FRAX®: measure or trust?
DOI:
https://doi.org/10.25759/spmfr.89Abstract
Introduction: FRAXTM (Fracture Risk Assessment Tool) is a tool used to calculate the risk of osteoporotic fracture within the next 10 years, by analyzing certain parameters entered by the clinician. One of these parameters is the Body Mass Index (BMI) and so the measurement of height and weight of the patient is a fundamental procedure as possible influences on the calculated result may affect the therapeutic decision.
Objectives: The authors attempted to identify, in a sample of patients, the percentage of individuals that provide data on weight and height, and to assess its reliability and analyze the possible impact of the use of data provided to calculate the risk of fracture using the FRAXTM tool.
Population and Methods: Cross sectional, non-randomized study. 91 women over 65 years of age (convenience sample) were included. The risk of major and femoral neck fracture was calculated using FRAXTM, applying data supplied by patients (estimated) and the values of weight and height measured by the authors (actual values). Statistically significant differences between the values obtained were sought, and the effects of those differences in therapeutic decisions were evaluated. The SPSS program v15.0 was used for data processing.
Results: Eight women (8,79%) did not provide their weight and / or height. For the remainder, there was an agreement on the estimated and real weight, but a disagreement with regard to height (p <0.001). The actual BMI was higher than the estimated BMI (p = 0.001). The real risk of fracture (major and femoral neck) was lower than the estimated risk of fracture. The indication for drug therapy was slightly lower when the measured data was used.
Conclusions: Most women provided data on their weight and height. Although the weight was correctly assessed, height was overestimated. The FRAXTM results obtained using these data underestimated BMI and overestimated the risk of fracture. Statistically, these results did not influence therapeutic decisions. The authors believe, therefore, that anthropometric data should be objectified whenever possible.
Keywords: Osteoporotic Fractures; Fractures, Bone; Algorithms.
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