Risk factors for revision of primary total hip replacement: Results from a national case–control study

Abstract

Objective To study risk factors for revision of primary total hip replacement (THR) in a US population-based sample. Methods Using Medicare claims, we identified beneficiaries from 29 US states who underwent primary THR between 7/1/1995 and 6/30/1996, and followed them through 12/31/2008. Potential cases had ICD-9 codes indicating revision THR. Each case was matched by state with one control THR recipient who was alive and unrevised when the case had revision THR. We abstracted hospital records to document potential risk factors. We examined associations between preoperative factors and revision risk using multivariate conditional logistic regression. Results The analysis data set consisted of 719/836 case-control pairs with complete data for analysis variables. Factors associated with higher revision odds in multivariate models were age ≤75 at primary surgery (OR 1.52, 95% CI 1.20, 1.92), height in highest tertile (OR 1.40, 95% CI 1.06, 1.85), weight in highest tertile (OR 1.66, 95% CI 1.24, 2.22), cemented femoral component (OR 1.44, 95% CI 1.10, 1.87), prior contralateral primary THR (OR 1.36, 95% CI 1.05, 1.76), other prior orthopedic surgery (OR 1.45, 95% CI 1.13, 1.84), and living with others (versus alone; OR 1.26, 95% CI 0.99, 1.61). Conclusion This first US population-based case-control study of risk factors for revision of primary THR showed that younger, taller, and heavier patients and those receiving a cemented femoral component had greater likelihood of revision THR over twelve-year follow-up. Effects of age and body size on revision risk should be addressed by clinicians with patients considering primary THR.

Can patient-reported outcomes predict re-operations after total hip replacement?

“…In a systematic review by Prokopetz et al [13] including 65 articles investigated with revision following THR for any reason as outcome, age (40%) and sex (28%) were the most common variables associated with predicting risk of future revision. This is also supported by later reports Categorical data presented as n (%) and continuous data as mean (standard deviation) for sex [11,13] and age [10][11][12][13]. In our study we also present an association with a higher risk of re-operation for younger patients and males, but these factors are weaker than postoperative PROMs to predict the risk of a late re-operation.…”

“…Factors other than PROMs have been previously reported [10][11][12][13] as contributing to the risk of re-operation, such as high BMI and long surgery time. We have not taken all of these confounders into consideration in our model, which is a limitation that needs to be given attention when interpreting results.…”

“…We have also selected our patients in order to reduce confounding biases and provide a homogenous group to investigate. The previously described studies presenting patient-related factors [10][11][12][13] and PROMs [14][15][16] to predict the risk of future revision following THR used OR (odds ratio) and HR (hazard ration) to predict the risk of revision. But these methods have been declared unsuitable for such conclusions since they lack predictive strength [25].…”

“…There are several reports presenting risk factors for revision following THR, including patient-related factors [10][11][12][13], and implant and surgical procedure-related factors [12,13], as well as PROMs-related factors such as the Harris Hip [14] and Oxford Hip scores [15,16]. To our knowledge there are no reports using time-dependent area under the curve values (AUC-values)/concordance indices (C).…”

Comparative Epidemiology of Revision Arthroplasty: Failed THA Poses Greater Clinical and Economic Burdens Than Failed TKA

“…The etiology of the increase in the number of revision procedures is multifactorial. The increasing absolute number of primary arthroplasties [21,44,53,58], expansion of the indications to include younger and more active individuals [11,18,19,23,29,30,34,42,44,46,49], and certain patient factors such as obesity [55,60], all likely contribute to overall revision rates. Projections based on population studies point to continued increases in the prevalence of revision procedures [22].…”