BACKGROUND: this study aims to develop and evaluate a simple fracture risk index for use in frail older people. METHODS: clinical risk factors were assessed at baseline for 2,005 older people (473 males, 1,532 females; mean age 85.7 years, SD 7.1 years) living in aged-care facilities. Fractures were ascertained for 2 years from baseline. Cox regression model was used to identify significant risk factors for fracture. Hazard ratios (HRs) from the model were assigned as weights. The risk index was calculated by multiplying the weights of all risk factors. RESULTS: during a mean follow-up of 1.64 years, 401 fractures occurred in 338 participants. Significant independent clinical risk factors for fracture were institution type, balance, history of previous fracture, cognitive function, number of medications, weight and lower leg length (n = 1,813). The index was capable of identifying higher-risk individuals, with almost an 8-fold increase in the risk of fracture for residents from the lowest 15% to the highest 18% of the score. Among 1-year survivors, a high score (>or=15) indicated approximately a one-in-six chance of fracture, while a low score (<8) indicated only a one-in-forty chance of fracture within a year. The area under the receiver operating characteristic (ROC) curve was 0.69 (95% CI: 0.65-0.72) and 0.68 (95% CI: 0.65-0.71) for identifying someone who would have a fracture in 1 and 2 years respectively. CONCLUSIONS: this risk index could identify individuals at higher fracture risk among institutionalised older people, and thus, could help to rationalise the provision of fracture prevention programs in this population.
BACKGROUND: this study aims to develop and evaluate a simple fracture risk index for use in frail older people. METHODS: clinical risk factors were assessed at baseline for 2,005 older people (473 males, 1,532 females; mean age 85.7 years, SD 7.1 years) living in aged-care facilities. Fractures were ascertained for 2 years from baseline. Cox regression model was used to identify significant risk factors for fracture. Hazard ratios (HRs) from the model were assigned as weights. The risk index was calculated by multiplying the weights of all risk factors. RESULTS: during a mean follow-up of 1.64 years, 401 fractures occurred in 338 participants. Significant independent clinical risk factors for fracture were institution type, balance, history of previous fracture, cognitive function, number of medications, weight and lower leg length (n = 1,813). The index was capable of identifying higher-risk individuals, with almost an 8-fold increase in the risk of fracture for residents from the lowest 15% to the highest 18% of the score. Among 1-year survivors, a high score (>or=15) indicated approximately a one-in-six chance of fracture, while a low score (<8) indicated only a one-in-forty chance of fracture within a year. The area under the receiver operating characteristic (ROC) curve was 0.69 (95% CI: 0.65-0.72) and 0.68 (95% CI: 0.65-0.71) for identifying someone who would have a fracture in 1 and 2 years respectively. CONCLUSIONS: this risk index could identify individuals at higher fracture risk among institutionalised older people, and thus, could help to rationalise the provision of fracture prevention programs in this population.
Authors: Gustavo Duque; Stephen R Lord; Jenson Mak; Kirtan Ganda; Jacqueline J T Close; Peter Ebeling; Alexandra Papaioannou; Charles A Inderjeeth Journal: J Am Med Dir Assoc Date: 2016-06-24 Impact factor: 4.669
Authors: Rathi Ravindrarajah; Nisha C Hazra; Judith Charlton; Stephen H D Jackson; Alex Dregan; Martin C Gulliford Journal: BMJ Open Date: 2018-01-21 Impact factor: 2.692
Authors: Kinda Ibrahim; Mark Mullee; Guiqing Lily Yao; Shihua Zhu; Mark Baxter; Simon Tilly; Cynthia Russell; Helen C Roberts Journal: BMJ Open Date: 2019-08-15 Impact factor: 2.692