Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, United States of America; Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, MA, United States of America.
Brown University School of Public Health, Providence, RI, United States of America; Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, United States of America.
Bone. 2019 Nov;128:115050. doi: 10.1016/j.bone.2019.115050. Epub 2019 Aug 28.
Tools were unavailable to assess fracture risk in nursing homes (NH); therefore, we developed the Fracture Risk Assessment in Long term care (FRAiL) model. The objective of this validation study was to assess the performance of the FRAiL model to predict 2-year risk of non-vertebral and hip fractures in a separate large cohort of NH residents.
This retrospective cohort study included most long-stay NH residents in the United States (N = 896,840). Hip and non-vertebral fractures were identified using Medicare claims. The Minimum Data Set (MDS) was used to identify characteristics from the original FRAiL model. Multivariable competing risk regression was used to model risk of fracture.
Mean age was 83.8 years (±8.2 years) and 70.7% were women. Over a mean follow-up of 1.52 years (SD 0.65), 41,531 residents (4.6%) were hospitalized with non-vertebral fracture (n = 30,356 hip fractures). In the fully adjusted model, 14/15 model characteristics remained significant predictors of non-vertebral fracture. Female sex (HR = 1.55, 95% CI 1.52, 1.59), wandering (HR = 1.30, 95% CI 1.26, 1.34), and falls (HR = 1.28, 95% CI 1.26, 1.31) were strongly associated with non-vertebral fracture rate. Total dependence in ADLs (versus independence) was associated with a decrease in non-vertebral fracture rate (HR = 0.57, 95% CI 0.52, 0.64). Discrimination was moderate in men (C-index = 0.68 for hip, 0.66 for non-vertebral) and women (C-index = 0.68 for hip, 0.65 for non-vertebral), and calibration was excellent.
Our model comprised entirely from routinely collected data was able to identify NH residents at greatest risk for non-vertebral fracture.
目前尚无工具可用于评估养老院（NH）中的骨折风险；因此，我们开发了骨折风险评估在长期护理中的模型（FRAiL）。本验证研究的目的是评估 FRAiL 模型在另一个大型 NH 居民队列中预测 2 年非椎体和髋部骨折风险的性能。
本回顾性队列研究纳入了美国大多数长期 NH 居民（N=896840）。使用医疗保险索赔来确定髋部和非椎体骨折。最小数据集（MDS）用于识别原始 FRAiL 模型中的特征。多变量竞争风险回归用于对骨折风险进行建模。
平均年龄为 83.8±8.2 岁，70.7%为女性。在平均 1.52 年（标准差 0.65）的随访期间，41531 名居民（30356 例髋部骨折）因非椎体骨折住院治疗。在完全调整的模型中，15 个模型特征中有 14 个仍然是非椎体骨折的显著预测因子。女性（HR=1.55，95%CI 1.52，1.59）、游荡（HR=1.30，95%CI 1.26，1.34）和跌倒（HR=1.28，95%CI 1.26，1.31）与非椎体骨折发生率密切相关。日常生活活动的完全依赖（与独立相比）与非椎体骨折发生率降低相关（HR=0.57，95%CI 0.52，0.64）。男性（髋部 C 指数=0.68，非椎体 C 指数=0.66）和女性（髋部 C 指数=0.68，非椎体 C 指数=0.65）的区分度适中，校准度良好。
我们的模型完全由常规收集的数据组成，能够识别出非椎体骨折风险最高的 NH 居民。
