Department of Preventive and Environmental Medicine, Graduate School of Medical and Pharmaceutical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto, 860-8556, Japan,
Environ Health Prev Med. 2008 May;13(3):138-47. doi: 10.1007/s12199-007-0023-8. Epub 2008 Apr 5.
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.
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.
(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.
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.
我们开发了一种评估表，用于预测中风住院患者的跌倒风险，以便病房工作人员在患者入院时即可为每位患者制定预防跌倒策略。
该研究包括三个步骤：（1）制定数据采样表，记录与中风住院患者跌倒风险相关的变量，并使用该表对住院患者进行从入院到出院的随访调查；（2）对本研究对象的特征进行分析，并使用 Cox 回归分析选择跌倒风险比（HR）较高的变量；（3）根据第二步确定的 HR，为跌倒预测开发一个评估表，其中包含每个变量的积分系数。
（1）本调查的对象为来自 17 家医院的 704 名住院患者，其中 270 名为跌倒患者。（2）我们选择了 7 个变量作为首次跌倒的预测因子：中枢性瘫痪、既往跌倒史、使用精神药物、视力障碍、尿失禁、运动方式和认知障碍。（3）我们结合每个变量的可能系数制作了 960 个试验模型，最终选择了最适合的模型，除了运动方式，其他变量都赋予了 1 的系数。该模型的 ROC 曲线下面积为 0.73，敏感性和特异性分别为 0.70 和 0.69（4/5 切点）。根据本研究对象的评估表计算的得分呈正态分布，跌倒者的平均得分（4.94±1.29）明显高于非跌倒者（3.65±1.58）（P=0.001）。每个患者的日常生活活动（ADL）指标巴氏指数的值与每个患者的评估得分成正比。
我们开发了一种用于预测中风住院患者跌倒的评估表，该表可用于在患者入院时立即筛查有跌倒风险的患者。
