Your browser doesn't support javascript.
loading
A clinical tool to identify older women with back pain at high risk of osteoporotic vertebral fractures (Vfrac): a population-based cohort study with exploratory economic evaluation.
Khera, Tarnjit K; Hunt, Linda P; Davis, Sarah; Gooberman-Hill, Rachael; Thom, Howard; Xu, Yixin; Paskins, Zoe; Peters, Tim J; Tobias, Jon H; Clark, Emma M.
Afiliação
  • Khera TK; Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Hunt LP; Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Davis S; School of Health & Related Research, University of Sheffield, Sheffield, UK.
  • Gooberman-Hill R; NIHR Bristol Biomedical Research Centre, Bristol, UK.
  • Thom H; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Xu Y; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Paskins Z; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Peters TJ; School of Medicine, Keele University, Staffordshire, UK.
  • Tobias JH; Haywood Academic Rheumatology Centre, Midland Partnership NHS Foundation Trust, Stoke-on-Trent, UK.
  • Clark EM; Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Age Ageing ; 51(3)2022 03 01.
Article em En | MEDLINE | ID: mdl-35284926
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 health care professionals decide which older women with back pain should have a spinal radiograph.

METHODS:

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.

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 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.

CONCLUSIONS:

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.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fraturas da Coluna Vertebral / Fraturas por Osteoporose Tipo de estudo: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans Idioma: En Revista: Age Ageing Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fraturas da Coluna Vertebral / Fraturas por Osteoporose Tipo de estudo: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans Idioma: En Revista: Age Ageing Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido