Identifying interacting predictors of falling among hospitalized elderly in Japan: A signal detection approach
Identifying interacting predictors of falling among hospitalized elderly in Japan: A signal detection approach
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识别日本住院老年人跌倒的相互作用预测因素：信号检测方法
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
J. Okochi
中科院分区：
文献类型：
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作者：
A. Nabeshima;A. Hagihara;Kazuo Hayashi;S. Nabeshima;J. Okochi
跌倒是一种复杂的现象，涉及多种风险因素的相互作用。作者分析了一家老年病医院的福尔斯相关因素，以阐明老年住院患者福尔斯的多个危险因素的相互作用。受试者为364例患者（平均年龄81.7岁，女性76.7%），年龄60岁及以上，在2000年4月至2001年3月期间住院超过6个月。 使用信号检测模型来确定基线变量，该基线变量最好将样本分为亚组，使用跌倒发生率作为结局变量。在随访期间，91例患者（25%）至少发生1次跌倒事件。在14个自变量中，确定了由6个显著变量组成的高阶相互作用。因此，受试者被分为7个亚组，跌倒率为5.7- 80.9%。我们发现，非卧床不起状态、痴呆和服用镇静剂或安眠药的组合是跌倒率最高的（80.9%）。信号检测分析有助于识别跌倒的多个危险因素的组合，并适用于为每个亚组制定预防方案。
Falling is a complex phenomenon that involves interaction of multiple risk factors. The authors analyzed factors related to falls in a geriatric hospital to elucidate interaction of multiple risk factors for falls in elderly inpatients. Subjects were 364 patients (mean age, 81.7; women 76.7%) who were aged 60 years and over and had been hospitalized for more than 6 months between April 2000 and March 2001. A signal detection model was used to identify baseline variables that best divided the sample into subgroups using incidence of falling as an outcome variable. During a follow‐up period, 91 patients (25%) had at least one incident of fall. Out of 14 independent variables, a higher‐order interaction consisting of six significant variables was identified. Consequently, the subjects were categorized into seven subgroups whose fall rate varied 5.7–80.9%. We found that the combination of non‐bedridden state, dementia, and medication of tranquilizers or sleeping drugs was the highest fall rate (80.9%). Signal detection analysis is useful to identify the combination of multiple risk factors of falling, and applicable to develop prevention programs for each subgroups.