stroke treated with intravenous thrombolysis. We assessed the performance of the score in predicting SICH per the ECASS II and Safe Implementation of Treatments in Stroke Monitoring Study (SITS-MOST) definitions in the SITS-International Stroke Thrombolysis Register (SITS-ISTR).
METHODS: We calculated the SEDAN score in 34 251 patients with complete data, enrolled into the SITS-ISTR. The risk for SICH by both definitions was calculated per score category. Odds ratios for SICH per point increase of the score were obtained using logistic regression. The predictive performance was assessed using area under the curve of the receiver operating characteristic (AUC-ROC).
RESULTS: The predictive capability for SICH per ECASS II was moderate at AUC-ROC=0.66. With rising scores, there was a moderate increase in risk for SICH per ECASS II (odds ratio, 1.65 per point; 95% confidence interval, 1.59-1.72; P<0.001), with SICH rates between 1.6% for 0 points and 16.9% for ≥ 5 points, average 5.1%. The predictive capability for SICH per SITS-MOST was weaker, AUC-ROC=0.60, with lower increase per score point (odds ratio, 1.36 per point; 95% confidence interval, 1.28-1.46; P<0.001), and SICH rates between 0.8% for 0 points and 5.4% for ≥ 5 points, average 1.8%.
CONCLUSIONS: In this very large data set, the predictive and discriminatory performances of the SEDAN score were only moderate for SICH per ECASS II and low for SICH per SITS-Monitoring Study.

Entities:  

Keywords:  cerebral infarct; database; intracerebral hemorrhage; prognosis; stroke management; thrombolysis

Mesh:

Substances:

Year:  2013        PMID: 23632975     DOI: 10.1161/STROKEAHA.113.000794

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  7 in total

1.  Comparison of 8 scores for predicting symptomatic intracerebral hemorrhage after IV thrombolysis.

Authors:  David Asuzu; Karin Nystrom; Hardik Amin; Joseph Schindler; Charles Wira; David Greer; Nai Fang Chi; Janet Halliday; Kevin N Sheth
Journal:  Neurocrit Care       Date:  2015-04       Impact factor: 3.210

2.  IV thrombolysis in very severe and severe ischemic stroke: Results from the SITS-ISTR Registry.

Authors:  Michael V Mazya; Kennedy R Lees; David Collas; Viiu-Marika Rand; Robert Mikulik; Danilo Toni; Nils Wahlgren; Niaz Ahmed
Journal:  Neurology       Date:  2015-11-06       Impact factor: 9.910

3.  External validation of the SEDAN score: The real world practice of a single center.

Authors:  Sombat Muengtaweepongsa; Pornpoj Prapa-Anantachai; Pornpatr A Dharmasaroja; Pattarawit Rukkul; Pornchai Yodvisitsak
Journal:  Ann Indian Acad Neurol       Date:  2015 Apr-Jun       Impact factor: 1.383

Review 4.  Deep into the Brain: Artificial Intelligence in Stroke Imaging.

Authors:  Eun-Jae Lee; Yong-Hwan Kim; Namkug Kim; Dong-Wha Kang
Journal:  J Stroke       Date:  2017-09-29       Impact factor: 6.967

5.  Not only the Sugar, Early infarct sign, hyperDense middle cerebral artery, Age, Neurologic deficit score but also atrial fibrillation is predictive for symptomatic intracranial hemorrhage after intravenous recombinant tissue plasminogen activator.

Authors:  Sombat Muengtaweepongsa; Pornpoj Prapa-Anantachai; Pornpat A Dharmasaroja
Journal:  J Neurosci Rural Pract       Date:  2017 Jan-Mar

6.  Prediction of stroke thrombolysis outcome using CT brain machine learning.

Authors:  Paul Bentley; Jeban Ganesalingam; Anoma Lalani Carlton Jones; Kate Mahady; Sarah Epton; Paul Rinne; Pankaj Sharma; Omid Halse; Amrish Mehta; Daniel Rueckert
Journal:  Neuroimage Clin       Date:  2014-03-30       Impact factor: 4.881

7.  MRI-Based Predictors of Hemorrhagic Transformation in Patients With Stroke Treated by Intravenous Thrombolysis.

Authors:  Rody El Nawar; Jennifer Yeung; Julien Labreuche; Marie-Laure Chadenat; Duc Long Duong; Maxime De Malherbe; Yves-Sebastien Cordoliani; Bertrand Lapergue; Fernando Pico
Journal:  Front Neurol       Date:  2019-08-27       Impact factor: 4.003

  7 in total

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