Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
School of Health & Related Research, University of Sheffield, Sheffield, UK.
Age Ageing. 2022 Mar 1;51(3). doi: 10.1093/ageing/afac031.
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 health care professionals decide which older women with back pain should have a spinal radiograph.
a population-based cohort of 1,635 women aged 65+ years with self-reported back pain in the previous 4 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 calculated for the final model, and a cut-point was identified.
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 was 72.9%. Vfrac identified 93% of those with more than one 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.
the Vfrac clinical tool appears to be 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.
骨质疏松性椎体骨折（OVF）可识别出未来骨折风险较高的人群，但尽管如此，只有不到三分之一的人引起临床关注。本研究的目的是开发一种临床工具，以帮助医疗保健专业人员决定哪些有背痛的老年女性需要进行脊柱 X 光检查。
从初级保健中招募了 1635 名年龄在 65 岁以上、过去 4 个月内自述有背痛的人群，进行了一项基于人群的队列研究。通过自我完成的问卷调查和体格检查收集暴露数据，包括背痛描述和骨质疏松症的传统危险因素。结果是脊柱 X 光片上是否存在 OVF。逻辑回归模型确定了 OVF 的独立预测因素，计算了最终模型的曲线下面积（接收者操作），并确定了一个切点。
平均年龄为 73.9 岁，209 人（12.8%）有 OVF。最终的 Vfrac 模型包含 15 个 OVF 预测因素，AUC 为 0.802（95%CI：0.764-0.840）。敏感性为 72.4%，特异性为 72.9%。Vfrac 确定了 93%有多个 OVF 的患者和三分之二有一个 OVF 的患者。通过纳入自述背痛描述，可提高性能，敏感性提高至 66.5%，但 AUC 降低至 0.742（95%CI：0.696-0.788）。支持未来试验的健康经济学建模是有利的。
Vfrac 临床工具似乎有效，并通过增加自述背痛症状而得到改善。该工具现在需要进行测试，以确定其在现实世界中的临床和成本效益。
