BMC Musculoskeletal Disorders (Jul 2020)

Predicting developmental dysplasia of the hip in at-risk newborns

  • Andreas Roposch,
  • Evangelia Protopapa,
  • Olivia Malaga-Shaw,
  • Yael Gelfer,
  • Paul Humphries,
  • Deborah Ridout,
  • John H. Wedge

DOI
https://doi.org/10.1186/s12891-020-03454-4
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 8

Abstract

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Abstract Background The development of developmental dysplasia of the hip can be attributed to several risk factors and often in combination with each other. When predicting the likelihood of developing this condition, clinicians tend to over and underestimate its likelihood of occurring. Therefore, the study aim is to determine among at-risk newborns how to best predict developmental dysplasia of the hip (DDH) within 8 weeks post-partum. Methods Prospective cohort study in secondary care. Patient population included newborns at-risk for DDH – we assessed 13,276 consecutive newborns for the presence of DDH risk factors. Only newborns with at least one of the predefined risk factors and those showing an abnormal examination of the hip were enrolled (n = 2191). For the development of a risk prediction model we considered 9 candidate predictors and other variables readily available at childbirth. The main outcome measure was ultrasonography at a median age of 8 weeks using consensus diagnostic criteria; outcome assessors were blinded. Results The risk model includes four predictors: female sex (OR = 5.6; 95% CI: 2.9–10.9; P 4000 g (OR = 1.6; 95% CI: 0.6–4.2; P = 0.34), and abnormal examination of hip (OR = 58.8; 95% CI: 31.9, 108.5; P < 0.001). This model demonstrated excellent discrimination (C statistic = 0.9) and calibration of observed and predicted risk (P = 0.35). A model without the variable ‘hip examination’ demonstrated similar performance. Conclusion The risk model quantifies absolute risk of DDH within 8 weeks postpartum in at-risk newborns. Based on clinical variables readily available at the point of childbirth, the model will enhance parental counselling and could serve as the basis for real time decisions prior to discharge from maternity wards.

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