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New Tool Shows Promise in Identifying Patients Who Need Post-Stroke Spasticity Care

by Fred Pennic 07/12/2024 Leave a Comment

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New Tool Shows Promise in Identifying Patients Who Need Post-Stroke Spasticity Care

What You Should Know: 

– Early detection and treatment of post-stroke spasticity (PSS) are essential for improving a patient’s ability to function and overall quality of life after a stroke. 

– To address this need, AbbVie researchers developed the PSS Referral Tool to help clinicians involved in stroke rehabilitation identify and refer patients with PSS more quickly. A recent study investigated the reliability of this tool in a clinical setting.

Study Design and Findings

The researchers conducted a prospective study with three phases. In the first phase, they created standardized videos showing patients undergoing clinical assessments. In the second phase, a panel of PSS experts categorized the videos into different referral categories: urgent referral, routine referral, and periodic monitoring. Finally, in the third phase, the researchers recruited clinicians, including physical therapists, non-injecting physiatrists, and neurologists, from various regions around the world. These clinicians had no prior experience with the PSS Referral Tool and were trained on how to use it before classifying referral needs for patients in the videos.

The researchers assessed inter-rater reliability using a statistical method called the intraclass correlation coefficient (ICC). This score indicates the level of agreement between the clinicians’ ratings. An ICC score closer to 1 reflects better agreement.

The study recruited a total of 50 clinicians from various regions, with approximately 70% having no prior experience with the PSS Referral Tool. The overall ICC for clinician ratings was 0.68, indicating good reliability. The accuracy rates for different referral categories were as follows:

  • Urgent Referral: 69.2% (173/250)
  • Routine Referral: 69.2% (173/250)
  • Periodic Monitoring: 88.0% (220/250)

Interestingly, even clinicians with no experience using the tool were able to correctly classify a high proportion of videos. Clinicians with and without experience correctly classified 14/15 and 13/15 videos, respectively, translating to sensitivity rates of 93.3% and 86.7%.

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