• Clark, Emma
• Khera, Tarnjit
• Thom, Howard
• Davis, Sarah
• Peters, Tj
• Gooberman-Hill, Rachael
• Hunt, Linda P.
• Paskins, Zoe
• Tobias, Jon
• Xu, Yixin

Abstract

Background: Osteoporotic vertebral fractures (OVFs) identify people at high risk of future fractures, but despite this, less than a third come to clinical attention. The objective of this study was to develop a clinical tool to aid healthcare professionals decide which older women with back pain should have a spinal radiograph. <br/><br/>Methods: A population-based cohort of 1635 women aged 65+ years with self-reported back pain in the previous four months were recruited from primary care. Exposure data were collected through self-completion questionnaires and physical examination including descriptions of back pain and traditional risk factors for osteoporosis.Outcome was the presence/absence of OVFs on spinal radiographs. Logistic regression models identified independent predictors of OVFs, with the Area Under the (Receiver Operating) Curve (AUC) calculated for the final model, and a cut-point identified.<br/><br/>Results: Mean age was 73.9 years and 209 (12.8%) had OVFs. The final Vfrac model comprised 15 predictors of OVF, with an AUC of 0.802 (95%CI 0.764-0.840). Sensitivity was 72.4% and specificity 72.9%. Vfrac identified 93% of those with &gt;1 OVF and two-thirds of those with one OVF. Performance was enhanced by inclusion of self-reported back pain descriptors, removal of which reduced AUC to 0.742 (95%CI 0.696-0.788) and sensitivity to 66.5%. Health economic modelling to support a future trial was favourable.<br/><br/>Conclusions: The Vfrac clinical tool appears valid and is improved by the addition of self-reported back pain symptoms. The tool now requires testing to establish real-world clinical and cost-effectiveness.<br/>

Topics

• impedance spectroscopy
• inclusion
• laser emission spectroscopy
• chemical ionisation