BACKGROUND AND PURPOSE: The objective of this retrospective case-control study was to develop a model for predicting the likelihood of falls among community-dwelling older adults. SUBJECTS: Forty-four community-dwelling adults (> or = 65 years of age) with and without a history of falls participated. METHODS: Subjects completed a health status questionnaire and underwent a clinical evaluation of balance and mobility function. Variables that differed between fallers and nonfallers were identified, using t tests and cross tabulation with chi-square tests. A forward stepwise regression analysis was carried out to identify a combination of variables that effectively predicted fall status. RESULTS: Five variables were found to be associated with fall history. These variables were analyzed using logistic regression. The final model combined the score on the Berg Balance Scale with a self-reported history of imbalance to predict fall risk. Sensitivity was 91%, and specificity was 82%. CONCLUSION AND DISCUSSION: A simple predictive model based on two risk factors can be used by physical therapists to quantify fall risk in community-dwelling older adults. Identification of patients with a high fall risk can lead to an appropriate referral into a fall prevention program. In addition, fall risk can be used to calculate change resulting from intervention.
BACKGROUND AND PURPOSE: The objective of this retrospective case-control study was to develop a model for predicting the likelihood of falls among community-dwelling older adults. SUBJECTS: Forty-four community-dwelling adults (> or = 65 years of age) with and without a history of falls participated. METHODS: Subjects completed a health status questionnaire and underwent a clinical evaluation of balance and mobility function. Variables that differed between fallers and nonfallers were identified, using t tests and cross tabulation with chi-square tests. A forward stepwise regression analysis was carried out to identify a combination of variables that effectively predicted fall status. RESULTS: Five variables were found to be associated with fall history. These variables were analyzed using logistic regression. The final model combined the score on the Berg Balance Scale with a self-reported history of imbalance to predict fall risk. Sensitivity was 91%, and specificity was 82%. CONCLUSION AND DISCUSSION: A simple predictive model based on two risk factors can be used by physical therapists to quantify fall risk in community-dwelling older adults. Identification of patients with a high fall risk can lead to an appropriate referral into a fall prevention program. In addition, fall risk can be used to calculate change resulting from intervention.
Authors: Poonam K Pardasaney; Pengsheng Ni; Mary D Slavin; Nancy K Latham; Robert C Wagenaar; Jonathan Bean; Alan M Jette Journal: Arch Phys Med Rehabil Date: 2014-03-28 Impact factor: 3.966
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Authors: A C Lee; W F Harvey; X Han; L L Price; J B Driban; R R Bannuru; C Wang Journal: Osteoarthritis Cartilage Date: 2018-01-31 Impact factor: 6.576
Authors: Kelson Nonato Gomes da Silva; Lucas Emmanuel Pedro de Paiva Teixeira; Aline Mizusaki Imoto; Alvaro Nagib Atallah; Maria Stella Peccin; Virginia Fernandes Moça Trevisani Journal: Rheumatol Int Date: 2013-03-03 Impact factor: 2.631