Stalenhoef P A, Diederiks J P M, Knottnerus J A, Kester A D M, Crebolder H F J M
Department of General Practice, Maastricht University, Postbox 616, The Netherlands.
J Clin Epidemiol. 2002 Nov;55(11):1088-94. doi: 10.1016/s0895-4356(02)00502-4.
The object of this article was to determine the predictive value of risk factors for recurrent falls and the construction of a fall risk model as a contribution to a mobility assessment for the identification of community-dwelling elderly at risk for recurrent falling in general practice. The design was a prospective cohort study (n = 311). There were four primary health care centers. A sample stratified on previous falls, age, and gender of community-dwelling elderly persons aged 70 years or over (n = 311) was taken from the respondents to a mail questionnaire (n = 1660). They were visited at home to assess physical and mental health, balance and gait, mobility and strength. A 36-week follow-up with telephone calls every 6 weeks was conducted. Falls and fall injuries were measured. During follow-up 197 falls were reported by 33% of the participants: one fall by 17% and two or more falls by 16%. Injury due to a fall was reported by 45% of the fallers: 2% hip fractures, 4% other fractures, and 39% minor injuries. A fall risk model for the prediction of recurrent falls with an area under the curve (AUC) of 0.79, based on logistic regression analysis, showed that the main determinants for recurrent falls were: an abnormal postural sway (OR 3.9; 95% Cl 1.3-12.1), two or more falls in the previous year (OR 3.1; 95% Cl 1.5-6.7), low scores for hand grip strength (OR 3.1; 95% Cl 1.5-6.6), and a depressive state of mind (OR 2.2; 95% CI 1.1-4.5). To facilitate the use of the model for clinical practice, the model was converted to a "desk model" with three risk categories: low risk (0-1 predictor), moderate risk (two predictors), and high risk (> or =3 predictors). A fall risk model converted to a "desk model," consisting of the predictors postural sway, fall history, hand dynamometry, and depression, provides added value in the identification of community-dwelling elderly at risk for recurrent falling and facilitates the prediction of recurrent falls.
本文的目的是确定复发性跌倒风险因素的预测价值，并构建跌倒风险模型，以助力一般实践中对社区居住老年人复发性跌倒风险的识别进行移动性评估。研究设计为前瞻性队列研究（n = 311）。研究选取了四个初级卫生保健中心。从一份邮寄问卷（n = 1660）的受访者中，抽取了70岁及以上社区居住老年人（n = 311）作为样本，样本根据既往跌倒情况、年龄和性别进行分层。研究人员到他们家中进行家访，评估其身心健康、平衡和步态、移动性和力量。研究进行了为期36周的随访，每6周进行一次电话随访。对跌倒和跌倒损伤情况进行了测量。在随访期间，33%的参与者报告了197次跌倒：17%的人发生过一次跌倒，16%的人发生过两次或更多次跌倒。45%的跌倒者报告有跌倒损伤：2%为髋部骨折，4%为其他骨折，39%为轻伤。基于逻辑回归分析构建的用于预测复发性跌倒的跌倒风险模型，曲线下面积（AUC）为0.79，结果显示复发性跌倒的主要决定因素为：姿势摆动异常（比值比[OR] 3.9；95%置信区间[Cl] 1.3 - 12.1）、前一年发生过两次或更多次跌倒（OR 3.1；95% Cl 1.5 - 6.7）、握力得分低（OR 3.1；95% Cl 1.5 - 6.6）以及抑郁情绪（OR 2.2；95% CI 1.1 - 4.5）。为便于在临床实践中使用该模型，该模型被转换为一个“桌面模型”，分为三个风险类别：低风险（0 - 1个预测因素）、中度风险（两个预测因素）和高风险（≥3个预测因素）。一个转换为“桌面模型”的跌倒风险模型，由姿势摆动、跌倒史、握力测量和抑郁等预测因素组成，在识别社区居住的有复发性跌倒风险的老年人方面具有附加价值，并有助于预测复发性跌倒。
