만성 뇌졸중 환자들의 독립 보행 예측을 위한 Postural Assessment Scale for Stroke의 변별력과 예측 타당도
Discriminative Ability and Predictive Validity of Postural Assessment Scale for Stroke as Independent Ambulation for Chronic Stroke Patients
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초록
Postural Assessment Scale for Stroke(PASS)은 자세유지와 변환에 관한 평가도구로 신뢰도와 타당도가 입증되었고, 낙상을 예측할 수 있는 평가도구이다. 만성 뇌졸중 환자들의 독립 보행 수준을 예측하는 것은 빠른 사회복귀에 대한 변별력을 알 수 있는 중요한 기능이다. 본 연구의 목적은 만성 뇌졸중 환자를 대상으로 독립 보행을 구분하기 위한 PASS의 변별력과 예측 타당도를 알아보고자 하였다. 재활병원에 입원해 있는 만성 뇌졸중 환자 68명을 대상으로 하였다. 기능적 보행 지수(Functional Ambulation Category(FAC)를 기준으로 독립 보행 군(FAC≥4점)(n=27명)과 불가능 한 군(FAC<4점)(n=41명)으로 분류하였다. PASS의 독립 보행 예측 변별력은 수용자 작업 특성 곡선(area under the curve, AUC)을 구하였고, 예측 타당도는 일반의학적인 특성(나이, 유병 기간)과 PASS의 선별 기준값을 이용하여 교차비를 구하였다. 지역 사회 보행 수준 예측 변별력에 대한 최적의 선별 기준값과 AUC는 PASS정적의 경우 13.50점(ACU=.776), PASS동적의 경우 15.50점(AUC=.802)이었고 PASS총점은 27.50 (AUC=.859)점이었다. 이분형 로지스틱 회귀 분석에서 PASS정적(p<.002), PASS동적(p<.001), PASS총점(p<.001)은 독립 보행 수준을 예측할 수 있는 것으로 확인되었다. PASS는 자세 조절과 균형을 양적으로 평가할 수 있으므로 만성 뇌졸중 환자들의 보행 수준을 예측하거나 변별력이 있는 효과적인 평가 도구로 활용이 가능 할 것이다. 추후 연구에서 보행의 부가적인 요소인 보행지구력, 보행 속도, 자가 균형 자신감을 포함한 연구가 필요하다.
Abstract
The Postural Assessment Scale for Stroke patients(PASS) is used to assess static and dynamic balance & postural control of stroke patients. PASS has demonstrated good measurement properties for reliability and validity & prediction of fall, but its predictive value and discriminative validity for ambulation in stroke patients has not been investigated. The aim of this study was to investigate the predictive and discriminative validity of PASS for ambulation in patients with chronic stroke. A total of 68 stroke patients were recruited from rehabilitation center. The patients were divided in to 2 group by Functional ambulation category(FAC): independently ambulatory group(FAC≥4, n=27) and non-ambulatory group(FAC<4, n=41). Receiver operating characteristic curve(ROC) and adjusted bivariate logistic regression was applied to analyse the predictive value and discriminative validity of PASS-static, PASS-dynamic, PASS-total scores, variables of demographic data(age, duration). The optimal ROC curve was obtained with a cut-off score of 13.50 points for static PASS(AUC=.776), 15.50 points for dynamic PASS(AUC=.802), and 27.50 points for total PASS(AUC=.859), demonstrating the highest percentage of accurately discriminative ability of independently walking. Adjusted bivariate logistic regression found PASS-static(p<.002), PASS-dynamic(p<.001) and PASS-total score(p<.001) to be predictors for ambulation of chronic stroke patients. Our results found PASS to be an accurate predictor of ambulation ability in chronic stroke patients. As a quantitative factor(postural control & balance ability), PASS is an effective predictive and discriminative tool for clinical application. We also recommended further study of additional walking ability factors, such as walking endurance and gait speed and self-perceived balance which are crucial for walking ability.
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