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Arguments for the biological and predictive relevance of the proportional recovery rule

PUBLICATION: 
Journal Article
Authors: 
Jeff Goldsmith, Tomoko Kitago, Angel Garcia de la Garza, Robinson Kundert, Andreas Luft, Cathy Stinear, Winston D Byblow, Gert Kwakkel, John W Krakauer
Year Published: 
2022
Publisher: 
Elife. 2022 Oct 18;11:e80458. doi: 10.7554/eLife.80458.
Identifiers: 
PMID: 36255057 | DOI: 10.7554/eLife.80458
Full-Text on eLife

Abstract

The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explicitly relates change scores to baseline values - an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery.

Conditions & Recovery

Stroke icon
Stroke is the leading cause of disability in the U.S.
Motor Recovery Icon
Write and walk again.