뇌졸중환자에서 재원기간과 퇴원장소 예측을 위한 K-MBI의 유용성

• Published in: Han'guk Chŏnmun Mulli Ch'iryo Hakhoe chi = Journal of the Korean Academy of University Trained Physical Therapists Vol. 14; no. 3; pp. 81 - 89
• Main Authors: 노동국, Dong Koog Noh, 김경호, Kyung Ho Kim, 강대희, Dae Hee Kang, 이지선, Ji Sun Lee, 남경완, Kyung Wan Nam, 신형익, Hyung Ik Shin
• Format: Journal Article
• Language: Korean
• Published: 한국전문물리치료학회 30.09.2007; Korean Academy Of University Trained Physical Therapy
• Subjects: Discharge destination; Korean Modified Barthel Index; Length of stay; Stroke; 물리치료학; Stroke; Discharge destination; Korean Modified Barthel Index; Length of stay
• ISSN: 1225-8962; 2287-982X

The purpose of this study was to utilize the K-MBI (Korean Modified Barthel Index) and subscales of K-MBI in predicting the length of hospital stay (LOS) and the discharge destinations for stroke patients. The study population consisted of 97 stroke patients (57 men and 40 women) admitted to the Seoul National University at the Bundang Hospital. All participants were assessed by K-MBI at admission and discharge after rehabilitation therapy and the information available was investigated at admission. The data were analyzed by using the Mann-Whitney U test, the stepwise multiple regression and the logistic regression. The median LOS was 30 days (mean, 32.8 days; range, 22 to 43 days). The K-MBI score at initiation of rehabilitation therapy (p<.001), the type of stroke and living habits before a stroke were the main explanatory indicators for LOS (p<.05). Within the parameters of K-MBI measured at initiation for rehabilitation, feeding and chair/bed transfer were the explanatory factors for LOS prediction (p<.01). Confidence in the prediction of LOS was 20%. Significant predictors of discharge destination in a logistic regression model were the discharge K-MBI score, sex and hemiplegic side. Dressing in items of discharge K-MBI was the significant predictor of discharge destination. The K-MBI score was the most important factor to predict LOS and discharge destination. Knowledge of these predictors can contribute to more appropriate treatment and discharge planning.