Skip to main navigation Skip to search Skip to main content

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

  • Jeff Goldsmith*
  • , Tomoko Kitago
  • , Angel Garcia de la Garza
  • , Robinson Kundert
  • , Andreas Luft
  • , Cathy Stinear
  • , Winston D. Byblow
  • , Gert Kwakkel
  • , John W. Krakauer
  • *Corresponding author for this work
  • Department of Epidemiology, Mailman School of Public Health Columbia University, New York, NY, USA
  • Burke Neurological Institute
  • Cornell University
  • Center for Neurology and Rehabilitation
  • University of Zurich
  • The University of Auckland
  • Reade, Rheumatology, Amsterdam, The Netherlands
  • Johns Hopkins University
  • Santa Fe Institute

Research output: Contribution to journalArticleAcademicpeer-review

22 Downloads (Pure)

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 explic-itly 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 to 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.
Original languageEnglish
Article numbere80458
JournaleLife
Volume11
Early online date18 Oct 2022
DOIs
Publication statusPublished - 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Arguments for the biological and predictive relevance of the proportional recovery rule'. Together they form a unique fingerprint.

Cite this