Related Experiment Video

Updated: Jun 29, 2025

Isokinetic Robotic Device to Improve Test-Retest and Inter-Rater Reliability for Stretch Reflex Measurements in Stroke Patients with Spasticity
08:40

Isokinetic Robotic Device to Improve Test-Retest and Inter-Rater Reliability for Stretch Reflex Measurements in Stroke Patients with Spasticity

Published on: June 12, 2019

7.4K

An automated flowchart for the Modified Rankin Scale assessment: A multicenter inter-rater agreement analysis

Joao Brainer C de Andrade1,2,3,4, Terence J Quinn5, Leonardo Augusto Carbonera6

  • 1Departments of Health Informatics and Neurology, Universidade Federal de São Paulo, São Paulo, Brazil.

International Journal of Stroke : Official Journal of the International Stroke Society
|March 28, 2024
PubMed
Abstract

Insights

The iRankin tool improves consistency in Modified Rankin Scale (mRS) assessments for stroke recovery. This digital solution enhances agreement among healthcare professionals, aiding clinical and research applications.

Area of Science:

  • Neurology
  • Clinical Trials
  • Digital Health

Background:

  • The Modified Rankin Scale (mRS) is crucial for stroke recovery assessment but suffers from inconsistent application among clinical staff.
  • This inconsistency can lead to errors in clinical practice and research.
  • There is a need for standardized tools to improve mRS assessment accuracy.

Purpose of the Study:

  • To develop and validate an interactive, automated digital tool named iRankin for assessing the Modified Rankin Scale.
  • To enhance the congruency and accuracy of mRS scoring among healthcare professionals.

Main Methods:

  • An automated flowchart was developed by vascular neurologists based on mRS literature.
  • The iRankin platform included vignettes and video cases for assessing mRS grades 0-5.
  • Neurological staff from six stroke centers participated in a randomized controlled trial comparing iRankin to usual practice.

Main Results:

  • The iRankin tool significantly improved agreement (weighted kappa) among nurses and vascular neurologists.
  • Participants using iRankin achieved higher accuracy scores in mRS assessment compared to the control group (10.6 vs. 8.2, p=0.02).
  • iRankin adoption was independently associated with improved congruency scores.

Conclusions:

  • The iRankin tool demonstrated substantial to near-perfect agreement across professional categories, enhancing mRS assessment.
  • Further trials are recommended to generalize these findings.
  • The user-friendly, free iRankin platform is accessible online.
Keywords:
Modified Rankin Scaleautomated algorithmstroke

More Related Videos

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

40.3K
Computerized Adaptive Testing System of Functional Assessment of Stroke05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

5.8K

Related Concept Videos

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
236
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
332
Interpreting R Charts01:22

Interpreting R Charts

R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
63
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
194
The R Chart01:02

The R Chart

In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
80