Clinical Characteristics of Proper Robot- Assisted Gait Training Group in Non-ambulatory Subacute Stroke Patients
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Objective To identify the clinical characteristics of proper robot-assisted gait training group using exoskeletal locomotor devices in non-ambulatory subacute stroke patients.Methods A total of 38 stroke patients were enrolled in a 4-week robotic training protocol (2 sessions/day, 5 times/week). All subjects were evaluated for their general characteristics, Functional Ambulatory Classification (FAC), Fugl-Meyer Scale (FMS), Berg Balance Scale (BBS), Modified Rankin Scale (MRS), Modified Barthel Index (MBI), and Mini-Mental Status Examination (MMSE) at 0, 2, and 4 weeks. Statistical analysis were performed to determine significant clinical characteristics for improvement of gait function after robot-assisted gait training. Results Paired t-test showed that all functional parameters except MMSE were improved significantly (p<0.05). The duration of disease and baseline BBS score were significantly (p<0.05) correlated with FAC score in multiple regression models. Receiver operating characteristic (ROC) curve showed that a baseline BBS score of ‘9’ was a cutoff value (AUC, 0.966; sensitivity, 91%–100%; specificity, 85%). By repeated-measures ANOVA, the differences in improved walking ability according to time were significant between group of patients who had baseline BBS score of ‘9’ and those who did not have baseline BBS score of ‘9’. Conclusion Our results showed that a baseline BBS score above ‘9’ and a short duration of disease were highly correlated with improved walking ability after robot-assisted gait training. Therefore, baseline BBS and duration of disease should be considered clinically for gaining walking ability in robot-assisted training group.
Abstract
Objective To identify the clinical characteristics of proper robot-assisted gait training group using exoskeletal locomotor devices in non-ambulatory subacute stroke patients.Methods A total of 38 stroke patients were enrolled in a 4-week robotic training protocol (2 sessions/day, 5 times/week). All subjects were evaluated for their general characteristics, Functional Ambulatory Classification (FAC), Fugl-Meyer Scale (FMS), Berg Balance Scale (BBS), Modified Rankin Scale (MRS), Modified Barthel Index (MBI), and Mini-Mental Status Examination (MMSE) at 0, 2, and 4 weeks. Statistical analysis were performed to determine significant clinical characteristics for improvement of gait function after robot-assisted gait training. Results Paired t-test showed that all functional parameters except MMSE were improved significantly (p<0.05). The duration of disease and baseline BBS score were significantly (p<0.05) correlated with FAC score in multiple regression models. Receiver operating characteristic (ROC) curve showed that a baseline BBS score of ‘9’ was a cutoff value (AUC, 0.966; sensitivity, 91%–100%; specificity, 85%). By repeated-measures ANOVA, the differences in improved walking ability according to time were significant between group of patients who had baseline BBS score of ‘9’ and those who did not have baseline BBS score of ‘9’. Conclusion Our results showed that a baseline BBS score above ‘9’ and a short duration of disease were highly correlated with improved walking ability after robot-assisted gait training. Therefore, baseline BBS and duration of disease should be considered clinically for gaining walking ability in robot-assisted training group.
참고문헌 (27)
- Langhammer B, "Exercise and health-related quality of life during the first year following acute stroke: a randomized controlled trial", Brain Inj, 22, pp.135~145 (2008)
- Mehrholz J, "Electromechanical-assisted training for walking after stroke: updated evidence", Stroke, 44, pp.e127~e128 (2013)
- Schwartz I, "The effectiveness of locomotor therapy using robotic-assisted gait training in subacute stroke patients: a randomized controlled trial", PM R, 1, pp.516~523 (2009)
- Morone G, "Who may have durable benefit from robotic gait training? A 2-year follow-up randomized controlled trial in patients with subacute stroke", Stroke, 43, pp.1140~1142 (2012)
- Cortes M, "Improved motor performance in chronic spinal cord injury following upper-limb robotic training", NeuroRehabilitation, 33, pp.57~65 (2013)
- Geroin C, "Systematic review of outcome measures of walking training using electromechanical and robotic devices in patients with stroke", J Rehabil Med, 45, pp.987~996 (2013)
- Holden MK, "Gait assessment for neurologically impaired patients: standards for outcome assessment", Phys Ther, 66, pp.1530~1539 (1986)
- Mehrholz J, "Predictive validity and responsiveness of the functional ambulation category in hemiparetic patients after stroke", Arch Phys Med Rehabil, 88, pp.1314~1319 (2007)
- Duncan PW, "Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident", Phys Ther, 63, pp.1606~1610 (1983)
- Berg KO, "Measuring balance in the elderly: validation of an instrument", Can J Public Health, 83(2), pp.S7~S11 (1992)
- Sulter G, "Use of the Barthel index and modified Rankin scale in acute stroke trials", Stroke, 30, pp.1538~1541 (1999)
- Cifu DX, "Factors affecting functional outcome after stroke: a critical review of rehabilitation interventions", Arch Phys Med Rehabil, 80(5 Suppl 1), pp.S35~S39 (1999)
- Speach DP, "Recovery from stroke: rehabilitation", Baillieres Clin Neurol, 4, pp.317~338 (1995)
- Hu MH, "Early and intensive rehabilitation predicts good functional outcomes in patients admitted to the stroke intensive care unit", Disabil Rehabil, 32, pp.1251~1259 (2010)
- Salter K, "Impact of early vs delayed admission to rehabilitation on functional outcomes in persons with stroke", J Rehabil Med, 38, pp.113~117 (2006)
- Nilsson L, "Walking training of patients with hemiparesis at an early stage after stroke: a comparison of walking training on a treadmill with body weight support and walking training on the ground", Clin Rehabil, 15, pp.515~527 (2001)
- Laufer Y, "The effect of treadmill training on the ambulation of stroke survivors in the early stages of rehabilitation: a randomized study", J Rehabil Res Dev, 38, pp.69~78 (2001)
- Safer VB, "Timing of inpatient rehabilitation initiation in stroke patients: factors influencing early admission", J Phys Ther Sci, 27, pp.1913~1917 (2015)
- Turton A, "When should upper limb function be trained after stroke? Evidence for and against early intervention", NeuroRehabilitation, 17, pp.215~224 (2002)
- Stroemer RP, "Neocortical neural sprouting, synaptogenesis, and behavioral recovery after neocortical infarction in rats", Stroke, 26, pp.2135~2144 (1995)
- Liepert J, "Treatment-induced cortical reorganization after stroke in humans", Stroke, 31, pp.1210~1216 (2000)
- Stevenson TJ, "Detecting change in patients with stroke using the Berg Balance Scale", Aust J Physiother, 47, pp.29~38 (2001)
- Fugl-Meyer AR, "The post-stroke hemiplegic patient. 1: A method for evaluation of physical performance", Scand J Rehabil Med, 7, pp.13~31 (1975)
- Kollen B, "Predicting improvement in gait after stroke: a longitudinal prospective study", Stroke, 36, pp.2676~2680 (2005)
- Blum L, "Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review", Phys Ther, 88, pp.559~566 (2008)
- Wee JY, "Validation of the Berg Balance Scale as a predictor of length of stay and discharge destination in stroke rehabilitation", Arch Phys Med Rehabil, 84, pp.731~735 (2003)
- Makizako H, "Use of the Berg Balance Scale to predict independent gait after stroke: a study of an inpatient population in Japan", PM R, 7, pp.392~399 (2015)
