Sarah D Berry1, Andrew R Zullo2, Tingting Zhang3, Yoojin Lee3, Kevin W McConeghy2, Douglas P Kiel4. 1. 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. Electronic address: sarahberry@hsl.harvard.edu. 2. 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. 3. Brown University School of Public Health, Providence, RI, United States of America. 4. 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.
Abstract
OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: Our model comprised entirely from routinely collected data was able to identify NH residents at greatest risk for non-vertebral fracture.
OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: Our model comprised entirely from routinely collected data was able to identify NH residents at greatest risk for non-vertebral fracture.
Authors: Lauren A Beaupre; C Allyson Jones; D William C Johnston; Donna M Wilson; Sumit R Majumdar Journal: J Am Geriatr Soc Date: 2012-06-15 Impact factor: 5.562
Authors: J M Chandler; S I Zimmerman; C J Girman; A R Martin; W Hawkes; J R Hebel; P D Sloane; L Holder; J Magaziner Journal: JAMA Date: 2000 Aug 23-30 Impact factor: 56.272
Authors: G Ioannidis; J Flahive; L Pickard; A Papaioannou; R D Chapurlat; K G Saag; S Silverman; F A Anderson; S H Gehlbach; F H Hooven; S Boonen; J E Compston; C Cooper; A Díez-Perez; S L Greenspan; A Z Lacroix; R Lindsay; J C Netelenbos; J Pfeilschifter; M Rossini; C Roux; P N Sambrook; E S Siris; N B Watts; J D Adachi Journal: Osteoporos Int Date: 2012-04-12 Impact factor: 4.507
Authors: Ahmed M Negm; George Ioannidis; Micaela Jantzi; Jenn Bucek; Lora Giangregorio; Laura Pickard; John P Hirdes; Jonathan D Adachi; Julie Richardson; Lehana Thabane; Alexandra Papaioannou Journal: BMC Geriatr Date: 2018-12-27 Impact factor: 3.921