Post-Stroke Recovery Data Repository
This repository contains various resources related to the study on post-stroke recovery in a mouse model, focusing on the application of the Proportional Recovery Rule (PRR).
Repository Structure
code/
: Contains all the code used for the analysis in this study. Detailed information is available in the README within the code folder.
input/
: This folder contains all datasets used in the publication.
output/
: This directory includes the final results generated for each dataset. Detailed information for each dataset's output can be found in their respective subfolders.
docs/
: Additional documentation related to this project, including extra resources in the form of a README file within this folder.
Methodology Overview
Introduction
The Fugl-Meyer upper extremity score is a widely used assessment tool in clinical settings to evaluate motor function in stroke patients. With a maximum score of 66, higher values indicate better motor performance, while lower values signify greater deficits.
The Proportional Recovery Rule (PRR) suggests that the magnitude of recovery from nonsevere upper limb motor impairment after stroke is approximately 0.7 times the initial impairment. This rule, proposed in 2008, has been applied to various motor and nonmotor impairments, leading to inconsistencies in its formulation and application across studies.
Translating PRR to Deficit Score
In this study, we translated the Fugl-Meyer upper extremity score into a deficit score suitable for use in a mouse model. The PRR posits that the change in impairment can be predicted as 0.7 times the initial impairment, plus an error term. We adapted this rule by fitting a linear regression model without an intercept to relate the initial impairment to the change in impairment.
Data Analysis
Initial Impairment Calculation:
- Initial impairment (d-score) is calculated as the difference between the deficit score at day 3 post-stroke and the baseline deficit score.
Change Observed and Predicted:
- Change observed: Initial impairment minus deficit score on day 28.
- Change predicted: 0.7 times the initial impairment plus an error term.
Cluster Analysis:
- Data were plotted with initial impairment on the x-axis and change observed on the y-axis.
- A linear fit was applied to generate two lines: one based on the proportional recovery rule and one from the data fit.
- Subjects were clustered based on their proximity to these lines, iterating the process until convergence.
Outlier Removal:
- Outliers were identified and removed based on the interquartile range rule both initially and during each iteration of the clustering process.
Results
Cluster Characteristics:
- The final clustering resulted in 65 subjects following the PRR, with a fixed slope of 0.7 and an intercept of -0.42.
- The other cluster contained 21 subjects with a distinct recovery pattern, characterized by a slope of 0.84.
Statistical Analysis:
- The slope of the overall linear fit was found to be 0.93.
- Approximately 75.58% of the subjects adhered to the PRR, indicating the potential relevance of the PRR in the mouse model.
Additional Information
This structured dataset was created with reference to the following publication:
DOI:10.1038/s41597-023-02242-8
If you have any questions or require further assistance, please do not hesitate to reach out to us. Contact us via email at markus.aswendtATuk-koeln.de or aref.kalantari-sarcheshmehATuk-koeln.de.