The minimal clinically important difference of the motricity index score

ABSTRACT

Introduction

The Motricity Index (MI) can predict motor function after rehabilitation, but its minimal clinically important difference (MCID) has not been established. The primary study aim was to estimate the MCID value of the MI arm score.

Methods

Between 2017 and 2018, 173 participants hospitalized with confirmed ischemic stroke were recruited into an observational rehabilitation study. Participants with motor weakness as measured by the Fugl-Meyer upper-extremity (FM-UE) and MI with complete baseline and follow-up assessments at 3 months were included in this analysis. The longitudinal recovery of the MI arm score was anchored to having a poor outcome based on the FM-UE recovery (<9) longitudinally. Results reported include the area-under-curve (AUC), along with sensitivity, specificity, and optimal cut-points based on maximizing the Youden statistic.

Results

Sixty-nine patients (median [IQR] age 70 [18] years; 48% male; 54% white) were included in the final analysis. Mean ± standard deviation outcome scores at 3-months were: MI arm: 83.19 ± 22.80; FM-UE: 53.04 ± 17.26. For the primary results, the MI arm score optimal MCID cutoff for observed recovery was 13 points with a sensitivity of 80% (95% Confidence Interval (CI)(67.6%, 92.4%)) and a specificity of 69.0% (95% CI (52.1, 85.8%)), and the AUC was 0.8082 (0.7007, 0.9157).

Conclusions

This was the first study to report the MCID of the MI arm score, as anchored to the FM-UE recovery between acute evaluation and 3-months. The estimated optimal MCID of improvement in the MI arm score was 13 points.

KEYWORDS:

• Stroke rehabilitation
• stroke outcomes
• minimal clinically important difference
• motricity index
• upper limb
• functional outcome measure

Disclosure statement

CL is supported by the VA IK2 CX002104 and VA I21 RX003612.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

This work was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR003096;National Institute of Neurological Disorders and Stroke; U.S. department of veterans affairs.