The Journal of Arthroplasty xxx (2015) xxx–xxx

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Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty? Matthew R. Boylan, ScB a,b, Niladri Basu, MD a, Qais Naziri, MD a, Kimona Issa, MD c, Aditya V. Maheshwari, MD a, Michael A. Mont, MD d a

Department of Orthopaedics, SUNY Downstate Medical Center, Brooklyn, New York Department of Epidemiology and Biostatistics, SUNY Downstate Medical Center, Brooklyn, New York Department of Orthopaedic Surgery, Seton Hall University School of Health and Medical Sciences, South Orange, New Jersey d Rubin Institute for Advanced Orthopaedics, Center for Joint Preservation and Reconstruction, Sinai Hospital of Baltimore, Baltimore, Maryland b c

a r t i c l e

i n f o

Article history: Received 30 January 2015 Accepted 16 March 2015 Available online xxxx Keywords: HIV total knee arthroplasty wound infection complications TKA

a b s t r a c t Using the Nationwide Inpatient Sample, we assess the: (1) demographic trends; (2) complications; and (3) length of hospital stay among total knee arthroplasty (TKA) patients with and without human immunodeficiency virus (HIV). The study population consisted of 2772 patients with HIV and 5,672,314 controls. Patients with HIV were more likely to be younger, male, and nonwhite. Patients with HIV were at an increased risk for perioperative wound infections (OR = 2.78; P = 0.024), although they were not at an increased risk for overall complications (OR = 1.21; P = 0.321). Mean length of stay was 17% longer for patients with HIV (P b 0.001). Given these findings, orthopedic surgeons should have a low threshold to work up a patient with HIV for a wound infection following TKA. © 2015 Elsevier Inc. All rights reserved.

In the United States, the Center for Disease Control estimates that the prevalence of human immunodeficiency virus (HIV) infection is greater than 1,000,000 individuals, including at least 180,000 who are unaware that they are infected [1]. Since the advent of highly active anti-retroviral treatment (HAART) treatment in 1997 [2], the face of HIV has changed from a life-threatening condition with significant morbidity and early mortality to a managed chronic disease that allows patients to have an active lifestyle with a near-normal life expectancy [3,4]. As more patients with HIV populate older age demographics, it is expected that many of these patients will develop chronic degenerative diseases such as osteoarthritis. Furthermore, infection with HIV may be a risk factor for degenerative joint disease, likely secondary to the risk of osteonecrosis (ON). This relationship has a complex pathophysiology that is hypothesized to be associated with HAART therapy, protease inhibitors, CD4 counts b 200 cells/μL, hypercholesterolemia, corticosteroid use, dyslipidemias, smoking, and alcohol abuse [5]. Symptomatic ON of the knee, while less common than ON of the hip [1], is a frequent complication of HIV infection, with an estimated 100fold increased risk as compared to the general population [5]. One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to doi: http://dx.doi.org/10.1016/j.arth.2015.03.018. Reprint requests: Michael A. Mont, MD, Center for Joint Preservation and Replacement, Rubin Institute for Advanced Orthopedics, Sinai Hospital of Baltimore, 2401 West Belvedere Avenue, Baltimore, MD 21215.

While many patients with HIV are candidates for joint arthroplasty, the potential risk of periprosthetic infection and other multisystem postoperative complications secondary to compromised immune function are concerning to surgeons [6,7]. Studies performed prior to the widespread use of HAART found that complication rates among patients with HIV approached 50% [8–10]. Recent data, however, have shown that joint arthroplasty outcomes for patients with HIV are improving, with one study observing a complication rate of 13% at a mean follow-up of 6 years [8] and another study observing no difference in implant survivorship and function scores at 5-year and 10-year follow-up [11]. With improvements in HIV medication, earlier diagnoses of HIV, and improvements in surgical devices and techniques, joint arthroplasties are becoming safer for patients with HIV. However, despite published data on mid-term outcomes following joint arthroplasty in patients with HIV, there are limited data on the risk of short-term perioperative complications within this patient population. We therefore sought to use a large US database, the Nationwide Inpatient Sample (NIS), to address the paucity of data on this topic. We specifically assessed: (1) the demographics of patients with HIV who underwent a primary TKA; (2) the difference in the risk of wound infections and other perioperative complications among patients with and without HIV; and (3) the difference in mean length of hospital stay among patients with and without HIV. Methods The Nationwide Inpatient Sample (NIS) contains a 20% representative sample of annual hospital admissions in the United States [12].

http://dx.doi.org/10.1016/j.arth.2015.03.018 0883-5403/© 2015 Elsevier Inc. All rights reserved.

Please cite this article as: Boylan MR, et al, Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty?, J Arthroplasty (2015), http://dx.doi.org/10.1016/j.arth.2015.03.018

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M.R. Boylan et al. / The Journal of Arthroplasty xxx (2015) xxx–xxx

The NIS contains demographic and clinical variables for each admission, including International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnostic and procedure codes. In addition, discharge weights, which are based on the size and location of the hospital where each admission occurred, allow researchers to calculate nationwide estimates of patient discharges. The NIS is publicly available to researchers and contains deidentified data. Our study population included all patients between 1998 and 2010 who had a TKA as their primary ICD-9 procedure code (81.54). We excluded patients with diagnosis codes indicating pathological fracture, malunion of fracture, and long-term mechanical loosening associated with revisions, as has been done previously [13], because these admissions predominantly are nonelective. We extracted data for each admission concerning length of stay, which was log-transformed in regression analyses as a result of its right skew. Perioperative wound infection and other perioperative complications were calculated using diagnosis codes as defined by a recent study of orthopedic-related complications [14]. Perioperative wound infection and other perioperative complications were calculated using diagnosis codes as defined by a recent study of orthopedic-related complications [14]. Since ICD-9 coding does not specify for superficial, deep, and organ/space surgical site wound infection, codes indicating cellulitis, abscess, or unspecified local infection of the leg, complicated open wounds of the leg, postoperative infection not elsewhere classified, infected postoperative seroma, and nonhealing surgical wound were used to identify patients with this complication. In addition, we defined a “medical complication” as death, myocardial infarction, pulmonary embolism, pneumonia, acute renal failure, deep vein thrombosis, sepsis, urinary tract infection, or stroke, and we defined a “surgical complication” as wound hemorrhage, wound complication, wound infection, implant infection, irrigation and debridement, or postoperative dislocation. We used diagnosis codes to identify patients who had HIV (042, 795.71, V08) and designated all other TKA admissions as controls. We also used diagnosis codes to identify patients with osteonecrosis (733.40, 733.43, 733.49). For each admission, we extracted data on demographic variables including age (in years), sex, race (white, black, Hispanic, other), and insurance (Medicare, Medicaid, private, other). We calculated the severity of comorbidities from diagnosis codes using Charlson and Deyo's method [15], excluding HIV/AIDS from the patient's total score, and distributed patients into score categories of 0, 1, and ≥2. We used logistic regression to calculate the odds ratios (ORs) of perioperative complications during the hospital stay for patients with HIV as compared with patients without HIV. We also used linear regression to calculate parameter estimates for mean length of stay and mean total hospital charges. We interpreted the results of our linear regressions as percent differences using the formula 100⁎(e b-1), where b is the

regression coefficient of a log-transformed outcome variable [16]. All of our regression models were adjusted for age, sex, race, insurance, and the Deyo comorbidity score. Admissions with missing age (N = 4194), sex (N = 13,466), race (N = 1,402,920), and insurance (N = 10,784) could not be included in multivariable regression models. However, to rule out the possibility that the exclusion of this subset of admissions with missing data biased our results, we also performed sensitivity analyses on our data, in which we removed each covariate from our regression model, thereby including all patients the missing covariate. We also used regression models with HIV (no, yes) as the outcome variable and age, sex, race, insurance, comorbidities, and osteonecrosis as independent predictor variables, to assess the effect size of each demographic variable. We used weighting variables in all our analyses to simulate national US rates of TKA admission. All statistical analyses were performed using SAS Version 9.3 (SAS Institute Inc, Cary, NC, USA). All P values were two-tailed, and P b 0.05 was interpreted as being statistically significant. All figures were generated using Microsoft Excel 2010 (Microsoft Corporation, Redmond, WA, USA).

Results After exclusions, our study population of TKA admissions consisted of 2772 patients with HIV and 5,672,314 patients without HIV. The proportion of admissions with HIV admitted annually increased gradually during the study period from 0.2 per 1000 in 1998 to 0.6 per 1000 in 2010 (m = 0.03; r = 0.73; P = 0.004) (Fig. 1). We observed that patients with HIV were younger (52 versus 67 years; OR = 0.90; P b 0.001), were less likely to be female compared to male (OR = 0.37; P b 0.001), were more likely to be black (OR = 9.92; P b 0.001), Hispanic (OR = 2.92; P b 0.001), or other race (OR = 2.08; P = 0.002) compared to white race, and were more likely to pay with Medicaid (OR = 9.57; P b 0.001), private insurance (OR = 1.42; P b 0.001) or other insurance (OR = 1.78; P = 0.005) compared to Medicare. We did not observe any difference in the number of patients with a Deyo score of 1 (P = 0.947), although patients with HIV were more likely to have a Deyo score of ≥2 (OR = 1.78, P = 0.005). Osteonecrosis was observed in 10% of patients with HIV, compared with 1% of patients without HIV (OR = 14.60; P b 0.001) (Table 1). The risk of perioperative complication was increased among patients with HIV, but this increase was not statistically significant compared to patients without HIV (OR = 1.21; 95% CI, 0.83–1.77; P = 0.321). This was also true for medical complications (OR = 1.13; 95% CI, 0.73–1.74; P = 0.579) and surgical complications (OR = 1.50; 95% CI, 0.80–2.84 P = 0.207) (Table 2). However, when we looked at individual complication risk, we found that patients with HIV were more likely to

HIV+ Admissions (per 1,000 THA)

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Year Fig. 1. The annual number of admissions with HIV per 1000 TKA admissions is shown.

Please cite this article as: Boylan MR, et al, Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty?, J Arthroplasty (2015), http://dx.doi.org/10.1016/j.arth.2015.03.018

M.R. Boylan et al. / The Journal of Arthroplasty xxx (2015) xxx–xxx

to our full multivariable model, suggesting that the exclusion of patients with missing demographic data did not bias our results. Patients with HIV had a longer mean length of stay. The mean length of stay was 4.79 days (95% CI, 4.24–5.33) for patients with HIV and 3.75 days (95% CI, 3.74–3.76) for patients without HIV. Patients with HIV had a multivariate-adjusted mean length of stay that was 17% (95% CI, 12–23; P b 0.001) longer compared with patients without HIV (Table 2). We observed a negative linear trend in length of stay for both patients with (b = −0.20, P b 0.001) and without (b = −0.10, P b 0.001) HIV who were admitted for TKA between 1998 and 2010 (Fig. 2).

Table 1 Patient Characteristics, According to HIV Status. No Admissions (N) Mean age (years) Gender, % (N) Male Female Missing Race, % (N) White Black Hispanic Other Missing Deyo score, % (N) 0 1 ≥2 Insurance, % (N) Medicare Medicaid Private Other Missing Osteonecrosis, % (N) No Yes a

Yes

5672314 67

2772 52

36 (2052634) 64 (3606214) 13466

OR (95% CI)

P

0.90 (0.89–0.90)a

b0.001

61 (1681) 39 (1091) 0

Referent 0.37 (0.31–0.44)

b0.001

85 (3623578) 7 (292078) 5 (206081) 3 (148166) 1402412

49 (1104) 39 (883) 8 (183) 4 (94) 508

Referent 9.92 (8.14–12.08) 2.92 (2.06–4.14) 2.08 (1.30–3.34)

b0.001 b0.001 0.002

63 (3573333) 27 (1542308) 10 (556674)

61 (1691) 27 (735) 12 (346)

Referent 1.01 (0.83–1.22) 1.32 (1.02–1.70)

58 (3288973) 2 (144488) 36 (2017766) 4 (210308) 10779

42 (1151) 17 (484) 36 (1001) 5 (131) 5

Referent 9.57 (7.53–12.16) 1.42 (1.17–1.71) 1.78 (1.20–2.66)

b0.001 b0.001 0.005

99 (5631655) 1 (40659)

90 (2508) 10 (264)

Referent 14.60 (10.97–19.43)

b0.001

Discussion

0.947 0.036

Interpret as chance of having HIV for each 1-year increase in age.

Table 2 Risk of Perioperative Complications and Length of Stay, According to HIV Status.

Any complication OR Medical complication OR Surgical complication OR Wound infection OR Length of stay estimateb

No

Yesa

P

Referent Referent Referent Referent Referent

1.21 (0.83–1.77) 1.13 (0.73–1.74) 1.50 (0.80–2.84) 2.78 (1.15–6.72) 17.63 (12.43–23.07)

0.321 0.579 0.207 0.024 b0.001

3

a

Models adjusted for age, sex, race, insurance, and Deyo comorbidity score. Interpret as percentage difference, under the formula 100(eb-1), where b is the estimated standardized regression coefficient of a log-transformed outcome variable. b

have wound infection (OR = 2.78; 95% CI, 1.15–6.72; P = 0.024) compared with patients without HIV. In stratified analysis of complication risk, the risk of any complication for patients with HIV from 1998 to 2003 (OR = 1.05; 95% CI, 0.37–2.98; P = 0.928) was not significantly different from the risk from 2004 to 2010 (OR = 1.22; 95% CI, 0.82–1.83; P = 0.330). In our sensitivity analyses, the risk of any complication when patients with missing age (OR = 0.93; P = 0.682), sex (OR = 1.21; P = 0.315), race (OR = 1.27; P = 0.212), and insurance (OR = 1.25; P = 0.209) were included was similar

This study was designed to address the paucity of data on demographic trends, early complications, length of stay, and total charges following admission for TKA among patients who had an HIV infection. Using a large US inpatient database, and after adjusting our statistical models for important confounders including age, sex, race, insurance, and comorbidities, we observed that patients with HIV had no statistically significant difference in their overall risk of perioperative complications compared with patients without HIV. However, we found that patients with HIV had an increased risk of wound infection and a longer mean length of stay. Demographic data of patients with HIV undergoing total joint arthroplasty (TJA) in patients with HIV have been described previously, but little existing data are specific for TKA. In these studies, mean age has ranged from 45 to 50 years with the proportion of male patients ranging from 58% to 71% [10,11,17,18]. Our data for TKA patients are consistent with these previous studies, observing an average age of 52 years with 61% of admissions being male. Furthermore, we were able to describe the racial (49% white, 39% black, 8% Hispanic, 4% other) and insurance (61% Medicare, 17% Medicaid, 36% private, 5% other) demographics of this population among a sample of more than 2500 patients with HIV undergoing TKA. Our observation that patients with HIV were more likely to pay with Medicaid is likely due to the younger age of patients with HIV undergoing TKA compared to the control population, which is more likely to include older patients paying with Medicare. Our finding that patients with HIV were at increased risk for perioperative wound infection provides clarity to existing data. A cohort of more than 300 patients undergoing TJA observed that the infection rate was higher among 22 patients with HIV (9% versus 2%), although this difference did not reach statistical significance secondary to small sample size [10]. Among our cohort of more than 2500 patients with HIV, we found that the risk of wound infection was 178% higher compared to patients without HIV. The etiology of this association is unclear and warrants further investigation.

No

Yes

Mean Length of Stay (Days)

8 7 6 5 4 3 2 1 0 1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Year Fig. 2. The annual mean length of stay of TKA admissions, according to HIV status, is shown.

Please cite this article as: Boylan MR, et al, Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty?, J Arthroplasty (2015), http://dx.doi.org/10.1016/j.arth.2015.03.018

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M.R. Boylan et al. / The Journal of Arthroplasty xxx (2015) xxx–xxx

In regard to the implications of surgical wound infections following orthopedic surgery in patients with HIV, prior studies have shown that most infections resolve after extended antibiotic therapy and/or debridement. Among 39 patients with HIV undergoing implant surgery, there were 6 cases of wound infection, with 5 cases resolving after antibiotics and 1 case progressing to a deep chronic infection [19,20]. A study of 36 patients with HIV undergoing orthopedic trauma surgery identified 14 cases of postoperative wound infection, of which 12 resolved after debridement and antibiotics and 2 progressed to chronic osteomyelitis [21]. Among 34 patients with HIV who underwent 44 total hip arthroplasties, there were 2 deep infections identified at 59 and 64 months postoperatively, with both resolving after revision surgery with extensive debridement and the placement of an antibiotic spacer [11]. The relationship between TKA and length of hospital stay in patients with HIV has not been comprehensively evaluated in prior studies. A previous study found that patients with HIV were more likely to have a hospital stay ≥4 days (36% vs. 20%) [10]. We observed that patients with HIV had a mean hospital stay that was 13% longer, but some caution should be used in interpreting these data. It is unclear whether this increased length of stay is secondary to additional precautions and/or complications precipitated by the presence of HIV infection, concomitant medical comorbidities that were present at a higher rate among patients with HIV, some other unknown factor, or a clinically insignificant difference. There were several limitations of the present study. NIS data are restricted to diagnoses recorded during each patient's hospital stay and provide no information on long-term outcomes such as readmission and arthroplasty revision. Many infections occur after the patient is discharged from the hospital, and it is possible that the association between HIV and wound infection might be under-estimated by our study. Therefore, further investigation with a longer follow-up period is warranted. ICD-9 coding for diagnoses and procedures limits our ability to account for differences in implant type, severity of joint degeneration, and reason for surgery. It is unlikely that all patients with HIV who underwent TKA were correctly identified, which may be secondary to medical record coding procedures for comorbid diagnoses, undiagnosed HIV infection, or presumed negative status by medical personnel. Because we do not know any of the characteristics of these misclassified patients, it is impossible to predict the potential effect of their misclassification on our outcomes. Furthermore, there are many potential ICD-9 diagnosis codes that indicate postoperative wound infection, and we were unable to specifically stratify according to superficial, deep, and organ/space surgical wound infection. However, given the paucity of reports on the shortterm risk of wound infections among HIV patients undergoing total knee arthroplasty, we believe these data provide the basis for further study on this topic. Another limitation of this study is that patients with HIV and controls who are undergoing an elective surgery such as TKA may be healthier than non-surgical patients. Our data, therefore, should be interpreted within the context of patients who are fit to undergo elective surgery. Our multivariable models excluded patients with missing demographic data, which may have biased our results. However, in our sensitivity analyses, there was no material difference in the risk of observed risk of complications in models that included patients with missing demographic data. Therefore, our data do not appear to be subject to this missing data bias. Lastly, one must note that our study is observational and we cannot rule out the effect of an unmeasured variable on our results. In conclusion, we observed that patients with HIV were at an increased risk for perioperative wound infection. Given this finding, for

patients with HIV with poor wound drainage or a suspicious-looking wound, orthopedic surgeons should have a low threshold to work up these individuals for infection. Furthermore, in patients with HIV, close monitoring postoperatively for wound integrity and potential infections is warranted. However, given our finding of no difference in risk of overall complications for patients with HIV compared to controls the benefits of TKA appear to outweigh the risks in patients with HIV who otherwise meet reasonable surgical indications. Acknowledgments We thank the HCUP Data Partners who contribute annually to the NIS. A full listing of participants can be found at http://www.hcup-us. ahrq.gov/hcupdatapartners.jsp. There were no reportable funding sources for this study. References 1. CDC. Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 U.S. dependent areas—2011. HIV Surveillance Supplemental Report, 18(No. 5); 2013 [Published October 2013]. 2. Hammer SM, Squires KE, Hughes MD, et al. A controlled trial of two nucleoside analogues plus indinavir in persons with human immunodeficiency virus infection and CD4 cell counts of 200 per cubic millimeter or less. AIDS Clinical Trials Group 320 Study Team. N Engl J Med 1997;337(11):725. 3. Samji H, Cescon A, Hogg RS, et al. Closing the gap: increases in life expectancy among treated hiv-positive individuals in the United States and Canada. PLoS One 2013; 8(12):e81355. 4. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet 2008;372(9635):293. 5. Mehta P, Nelson M, Brand A, et al. Avascular necrosis in HIV. Rheumatol Int 2013; 33(1):235. 6. Güerri-fernandez R, Vestergaard P, Carbonell C, et al. HIV infection is strongly associated with hip fracture risk, independently of age, gender, and comorbidities: a population-based cohort study. J Bone Miner Res 2013;28(6):1259. 7. Tornero E, García S, Larrousse M, et al. Total hip arthroplasty in HIV-infected patients: a retrospective, controlled study. HIV Med 2012;13(10):623. 8. Swensen S, Schwarzkopf R. Total joint arthroplasty in human immunodeficiency virus positive patients. Orthop Surg 2012;4(4):211. 9. Habermann B, Eberhardt C, Kurth AA. Total joint replacement in HIV positive patients. J Infect 2008;57(1):41. 10. Lin CA, Takemoto S, Kandemir U, et al. Mid-term outcomes in HIV-positive patients after primary total hip or knee arthroplasty. J Arthroplasty 2014;29(2):277. 11. Issa K, Naziri Q, Rasquinha V, et al. Outcomes of cementless primary THA for osteonecrosis in HIV-infected patients. J Bone Joint Surg Am 2013;95:1845. 12. Steiner C, Elixhauser A, Schnaier J. The healthcare cost and utilization project: an overview. Eff Clin Pract 2002;5(3):143. 13. Lin CA, Kuo AC, Takemoto S. Comorbidities and perioperative complications in HIVpositive patients undergoing primary total hip and knee arthroplasty. J Bone Joint Surg Am 2013;95(11):1028. 14. Parvizi J, Mui A, Purtill JJ, et al. Total joint arthroplasty: when do fatal or near-fatal complications occur? J Bone Joint Surg Am 2007;89(1):27. 15. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD9-CM administrative databases. J Clin Epidemiol 1992;45(6):613. 16. Glidden DV, Shiboski SC, McCulloch CE. Linear regression: checking model assumptions and fit. Regression methods in biostatistics: linear, logistic, survival, and repeated measures models. New York, NY, USA: Springer-Verlag; 2011. 17. Capogna BM, Lovy A, Blum Y, et al. Infection rate following total joint arthroplasty in the HIV population. J Arthroplasty 2013;28:1254. 18. Snir N, Wolfson TS, Schwarzkopf R, et al. Outcomes of total hip arthroplasty in human immunodeficiency virus-positive patients. J Arthroplasty 2014;29:157. 19. Harrison WJ, Lewis CP, Lavy CB. Wound healing after implant surgery in HIV-positive patients. J Bone Joint Surg (Br) 2002;84(6):802. 20. Harrison WJ. HIV/AIDS in trauma and orthopaedic surgery. J Bone Joint Surg (Br) 2005;87(9):1178. 21. Abalo A, Patassi A, James YE, et al. Risk factors for surgical wound infection in HIVpositive patients undergoing surgery for orthopaedic trauma. J Orthop Surg (Hong Kong) 2010;18(2):224.

Please cite this article as: Boylan MR, et al, Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty?, J Arthroplasty (2015), http://dx.doi.org/10.1016/j.arth.2015.03.018

Does HIV Infection Increase the Risk of Short-Term Adverse Outcomes Following Total Knee Arthroplasty?

Using the Nationwide Inpatient Sample, we assess the: (1) demographic trends; (2) complications; and (3) length of hospital stay among total knee arth...
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