下肢康复机器人不同强度辅助训练对脑卒中后下肢运动功能恢复的影响及预测因素研究OA

Objective:To analyze the effects of different intensities of lower limb rehabilitation robot-assisted training on post-stroke lower limb motor function recovery and to identify key predictive factors affecting rehabilitation outcomes.Methods:A retrospective study included 104 patients with post-stroke lower limb motor dysfunction who received robot-assisted rehabilitation training at the Second Affiliated Hospital of Xi'an Jiaotong University from January 2022 to December 2024.Patients were divided into the high-intensity group(n=54)and the low-intensity group(n=50)based on training intensity.The two groups were both underwent 8 weeks of intervention.Baseline data,motor function indicators,gait parameters,and lower limb motor function recovery rates were compared between the two groups.Patients were further categorized into good recovery and poor recovery groups based on rehabilitation outcomes.Logistic regression analysis was used to identify factors influencing post-stroke lower limb motor function recovery.Results:After 4 and 8 weeks of intervention,the high-intensity group showed significantly higher Fugl-Meyer assessment of lower extremity(FMA-LE)scores and Berg balance scale(BBS)scores than the low-intensity group(P<0.05).After 8 weeks of intervention,the high-intensity group also showed significantly higher functional ambulation category(FAC)scores,step frequency and walking speed,as well as shorter gait cycle duration compared to the low-intensity group(P<0.05).After 6 months of follow-up,the recovery rate in the high-intensity group was significantly higher than that in the low-intensity group(P<0.05).Univariate and multivariate analyses indicated that comorbid hypertension,comorbid diabetes,training intensity and pre-intervention FMA-LE score were independent factors influencing post-stroke lower limb motor function recovery(P<0.05).Receiver operating characteristic(ROC)curve analysis showed that comorbid hypertension,comorbid diabetes,training intensity,pre-intervention FMA-LE score,and the predictive model constructed based on the above indicators all had certain predictive value for the recovery of lower limb motor function after stroke,with area under the curve(AUC)values of 0.688,0.677,0.675,0.674,and 0.853,respectively,among which the predictive model had the highest AUC.When the cut-off value was applied,the respective sensitivities were 0.750,0.813,0.750,0.663,and 0.792,and the specificities were 0.625,0.542,0.600,0.625,and 0.875.Conclusion:High-intensity lower limb rehabilitation robot-assisted training is more beneficial for post-stroke lower limb motor function recovery.Comorbid hypertension,comorbid diabetes,training intensity and pre-intervention FMA-LE score are key factors affecting rehabilitation outcomes.The predictive model constructed based on these factors shows good predictive performance.