Bibliographic Details
| Title: |
Statistical analysis plan for the Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke randomised controlled clinical trial |
| Authors: |
Monique F. Kilkenny, Muideen T. Olaiya, Janette Cameron, Natasha A. Lannin, Nadine E. Andrew, Amanda G. Thrift, Maree Hackett, Ian Kneebone, Avril Drummond, Vincent Thijs, Olivia Brancatisano, Joosup Kim, Megan Reyneke, Shaun Hancock, Liam Allan, Fiona Ellery, Geoffrey Cloud, Rohan S. Grimley, Sandy Middleton, Dominique A. Cadilhac, on behalf of the Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke (ReCAPS) investigators |
| Source: |
Trials, Vol 25, Iss 1, Pp 1-10 (2024) |
| Publisher Information: |
BMC, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Medicine (General) |
| Subject Terms: |
Stroke, Digital health, eHealth, Statistical analysis plan, Randomised controlled clinical trial, Medicine (General), R5-920 |
| More Details: |
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 |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1745-6215 |
| Relation: |
https://doaj.org/toc/1745-6215 |
| DOI: |
10.1186/s13063-023-07864-2 |
| Access URL: |
https://doaj.org/article/141905639e0c4248bb89f755ce21a3a3 |
| Accession Number: |
edsdoj.141905639e0c4248bb89f755ce21a3a3 |
| Database: |
Directory of Open Access Journals |
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