Development of an assessment sheet for fall prediction in stroke inpatients in convalescent rehabilitation wards in Japan

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• 作者：Youichi Nakagawa (1)
  Katsuhiko Sannomiya (2)
  Makiko Kinoshita (3)
  Tsutomu Shiomi (4)
  Kouhei Okada (5)
  Hisayo Yokoyama (6)
  Yukiko Sawaguti (7)
  Keiko Minamoto (1)
  Chang-nian Wei (1)
  Shoko Ohmori (1)
  Susumu Watanabe (2)
  Koichi Harada (8)
  Atsushi Ueda (1)
  
• 关键词：Fall ; Stroke ; Risk factor ; Rehabilitation ; Assessment
• 刊名：Environmental Health and Preventive Medicine
• 出版年：2008
• 出版时间：May 2008
• 年：2008
• 卷：13
• 期：3
• 页码：138-147
• 全文大小：284KB
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• 作者单位：Youichi Nakagawa (1)
  Katsuhiko Sannomiya (2)
  Makiko Kinoshita (3)
  Tsutomu Shiomi (4)
  Kouhei Okada (5)
  Hisayo Yokoyama (6)
  Yukiko Sawaguti (7)
  Keiko Minamoto (1)
  Chang-nian Wei (1)
  Shoko Ohmori (1)
  Susumu Watanabe (2)
  Koichi Harada (8)
  Atsushi Ueda (1)
  
  1. Department of Preventive and Environmental Medicine, Graduate School of Medical and Pharmaceutical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto, 860-8556, Japan
  2. Kumamoto Kinoh Hospital, Kumamoto, Japan
  3. Hatsudai Rehabilitation Hospital, Tokyo, Japan
  4. Morinomiya Hospital, Osaka, Japan
  5. Chikamori Rehabilitation Hospital, Kochi, Japan
  6. Ukai Rehabilitation Hospital, Nagoya, Japan
  7. Ohta Atami Hospital, Fukushima, Japan
  8. Department of Microbiology and Environmental Chemistry, School of Health Sciences, Kumamoto University, Kumamoto, Japan
  

文摘

Objective We 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. Methods The 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. Conclusion We 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.