| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 14
| Issue : 1 | Page : 75-80 |
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Predicting short-term outcome of Metal-on-Metal Hip Resurfacing (MOMHR): A multivariate analysis using 14 independent variables
Amrit Goyal1, William Macaulay2, Jeffrey A Geller3, Wenbao Wang4, Jonathon D Nyce5
1 Department of Orthopaedics, SMMH Medical College, India
2 Chief, Division of Adult Reconstruction, NYU Langone Health, NY, USA
3 Chief, Division of Hip & Knee Reconstruction, Columbia University Medical Center, NY, USA
4 Physician, Baylor Scott & White Physical Medicine and Rehabilitation, TX, USA
5 Icahn School of Medicine Mount Sinai, NY, USA
Correspondence Address:
Dr. Amrit Goyal
Department of Orthopaedics, SMMH Medical College, Ambala Road, Saharanpur - 247 232, Uttar Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jotr.jotr_18_21
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Introduction: The aim of this study was to research factors affecting the short-term outcome of metal-on-metal hip resurfacing (MOMHR) and develop a multivariate regression model that may predict outcome. Materials and Methods: This was a prospective study of 154 patients who underwent MOMHR and were followed for a minimum of 1 year. Fourteen independent variables (age, gender, diagnosis, co-morbidities, body mass index (BMI), pr-operative Western Ontario and McMaster Universities Osteoarthritis (WOMAC) physical component/stiffness (S)/pain (P), short form 12 (SF-12) physical (SP), SF-12 mental (SM), acetabular and femoral component sizes, operative time, and estimated blood loss) were analyzed using correlation and multivariate regression analyses. Multivariate regression model was tested by using an independent cohort for validation. Results: Correlation analyses found four variables that significantly influence short term MOMHR outcome. These include comorbidities (C, P = 0.0001), preoperative SF-12 mental (SM, P = 0.0004), BMI (P = 0.0006), and gender (G, P = 0.0454). By multivariate analysis, the subsequent regression model was obtained with an R2 value of 0.3816: Outcome = G*4.72 ‒ BMI*0.70 ‒ C*0.11 + SM*0.31 + 87.44. The average predicted outcome using this equation did not differ significantly from the observed WOMAC physical function outcome at a minimum of 1 year postoperatively. Conclusion: To the best of our knowledge, this study is the first reported multivariate analysis of factors affecting MOMHR and confirms the correlation of some of the previously proposed factors such as gender, BMI, comorbidities, and preoperative function. The multivariate regression equation can be used to predict the short-term outcome of MOMHR.
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