Literature DB >> 27456206

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

G Ntaios1, F Gioulekas2, V Papavasileiou3, D Strbian4, P Michel5.   

Abstract

BACKGROUND AND
PURPOSE: ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated.
METHODS: Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome.
RESULTS: In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001).
CONCLUSIONS: ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke.
© 2016 EAN.

Entities:  

Keywords:  zzm321990ASTRALzzm321990; zzm321990DRAGONzzm321990; zzm321990SEDANzzm321990

Mesh:

Year:  2016        PMID: 27456206     DOI: 10.1111/ene.13100

Source DB:  PubMed          Journal:  Eur J Neurol        ISSN: 1351-5101            Impact factor:   6.089


  9 in total

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Authors:  Kelly L Sloane; Julie J Miller; Amanda Piquet; Brian L Edlow; Eric S Rosenthal; Aneesh B Singhal
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2.  Integrated care for optimizing the management of stroke and associated heart disease: a position paper of the European Society of Cardiology Council on Stroke.

Authors:  Gregory Y H Lip; Deirdre A Lane; Radosław Lenarczyk; Giuseppe Boriani; Wolfram Doehner; Laura A Benjamin; Marc Fisher; Deborah Lowe; Ralph L Sacco; Renate Schnabel; Caroline Watkins; George Ntaios; Tatjana Potpara
Journal:  Eur Heart J       Date:  2022-07-07       Impact factor: 35.855

3.  Low self-reported sports activity before stroke predicts poor one-year-functional outcome after first-ever ischemic stroke in a population-based stroke register.

Authors:  Christian Urbanek; Viola Gokel; Anton Safer; Heiko Becher; Armin J Grau; Florian Buggle; Frederick Palm
Journal:  BMC Neurol       Date:  2018-11-03       Impact factor: 2.474

4.  Effect of glycated hemoglobin index and mean arterial pressure on acute ischemic stroke prognosis after intravenous thrombolysis with recombinant tissue plasminogen activator.

Authors:  Shi-Ying Liu; Wen-Feng Cao; Ling-Feng Wu; Zheng-Bing Xiang; Shi-Min Liu; Hai-Yan Liu; Yang Pan; Feng Nie; Xiao-Mu Wu; Xu-Fang Xie
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5.  Using a Multiclass Machine Learning Model to Predict the Outcome of Acute Ischemic Stroke Requiring Reperfusion Therapy.

Authors:  I-Min Chiu; Wun-Huei Zeng; Chi-Yung Cheng; Shih-Hsuan Chen; Chun-Hung Richard Lin
Journal:  Diagnostics (Basel)       Date:  2021-01-06

6.  Different Scores Predict the Value of Hemorrhagic Transformation after Intravenous Thrombolysis in Patients with Acute Ischemic Stroke.

Authors:  Xiaozan Chang; Xiaoxi Zhang; Guanglin Zhang
Journal:  Evid Based Complement Alternat Med       Date:  2021-10-21       Impact factor: 2.629

7.  Machine Learning Models for Predicting Influential Factors of Early Outcomes in Acute Ischemic Stroke: Registry-Based Study.

Authors:  Po-Yuan Su; Yi-Chia Wei; Hung-Yu Wei; Tsong-Hai Lee; Hao Luo; Chi-Hung Liu; Wen-Yi Huang; Kuan-Fu Chen; Ching-Po Lin
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Review 8.  Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.

Authors:  Anna K Bonkhoff; Christian Grefkes
Journal:  Brain       Date:  2022-04-18       Impact factor: 15.255

Review 9.  Clinical prediction models for mortality and functional outcome following ischemic stroke: A systematic review and meta-analysis.

Authors:  Marion Fahey; Elise Crayton; Charles Wolfe; Abdel Douiri
Journal:  PLoS One       Date:  2018-01-29       Impact factor: 3.240

  9 in total

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