Literature DB >> 25633632

Development and Validation of Prognostic Indices for Recovery of Physical Functioning Following Stroke: Part 1.

Barbara E Bates1,2, Dawei Xie3, Pui L Kwong3, Jibby E Kurichi3, Diane Cowper Ripley4, Claire Davenport2, W Bruce Vogel4,5, Margaret G Stineman3,6.   

Abstract

OBJECTIVE: To develop a prognostic index using Functional Independence Measure grades and stages that would enable clinicians to determine the likelihood of achieving a level of minimum assistance with physical functioning after a stroke. Grades define varying levels of physical function, and stages define varying levels of cognitive functioning.
DESIGN: Retrospective cohort study.
SETTING: Veterans Affairs Medical Centers throughout the United States. PARTICIPANTS: Veterans with a diagnosis of a new stroke discharged between October 1, 2006, and September 30, 2008, who were below physical grade IV (requiring minimal assistance) at initial rehabilitation assessment. MAIN OUTCOME MEASURE: Achievement of physical grade IV or above at final rehabilitation assessment.
RESULTS: Physical grade IV was reached by 25.8% of participants who were initially below this grade. Seven variables remained independently predictive of physical grade IV after adjustment. These variables were assigned the following points: age, ≤69 years = 2, 70-79 years = 1, ≥80 years = 0; initial physical grade, I = 0, II = 3, III = 4; initial cognitive stage, I or II = 0, III = 2, IV or V = 3, VI or VII = 4; absence of renal failure = 1; no serious nutritional compromise = 3; the type of rehabilitation services received, consultative = 0, comprehensive = 4; and recovery time between admission and discharge physical grade assessment, 1-2 days = 0, 3-7 days = 4, and ≥8 days = 5. The area under the receiver operating characteristic curve was 0.84 and 0.83 for the point system in the derivation and validation cohorts, respectively. The Hosmer-Lemeshow statistic was not significant (P = .93) in the derivation cohort, indicating that the regression model demonstrated adequate fit. The proportions of patients recovered to physical grade IV in the first (score ≥9), second (score = 10-12), third (score = 13-15), and fourth (score >15) score quartiles were 2.72%, 11.38%, 28.96%, and 60.34%, respectively.
CONCLUSION: By using a simple tool, clinicians can forecast the likelihood of recovery to or above the physical grade IV benchmark by the conclusion of rehabilitation services during the acute stroke hospitalization.
Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2015        PMID: 25633632     DOI: 10.1016/j.pmrj.2015.01.011

Source DB:  PubMed          Journal:  PM R        ISSN: 1934-1482            Impact factor:   2.298


  2 in total

Review 1.  Machine learning methods for functional recovery prediction and prognosis in post-stroke rehabilitation: a systematic review.

Authors:  Silvia Campagnini; Chiara Arienti; Michele Patrini; Piergiuseppe Liuzzi; Andrea Mannini; Maria Chiara Carrozza
Journal:  J Neuroeng Rehabil       Date:  2022-06-03       Impact factor: 5.208

2.  Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Authors:  Ching-Heng Lin; Kai-Cheng Hsu; Kory R Johnson; Yang C Fann; Chon-Haw Tsai; Yu Sun; Li-Ming Lien; Wei-Lun Chang; Po-Lin Chen; Cheng-Li Lin; Chung Y Hsu
Journal:  Comput Methods Programs Biomed       Date:  2020-02-01       Impact factor: 5.428

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.