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Statistical analysis plan for the recovery-focused community support to avoid readmissions and improve participation after stroke randomised controlled clinical trial
Kilkenny, Monique F. Olaiya, Muideen T. Cameron, Janette Lannin, Natasha A. Andrew, Nadine E. Thrift, Amanda G. Hackett, Maree Kneebone, Ian Drummond, Avril Thijs, Vincent
Kilkenny, Monique F.
Olaiya, Muideen T.
Cameron, Janette
Lannin, Natasha A.
Andrew, Nadine E.
Thrift, Amanda G.
Hackett, Maree
Kneebone, Ian
Drummond, Avril
Thijs, Vincent
Author
Kilkenny, Monique F.
Olaiya, Muideen T.
Cameron, Janette
Lannin, Natasha A.
Andrew, Nadine E.
Thrift, Amanda G.
Hackett, Maree
Kneebone, Ian
Drummond, Avril
Thijs, Vincent
Brancatisano, Olivia
Kim, Joosup
Reyneke, Megan
Hancock, Shaun
Allan, Liam
Ellery, Fiona
Cloud, Geoffrey
Grimley, Rohan S.
Middleton, Sandy
Cadilhac, Dominique A.
Olaiya, Muideen T.
Cameron, Janette
Lannin, Natasha A.
Andrew, Nadine E.
Thrift, Amanda G.
Hackett, Maree
Kneebone, Ian
Drummond, Avril
Thijs, Vincent
Brancatisano, Olivia
Kim, Joosup
Reyneke, Megan
Hancock, Shaun
Allan, Liam
Ellery, Fiona
Cloud, Geoffrey
Grimley, Rohan S.
Middleton, Sandy
Cadilhac, Dominique A.
Abstract
Background
Unplanned hospital presentations may occur post-stroke due to inadequate preparation for transitioning from hospital to home. The Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke (ReCAPS) trial was designed to test the effectiveness of receiving a 12-week, self-management intervention, comprising personalised goal setting with a clinician and aligned educational/motivational electronic messages. Primary outcome is as follows: self-reported unplanned hospital presentations (emergency department/admission) within 90-day post-randomisation. We present the statistical analysis plan for this trial.
Methods/design
Participants are randomised 1:1 in variable block sizes, with stratification balancing by age and level of baseline disability. The sample size was 890 participants, calculated to detect a 10% absolute reduction in the proportion of participants reporting unplanned hospital presentations/admissions, with 80% power and 5% significance level (two sided). Recruitment will end in December 2023 when funding is expended, and the sample size achieved will be used. Logistic regression, adjusted for the stratification variables, will be used to determine the effectiveness of the intervention on the primary outcome. Secondary outcomes will be evaluated using appropriate regression models. The primary outcome analysis will be based on intention to treat. A p-value ≤ 0.05 will indicate statistical significance. An independent Data Safety and Monitoring Committee has routinely reviewed the progress and safety of the trial.
Conclusions
This statistical analysis plan ensures transparency in reporting the trial outcomes. ReCAPS trial will provide novel evidence on the effectiveness of a digital health support package post-stroke.
Trial registration
ClinicalTrials.gov ACTRN12618001468213. Registered on August 31, 2018.
SAP version
1.13 (October 12 2023)
Protocol version
1.12 (October 12, 2022)
SAP revisions
Nil
Keywords
stroke, digital health, eHealth, statistical analysis plan, randomised controlled clinical trial
Date
2024
Type
Journal article
Journal
Trials
Book
Volume
25
Issue
1
Page Range
1-10
Article Number
Article 78
ACU Department
Nursing Research Institute
Faculty of Health Sciences
Faculty of Health Sciences
Collections
Relation URI
Source URL
Event URL
Open Access Status
Published as ‘gold’ (paid) open access
License
CC BY 4.0
File Access
Open
Notes
© The Author(s) 2024.
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