Literature DB >> 16497980

Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?

Sven K Schiemanck1, Gert Kwakkel, Marcel W M Post, L Jaap Kappelle, Arie J H Prevo.   

Abstract

BACKGROUND AND
PURPOSE: To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke.
METHODS: Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in logistic regression analyses. Model 1 was derived on the basis of clinical variables; for model 2, neuroimaging variables were added to model 1. Independent variables were stroke severity (National Institutes of Health Stroke Scale), consciousness (Glasgow Coma Scale), urinary continence, demographic variables (age, gender, relationship, educational level), hospital of admission, and clinical instruments: sitting balance (trunk control test), motor functioning (Motricity Index), and ADL (Barthel Index). Neuroimaging variables, determined on conventional MRI scans, included: number of days to scanning, lesion volume, lesion localization (cortex/subcortex), hemisphere, and the presence of white matter lesions. ADL independency was defined as 19 and 20 points on Barthel Index. Differences in accuracy of prediction of ADL independence between models 1 and 2 were analyzed by comparing areas under the curve (AUC) in a receiver operating characteristic analysis.
RESULTS: Model 1 contained as significant predictors: age and ADL (AUC 0.84), correctly predicting 77%. In model 2, number of days to scanning, hemisphere, and lesion volume were added to model 1, increasing the AUC from 0.84 to 0.87, accurately predicting 83% of the surviving patients.
CONCLUSIONS: Clinical variables in the second week after stroke are good predictors for independency in ADL 1 year after stroke. Neuroimaging variables on conventional MRI scans do not have added value in long-term prediction of ADL.

Entities:  

Mesh:

Year:  2006        PMID: 16497980     DOI: 10.1161/01.STR.0000206462.09410.6f

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


  21 in total

1.  Walking performance and its recovery in chronic stroke in relation to extent of lesion overlap with the descending motor tract.

Authors:  H Dawes; C Enzinger; H Johansen-Berg; M Bogdanovic; C Guy; J Collett; H Izadi; C Stagg; D Wade; P M Matthews
Journal:  Exp Brain Res       Date:  2007-12-21       Impact factor: 1.972

2.  A novel fuzzy approach for automatic Brunnstrom stage classification using surface electromyography.

Authors:  Luca Liparulo; Zhe Zhang; Massimo Panella; Xudong Gu; Qiang Fang
Journal:  Med Biol Eng Comput       Date:  2016-12-01       Impact factor: 2.602

3.  The functional role of beta-oscillations in the supplementary motor area during reaching and grasping after stroke: A question of structural damage to the corticospinal tract.

Authors:  Fanny Quandt; Marlene Bönstrup; Robert Schulz; Jan E Timmermann; Maike Mund; Maximilian J Wessel; Friedhelm C Hummel
Journal:  Hum Brain Mapp       Date:  2019-03-29       Impact factor: 5.038

Review 4.  Chronic Stroke Outcome Measures for Motor Function Intervention Trials: Expert Panel Recommendations.

Authors:  Cheryl Bushnell; Janet Prvu Bettger; Kevin M Cockroft; Steven C Cramer; Maria Orlando Edelen; Daniel Hanley; Irene L Katzan; Soeren Mattke; Dawn M Nilsen; Tepring Piquado; Elizabeth R Skidmore; Kay Wing; Gayane Yenokyan
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2015-10

5.  Stroke outcomes are worse with larger leukoaraiosis volumes.

Authors:  Wi-Sun Ryu; Sung-Ho Woo; Dawid Schellingerhout; Min Uk Jang; Kyoung-Jong Park; Keun-Sik Hong; Sang-Wuk Jeong; Jeong-Yong Na; Ki-Hyun Cho; Joon-Tae Kim; Beom Joon Kim; Moon-Ku Han; Jun Lee; Jae-Kwan Cha; Dae-Hyun Kim; Soo Joo Lee; Youngchai Ko; Yong-Jin Cho; Byung-Chul Lee; Kyung-Ho Yu; Mi Sun Oh; Jong-Moo Park; Kyusik Kang; Kyung Bok Lee; Tai Hwan Park; Juneyoung Lee; Heung-Kook Choi; Kiwon Lee; Hee-Joon Bae; Dong-Eog Kim
Journal:  Brain       Date:  2016-12-22       Impact factor: 13.501

6.  Predicting Domain-Specific Health-Related Quality of Life Using Acute Infarct Volume.

Authors:  Chen Lin; Jungwha Lee; Neil Chatterjee; Carlos Corado; Timothy Carroll; Andrew Naidech; Shyam Prabhakaran
Journal:  Stroke       Date:  2017-05-23       Impact factor: 7.914

7.  Quantifying the Impact of Chronic Ischemic Injury on Clinical Outcomes in Acute Stroke With Machine Learning.

Authors:  Yee-Haur Mah; Parashkev Nachev; Andrew D MacKinnon
Journal:  Front Neurol       Date:  2020-01-24       Impact factor: 4.003

Review 8.  Why use a connectivity-based approach to study stroke and recovery of function?

Authors:  Alex R Carter; Gordon L Shulman; Maurizio Corbetta
Journal:  Neuroimage       Date:  2012-03-05       Impact factor: 6.556

9.  Molecular biomarkers in stroke diagnosis and prognosis.

Authors:  Matthew B Maas; Karen L Furie
Journal:  Biomark Med       Date:  2009-08-01       Impact factor: 2.851

10.  Motor neuroprosthesis for promoting recovery of function after stroke.

Authors:  Luciana A Mendes; Illia Ndf Lima; Tulio Souza; George C do Nascimento; Vanessa R Resqueti; Guilherme Af Fregonezi
Journal:  Cochrane Database Syst Rev       Date:  2020-01-14
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.