This is a cross-sectional study. To evaluate the effectiveness of a novel finger Kinematic Parameter-Based Tool in the grip and release (G&R) test for assessing degenerative cervical myelopathy (DCM). The development and progression of DCM symptoms are gradual and obscure. Although previous studies have objectively evaluated hand movements specific to myelopathy using the G&R test, virtual reality, or wearable sensors, these methods have limitations, such as limited discrimination or inconvenience for simple screening. Consequently, there is a need to develop effective screening methods. Totally, 297 asymptomatic volunteers and 258 DCM patients were enrolled. This system comprises a wearable acceleration/gyro sensor. The acceleration/gyro sensor was placed on the little finger of the participants to perform 40 cycles of full-range G&R as quickly as possible. The collected data were then transformed into kinematic parameters using sensor-based software and R studio software (version: RStudio 2022.07.2+576, Boston, USA). Gender, age, and body mass index (BMI) subgroups (classified as BMI<18.5-below normal weight; 18.5≤BMI<25-normal weight group; BMI≥25-overweight group) were matched as predictor variables, and 201 pairs were matched. Nonparametric analysis using the Mann-Whitney U test was used for diagnosing the differences between the two groups, and Kruskal-Wallis's test followed by the Mann-Whitney U test was used for analyzing the differences among three different age groups (<40, 41-60, and >60 yr group). The cut-off value of 10s G&R cycles and a combined parameter were determined using receiver operating characteristics curve analysis, area under the curve, and Youden index. The authors found that little finger kinematic parameters were significantly lower in DCM patients than in asymptomatic participants. The optimal diagnostic indicator appeared to be the average of the top 10 linear accelerations with an area under the curve of 0.923. The Finger Kinematic Test System is an objective, practical, and quantitative utility that appears to have the capacity to diagnose and evaluate the severity of DCM. 3.
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