Prediction of fracture in nursing home residents
Prediction of fracture in nursing home residents
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DOI：
10.1046/j.1532-5415.2002.50354.x
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发表时间：
2002-08-01
影响因子：
6.3
通讯作者：
Magaziner, J
中科院分区：
文献类型：
--
作者：
Girman, CJ;Chandler, JM;Magaziner, J
设计：前瞻性队列研究，随访18个月。设置：在马里兰随机选择47家疗养院。研究对象：1,427名65岁及以上的白人女性疗养院居民，在基线评估后对骨折进行18个月的跟踪调查。测量：通过医生笔记或图表摘要中的X光检查确定骨折；从最小数据集(MDS)中提取的人口学和基线数据。结果：对数据(发展样本)中的随机子集(67%)的探索性分析确定了可能对预测后续骨折很重要的变量，包括居民如何在她房间或相邻走廊的不同位置之间移动(活动能力)、年龄、体重、身高、饮食和穿衣的独立性、尿失禁、对护理的抵抗力、在过去6个月内跌倒、痴呆症评分和其他日常生活活动。根据这些MDS变量的子集得出的简单评分算法在随机验证样本中显示出良好的敏感度(0.70)但较低的特异度(0.39)。结论：在马里兰州47家养老院的1400多名白人女性中开发的评分算法对识别骨折风险增加的女性具有很高的敏感度，可能在有针对性的骨折预防计划中有用。
OBJECTIVES: To investigate cross-validated methods of identifying patients at increased risk of fracture in nursing homes using readily available data.DESIGN: Prospective cohort study with 18 months of follow-up.SETTING: Forty-seven randomly selected nursing homes in Maryland.PARTICIPANTS: One thousand four hundred twenty-seven white female nursing home residents aged 65 and older were followed for fracture for 18 months after baseline assessment.MEASUREMENTS: Fracture ascertained by physician note or x-ray from chart abstraction; demographic and baseline data extracted from the Minimum Data Set (MDS).RESULTS: Exploratory analyses on a random subset (67%) of the data (development sample) identified variables that might be important in predicting subsequent fracture and included variables for how the resident moved between locations in her room or adjacent corridor (mobility), age, weight, height, independence in eating and dressing, urinary incontinence, resistance to care, falls in the previous 6 months, a dementia score, and other activities of daily living. A simple scoring algorithm derived from a subset of these MDS variables showed good sensitivity (.70) but low specificity (.39) in the random validation sample.CONCLUSION: A scoring algorithm developed in more than 1,400 white females from 47 nursing homes in the state of Maryland shows high sensitivity for identifying women at increased risk for fracture and may be useful in targeting fracture prevention programs.