Related Experiment Video
Updated: Feb 1, 2026

Author Spotlight: A Novel 3D-Printed Titanium Implant for Minimally Invasive Treatment of Hip Dysplasia in Young Dogs
Published on: April 19, 2024
The importance of hip shape in predicting hip osteoarthritis
Purpose Of Review:
This narrative review summarizes the evidence relating hip shape and risk of osteoarthritis at the hip, with a focus on the most recent body of work.
Recent Findings:
Hip OA is a prevalent and potentially disabling condition with few effective non-surgical treatment options. Risk factors for hip OA appear to differ somewhat from those at other sites. Variations in hip morphology, whether assessed through standard geometric measures or statistical modeling methods, seem to increase hip OA risk and may provide a novel approach to interventions to reduce or prevent OA. Such variations have also led to focused surgical interventions to "correct" abnormal shape, although comparisons with non-surgical management are lacking.
Summary:
There remains a lack of understanding regarding the optimal management, whether surgical, non-surgical, or a combination, for FAI syndrome. Even less is known regarding other potential morphologic variations that may contribute to OA risk. Additionally, many individuals who have shape variations that would seem to increase their risk will never develop hip OA. Questions remain regarding key risk factors for hip OA development, which individuals should be targeted for therapies, whether directed at symptoms, function, or prevention, and which therapies should be studied and offered. Trials are underway to help address some of these questions.
Related Concept Videos
VSEPR Theory and the Basic Shapes
Predicting Molecular Geometry
Molecular Shape and Polarity
Molecular Shapes
Two regions of electron density in a diatomic...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
First Derivatives and the Shape of a Graph

