Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
Hebrew SeniorLife, Institute for Aging Research, Boston, Massachusetts.
J Gerontol A Biol Sci Med Sci. 2018 May 9;73(6):763-769. doi: 10.1093/gerona/glx147.
Strategies used to predict fracture in community-dwellers may not be useful in the nursing home (NH). Our objective was to develop and validate a model (Fracture Risk Assessment in Long-term Care [FRAiL]) to predict the 2-year risk of hip fracture in NH residents using readily available clinical characteristics.
The derivation cohort consisted of 419,668 residents between May 1, 2007 and April 30, 2008 in fee-for service Medicare. Hip fractures were identified using Part A diagnostic codes. Resident characteristics were obtained using the Minimum Data Set and Part D claims. Multivariable competing risk regression was used to model 2-year risk of hip fracture. We validated the model in a remaining 1/3 sample (n = 209,834) and in a separate cohort in 2011 (n = 858,636).
Mean age was 84 years (range 65-113 years) and 74.5% were female. During 1.8 years mean follow-up, 14,553 residents (3.5%) experienced a hip fracture. Fifteen characteristics in the final model were associated with an increased risk of hip fracture including dementia severity, ability to transfer and walk independently, prior falls, wandering, and diabetes. In the derivation sample, the concordance index was 0.69 in men and 0.71 in women. Calibration was excellent. Results were similar in the internal and external validation samples.
The FRAiL model was developed specifically to identify NH residents at greatest risk for hip fracture, and it identifies a different pattern of risk factors compared with community models. This practical model could be used to screen NH residents for fracture risk and to target intervention strategies.
用于预测社区居民骨折的策略可能不适用于疗养院（NH）。我们的目的是开发和验证一种模型（长期护理中的骨折风险评估[FRAiL]），该模型使用易于获得的临床特征来预测 NH 居民的 2 年髋部骨折风险。
推导队列由 2007 年 5 月 1 日至 2008 年 4 月 30 日在收费服务 Medicare 中的 419,668 名居民组成。使用部分 A 诊断代码确定髋部骨折。使用最低数据集和部分 D 索赔获得居民特征。多变量竞争风险回归用于建立 2 年髋部骨折风险模型。我们在剩余的 1/3 样本（n = 209,834）和 2011 年的单独队列（n = 858,636）中验证了该模型。
平均年龄为 84 岁（范围为 65-113 岁），74.5%为女性。在 1.8 年的平均随访期间，有 14,553 名居民（3.5%）发生髋部骨折。最终模型中的 15 个特征与髋部骨折风险增加相关，包括痴呆严重程度、独立转移和行走能力、既往跌倒、徘徊和糖尿病。在推导样本中，男性的一致性指数为 0.69，女性为 0.71。校准效果很好。内部和外部验证样本的结果相似。
FRAiL 模型是专门为识别 NH 居民中髋部骨折风险最高的人群而开发的，与社区模型相比，它确定了不同的风险因素模式。这种实用的模型可用于筛选 NH 居民的骨折风险，并针对干预策略。
