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Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 48 - 48
1 Oct 2018
Galea VP Connelly JW Matuszak SJ Rojanasopondist P Bragdon CR Huddleston JI Rubash HE Malchau H
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Introduction

Within the field of arthroplasty, the use of patient-reported outcome measures (PROMs) is becoming increasingly ubiquitous in an effort to employ more patient-centered methods of evaluating success. PROMs may be used to assess general health, joint-specific pain or function, or mental health. General and joint-specific questionnaires are most often used in arthroplasty research, but the relationship between arthroplasty and mental health is less well understood. Furthermore, longitudinal reports of PROM changes after arthroplasty are lacking in the literature.

Our primary aim was to quantify the improvement in general, joint-specific, and mental health PROMs following total hip arthroplasty (THA) as well as the extent of any deterioration through the 7 years follow-up. Our secondary aim was to identify predictors of clinically significant PROM decline.

Methods

A total of 864 patients from 17 centers across 8 countries were enrolled into a prospective study. Patients were treated with components from a single manufacturer, which have been shown to be well-functioning in other studies.

Patients completed a battery of PROMs preoperatively, and at one, three, five, and seven years post-THA. Changes in PROMs between study visits were assessed via paired tests.

Postoperative trends for each PROM were determined for each subject by the slope of the best-fit line of the four postoperative data points. Significant PROM deterioration was defined as one literature-defined minimum clinically important difference over 5-years. Binary logistic regressions were used to identify independent predictors of significant decline in the EuroQol (EQ-5D) visual analogue scale (VAS) for Health State, 36-Item Short Form Survey (SF-36) physical composite summary (PCS), and SF-36 mental composite summary (MCS).


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 46 - 46
1 Oct 2018
Matuszak SJ Galea VP Rojanasopondist P Connelly JW Bragdon CR Huddleston JI Malchau H
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Introduction

The goal of the current study was to determine if SES affects PROMs in patients treated with THA. Specifically, we sought to determine any potential differences between low and high SES patients in pre-surgical PROMs, post-surgical PROMs, and PROM improvement after surgery while controlling for any potential confounding demographic factors.

Methods

Patients were selected from a clinical registry at an urban tertiary academic medical center. All patients undergoing primary THA between January 1, 2000 and April 1, 2016 were eligible for this study. During this period, patients were asked to complete the Harris Hip Score (HHS), Euro-QoL 5 Dimension (EQ-5D), 0–10 Numerical Rating Scale (NRS) Pain, 0–10 NRS Satisfaction (only given postoperatively), the Charnley Classifier, and the University of California Los Angeles (UCLA) Activity Score.

To determine SES, patients were matched by zip code to corresponding median household income as reported by the United States Census Bureau. Patients were then dichotomized into low and high SES groups using 2016 median household income of $57,617 USD as a cutoff point.

Statistical differences between low and high SES patients were determined for demographic factors, preoperative PROMs, postoperative PROMs, and PROM change. Non-parametric variables were tested with the Mann Whitney U test and categorical variables were tested with the Chi squared test.

Multivariate models were created to determine if SES group was independently predictive of achieving a minimal clinically important improvement (MCII) in PROMs (18.0 for HHS, −2.0 for NRS Pain, and 0.92 for UCLA). As potential confounders, we tested body mass index (BMI), preoperative health state from EQ-5D visual analog scale (EQ VAS), age at surgery, preoperative Charnley class, sex, and time between PROMs.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 47 - 47
1 Oct 2018
Rojanasopondist P Galea VP Connelly JW Matuszak SJ Bragdon CR Rolfson O Malchau H
Full Access

Introduction

As orthopaedics shifts towards value-based models of care, methods of evaluating the value of procedures such as a total hip arthroplasty (THA) will become crucial. Patient reported outcome measures (PROMs) can offer a meaningful way for patient-centered input to factor into the determination of value.

Despite their benefits, PROMs can be difficult to interpret as statistically significant, but not clinically relevant, differences between groups can be found. One method of correcting this issue is by using a minimal clinically important improvement (MCII), defined as the smallest improvement in a PROM determined to be important to patients.

This study aims to find demographic and surgical factors that are independently predictive of failing to achieve a MCII in pain and physical function at 1-year following THA.

Methods

A total of 976 patients were enrolled into a prospective international, multicenter study evaluating the long-term clinical performance of two acetabular shells and two polyethylene liners from a single manufacturer. All patients consented to be followed with plain radiographs and a set of PROMs preoperatively and at 1-year after surgery.

The outcomes considered in this study were achieving literature-defined MCIIs in pain and physical function at one year after THA. The MCII in pain was defined as achieving a 2-point decrease on the Numerical Rating Scale (NRS)-Pain or reporting a 1-year NRS-Pain value of 0, indicating no pain. The MCII in physical function was defined as achieving an 8.29-point increase on the SF-36 Physical Function subscore.

Univariate analyses were conducted to determine if there were statistically significant differences between patients who did achieve and did not achieve a MCII. Variables tested included: demographic and surgical factors, general and mental health state, and preoperative radiographic findings such as deformity and joint space width (JSW). Significant variables were entered into a multivariable binary logistic regression.

Receiver-operating characteristic (ROC) analysis was used to generate cutoff values for significant continuous variables. Youden's index was used to identify cutoff points that maximized both specificity and sensitivity.