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The TWIST Algorithm Predicts Time to Walking Independently After Stroke
- Source :
- Neurorehabilitation and Neural Repair. 31:955-964
- Publication Year :
- 2017
- Publisher :
- SAGE Publications, 2017.
-
Abstract
- Background and Objective. The likelihood of regaining independent walking after stroke is of concern to patients and their families and influences hospital discharge planning. The objective of this study was to explore factors that could be combined in an algorithm for predicting whether and when a patient will walk independently after stroke. Methods. Adults with new lower limb weakness were recruited within 3 days of having a stroke. Clinical assessment, transcranial magnetic stimulation, and magnetic resonance imaging were completed 1 to 2 weeks poststroke. Classification and regression tree (CART) analysis was used to identify factors that predicted whether a patient achieved independent walking by 6 or 12 weeks, or remained dependent at 12 weeks. Results. We recruited 41 patients (24 women; median age 72 years, range 43-96 years). The CART analysis results were used to create the Time to Walking Independently after STroke (TWIST) algorithm, which made accurate predictions for 95% of patients. Patients with a trunk control test score >40 at 1 week walked independently within 6 weeks. Patients with a trunk control test score
- Subjects :
- Adult
Male
Trunk control
030506 rehabilitation
medicine.medical_specialty
Time Factors
medicine.medical_treatment
Walking
Neuropsychological Tests
Sensitivity and Specificity
Independent walking
03 medical and health sciences
0302 clinical medicine
Physical medicine and rehabilitation
Predictive Value of Tests
medicine
Hospital discharge
Humans
Twist
Stroke
Gait Disorders, Neurologic
Aged
Aged, 80 and over
medicine.diagnostic_test
business.industry
Magnetic resonance imaging
Recovery of Function
General Medicine
Middle Aged
medicine.disease
Magnetic Resonance Imaging
Transcranial Magnetic Stimulation
Transcranial magnetic stimulation
Predictive value of tests
Physical therapy
Female
0305 other medical science
business
human activities
Algorithms
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 15526844 and 15459683
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- Neurorehabilitation and Neural Repair
- Accession number :
- edsair.doi.dedup.....da76e5188f06432229db2ba84c236b29
- Full Text :
- https://doi.org/10.1177/1545968317736820