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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Objective

To study the 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 July 1, 1995 and June 30, 1996, with followup through December 31, 2008. Potential cases had International Classification of Diseases, Ninth Revision, Clinical Modification codes indicating a revision THR. Each case was matched by state with 1 control THR recipient who was alive and unrevised when the case had a revision THR. We abstracted hospital records to document potential risk factors. We examined the associations between preoperative factors and revision risk using multivariate conditional logistic regression.

Results

The analysis data set contained 719 of 836 case–control pairs with complete data for analysis variables. The factors associated with higher revision odds in multivariate models were age ≤75 years at primary surgery (odds ratio [OR] 1.52 [95% confidence interval (95% CI) 1.20–1.92]), height in the highest tertile (OR 1.40 [95% CI 1.06–1.85]), weight in the 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 a greater likelihood of undergoing a revision THR over a 12-year followup period. Effects of age and body size on revision risk should be addressed by clinicians with patients considering primary THR.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Total hip replacement (THR) is a highly effective intervention to improve pain and fun ction in a hip affected by advanced arthritis. More than 280,000 primary THRs are performed every year in the US (1). However, some patients experience symptomatic prosthesis failure due to a range of problems, including loosening, infection, or dislocation. A subset of these patients subsequently undergoes revision surgery. Prior estimates place the revision risk at ∼1% per year (2, and Katz JN, et al: unpublished observations). Due in part to the growing number of primary procedures, revision of THR is now performed on over 50,000 people every year in the US at a direct cost exceeding $1 billion (1).

Prior studies identify male sex (3, 4), younger age (3–6), high comorbidity scores (3, 5, 7, 8), and uncemented prostheses (4) as risk factors for revision of primary THR. Low surgeon THR procedure volume has also been cited as a risk factor, but only in the early period after revision (7, 9). Additional risk factors have been associated with specific indications for revision, such as infection (10–14). The study of revision risk in primary THR is challenging because it is a relatively infrequent outcome that can occur a decade or more after the primary procedure. An additional methodologic challenge is the high mortality rate among older patients, who often face a higher risk of death than of revision (15, and Katz JN, et al: unpublished observations).

The objective of this study was to evaluate the risk factors for revision of primary THR in the US Medicare population over 12 years of followup. We hypothesized that younger age, male sex, and greater biomechanical load (as represented by height and weight) would be associated with revision risk.

Significance & Innovations

  • Over 280,000 primary and 50,000 revision total hip replacements (THRs) are performed annually in the US.

  • This is the first US population-based study of demographic, clinical, and operative risk factors for revision of primary THR.

  • In this nested case–control study with 12 years of followup, younger age and greater body size (both weight and height) were associated with revision risk, as was use of a cemented femoral component.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Study design and selection of patients.

We performed a nested case–control study of risk factors for revision of hip replacement. A sample of 46,877 Medicare beneficiaries in 29 US states reported to have undergone primary THR surgery between July 1, 1995 and June 30, 1996 was followed up in annual Medicare Provider Analysis and Review billing records through the end of 2008 to identify hospital admissions for revision THR surgery. The states were chosen to provide a wide geographic range across the US. The surgery procedure code identifying revision surgery was 8153 until September 2005, when new International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes of 0070 through 0073 were added for revision THR. We selected all patients with a code for revision hip replacement surgery, which yielded 3,647 putative cases. For each of these potential cases, we randomly selected 1 control from patients who had primary THR in the same state and who were alive and not revised as of the case revision surgery date. All patients were censored at the date of a second THR (in order to reduce the confusion caused by revisions performed on the contralateral rather than the index hip). Cases were eligible to be controls until 2 years prior to their revision surgery, since this was considered a conservative estimate for the first appearance of symptoms ultimately leading to revision.

Identification of cases and controls.

For each of the 3,647 potential cases and 3,647 controls, patient medical records for the dates of the primary THR surgery were requested from the hospitals. For each of the cases, patient medical records for the date of the revision surgery were also requested. Ineligible cases were those whose primary or revision record was inaccessible, whose index surgery was not a primary THR, whose putative revision surgery was shown on the medical record not to be a revision THR, whose primary and revision surgeries were on opposite sides, or whose record showed an ineligible indication for THR (e.g., tumor, acute fracture of hip/pelvis, or history of hip infection). Ineligible controls were those whose index surgery was not a primary THR or whose record indicated an ineligible indication for THR. The cases matched to controls whose records were ineligible or unobtainable were then matched to other eligible controls from providers in the same state. Figures 1 and 2 show the steps used to select matched cases and controls.

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Figure 1. Selection of eligible cases and potential controls. THR = total hip replacement.

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Figure 2. Random selection of one matched control per case.

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Medical record review.

The medical charts were abstracted by trained medical abstractors at Information Collection Enterprises in York, Pennsylvania. The data collected included demographic information, surgical data to determine case eligibility, patient history, lifestyle factors, and operative variables.

Data elements.

Demographic data included age at surgery (dichotomized as 65–75 years and >75 years), sex, race (categorized as white or nonwhite), Medicaid buy-in (a variable that identifies subjects with very low income), and zip code at the time of surgery (for classification of a rural, suburban, or urban residence). Patient history variables reflecting patient status prior to the primary THR included prior surgery on the index and nonindex hip, other major musculoskeletal surgeries, underlying disease leading to THR, height, weight, and comorbidities. The Charlson Comorbidity Index score (16, 17) was calculated from comorbidities documented in the medical chart at the time of primary THR and was dichotomized as 0–1 or >1 for the analysis. Body mass index (BMI) was calculated from height and weight (kg/m2) at the time of THR primary surgery and divided into tertiles (<25/25–29/≥30). Height and weight were divided into tertiles by sex (for men, height in inches [≤68/69–71/≥72] and weight in pounds [≤177/178–203/≥204]; for women, height in inches [≤63/64–65/≥66] and weight in pounds [≤145/146–173/≥174]). Lifestyle factors ascertained at the time of primary THR surgery included smoking habits (both current and past), alcohol use, and living situation (living alone versus living with others).

Operative variables pertaining to the primary THR included type of anesthesia (general/spinal/epidural), American Society of Anesthesiologists (ASA) Physical Status System score, duration of the primary THR surgery (<2.5 versus ≥2.5 hours), and acetabular and femoral prosthesis fixations (cemented or uncemented).

Statistical analysis.

Comparison of available and unavailable records.

We compared the characteristics (ascertained from Medicare claims data) of subjects whose records were obtained from hospitals with subjects whose records were not obtained using the chi-square test for categorical variables and the t-test for continuous factors.

Main analysis with matched data.

The goal of the analysis was to identify factors associated with the revision of a THR. The analysis cohort consisted of those with complete data for the factors being analyzed. Bivariate associations between potential risk factors and revision status were evaluated with McNemar's chi-square test and conditional logistic regression. The variables associated with revision status with P values less than or equal to 0.05 were advanced to multivariate conditional logistic regression models.

Sensitivity analysis.

The predictor variables with the most missing data were height and weight. Subjects with missing data on one or both of these variables were no more likely to have had a revision (i.e., to be a case) than subjects with complete data on these variables (chi-square P = 0.61). Weight and height were moderately correlated (r = 0.39 in men and r = 0.24 in women). These observations support the imputation we performed with the SAS MI and MIANALYZE procedures, which assume that data are missing at random and that the probability of missing values for a given variable is conditioned on the other variables in the analysis.

Unmatched analyses were also performed predicting case status using logistic regression, adjusting for covariates in the final model plus the state of the hospital for the primary THR surgery. For one of these analyses, a 4-category variable was created representing combinations of cemented and uncemented acetabular and femoral components. All analyses were done using SAS, version 9.1 for UNIX.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Description of the study sample.

Record accrual.

From the 3,647 potential cases for which medical records were requested, 836 eligible cases (23%) were obtained (pairs of primary and revision records). Of the unavailable potential cases, hospitals did not respond to 56% of our requests and hospitals were not able to obtain the medical record in 36% of our requests. Another 7% of subjects were ineligible because the revision surgery was performed on the nonindex hip. The reasons reported by hospitals for not obtaining and/or sending the records for abstraction included destruction of records (47%), need for patient consent (14%), inability to find record (13%), hospital refusal (10%), as well as hospital closure (7%), cost (5%), and institutional review board issues (4%).

An analysis comparing eligible cases and controls whose records were obtained to potential cases and controls whose records were not obtained suggested that our study sample was similar to the patients whose records were unavailable with respect to age, sex, race, and comorbidities (see Supplementary Table 1, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658). However, subjects who were included in the analysis were less likely to be operated on at a high-volume hospital (>100 THRs per year in the Medicare population) than subjects whose records were not obtained. This pattern was observed for both cases and controls.

Characteristics of the analysis cohort.

The sample for the main analysis included the 719 case–control pairs with complete data for the predictors of interest. The mean ± SD age of these 1,438 patients was 74.0 ± 5.8 years, 39% were men, 34% had a BMI ≥30 kg/m2, 54% had at least 2 Charlson comorbidities, 5% had Medicaid coverage, and 5% were nonwhite.

Characteristics of the cases at the time of the revision THR.

Case medical records showed multiple clinical indications for revision of the THR. The reasons cited, in order of frequency, were loosening of the prosthesis (51%), repeated dislocations (38%), polyethylene liner wear (14%), osteolysis (11%), periprosthetic fracture of the femur or pelvis (9%), and infection of the THR (5%). When each failure mechanism was stratified by time to revision (≤2 versus >2 years), dislocations were associated with earlier revisions (P < 0.0001), while loosening, osteolysis, liner wear, and periprosthetic fracture were associated with later revisions (P < 0.0001, P < 0.0001, P < 0.0001, and P = 0.04, respectively). The data did not suggest that the risk of revision for infection varied over time.

Results of the bivariate analysis.

Cases were significantly younger than controls, with 67% of the cases versus 55% of the controls between ages 65 and 75 years, yielding an odds ratio (OR) for comparison with those ages >75 years of 1.7 (95% confidence interval [95% CI] 1.4–2.1). Cases were significantly more likely than controls to live with others as opposed to alone at the time of the primary THR (OR 1.4 [95% CI 1.1–1.7]). Cases were also more likely than controls to have had a prior contralateral THR (OR 1.4 [95% CI 1.1–1.8]), to have had prior major musculoskeletal surgery (OR 1.5 [95% CI 1.2–1.9]), to have had a cemented (as opposed to uncemented) femoral component implanted at the index THR (OR 1.3 [95% CI 1.0–1.7]), to be obese (BMI ≥30 kg/m2; OR 1.8 [95% CI 1.4–2.4]), and to be in the highest tertiles for height (OR 1.6 [95% CI 1.3–2.1]) and weight (OR 2.0 [95% CI 1.6–2.7]) (Table 1). We did not observe clinically or statistically meaningful differences between cases and controls in a range of preoperative and operative features, including sex, race, Charlson comorbidity count, Medicaid eligibility, residence population density, smoking status, alcohol intake, hospital and surgeon annual primary THR volumes, ASA Physical Status System score at primary surgery, type of anesthesia, fixation of acetabular component, and surgery duration. Of 8 prosthesis manufacturers, only 2 were significant (for the full results of the bivariate analysis, see Supplementary Table 2, available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658).

Table 1. Predictors of revision THR in bivariate and multivariate analyses*
FactorCases, no. (%)Controls, no. (%)Crude OR (95% CI)Adjusted OR (95% CI)
  • *

    Only statistically significant predictors of revision in bivariate analyses (P ≤ 0.05) were included in the multivariate models. For a full listing of all factors studied, see Supplementary Table 2 (available in the online version of this article at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2151-4658). THR = total hip replacement; OR = odds ratio; 95% CI = 95% confidence interval.

  • Significant.

Age    
 65–75 years485 (67)392 (55)1.73 (1.39–2.15)1.52 (1.20–1.92)
 >75 years234 (33)327 (45)1.01.0
Sex    
 Male294 (41)270 (38)1.14 (0.93–1.40)
 Female425 (59)449 (62)1.0
Living status    
 With others519 (72)469 (65)1.39 (1.11–1.74)1.26 (0.99–1.61)
 Alone200 (28)250 (35)1.01.0
Prior contralateral THR    
 Yes194 (27)147 (20)1.43 (1.12–1.83)1.36 (1.05–1.76)
 No525 (73)572 (80)1.01.0
Other orthopedic surgery    
 Yes247 (34)188 (26)1.49 (1.18–1.88)1.45 (1.13–1.84)
 No472 (66)531 (74)1.01.0
Height (by sex)    
 Tertile 3219 (30)162 (23)1.62 (1.25–2.10)1.40 (1.06–1.85)
 Tertile 2233 (32)232 (32)1.21 (0.96–1.55)1.10 (0.85–1.43)
 Tertile 1267 (37)325 (45)1.01.0
Weight (by sex)    
 Tertile 3282 (39)195 (27)2.04 (1.56–2.67)1.66 (1.24–2.22)
 Tertile 2231 (32)243 (34)1.31 (1.01–1.69)1.12 (0.85–1.48)
 Tertile 1206 (29)281 (39)1.01.0
Cemented femur    
 Yes555 (77)521 (72)1.31 (1.02–1.68)1.44 (1.10–1.87)
 No164 (23)198 (28)1.01.0

Results of the multivariate analysis.

We built multivariate conditional logistic regression models predicting revision using variables statistically significantly associated with case status in unadjusted models. With the exception of the prosthesis manufacturer variables, all variables remained independent significant predictors of revision, including age ≤75 years (OR 1.5 [95% CI 1.2–1.9]), living with others (OR 1.3 [95% CI 1.0–1.6]), prior contralateral THR (OR 1.4 [95% CI 1.1–1.8]), prior musculoskeletal surgery (OR 1.4 [95% CI 1.1–1.8]), cemented femoral component (OR 1.4 [95% CI 1.1–1.9]), height in the highest tertile (OR 1.4 [95% CI 1.1–1.9]), and weight in the highest tertile (OR 1.7 [95% CI 1.2–2.2]) (Table 1).

Results of the sensitivity analyses.

Alternative models replacing weight in tertiles with BMI in tertiles yielded qualitatively the same results as the main model, with height in the highest tertile as well as BMI in the highest tertile being significantly associated with revision risk (OR 1.7 [95% CI 1.3–2.2] for height and OR 1.7 [95% CI 1.3–2.3] for BMI). However, in models replacing height in tertiles with BMI in tertiles, BMI was no longer statistically significantly associated with revision risk. The main analysis was also repeated after excluding the 35 case–control pairs in which infection was listed as an indicator for revision, and the results remained unchanged.

We repeated the multivariate modeling on all 836 case–control pairs after multiple imputation of missing values for variables with incomplete data (living status [1% missing], fixation of femoral component [3% missing], weight [7% missing], height [11% missing], and BMI [11% missing]). The set of pooled estimates based on these models was qualitatively the same as the results of the main analysis, with ORs for the predictor variables differing between the models by no more than 7%.

The results in an unmatched multivariate analysis were nearly identical to the results of the primary matched analysis, with ORs for the predictor variables differing between the 2 analyses by no more than 5%. In a secondary unmatched analysis, a variable representing combinations of cemented and uncemented femoral and acetabular components was substituted for the cemented femoral component variable. The category for uncemented femoral and cemented acetabular components was excluded because only 8 patients received this type of prosthesis. In the analysis, those with cemented femoral and acetabular components had a greater risk for revision than subjects with uncemented femoral and acetabular components (OR 1.5 [95% CI 1.0–2.4]), and those with cemented femoral and uncemented acetabular components also had a greater risk for revision than those with uncemented femoral and acetabular components (OR 1.5 [95% CI 1.1–1.9]). Finally, we found no evidence of an interaction between age at the time of surgery and cementing of the femoral component on the risk of revision.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

We used a nested case–control study to examine the predictors of revision risk in a cohort of Medicare patients who received primary THR surgery between July 1, 1995 and June 30, 1996. We performed followup of the patients in Medicare files through December 31, 2008 and collected data on potential predictors through medical record review. We found the following risk factors for failure leading to revision THR surgery: younger age (ages 65–75 versus >75 years), greater height, greater weight, a cemented femoral component, prior contralateral primary THR surgery, other orthopedic surgery, and living with others (as opposed to living alone) at the time of the primary THR. We also found that greater BMI was predictive of revision with similar tertile ORs to those of weight. The reasons for revision surgery in our case sample were similar to those reported previously in the literature (18).

In contrast to an earlier study of long-term outcomes of THR utilizing Medicare data, the cases in our study were verified to be revisions of the index primary THR by subsequent medical chart review. This ensures a more accurate case determination and eliminates the substantial error inherent in Medicare data, which lack information on laterality (19).

Similar to earlier studies, we found that younger age, in our case ages 65–75 years compared to >75 years, is associated with higher revision risk (3–6). We also found that a prior contralateral primary THR surgery (20) or other orthopedic surgery is associated with an elevated risk of revision. These factors may be surrogates for accessibility to health care, a greater willingness to undergo surgery, and more favorable expectations of THR surgery, or they may reflect orthopedic comorbidity. Similarly, the suggestion in our data that living with others leads to a higher risk of revision surgery may be due to the fact that a social support network facilitates transportation and rehabilitation postsurgery.

Studies regarding the revision risk of cemented and uncemented prostheses are discordant. Since 92% of both patients and controls in our study had uncemented acetabular components, we were unable to study the effect of acetabular fixation. However, we found that the use of cemented femoral components was associated with an increased revision risk. In an unmatched sensitivity analysis, we found no evidence of an interaction between age at the time of surgery and cementing of the femoral component on the risk of revision. Furthermore, the same increased risk for cemented femoral components was found whether the acetabular component was cemented or not. In contrast, an analysis of revision following cemented and uncemented primary THR in New Zealand for cases from 1999–2006 found similar rates of revision for cemented and uncemented femoral components, except in patients ages >75 years, where revision rates for those with cemented components were significantly lower (21). Also, in a meta-analysis of studies from 1991–2004, Morshed et al (22) found that cemented THRs had a longer implant survival than uncemented THRs in large subsets of study populations, but the authors indicated that a more recent year of study publication was associated with lower revision risk for uncemented fixation relative to cemented fixation. The relative utilization of cemented and uncemented fixation for THR varies widely throughout the world. For example, the rate of fully cemented THR in Canada between 2006 and 2007 was only 3% (23), whereas the rate of cemented THR in Sweden in 2009 was ∼70%, and cemented prostheses were the preferred choice for older patients (mean age >70 years) (24). Geographic differences in fixation preferences and patient populations combined with the ongoing development of new techniques and materials make this issue difficult to evaluate.

We found a strong association between the risk of revision THR surgery and height, weight, and BMI. These findings are in contrast to recent studies reporting no significant association between revision risk and BMI (25–28) or body weight (25). Lubbeke et al reported an increased risk of revision for obese patients compared to nonobese patients, although the risk was not statistically significant (hazard ratio 2.2 [95% CI 0.9–5.3]) (27). Two studies have reported lower postoperative functional outcomes for obese patients, but these studies did not find an elevated risk of revision (26, 28). One possible explanation is that obesity may affect revision risk in younger and older age groups differently. Our study was limited to patients who were at least 65 years of age at the time of the primary THR. It may be that in younger patients, obesity both loads the joint (increasing the risk of revision) and reduces physical activity level (reducing risk), while in older patients, such as those that we studied, physical activity may be low irrespective of weight. The lower percentages of obesity observed in European studies, such as 24% in the study by Lubbeke et al (27) and 9% in the study by Haverkamp et al (25), which are in contrast to our cohort (34% obese and 12% morbidly obese [BMI ≥40 kg/m2]), suggest that some earlier studies may have lacked sufficient power to show revision risk from BMI or body weight. We observe that height had an effect on revision that was independent of weight or BMI. This suggests that beyond mass or obesity, the size of the individual's frame affects revision risk. This effect could be due to increased loads and moment arms associated with persons who have larger frames.

We note that revision is not a perfect proxy for the failure of a primary THR. Patients with symptomatic THR failure may not seek care, may seek care but not be offered revision surgery, or may be offered the option of revision surgery and decline. These outcomes could arise from patient comorbidities that make surgery less advisable or from patient preferences for undertaking the procedure upon consideration of its potential risks and benefits. For example, older patients may experience lower rates of prosthesis failure due to lower activity levels, but they may also be less likely to undergo revision for prosthesis failure than younger patients due to concerns about the safety of another major surgery. Similarly, the associations of a prior contralateral primary THR, other orthopedic surgery, and living alone (as noted above) may relate more to the decision of whether to have revision for a failed THR than to the risk of failure per se. We note as well that other orthopedic surgery may be a marker for other orthopedic comorbidities, which in turn may be associated with revision risk.

The results of our study should be viewed in light of several limitations. Since our study focused on persons at least 65 years of age at the time of the index THR between 1995 and 1996, we were unable to make any conclusions about revision risk in patients younger than age 65 years, who are the fastest-growing group of THR recipients in the US (1, 29). Death is an important competing risk in an elderly cohort. Indeed, 50% of our cohort died by the end of the 12-year followup period. However, since each control had to be alive at the time of the case's revision, death did not arise as a competing risk in our analysis. Our ability to investigate clinical factors relating to failure leading to revision was limited by the amount of detail and lack of uniformity present in the medical charts collected from many different hospitals, as well as by the unavailability of radiograph analysis. Because we asked hospitals for medical records that were up to 15 years old, some hospitals were unable to meet our requests due to factors such as hospital closings or mergers and destruction or loss of records. While our cases were similar to patients whose charts were unavailable in most respects, cases were much more likely to have had their primary and revision surgeries in the same hospital than patients whose charts were unavailable. This reflects the higher likelihood of obtaining both the case primary and case revision records when both surgeries occurred in the same hospital. This could imply a selection of a less mobile population, or of those more satisfied with their primary THR surgery. In addition, the potential for bias due to unmeasured factors and missing data remains an unavoidable limitation of this study. Finally, the advantage of long-term followup data such as ours must be weighed against the fact that trends in clinical practice and patient demographics are always changing.

This study of a Medicare population emphasizes that age between 65 and 75 years and greater height and weight at the time of the THR are potent risks for failure of THR leading to revision surgery. Since both height and weight are independent risk factors in multivariate models, the risk factor for revision may not be obesity per se, but body size, which potentially is a surrogate for the biomechanical load borne by the implant. This study also identifies prior THRs and other orthopedic surgeries as risk factors, possibly highlighting a connection of access to health care or favorable expectations of surgery to motivators for revision surgery. Prospective studies that are more detailed would facilitate the interpretation of these findings. We conclude that the effects of age and larger body size on revision risk should be included in discussions between surgeons and patients about the potential risk of failure of a primary THR.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Elizabeth A. Wright had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Elizabeth A. Wright, Katz, Baron, R. John Wright, Malchau, Mahomed, Losina.

Acquisition of data. Elizabeth A. Wright, Katz, Losina.

Analysis and interpretation of data. Elizabeth A. Wright, Katz, Baron, Mahomed, Prokopetz, Losina.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
  9. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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ACR_21760_sm_SupplTable1.doc40KSupplementary Table 1
ACR_21760_sm_SupplTable2.doc102KSupplementary Table 2

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