# Developing and validating a frailty score based on patient-reported outcome 3 months after stroke: A Riksstroke-based study

## TL;DR

This study created a new patient-reported frailty score for stroke survivors using data from a large Swedish registry, showing it is reliable and predicts mortality.

## Contribution

A novel patient-reported frailty score was developed and validated using item response theory and real-world registry data.

## Key findings

- A bifactor IRT model best represented the frailty score with two correlated facets: Physical Functioning and Well-being/Mental Health.
- Higher frailty scores were strongly associated with increased mortality in stroke survivors.
- The score showed minimal bias across sex and education, with modest age-related differences.

## Abstract

Background: Frailty is common after stroke and linked to poor outcomes, but many measures are clinician-rated, time-consuming, and not suited to patient-reported data. To address these issues, we developed and validated a frailty score from the Swedish Stroke Register (Riksstroke) three-month follow-up questionnaire.

Methods: We analyzed responses from 19,470 stroke survivors to nine patient-reported items covering function, mood, fatigue, pain and general health, in the 2021–2022 Riksstroke questionnaire. Dimensionality was assessed with Mokken Scale Analysis and exploratory factor analysis. Item response theory (IRT) was used for score computation. Competing graded response IRT models (unidimensional, correlated-factor, bifactor) were compared, and measurement fairness was examined using differential item functioning (DIF) across age, sex, and education. Prognostic validity was tested with Kaplan–Meier curves and Cox regression for all-cause mortality.

Results: From the Mokken Scale Analysis, all items met scalability criteria. Factor analysis suggested two correlated interpretable facets (Physical Functioning; Well-being/Mental Health). A bifactor IRT model provided the best fit to the data, comprising a general frailty dimension while addressing the strong correlation between the facets. DIF was minimal for sex and education, with modest age-related effects. Higher frailty scores were associated with increased mortality in adjusted Cox models and Kaplan–Meier curves. Tools for computing frailty scores are available at https://github.com/joakimwallmark/frailty-irt-scores.

Conclusions: A robust, fair, and prognostically meaningful frailty score can be derived from patient-reported items in Riksstroke. More broadly, the study demonstrates how routinely collected patient-reported outcome measures can be leveraged to build scalable frailty scores, offering efficient cost-effective tools for monitoring outcome and guiding quality improvement in stroke care.