External Validation of Two Prediction Models for Independent Gait After Stroke

Stroke Clinical Trial

— REPEAT  

Official title:

External Validation of Two Prediction Models for Independent Gait After Stroke

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05039047
• Other study ID #: BASEC-ID 2021-01519
• Status: Recruiting
• Start date: October 19, 2021
• Est. completion date: March 2025

Study information

• Verified date: March 2023
• Source: Luzerner Kantonsspital
• Contact: Janne M. Veerbeek, PhD
• Phone: +41 41 205 13 17
• Email: janne.veerbeek[@]luks.ch
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Regaining independent gait is one of the main goals in stroke rehabilitation and early prediction of gait outcome is important to guide discharge planning at acute stroke units, design rehabilitation and inform patients and relatives. In the last decade, two easy-to-apply prediction models for gait were developed: the EPOS model in the Netherlands and the TWIST model in New Zealand. Although the models' performance in the development cohorts was good, this does not automatically mean that the models are ready for application in clinical practice, as it is unknown whether their performance is also good in an independent cohort from a different country and with different patient characteristics. Such external validation is an essential step towards clinical implementation of prediction models. A mobility-related problem is the occurrence of falls after stroke. Walking is among the Top 3 activities during which stroke patients fall, with the other two activities being transferring or sitting in a wheelchair. Especially soft tissue injuries after a fall are common and in 1-15% of the patients, the fall results in a fracture. Apart from the costs that arise from these injuries, falls have a negative impact on the patient's physical functioning and psychological status, with an increased dependency and fear of falling, resulting in a reduced quality of life. A systematic review found 12 studies that developed fall risk prediction models for either inpatient rehabilitation stroke patients or those living in the community. Important predictors for falls are the presence of hemi-inattention, fall history and balance deficits. However, none of the models had an acceptable performance and predictors were not always captured by a validated assessment, which is an important prerequisite for an unbiased prediction model. The primary aim of this study is to externally validate the EPOS and TWIST models for independent gait after stroke in a heterogeneous sample of subjects admitted to the hospital with an acute stroke. It is hypothesized that the performance of both models in this independent cohort will be lower than in the development cohorts, but still be adequate. The secondary objective is to investigate the occurrence and predictability of falls within the first six months after stroke and its relationship with the prognosis for independent gait within this sample.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 500
• Est. completion date: March 2025
• Est. primary completion date: March 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion criteria:

• First-ever or recurrent stroke as confirmed by computerized tomography and/ or magnetic resonance imaging
• Not able to walk independently within the first 72 hours after stroke (Functional Ambulation Categories <4)
• Age =18 year
• Written informed consent

Exclusion criterion:

• Not able to walk independently before hospital admission (Functional Ambulation Categories <4)

Related Conditions & MeSH terms

• Stroke

Intervention

Other:
• Standard stroke acute care and rehabilitation
According to Swiss national guidelines and local protocols

Locations

Country	Name	City	State
Switzerland	Luzerner Kantonsspital	Lucerne

Sponsors (1)

Lead Sponsor	Collaborator
Janne Veerbeek

Country where clinical trial is conducted

Switzerland, 

References & Publications (9)

Batchelor FA, Mackintosh SF, Said CM, Hill KD. Falls after stroke. Int J Stroke. 2012 Aug;7(6):482-90. doi: 10.1111/j.1747-4949.2012.00796.x. Epub 2012 Apr 12. — View Citation

Lamb SE, Jorstad-Stein EC, Hauer K, Becker C; Prevention of Falls Network Europe and Outcomes Consensus Group. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc. 2005 Sep;53(9):1618-22. doi: 10.1111/j.1532-5415.2005.53455.x. — View Citation

Moons KG, Kengne AP, Grobbee DE, Royston P, Vergouwe Y, Altman DG, Woodward M. Risk prediction models: II. External validation, model updating, and impact assessment. Heart. 2012 May;98(9):691-8. doi: 10.1136/heartjnl-2011-301247. Epub 2012 Mar 7. — View Citation

Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S. PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration. Ann Intern Med. 2019 Jan 1;170(1):W1-W33. doi: 10.7326/M18-1377. — View Citation

Smith MC, Barber PA, Stinear CM. The TWIST Algorithm Predicts Time to Walking Independently After Stroke. Neurorehabil Neural Repair. 2017 Oct-Nov;31(10-11):955-964. doi: 10.1177/1545968317736820. Epub 2017 Nov 1. — View Citation

Steyerberg EW, Moons KG, van der Windt DA, Hayden JA, Perel P, Schroter S, Riley RD, Hemingway H, Altman DG; PROGRESS Group. Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS Med. 2013;10(2):e1001381. doi: 10.1371/journal.pmed.1001381. Epub 2013 Feb 5. — View Citation

Veerbeek JM, Van Wegen EE, Harmeling-Van der Wel BC, Kwakkel G; EPOS Investigators. Is accurate prediction of gait in nonambulatory stroke patients possible within 72 hours poststroke? The EPOS study. Neurorehabil Neural Repair. 2011 Mar-Apr;25(3):268-74. doi: 10.1177/1545968310384271. Epub 2010 Dec 26. — View Citation

Walsh M, Galvin R, Horgan NF. Fall-related experiences of stroke survivors: a meta-ethnography. Disabil Rehabil. 2017 Apr;39(7):631-640. doi: 10.3109/09638288.2016.1160445. Epub 2016 Mar 23. — View Citation

Walsh ME, Galvin R, Boland F, Williams D, Harbison JA, Murphy S, Collins R, Crowe M, McCabe DJH, Horgan F. Validation of two risk-prediction models for recurrent falls in the first year after stroke: a prospective cohort study. Age Ageing. 2017 Jul 1;46(4):642-648. doi: 10.1093/ageing/afw255. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	National Institutes of Health Stroke Scale (0-42 points, lower scores being better)	Neurological functions	Hospital admission, usually within 24 hours poststroke
Other	Trunk Control Test (0-100 points, higher scores being better)	Trunk control	within 72 hours poststroke
Other	Motricity Index - lower extremity subscale (0-100 points, higher scores being better)	Lower extremity isometric muscle strength	within 72 hours poststroke
Other	Medical Research Grading - hip extension (0-5 points, higher scores being better)	Hip extension muscle strength	within 72 hours poststroke
Other	Modified Rankin Scale (0-5 points, lower scores being better)	Global disability	6 weeks poststroke
Other	Modified Rankin Scale (0-5 points, lower scores being better)	Global disability	12 weeks poststroke
Other	Modified Rankin Scale (0-5 points, lower scores being better)	Global disability	26 weeks poststroke
Primary	Functional Ambulation Categories (0-5 points, higher scores being better)	Walking ability (independence)	6 weeks poststroke
Primary	Functional Ambulation Categories (0-5 points, higher scores being better)	Walking ability (independence)	12 weeks poststroke
Primary	Functional Ambulation Categories (0-5 points, higher scores being better)	Walking ability (independence)	26 weeks poststroke
Secondary	Falls	Number of falls	6 weeks poststroke
Secondary	Falls	Number of falls	12 weeks poststroke
Secondary	Falls	Number of falls	26 weeks poststroke