Development of an assessment sheet for fall prediction in stroke inpatients in convalescent rehabilitation wards in Japan.
- Author:
Youichi NAKAGAWA
1
;
Katsuhiko SANNOMIYA
;
Makiko KINOSHITA
;
Tsutomu SHIOMI
;
Kouhei OKADA
;
Hisayo YOKOYAMA
;
Yukiko SAWAGUTI
;
Keiko MINAMOTO
;
Chang-Nian WEI
;
Shoko OHMORI
;
Susumu WATANABE
;
Koichi HARADA
;
Atsushi UEDA
Author Information
- Publication Type:Journal Article
- From:Environmental Health and Preventive Medicine 2008;13(3):138-147
- CountryJapan
- Language:English
-
Abstract:
OBJECTIVEWe conducted a study to develop an assessment sheet for fall prediction in stroke inpatients that is handy and reliable to help ward staff to devise a fall prevention strategy for each inpatient immediately upon admission.
METHODSThe study consisted of three steps: (1) developing a data sampling form to record variables related to risk of falls in stroke inpatients and conducting a follow-up survey for stroke inpatients from their admission to discharge by using the form; (2) carrying out analyses of characteristics of the present subjects and selecting variables showing a high hazard ratio (HR) for falls using the Cox regression analysis; (3) developing an assessment sheet for fall prediction involving variables giving the integral coefficient for each variable in accordance with the HR determined in the second step.
RESULTS AND DISCUSSION(1) Subjects of the present survey were 704 inpatients from 17 hospitals including 270 fallers. (2) We selected seven variables as predictors of the first fall: central paralysis, history of previous falls, use of psychotropic medicines, visual impairment, urinary incontinence, mode of locomotion and cognitive impairment. (3) We made 960 trial models in combination with possible coefficients for each variable, and among them we finally selected the most suitable model giving coefficient number 1 to each variable except mode of locomotion, which was given 1 or 2. The area under the ROC curve of the selected model was 0.73, and sensitivity and specificity were 0.70 and 0.69, respectively (4/5 at the cut-off point). Scores calculated from the assessment sheets of the present subjects by adding coefficients of each variable showed normal distribution and a significantly higher mean score in fallers (4.94 +/- 1.29) than in non-fallers (3.65 +/- 1.58) (P = 0.001). The value of the Barthel Index as the index of ADL of each subject was indicated to be in proportion to the assessment score of each subject.
CONCLUSIONWe developed an assessment sheet for fall prediction in stroke inpatients that was shown to be available and valid to screen inpatients with risk of falls immediately upon admission.