Tennessee Medicine E-Journal



Background: Evaluating spasticity can be challenging, and the condition can pose significant problems when undiagnosed. In this study, a bedside tool for the diagnosis of spasticity was developed, and its inter-rater reliability was tested in a long-term care facility.

Objective: To test the inter-rater reliability of a novel flowchart-style algorithm designed to standardize the diagnosis of spasticity.

Design: Prospective study

Setting: A long-term care facility for veterans and their spouses.

Participants: 43 adult residents of a long-term care facility

Methods: Two movement disorders neurologists independently performed a neurological examination of each subject using the bedside diagnostic algorithm, which examined ten joints bilaterally for spastic postures and pathological indicators to determine the presence or absence of spasticity.

Main Outcome Measurements: The primary outcome measure was the extent of rater-agreement evaluated using Cohen’s kappa and interpreted according to the Koch-Landis scale for agreeability.

Results: Using the algorithm, the neurologists reached agreement in 88% of the 43 subjects evaluated (spasticity present = 7; spasticity absent = 31). Substantial inter-rater reliability was calculated (Cohen’s kappa = 0.662, 95% CI = 0.37-0.92, kappa max 0.80).

Conclusions: Spasticity is an under-diagnosed condition, and this novel bedside algorithm resulted in substantial inter-rater agreement on spasticity diagnosis. While more research is needed to improve and validate this instrument, use of this or a similar tool by primary care providers may lead to faster and more accurate identification of patients who would benefit from referral for evaluation and treatment of spasticity.

Level of Evidence: VI

Hudson Figure 1.tiff (742 kB)
Hudson Figure 1.tiff

Hudson Figure 2.pdf (69 kB)
Hudson Figure 2.pdf

Table 1 - demographics.docx (12 kB)
Table 1 - demographics.docx