- Email: [email protected]
Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database
Accepted Manuscript Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database Jimmy J. Chan, MD, Jonathan Robinson, MD, Jashvant Poeran, MD, PhD, Hsin-Hui Huang, MD, PhD, Calin S. Moucha, MD, Darwin Chen, MD PII:
S0883-5403(19)30229-3
DOI:
https://doi.org/10.1016/j.arth.2019.03.006
Reference:
YARTH 57129
To appear in:
The Journal of Arthroplasty
Received Date: 20 November 2018 Revised Date:
1 March 2019
Accepted Date: 2 March 2019
Please cite this article as: Chan JJ, Robinson J, Poeran J, Huang H-H, Moucha CS, Chen D, Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database, The Journal of Arthroplasty (2019), doi: https:// doi.org/10.1016/j.arth.2019.03.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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1. Department of Orthopaedic Surgery Icahn School of Medicine at Mount Sinai 5 East 98th Street, Box 1188 New York, NY 10029
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Jimmy J. Chan, MD1 Jonathan Robinson, MD1 Jashvant Poeran, MD, PhD2 Hsin-Hui Huang, MD, PhD2 Calin S. Moucha MD1 Darwin Chen, MD1
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Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database
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2. Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai One Gustave Levy Place, Box 1077 New York, NY 10029
Please address all correspondence to:
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Darwin Chen, MD Department of Orthopaedic Surgery Icahn School of Medicine at Mount Sinai 5 East 98th Street, Box 1188 New York, NY 10029
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Phone: (212) 241-1924 Fax: (212) 241-9710 Email: [email protected]
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Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database
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Abstract
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Introduction: The routine usage of antibiotic loaded bone cement (ALBC) in primary total knee arthroplasty (TKA) is controversial. Its effectiveness in reducing infection risk remains unclear while high dose antibiotics can lead to multiple adverse effects. The purpose of this population-based study is to evaluate utilization patterns of ALBC in primary TKA and its impact on clinical outcomes. Methods: This retrospective cohort study utilized data from the nationwide Premier Healthcare claims database (2006-2016). Multivariable models estimated associations between ALBC use and early postoperative infection, kidney injury, allergic reaction, hospital readmission, cost, and length of stay. Results: ALBC was utilized in 27.2% of all primary TKAs (N=1,184,270). Usage increased from 17.3% to 30.2% in 2006-2010, then plateaued. Study covariates differed minimally between groups, suggesting non-selective ALBC use. Utilization was lower in rural (21.4%) and higher in large (>500 beds; 29.4%) hospitals. After adjusting for relevant covariates, ALBC use was associated with significantly decreased odds for early post-operative infection (OR = 0.89 CI 0.83-0.96) and increased odds for AKI (OR = 1.06 CI 1.02-1.11). Conclusion: With utilization rates of around 30%, we found that ALBC reduced odds for early postoperative infection and increased odds for kidney injury. Strong consideration should be given for selective use of ALBC in primary TKA.
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Keywords: antibiotic cement; knee arthroplasty; infection; outcomes; acute renal failure
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Introduction
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Periprosthetic joint infection (PJI) remains one of the leading causes of failure after total knee arthroplasty (TKA), resulting in significant morbidity and mortality.[1, 2] With
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the routine use of prophylactic systemic antibiotics as well as other standard perioperative
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infection control measures, the infection rate after primary TKA is approximately 1%-
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3%.[3] The treatment of PJI after TKA is difficult because of bacterial biofilm formation on
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prosthetic joint surfaces as well as poor penetration and delivery of systemic antibiotics into
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the joint itself. Bucholz and Engelbrecht introduced the concept of antibiotic-loaded bone
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cement (ALBC) in 1970.[4] ALBC allows for immediate antibiotic delivery at the time of
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implantation and continuous elution of antibiotics for at least 30 days postoperatively.[5]
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Over the past twenty years, ALBC has become a critical component of the standard
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treatment for PJI, typically via one- or two-stage exchange revision arthroplasty.
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While considered an established method for the management of periprosthetic hip and knee joint infections, routine use of ALBC as prophylaxis in primary TKA remains
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controversial.[6] First, the introduction of high-dose antibiotics locally carries the risk of
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developing adverse systemic effects such as renal injury and hypersensitivity.[7, 8] Other
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concerns include the development of antibiotic resistance, reduction in the mechanical
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properties of bone cement, subsequent TKA failures due to mechanical loosening, and
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increased cost.[9-11] In addition, in the absence of high-quality evidence, there is currently
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no consensus on whether routine use of ALBC actually reduces the infection rate in primary
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TKA.[11] Most published data examining the effect of routine use of ALBC in TKA stems
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from trials involving select patient populations such as revision settings or those with a
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higher baseline comorbidity burden, thus imparting significant bias that negatively impacts
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the generalizability of these findings [5, 12-14]. The purpose of this large database driven,
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population-based study is to evaluate real-world utilization patterns of ALBC in primary
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TKA, and its impact on TKA outcomes and economic burden. We hypothesize that ALBC is
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associated with a decreased risk of infection without an increased risk of systemic
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complications.
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Methods
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Data Source, Study Design and Sample
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Our Institutional Review Board approved use of the HIPAA-compliant anonymized
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data for this study (project #14-00647). For this retrospective cohort study, data from the
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Premier Healthcare Database[15] (Premier Healthcare Solutions, Inc., Charlotte, NC) was
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used. This database contains administrative claims data on approximately 20-25% of US
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hospital discharges. Records include International Classification of Disease-9th revision
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(ICD-9) codes, Current Procedural Terminology (CPT) codes, and complete inpatient billing
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items in a standardized free text format. We included patients undergoing a TKA procedure
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(ICD-9 code 81.54) between 2006 and 2016. Cases with missing information on sex (n=217)
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or discharge status (n=654), labeled as outpatient (n=8,489), or cases performed in
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hospitals with a volume of <30 TKA procedures in the study period (n=4,139) were
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excluded. A total of 1,184,270 procedures were included in the final study cohort (Figure
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1).
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Study Variables The intervention of interest, i.e. the main predictor, was the use of ALBC which was identified from specific billing item descriptions (not codes) using the term “CEMENT
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BONE W/ ANTIBIOTIC” in the standardized free text to create the variable. The main
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outcomes of interest were early postoperative infection within 30 days (either during the
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index hospitalization or subsequent hospitalizations within that timeframe), acute renal
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failure, 30-day and 90-day readmission, acute perioperative dialysis need (as a proxy for
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renal compromise, defined from billing item descriptions), allergic complications,
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complications related to microbiome disruption, length of hospital stay (LOS), and cost of
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hospitalization. Appendix I details the definition of these variables, either the ICD-9 codes
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or billing items used from the standardized free text billing file. Cost of hospitalization was
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adjusted for inflation and reported in January 2016 US dollars; 30-day readmission and 90-
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day readmission included any readmission within 30 days and 90 days, respectively, to the
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same hospital where the primary procedure took place.
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A variety of other variables were considered that may lie in the pathway between ALBC and outcomes; these include patient demographics, healthcare-, procedure- and
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comorbidity-related variables. Patient demographics included age, sex, race (White, Black,
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other/unknown) and insurance type (Commercial, Medicaid, Medicare, uninsured,
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unknown). Healthcare-related variables included hospital location (rural, urban), bed size
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(<300, 300-499, ≥500 beds), teaching status and annual hospital-specific TKA volume.
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Procedure-related variables included the year in which the procedure was performed, type
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of anesthesia used, use of patient controlled analgesia, nonsteroidal anti-inflammatory
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drugs (NSAIDs), cyclooxygenase-2 (COX-2) inhibitors, ketamine, gabapentin, pregabalin,
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acetaminophen, and peripheral nerve blocks. Comorbidity-related variables included the
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Quan adaptation of the Charlson-Deyo Index[16], smoking, and obesity (body mass index
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≥30 kg/m2). The majority of our variables did not have missing information except for race,
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insurance status and anesthesia type. These were treated as separate categories within the
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respective variables. Excluding this information did not change our main conclusions.
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Statistical Analyses
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No a priori sample size calculation was performed. Based on an estimated overall infection risk 5%, our sample size had >90% power to detect a 10% relative difference in
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infection risk between cases with and without ALBC.[17]
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First, we assessed univariable associations between use of ALBC and the
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aforementioned variables. Given our large sample size, univariable differences between
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groups easily reached statistical significance. Therefore, in univariable comparisons, we
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used standardized differences instead of P-values. A standardized difference of 0.1 (or 10%)
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has been suggested to indicate a meaningful difference in covariate distribution between
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groups.[18, 19] Additionally, we assessed trends in utilization of ALBC stratified by hospital
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characteristics (hospital bed size, location, and teaching status).
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Mixed-effects models were used to measure the association between the use of
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ALBC and outcomes. The advantage of these models is that they account for the correlation
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of patients treated within the same hospital as they may be similar in terms of the care they
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receive.[20] Models were adjusted for all study variables mentioned above; no specific
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interactions were considered. Adjusted odds ratios (OR) and 95% confidence intervals (CI)
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are reported. LOS and cost of hospitalization represent skewed data and were therefore
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modeled using the gamma distribution with a log link function using the PROC GLIMMIX
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procedure in SAS statistical software.[21, 22] Therefore, for LOS and cost of hospitalization
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instead of ORs, percent (%) change compared to the reference (no use of ALBC) is reported.
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All analyses were performed using SAS v9.4 statistical software (SAS Institute, Cary, NC).
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Sensitivity Analyses
We performed two additional analyses to examine the robustness of our study
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results. First, we conducted an ‘instrumental variable analysis’ which aims to address both
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measured and unmeasured confounding (in contrast to other methods such as propensity
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score analysis). Instrumental variable analysis requires the selection of a valid
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‘instrumental variable’ that meets three key assumptions: 1) the instrumental variable is
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positively associated with the treatment variable, which in this context is ALBC use, 2) the
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instrumental variable is independent of (un)measured confounders, and 3) the
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instrumental variable is associated with the outcomes of interest, including early
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postoperative infection and acute renal failure, only indirectly through its effect on the
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treatment, i.e. ALBC use.[23] This approach adopts the framework of a randomized
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controlled trial in that the selected instrumental variable is used to represent a mechanism
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for assigning a treatment to patients. We selected surgeon-specific use (in %) of ALBC as an
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instrumental variable assuming that this will affect the probability that ALBC will be used
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in a case. In other words, cases performed by surgeons with higher use of ALBC are more
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likely to utilize ALBC. This variable was used to allocate the treatment variable after which
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mixed-effects models were applied.
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In the second sensitivity analysis we restricted our cohort to only hospitals in which ALBC was actually used as patients in hospitals without ALBC use theoretically are not at
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risk for exposure to this treatment. The main regression analysis was then performed in
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this restricted cohort (n=825,862).
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Sources of Funding
No funds were received in support of this work. No benefits in any form have been
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or will be received from any commercial party related directly or indirectly to the subject
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of this manuscript.
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Results
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Overall, data on 1,184,270 TKA procedures were included; ALBC was utilized in
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27.2% (n=322,476) of cases. Minor differences were seen in covariate distributions
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between patients receiving ALBC and those that did not (Table 1; most standardized
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differences <0.1). Interestingly, particularly lower use was seen in rural hospitals. ALBC
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usage increased from 2006 until 2010, after which a minimally decreasing trend was seen
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(Figure 2). When stratifying trends by hospital type, decreasing trends are more
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pronounced for teaching and large/medium-sized hospitals while a continued increase in
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usage of ALBC was seen in small hospitals, with less pronounced increasing trends in
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non-teaching hospitals (Figure 2).
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Most unadjusted outcomes did not differ between patients receiving ALBC and those that did not (Table 2; most standardized differences <0.1) except for median unadjusted
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cost of hospitalization, which was $16,251, and $15,698, respectively. These absolute
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numbers need to be taken into account when interpreting the adjusted relative effect
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estimates (Table 3); after adjustment for relevant covariates, the use of ALBC (compared
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to no use) was significantly associated with reduced odds for early postoperative infections
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(OR 0.89 CI 0.83-0.96). Importantly, increased odds for acute renal failure (OR 1.06 CI 1.02-
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1.11) were seen (both P<0.05) with ALBC use. No statistically significant effects existed for
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the other complications while minimal effects were seen for LOS (+0.5%) and cost of
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hospitalization (+3.5%); these are adjusted relative effects taking into account all
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confounders.
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The sensitivity analyses (Table 3) corroborated mainly the finding that ALBC use was associated with increased odds for acute renal failure while the association with early
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postoperative infection was not significant anymore (although with unchanged direction of
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effect). The sensitivity analyses also demonstrated associations with reduced odds for
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readmissions, corroborating the direction of effect in the main analysis.
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Discussion
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This is the first national, large database study on the prophylactic use of ALBC in
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primary TKA. We found an overall ALBC utilization rate of 27.2% with an overall stagnant
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trend over a ten-year span. However, differences exist when stratifying by hospital type,
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with increasing use in smaller hospitals and decreasing use in medium/large-sized and
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teaching hospitals over a 10 year span. After adjusting for relevant covariates, ALBC was
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associated with significantly decreased odds of early postoperative infection and
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significantly increased odds of acute renal failure. Particularly the latter finding was
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corroborated in sensitivity analyses. These relative effects have to be interpreted in the
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context of the overall low prevalence of complications in patients undergoing TKA. This is
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likely to result in a high number-needed-to-expose, i.e. a large number of patients need to
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be exposed to ALBC in order for one to benefit or be harmed. However, given that TKA is a
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high-volume procedure, the results from the current study may be relevant to individual
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hospitals as well as the population level.
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When evaluating the overall cohort, the trend of ALBC utilization is stagnant over a ten-year span. While several potential explanations exist, the lack of consensus and the
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absence of high-quality evidence supporting prophylactic use of ALBC in primary TKA may
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be the main driving mechanism. [11, 17, 24] An interesting pattern emerged when
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stratifying by hospital type, with slightly increasing trends in smaller, non-teaching, and
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rural hospitals. We can only speculate on the mechanisms behind these findings, however,
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previous studies have indeed demonstrated differences in care by hospital type. For
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example, academic and larger urban medical centers may be more likely to provide care
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and treatment protocols backed by the literature. Indeed, Shahian et al. demonstrated that
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surgical care in major teaching hospitals adhered to evidence-based guidelines and
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protocols more consistently than non-teaching hospitals in 4,809 hospitals from 2006-
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2009.[25] Therefore, without a clear demonstration of benefits, large academic centers
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may be less likely to change or implement new protocols on routine ALBC use in primary
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TKA patients. Increased cost of routine ALBC use may also be a driver of decreased usage in
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large hospital systems, where the total cost of care for joint replacement may be more
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carefully scrutinized.
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Our results demonstrated that patient characteristics and comorbidities did not impact the utilization rate of ALBC, suggesting non-selective use. Moreover, patients with
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different anesthesia types, Deyo-Charlson comorbidity index, and obesity all have
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comparable rates of ALBC use, further emphasizing this finding. Given the lack of
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high-quality evidence supporting routine use of ALBC, one alternative strategy could be the
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use of prophylactic ALBC among those perceived to be at increased risk of PJI such as
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patients with diabetes, as previously suggested.[26] In contrast to utilization rates in the
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US, international registry data demonstrates routine use of ALBC to be over 90% in the
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United Kingdom, Norway and Sweden, but is significantly lower in Spain and Russia.[27-
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29] This suggests that the decision to use ALBC may not be dependent on patients’
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individual risk factors but rather external factors such as local/regional protocols or
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surgeon preference. Future studies should focus on the drivers behind the choice of using
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ALBC as this may provide important information on how to modify its utilization and steer
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it towards use in the patients that are most likely to benefit.
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We found a small yet significant reduction in the odds of early postoperative infection associated with ALBC use. Compared to the demonstrated benefit of ALBC use in
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revision TKA for PJI, studies on the effect of ALBC on infection rates in primary TKA are
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controversial.[30-32] One randomized controlled trial examined 384 primary TKA
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procedures (with an average of 49 months follow-up) found a deep infection rate of 3.1%
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in controls compared to 0% in the ALBC group; no difference was seen in the superficial
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wound infection rate.[26] Wang et al. reported similar findings in a systematic review of
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eight studies including 6,381 primary TKA procedures. Here, the use of ALBC coincided
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with a significant reduction in the deep infection rate (RR = 0.41, p = 0.04), however, the
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effect was reverse for superficial infections (RR = 1.47, p=0.004).[33] Subgroup analysis
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further demonstrated that gentamycin was superior to cefuroxime in reducing deep
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infection. On the contrary, Tayton et al. used the New Zealand registry database and
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evaluated 64,566 primary TKAs between 1999 and 2012. They counter-intuitively found
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increased revision for PJI with use of ALBC (OR 1.93).[34] Some have postulated that the
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amount of cement use in TKA is typically low (compared to antibiotic spacers in a revision
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setting) which might lead to lower duration and magnitude of effective antibiotic level
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inside the joint.[35]
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Arguably the most important finding from our study is the significantly increased
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odds of acute renal failure associated with routine prophylactic ALBC use; this persisted in
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sensitivity analyses. Indeed, the use of ALBC is not without potential adverse effects.
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Gentamicin, vancomycin, and tobramycin are the three most commonly used antibiotics in
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ALBC, and all have potential for renal toxicity.[28, 36] Routine use of renal toxic
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perioperative systemic antibiotics has shown to increase acute renal failure in primary hip
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and knee joint replacement. [37, 38] ALBC places renal function at even higher stress than
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perioperative systemic antibiotics because the concentration of antibiotic release is
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significantly higher with a longer elution period of up to 30 days postoperatively. Despite
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the absence of high-quality evidence on acute renal failure risk in routine ALBC use,[39]
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development of postoperative acute renal failure in revision TKA has been well elucidated
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in the literature.[40, 41] Besides acute renal failure, we did not find any significant adverse
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effects including allergic complications and microbiome disruption that could be associated
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with high dose antibiotic use linked to ALBC. However, our study only focused on these
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events during the index hospitalization, and some of these adverse events make take time
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to develop as ALBC has a long elution time. Therefore, follow-up studies should be geared
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towards long-term effects of routine ALBC use to appreciate the full scope of risks and
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benefits. Our study has limitations. First, this is a database study, and therefore several
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potential confounding variables such as operative time, baseline renal status, hospital
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operating room infection control protocols, and importantly, intravenous antibiotic
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prophylaxis characteristics were not available. Also, we did not have information on the
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type of antibiotic included in the ALBC. As previous studies have shown, some antibiotics
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have more negative side effect profiles in terms of complications such as renal failure and
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microbiome disruption. The different antibiotics used in various ALBC brands may also
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have differing effects on reducing PJI. Our study only focused on the immediate index
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hospitalization, and some of these adverse events make take time to develop as ALBC has
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longer elution time. In addition, our ALBC definition may have only taken into account
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premixed but not hand-mixed ALBC. As commercially premixed ALBC has been available in
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the US for 15 years and we expect hand-mixing to be mainly used in revision TKA, this
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potential misclassification is likely to minimally affect our results. Even more, such a
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potential bias would lead to ‘bias towards the null’, i.e. if this bias is present, it would mean
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that our effects are an underestimation and the protective effect on infections and the harmful
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effect in terms of acute renal failure will both be stronger. Furthermore, our findings are
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contingent on the quality and accuracy of the data collector and coder, which may vary by
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hospital. However, we do not expect any bias from database quality concerns to
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differentially affect infection rate and acute renal failure detection in the ALBC versus non-
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ALBC group, thus minimizing its effect. Additionally, early postoperative infection after
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discharge and readmission only included information on patients who returned to the
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same hospital where the index surgery took place. This may lead to an underestimation of
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the prevalence of these variables. However, this underestimation should be independent of
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ALBC use and thus is not likely to affect our relative effect measures. We utilized ICD-9
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codes to detect early postoperative infection and acute renal failure; however, we were not
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able to discern between superficial versus deep infection and we do not have information
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on how acute renal failure is defined by each hospital. Last and most importantly, even
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though database studies provide a unique window into real-world practice, they can only
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report on associations and not causations.
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Despite these limitations, this is the largest study of its kind examining the effect of ALBC usage on outcomes after primary TKA. One significant challenge with assessing the
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effectiveness of ALBC in infection reduction in primary TKA lies in the fact that the baseline
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infection rate is very low at approximately 1%. Therefore, large databases such as the one
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used in the current study are crucial in discerning potential benefits and adverse events of
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interventions such as routine usage of ALBC. We found that ALBC is associated with
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decreased odds of early postoperative infection, but increased odds of acute renal failure.
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Our study demonstrates the critical need to balance the potential risks and benefits of
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routine ALBC use in primary TKA, and that there truly is “no free lunch”. Future studies
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should focus on the full scope of risks and benefits associated with this practice while also
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studying patient subgroups that may benefit the most from prophylactic ALBC usage. Based
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on the findings from this study, it is the authors’ recommendation to use ALBC in higher
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risk cases and also consider use in routine primary cases without preexisting renal disease.
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19. D. Y, JE. D. A unified approach to measuring the effect size between two groups using SAS. SAS Global Forum 2012, Paper 335-2012. Online: http://support.sas.com/resources/papers/proceedings12/335-2012.pdf (accessed 11-012017). 20. Witte JS, Greenland S, Kim LL, Arab L. Multilevel modeling in epidemiology with GLIMMIX. Epidemiology 11(6): 684, 2000 21. Moran JL, Solomon PJ, Outcome ACf, Resource Evaluation of the A, New Zealand Intensive Care S. A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009. BMC Med Res Methodol 12: 68, 2012 22. Rascati KL, Smith MJ, Neilands T. Dealing with skewed data: an example using asthmarelated costs of medicaid clients. Clin Ther 23(3): 481, 2001 23. Baiocchi M, Cheng J, Small DS. Instrumental variable methods for causal inference. Stat Med 33(13): 2297, 2014 24. Wang H, Qiu GX, Lin J, Jin J, Qian WW, Weng XS. Antibiotic Bone Cement Cannot Reduce Deep Infection After Primary Total Knee Arthroplasty. Orthopedics 38(6): e462, 2015 25. Shahian DM, Nordberg P, Meyer GS, Blanchfield BB, Mort EA, Torchiana DF, Normand SL. Contemporary performance of U.S. teaching and nonteaching hospitals. Acad Med 87(6): 701, 2012 26. Chiu FY, Chen CM, Lin CF, Lo WH. Cefuroxime-impregnated cement in primary total knee arthroplasty: a prospective, randomized study of three hundred and forty knees. J Bone Joint Surg Am 84-A(5): 759, 2002 27. Malik MH, Chougle A, Pradhan N, Gambhir AK, Porter ML. Primary total knee replacement: a comparison of a nationally agreed guide to best practice and current surgical technique as determined by the North West Regional Arthroplasty Register. Ann R Coll Surg Engl 87(2): 117, 2005 28. Randelli P, Evola FR, Cabitza P, Polli L, Denti M, Vaienti L. Prophylactic use of antibioticloaded bone cement in primary total knee replacement. Knee Surg Sports Traumatol Arthrosc 18(2): 181, 2010 29. Robertsson O, Knutson K, Lewold S, Lidgren L. The Swedish Knee Arthroplasty Register 1975-1997: an update with special emphasis on 41,223 knees operated on in 1988-1997. Acta Orthop Scand 72(5): 503, 2001 30. Silvestre A, Almeida F, Renovell P, Morante E, Lopez R. Revision of infected total knee arthroplasty: two-stage reimplantation using an antibiotic-impregnated static spacer. Clin Orthop Surg 5(3): 180, 2013 31. Bourne RB. Prophylactic use of antibiotic bone cement: an emerging standard--in the affirmative. J Arthroplasty 19(4 Suppl 1): 69, 2004 32. Gooding CR, Masri BA, Duncan CP, Greidanus NV, Garbuz DS. Durable infection control and function with the PROSTALAC spacer in two-stage revision for infected knee arthroplasty. Clin Orthop Relat Res 469(4): 985, 2011 33. Wang J, Zhu C, Cheng T, Peng X, Zhang W, Qin H, Zhang X. A systematic review and metaanalysis of antibiotic-impregnated bone cement use in primary total hip or knee arthroplasty. PLoS One 8(12): e82745, 2013 34. Tayton ER, Frampton C, Hooper GJ, Young SW. The impact of patient and surgical factors on the rate of infection after primary total knee arthroplasty: an analysis of 64,566 joints from the New Zealand Joint Registry. Bone Joint J 98-B(3): 334, 2016
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35. Bohm E, Zhu N, Gu J, de Guia N, Linton C, Anderson T, Paton D, Dunbar M. Does adding antibiotics to cement reduce the need for early revision in total knee arthroplasty? Clin Orthop Relat Res 472(1): 162, 2014 36. Eveillard M, Mertl P, Tramier B, Eb F. Effectiveness of gentamicin-impregnated cement in the prevention of deep wound infection after primary total knee arthroplasty. Infect Control Hosp Epidemiol 24(10): 778, 2003 37. Bailey O, Torkington MS, Anthony I, Wells J, Blyth M, Jones B. Antibiotic-related acute kidney injury in patients undergoing elective joint replacement. Bone Joint J 96-B(3): 395, 2014 38. Courtney PM, Melnic CM, Zimmer Z, Anari J, Lee GC. Addition of Vancomycin to Cefazolin Prophylaxis Is Associated With Acute Kidney Injury After Primary Joint Arthroplasty. Clin Orthop Relat Res 473(7): 2197, 2015 39. Lau BP, Kumar VP. Acute kidney injury (AKI) with the use of antibiotic-impregnated bone cement in primary total knee arthroplasty. Ann Acad Med Singapore 42(12): 692, 2013 40. Edelstein AI, Okroj KT, Rogers T, Della Valle CJ, Sporer SM. Nephrotoxicity After the Treatment of Periprosthetic Joint Infection With Antibiotic-Loaded Cement Spacers. J Arthroplasty 33(7): 2225, 2018 41. Patel RA, Baker HP, Smith SB. Acute Renal Failure due to a Tobramycin and Vancomycin Spacer in Revision Two-Staged Knee Arthroplasty. Case Rep Nephrol 2018: 6579894, 2018
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Table 1. Use of antibiotic-loaded bone cement by study variables; row percentages.
66 (59-73)
66 (59-74)
201,794 120,682
540,453 321,341
250,718 26,270 45,488
665,654 63,773 132,367
27.4% 29.2% 25.6%
307,120 27,779 491,444 3,203 32,248
STD
0.011 0.003
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27.2% 27.3%
26,732 295,744
98,300 763,494
21.4% 27.9%
92,698 113,072 116,706
222,805 288,794 350,195
29.4% 28.1% 25.0%
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27.5% 24.2% 27.3% 26.1% 25.7%
116,375 8,856 184,950 1,132 11,163
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DEMOGRAPHICS Age* Sex Female Male Race White Black Other Insurance Type Commercial Medicaid Medicare Uninsured Unknown HEALTHCARE-RELATED Hospital Location Rural Urban Hospital Size Small (<300 beds) Medium (300-499 beds) Large (≥500 beds) Hospital Teaching Status Non-Teaching Teaching No. of Annual Knee Arthroplasties Per Hospital* PROCEDURE-RELATED Year of Procedure 2006 2007 2008 2009 2010 2011
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Antibiotic-Loaded Bone Cement Yes No (N=322,476) (N=861,794) N* N* % Use
0.043
0.033
0.105
0.095
0.006
190,010 132,466
510,469 351,325
27.1% 27.4%
409 (243-662)
402 (232671)
-
0.042
0.164 12,670 18,289 21,054 25,474 31,121 32,884
60,582 60,932 63,068 68,109 71,824 77,083
17.3% 23.1% 25.0% 27.2% 30.2% 29.9%
34,431 35,479 36,798 38,497 35,779
85,272 89,570 91,777 99,397 94,180
28.8% 28.4% 28.6% 27.9% 27.5%
220,767 74,797 63,670
573,565 176,906 201,415
53,473 99,934 134,438 7,455 48,489 41,599 134,639 59,734
160,696 250,188 325,391 20,387 119,128 77,343 342,569 130,122
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172,265 95,508 33,632 21,071 74,786 80,324
0 (0-1)
0.041 0.065 0.088
28.5% 29.2% 26.8% 28.9% 35.0% 28.2% 31.5%
0.054 0.043 0.080 0.004 0.035 0.035 0.041 0.092
-
0.086
0.087 495,164 239,790 80,380 46,460 180,527 203,179
STD: standardized difference *Median and interquartile range instead of N and %
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27.8% 29.7% 24.0% 25.0%
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2012 2013 2014 2015 2016 Anesthesia Type General Neuraxial Unknown Patient Controlled Analgesia NSAIDs Cox-2 Inhibitors Ketamine Gabapentin Pregabalin Acetaminophen Peripheral Nerve Block COMORBIDITIES Deyo-Charlson Comorbidity Index (continuous)* Deyo-Charlson Comorbidity Index (categorized) 0 1 2 2+ Smoking Obesity
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25.8% 28.5% 29.5% 31.2% 29.3% 28.3%
0.054 0.031
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Table 2. Outcomes by use of antibiotic-loaded bone cement; column percentages
0.47
3966
5833 10634 15730 599 10127
1.81 3.30 4.88 0.19 3.14
1276
0.40
RESOURCE UTILIZATION Length of Stay* 3 Cost of $16,251 Hospitalization*
2-3 $13,501$20,128
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STD: standardized difference *Median and interquartile range instead of N and %
STD
0.46
0.001
12796 29538 42908 1456 23654
1.48 3.43 4.98 0.17 2.74
0.026 0.007 0.005 0.004 0.023
3072
0.36
0.006
2-3 $12,873$19,598
0.009
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CLINICAL OUTCOMES Early postoperative Infection Acute Renal Failure 30-Day Readmission 90-Day Readmission Acute Dialysis Allergic Complications Microbiome Disruption
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Antibiotic-Loaded Bone Cement Yes (N=322,476) No (N=861,794) N* % N* %
3
$15,698
0.111
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Instrumental variable analysis (n=1,184,270)
Restricted cohort analysis (n=825,862)
OR or % change
95% CI
OR or % change
0.90
0.83
0.96
0.97
1.06* 0.97 0.98 1.09 1.01 1.04
1.02 0.94 0.96 0.97 0.98 0.97
1.11 1.01 1.01 1.23 1.04 1.13
1.07* 0.91* 0.96* 0.93 1.01 1.07
RESOURCE UTILIZATION Length of Stay Cost of Hospitalization
0.5%* 3.5%*
0.2% 0.7% 0.9%* 3.2% 3.8% 2.1%*
1.06
1.02 0.88 0.93 0.82 0.97 0.10
1.12 0.94 0.98 1.07 1.04 1.16
95% CI
0.93
0.86
1.00
1.05* 0.97 0.97* 1.11 1.01 1.03
1.01 0.94 0.95 0.98 0.98 0.95
1.10 1.00 1.00 1.25 1.04 1.11
0.6% 1.2% 0.5%* 1.8% 2.5% 3.5%*
0.2% 0.7% 3.2% 3.8%
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Main analysis (n=1,184,270) OR or % change 95% CI CLINICAL OUTCOMES Early Postoperative infection Acute Renal Failure 30-Day Readmission 90-Day Readmission Acute Dialysis Allergic Complications Microbiome Disruption
*P<0.05
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Table 3. Results from multivariable analysis assessing the association between use of antibiotic-loaded bone cement (reference = no use) and outcomes; % change (instead of OR) for continuous outcomes (length of stay and cost of hospitalization)
Models adjusted for age, sex, insurance type, hospital location, size, teaching status and annual TKA volume, year of procedure, anesthesia type, use of patient controlled analgesia, NSAIDs, COX-2 inhibitors, ketamine, pregabalin, gabapentin, acetaminophen, peripheral nerve blocks, Deyo-Charlson comorbidities, smoking and obesity.
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Figure 1. Study flow diagram
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Figure 2. Trends in utilization of antibiotic-loaded bone cement stratified by hospital characteristics
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Appendix I Definitions of outcome variables Postoperative infection
ICD-9 996.66 and 998.59 ICD-9 584.9 Items selected from inpatient billing file: ‘HEMODIALYSIS SERVICES’ ICD-9 693.0 Dermatitis due to drugs/medicine ICD-9 995.0 Anaphylaxis ICD-9 708.0 Allergic urticaria ICD-9 995.1 Angioneurotic edema ICD-9 995.2 Unspecified adverse effect due to unspecified drug ICD-9 995.3 Allergy unspecified ICD-9 698.8 Specified pruritus ICD-9 698.9 Unspecified pruritis ICD-9 782.1 Rash ICD-9 708.9 Urticaria unspecified ICD-9 708.0 Allergic urticaria ICD-9 288.3 Eosinophilia ICD-9 695.9 Red man syndrome ICD-9 008.45 Clostridium difficile infection ICD-9 009.0 Intestinal infection ICD-9 787.91 Diarrhea ICD-9 112.1/112.9 Yeast infection
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Acute renal failure Dialysis need
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Allergic complications
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Complications related to microbiome disruption
S0883-5403(19)30229-3
DOI:
https://doi.org/10.1016/j.arth.2019.03.006
Reference:
YARTH 57129
To appear in:
The Journal of Arthroplasty
Received Date: 20 November 2018 Revised Date:
1 March 2019
Accepted Date: 2 March 2019
Please cite this article as: Chan JJ, Robinson J, Poeran J, Huang H-H, Moucha CS, Chen D, Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database, The Journal of Arthroplasty (2019), doi: https:// doi.org/10.1016/j.arth.2019.03.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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1. Department of Orthopaedic Surgery Icahn School of Medicine at Mount Sinai 5 East 98th Street, Box 1188 New York, NY 10029
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Jimmy J. Chan, MD1 Jonathan Robinson, MD1 Jashvant Poeran, MD, PhD2 Hsin-Hui Huang, MD, PhD2 Calin S. Moucha MD1 Darwin Chen, MD1
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Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database
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2. Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai One Gustave Levy Place, Box 1077 New York, NY 10029
Please address all correspondence to:
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Darwin Chen, MD Department of Orthopaedic Surgery Icahn School of Medicine at Mount Sinai 5 East 98th Street, Box 1188 New York, NY 10029
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Phone: (212) 241-1924 Fax: (212) 241-9710 Email: [email protected]
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Antibiotic-Loaded Bone Cement in Primary Total Knee Arthroplasty: Utilization Patterns and Impact on Complications Using a National Database
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Abstract
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Introduction: The routine usage of antibiotic loaded bone cement (ALBC) in primary total knee arthroplasty (TKA) is controversial. Its effectiveness in reducing infection risk remains unclear while high dose antibiotics can lead to multiple adverse effects. The purpose of this population-based study is to evaluate utilization patterns of ALBC in primary TKA and its impact on clinical outcomes. Methods: This retrospective cohort study utilized data from the nationwide Premier Healthcare claims database (2006-2016). Multivariable models estimated associations between ALBC use and early postoperative infection, kidney injury, allergic reaction, hospital readmission, cost, and length of stay. Results: ALBC was utilized in 27.2% of all primary TKAs (N=1,184,270). Usage increased from 17.3% to 30.2% in 2006-2010, then plateaued. Study covariates differed minimally between groups, suggesting non-selective ALBC use. Utilization was lower in rural (21.4%) and higher in large (>500 beds; 29.4%) hospitals. After adjusting for relevant covariates, ALBC use was associated with significantly decreased odds for early post-operative infection (OR = 0.89 CI 0.83-0.96) and increased odds for AKI (OR = 1.06 CI 1.02-1.11). Conclusion: With utilization rates of around 30%, we found that ALBC reduced odds for early postoperative infection and increased odds for kidney injury. Strong consideration should be given for selective use of ALBC in primary TKA.
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Keywords: antibiotic cement; knee arthroplasty; infection; outcomes; acute renal failure
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1
Introduction
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Periprosthetic joint infection (PJI) remains one of the leading causes of failure after total knee arthroplasty (TKA), resulting in significant morbidity and mortality.[1, 2] With
5
the routine use of prophylactic systemic antibiotics as well as other standard perioperative
6
infection control measures, the infection rate after primary TKA is approximately 1%-
7
3%.[3] The treatment of PJI after TKA is difficult because of bacterial biofilm formation on
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prosthetic joint surfaces as well as poor penetration and delivery of systemic antibiotics into
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the joint itself. Bucholz and Engelbrecht introduced the concept of antibiotic-loaded bone
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cement (ALBC) in 1970.[4] ALBC allows for immediate antibiotic delivery at the time of
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implantation and continuous elution of antibiotics for at least 30 days postoperatively.[5]
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Over the past twenty years, ALBC has become a critical component of the standard
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treatment for PJI, typically via one- or two-stage exchange revision arthroplasty.
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While considered an established method for the management of periprosthetic hip and knee joint infections, routine use of ALBC as prophylaxis in primary TKA remains
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controversial.[6] First, the introduction of high-dose antibiotics locally carries the risk of
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developing adverse systemic effects such as renal injury and hypersensitivity.[7, 8] Other
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concerns include the development of antibiotic resistance, reduction in the mechanical
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properties of bone cement, subsequent TKA failures due to mechanical loosening, and
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increased cost.[9-11] In addition, in the absence of high-quality evidence, there is currently
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no consensus on whether routine use of ALBC actually reduces the infection rate in primary
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TKA.[11] Most published data examining the effect of routine use of ALBC in TKA stems
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from trials involving select patient populations such as revision settings or those with a
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higher baseline comorbidity burden, thus imparting significant bias that negatively impacts
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the generalizability of these findings [5, 12-14]. The purpose of this large database driven,
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population-based study is to evaluate real-world utilization patterns of ALBC in primary
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TKA, and its impact on TKA outcomes and economic burden. We hypothesize that ALBC is
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associated with a decreased risk of infection without an increased risk of systemic
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complications.
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Methods
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Data Source, Study Design and Sample
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Our Institutional Review Board approved use of the HIPAA-compliant anonymized
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data for this study (project #14-00647). For this retrospective cohort study, data from the
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Premier Healthcare Database[15] (Premier Healthcare Solutions, Inc., Charlotte, NC) was
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used. This database contains administrative claims data on approximately 20-25% of US
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hospital discharges. Records include International Classification of Disease-9th revision
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(ICD-9) codes, Current Procedural Terminology (CPT) codes, and complete inpatient billing
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items in a standardized free text format. We included patients undergoing a TKA procedure
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(ICD-9 code 81.54) between 2006 and 2016. Cases with missing information on sex (n=217)
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or discharge status (n=654), labeled as outpatient (n=8,489), or cases performed in
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hospitals with a volume of <30 TKA procedures in the study period (n=4,139) were
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excluded. A total of 1,184,270 procedures were included in the final study cohort (Figure
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1).
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Study Variables The intervention of interest, i.e. the main predictor, was the use of ALBC which was identified from specific billing item descriptions (not codes) using the term “CEMENT
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BONE W/ ANTIBIOTIC” in the standardized free text to create the variable. The main
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outcomes of interest were early postoperative infection within 30 days (either during the
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index hospitalization or subsequent hospitalizations within that timeframe), acute renal
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failure, 30-day and 90-day readmission, acute perioperative dialysis need (as a proxy for
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renal compromise, defined from billing item descriptions), allergic complications,
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complications related to microbiome disruption, length of hospital stay (LOS), and cost of
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hospitalization. Appendix I details the definition of these variables, either the ICD-9 codes
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or billing items used from the standardized free text billing file. Cost of hospitalization was
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adjusted for inflation and reported in January 2016 US dollars; 30-day readmission and 90-
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day readmission included any readmission within 30 days and 90 days, respectively, to the
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same hospital where the primary procedure took place.
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A variety of other variables were considered that may lie in the pathway between ALBC and outcomes; these include patient demographics, healthcare-, procedure- and
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comorbidity-related variables. Patient demographics included age, sex, race (White, Black,
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other/unknown) and insurance type (Commercial, Medicaid, Medicare, uninsured,
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unknown). Healthcare-related variables included hospital location (rural, urban), bed size
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(<300, 300-499, ≥500 beds), teaching status and annual hospital-specific TKA volume.
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Procedure-related variables included the year in which the procedure was performed, type
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of anesthesia used, use of patient controlled analgesia, nonsteroidal anti-inflammatory
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drugs (NSAIDs), cyclooxygenase-2 (COX-2) inhibitors, ketamine, gabapentin, pregabalin,
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acetaminophen, and peripheral nerve blocks. Comorbidity-related variables included the
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Quan adaptation of the Charlson-Deyo Index[16], smoking, and obesity (body mass index
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≥30 kg/m2). The majority of our variables did not have missing information except for race,
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insurance status and anesthesia type. These were treated as separate categories within the
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respective variables. Excluding this information did not change our main conclusions.
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Statistical Analyses
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No a priori sample size calculation was performed. Based on an estimated overall infection risk 5%, our sample size had >90% power to detect a 10% relative difference in
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infection risk between cases with and without ALBC.[17]
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First, we assessed univariable associations between use of ALBC and the
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aforementioned variables. Given our large sample size, univariable differences between
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groups easily reached statistical significance. Therefore, in univariable comparisons, we
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used standardized differences instead of P-values. A standardized difference of 0.1 (or 10%)
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has been suggested to indicate a meaningful difference in covariate distribution between
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groups.[18, 19] Additionally, we assessed trends in utilization of ALBC stratified by hospital
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characteristics (hospital bed size, location, and teaching status).
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Mixed-effects models were used to measure the association between the use of
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ALBC and outcomes. The advantage of these models is that they account for the correlation
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of patients treated within the same hospital as they may be similar in terms of the care they
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receive.[20] Models were adjusted for all study variables mentioned above; no specific
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interactions were considered. Adjusted odds ratios (OR) and 95% confidence intervals (CI)
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are reported. LOS and cost of hospitalization represent skewed data and were therefore
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modeled using the gamma distribution with a log link function using the PROC GLIMMIX
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procedure in SAS statistical software.[21, 22] Therefore, for LOS and cost of hospitalization
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instead of ORs, percent (%) change compared to the reference (no use of ALBC) is reported.
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All analyses were performed using SAS v9.4 statistical software (SAS Institute, Cary, NC).
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Sensitivity Analyses
We performed two additional analyses to examine the robustness of our study
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results. First, we conducted an ‘instrumental variable analysis’ which aims to address both
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measured and unmeasured confounding (in contrast to other methods such as propensity
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score analysis). Instrumental variable analysis requires the selection of a valid
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‘instrumental variable’ that meets three key assumptions: 1) the instrumental variable is
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positively associated with the treatment variable, which in this context is ALBC use, 2) the
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instrumental variable is independent of (un)measured confounders, and 3) the
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instrumental variable is associated with the outcomes of interest, including early
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postoperative infection and acute renal failure, only indirectly through its effect on the
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treatment, i.e. ALBC use.[23] This approach adopts the framework of a randomized
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controlled trial in that the selected instrumental variable is used to represent a mechanism
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for assigning a treatment to patients. We selected surgeon-specific use (in %) of ALBC as an
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instrumental variable assuming that this will affect the probability that ALBC will be used
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in a case. In other words, cases performed by surgeons with higher use of ALBC are more
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likely to utilize ALBC. This variable was used to allocate the treatment variable after which
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mixed-effects models were applied.
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In the second sensitivity analysis we restricted our cohort to only hospitals in which ALBC was actually used as patients in hospitals without ALBC use theoretically are not at
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risk for exposure to this treatment. The main regression analysis was then performed in
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this restricted cohort (n=825,862).
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Sources of Funding
No funds were received in support of this work. No benefits in any form have been
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or will be received from any commercial party related directly or indirectly to the subject
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of this manuscript.
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Results
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Overall, data on 1,184,270 TKA procedures were included; ALBC was utilized in
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27.2% (n=322,476) of cases. Minor differences were seen in covariate distributions
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between patients receiving ALBC and those that did not (Table 1; most standardized
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differences <0.1). Interestingly, particularly lower use was seen in rural hospitals. ALBC
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usage increased from 2006 until 2010, after which a minimally decreasing trend was seen
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(Figure 2). When stratifying trends by hospital type, decreasing trends are more
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pronounced for teaching and large/medium-sized hospitals while a continued increase in
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usage of ALBC was seen in small hospitals, with less pronounced increasing trends in
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non-teaching hospitals (Figure 2).
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Most unadjusted outcomes did not differ between patients receiving ALBC and those that did not (Table 2; most standardized differences <0.1) except for median unadjusted
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cost of hospitalization, which was $16,251, and $15,698, respectively. These absolute
139
numbers need to be taken into account when interpreting the adjusted relative effect
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estimates (Table 3); after adjustment for relevant covariates, the use of ALBC (compared
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to no use) was significantly associated with reduced odds for early postoperative infections
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(OR 0.89 CI 0.83-0.96). Importantly, increased odds for acute renal failure (OR 1.06 CI 1.02-
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1.11) were seen (both P<0.05) with ALBC use. No statistically significant effects existed for
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the other complications while minimal effects were seen for LOS (+0.5%) and cost of
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hospitalization (+3.5%); these are adjusted relative effects taking into account all
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confounders.
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The sensitivity analyses (Table 3) corroborated mainly the finding that ALBC use was associated with increased odds for acute renal failure while the association with early
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postoperative infection was not significant anymore (although with unchanged direction of
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effect). The sensitivity analyses also demonstrated associations with reduced odds for
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readmissions, corroborating the direction of effect in the main analysis.
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Discussion
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This is the first national, large database study on the prophylactic use of ALBC in
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primary TKA. We found an overall ALBC utilization rate of 27.2% with an overall stagnant
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trend over a ten-year span. However, differences exist when stratifying by hospital type,
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with increasing use in smaller hospitals and decreasing use in medium/large-sized and
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teaching hospitals over a 10 year span. After adjusting for relevant covariates, ALBC was
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associated with significantly decreased odds of early postoperative infection and
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significantly increased odds of acute renal failure. Particularly the latter finding was
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corroborated in sensitivity analyses. These relative effects have to be interpreted in the
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context of the overall low prevalence of complications in patients undergoing TKA. This is
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likely to result in a high number-needed-to-expose, i.e. a large number of patients need to
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be exposed to ALBC in order for one to benefit or be harmed. However, given that TKA is a
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high-volume procedure, the results from the current study may be relevant to individual
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hospitals as well as the population level.
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When evaluating the overall cohort, the trend of ALBC utilization is stagnant over a ten-year span. While several potential explanations exist, the lack of consensus and the
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absence of high-quality evidence supporting prophylactic use of ALBC in primary TKA may
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be the main driving mechanism. [11, 17, 24] An interesting pattern emerged when
172
stratifying by hospital type, with slightly increasing trends in smaller, non-teaching, and
173
rural hospitals. We can only speculate on the mechanisms behind these findings, however,
174
previous studies have indeed demonstrated differences in care by hospital type. For
175
example, academic and larger urban medical centers may be more likely to provide care
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and treatment protocols backed by the literature. Indeed, Shahian et al. demonstrated that
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surgical care in major teaching hospitals adhered to evidence-based guidelines and
178
protocols more consistently than non-teaching hospitals in 4,809 hospitals from 2006-
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2009.[25] Therefore, without a clear demonstration of benefits, large academic centers
180
may be less likely to change or implement new protocols on routine ALBC use in primary
181
TKA patients. Increased cost of routine ALBC use may also be a driver of decreased usage in
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large hospital systems, where the total cost of care for joint replacement may be more
183
carefully scrutinized.
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Our results demonstrated that patient characteristics and comorbidities did not impact the utilization rate of ALBC, suggesting non-selective use. Moreover, patients with
186
different anesthesia types, Deyo-Charlson comorbidity index, and obesity all have
187
comparable rates of ALBC use, further emphasizing this finding. Given the lack of
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high-quality evidence supporting routine use of ALBC, one alternative strategy could be the
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use of prophylactic ALBC among those perceived to be at increased risk of PJI such as
190
patients with diabetes, as previously suggested.[26] In contrast to utilization rates in the
191
US, international registry data demonstrates routine use of ALBC to be over 90% in the
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United Kingdom, Norway and Sweden, but is significantly lower in Spain and Russia.[27-
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29] This suggests that the decision to use ALBC may not be dependent on patients’
194
individual risk factors but rather external factors such as local/regional protocols or
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surgeon preference. Future studies should focus on the drivers behind the choice of using
196
ALBC as this may provide important information on how to modify its utilization and steer
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it towards use in the patients that are most likely to benefit.
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We found a small yet significant reduction in the odds of early postoperative infection associated with ALBC use. Compared to the demonstrated benefit of ALBC use in
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revision TKA for PJI, studies on the effect of ALBC on infection rates in primary TKA are
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controversial.[30-32] One randomized controlled trial examined 384 primary TKA
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procedures (with an average of 49 months follow-up) found a deep infection rate of 3.1%
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in controls compared to 0% in the ALBC group; no difference was seen in the superficial
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wound infection rate.[26] Wang et al. reported similar findings in a systematic review of
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eight studies including 6,381 primary TKA procedures. Here, the use of ALBC coincided
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with a significant reduction in the deep infection rate (RR = 0.41, p = 0.04), however, the
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effect was reverse for superficial infections (RR = 1.47, p=0.004).[33] Subgroup analysis
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further demonstrated that gentamycin was superior to cefuroxime in reducing deep
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infection. On the contrary, Tayton et al. used the New Zealand registry database and
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evaluated 64,566 primary TKAs between 1999 and 2012. They counter-intuitively found
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increased revision for PJI with use of ALBC (OR 1.93).[34] Some have postulated that the
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amount of cement use in TKA is typically low (compared to antibiotic spacers in a revision
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setting) which might lead to lower duration and magnitude of effective antibiotic level
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inside the joint.[35]
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odds of acute renal failure associated with routine prophylactic ALBC use; this persisted in
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sensitivity analyses. Indeed, the use of ALBC is not without potential adverse effects.
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Gentamicin, vancomycin, and tobramycin are the three most commonly used antibiotics in
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ALBC, and all have potential for renal toxicity.[28, 36] Routine use of renal toxic
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perioperative systemic antibiotics has shown to increase acute renal failure in primary hip
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and knee joint replacement. [37, 38] ALBC places renal function at even higher stress than
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perioperative systemic antibiotics because the concentration of antibiotic release is
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significantly higher with a longer elution period of up to 30 days postoperatively. Despite
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the absence of high-quality evidence on acute renal failure risk in routine ALBC use,[39]
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development of postoperative acute renal failure in revision TKA has been well elucidated
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in the literature.[40, 41] Besides acute renal failure, we did not find any significant adverse
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effects including allergic complications and microbiome disruption that could be associated
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with high dose antibiotic use linked to ALBC. However, our study only focused on these
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events during the index hospitalization, and some of these adverse events make take time
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to develop as ALBC has a long elution time. Therefore, follow-up studies should be geared
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towards long-term effects of routine ALBC use to appreciate the full scope of risks and
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benefits. Our study has limitations. First, this is a database study, and therefore several
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potential confounding variables such as operative time, baseline renal status, hospital
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operating room infection control protocols, and importantly, intravenous antibiotic
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prophylaxis characteristics were not available. Also, we did not have information on the
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type of antibiotic included in the ALBC. As previous studies have shown, some antibiotics
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have more negative side effect profiles in terms of complications such as renal failure and
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microbiome disruption. The different antibiotics used in various ALBC brands may also
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have differing effects on reducing PJI. Our study only focused on the immediate index
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hospitalization, and some of these adverse events make take time to develop as ALBC has
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longer elution time. In addition, our ALBC definition may have only taken into account
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premixed but not hand-mixed ALBC. As commercially premixed ALBC has been available in
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the US for 15 years and we expect hand-mixing to be mainly used in revision TKA, this
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potential misclassification is likely to minimally affect our results. Even more, such a
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potential bias would lead to ‘bias towards the null’, i.e. if this bias is present, it would mean
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that our effects are an underestimation and the protective effect on infections and the harmful
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effect in terms of acute renal failure will both be stronger. Furthermore, our findings are
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contingent on the quality and accuracy of the data collector and coder, which may vary by
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hospital. However, we do not expect any bias from database quality concerns to
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differentially affect infection rate and acute renal failure detection in the ALBC versus non-
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ALBC group, thus minimizing its effect. Additionally, early postoperative infection after
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discharge and readmission only included information on patients who returned to the
254
same hospital where the index surgery took place. This may lead to an underestimation of
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the prevalence of these variables. However, this underestimation should be independent of
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ALBC use and thus is not likely to affect our relative effect measures. We utilized ICD-9
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codes to detect early postoperative infection and acute renal failure; however, we were not
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able to discern between superficial versus deep infection and we do not have information
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on how acute renal failure is defined by each hospital. Last and most importantly, even
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though database studies provide a unique window into real-world practice, they can only
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report on associations and not causations.
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Despite these limitations, this is the largest study of its kind examining the effect of ALBC usage on outcomes after primary TKA. One significant challenge with assessing the
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effectiveness of ALBC in infection reduction in primary TKA lies in the fact that the baseline
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infection rate is very low at approximately 1%. Therefore, large databases such as the one
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used in the current study are crucial in discerning potential benefits and adverse events of
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interventions such as routine usage of ALBC. We found that ALBC is associated with
268
decreased odds of early postoperative infection, but increased odds of acute renal failure.
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Our study demonstrates the critical need to balance the potential risks and benefits of
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routine ALBC use in primary TKA, and that there truly is “no free lunch”. Future studies
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should focus on the full scope of risks and benefits associated with this practice while also
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studying patient subgroups that may benefit the most from prophylactic ALBC usage. Based
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on the findings from this study, it is the authors’ recommendation to use ALBC in higher
274
risk cases and also consider use in routine primary cases without preexisting renal disease.
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19. D. Y, JE. D. A unified approach to measuring the effect size between two groups using SAS. SAS Global Forum 2012, Paper 335-2012. Online: http://support.sas.com/resources/papers/proceedings12/335-2012.pdf (accessed 11-012017). 20. Witte JS, Greenland S, Kim LL, Arab L. Multilevel modeling in epidemiology with GLIMMIX. Epidemiology 11(6): 684, 2000 21. Moran JL, Solomon PJ, Outcome ACf, Resource Evaluation of the A, New Zealand Intensive Care S. A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009. BMC Med Res Methodol 12: 68, 2012 22. Rascati KL, Smith MJ, Neilands T. Dealing with skewed data: an example using asthmarelated costs of medicaid clients. Clin Ther 23(3): 481, 2001 23. Baiocchi M, Cheng J, Small DS. Instrumental variable methods for causal inference. Stat Med 33(13): 2297, 2014 24. Wang H, Qiu GX, Lin J, Jin J, Qian WW, Weng XS. Antibiotic Bone Cement Cannot Reduce Deep Infection After Primary Total Knee Arthroplasty. Orthopedics 38(6): e462, 2015 25. Shahian DM, Nordberg P, Meyer GS, Blanchfield BB, Mort EA, Torchiana DF, Normand SL. Contemporary performance of U.S. teaching and nonteaching hospitals. Acad Med 87(6): 701, 2012 26. Chiu FY, Chen CM, Lin CF, Lo WH. Cefuroxime-impregnated cement in primary total knee arthroplasty: a prospective, randomized study of three hundred and forty knees. J Bone Joint Surg Am 84-A(5): 759, 2002 27. Malik MH, Chougle A, Pradhan N, Gambhir AK, Porter ML. Primary total knee replacement: a comparison of a nationally agreed guide to best practice and current surgical technique as determined by the North West Regional Arthroplasty Register. Ann R Coll Surg Engl 87(2): 117, 2005 28. Randelli P, Evola FR, Cabitza P, Polli L, Denti M, Vaienti L. Prophylactic use of antibioticloaded bone cement in primary total knee replacement. Knee Surg Sports Traumatol Arthrosc 18(2): 181, 2010 29. Robertsson O, Knutson K, Lewold S, Lidgren L. The Swedish Knee Arthroplasty Register 1975-1997: an update with special emphasis on 41,223 knees operated on in 1988-1997. Acta Orthop Scand 72(5): 503, 2001 30. Silvestre A, Almeida F, Renovell P, Morante E, Lopez R. Revision of infected total knee arthroplasty: two-stage reimplantation using an antibiotic-impregnated static spacer. Clin Orthop Surg 5(3): 180, 2013 31. Bourne RB. Prophylactic use of antibiotic bone cement: an emerging standard--in the affirmative. J Arthroplasty 19(4 Suppl 1): 69, 2004 32. Gooding CR, Masri BA, Duncan CP, Greidanus NV, Garbuz DS. Durable infection control and function with the PROSTALAC spacer in two-stage revision for infected knee arthroplasty. Clin Orthop Relat Res 469(4): 985, 2011 33. Wang J, Zhu C, Cheng T, Peng X, Zhang W, Qin H, Zhang X. A systematic review and metaanalysis of antibiotic-impregnated bone cement use in primary total hip or knee arthroplasty. PLoS One 8(12): e82745, 2013 34. Tayton ER, Frampton C, Hooper GJ, Young SW. The impact of patient and surgical factors on the rate of infection after primary total knee arthroplasty: an analysis of 64,566 joints from the New Zealand Joint Registry. Bone Joint J 98-B(3): 334, 2016
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35. Bohm E, Zhu N, Gu J, de Guia N, Linton C, Anderson T, Paton D, Dunbar M. Does adding antibiotics to cement reduce the need for early revision in total knee arthroplasty? Clin Orthop Relat Res 472(1): 162, 2014 36. Eveillard M, Mertl P, Tramier B, Eb F. Effectiveness of gentamicin-impregnated cement in the prevention of deep wound infection after primary total knee arthroplasty. Infect Control Hosp Epidemiol 24(10): 778, 2003 37. Bailey O, Torkington MS, Anthony I, Wells J, Blyth M, Jones B. Antibiotic-related acute kidney injury in patients undergoing elective joint replacement. Bone Joint J 96-B(3): 395, 2014 38. Courtney PM, Melnic CM, Zimmer Z, Anari J, Lee GC. Addition of Vancomycin to Cefazolin Prophylaxis Is Associated With Acute Kidney Injury After Primary Joint Arthroplasty. Clin Orthop Relat Res 473(7): 2197, 2015 39. Lau BP, Kumar VP. Acute kidney injury (AKI) with the use of antibiotic-impregnated bone cement in primary total knee arthroplasty. Ann Acad Med Singapore 42(12): 692, 2013 40. Edelstein AI, Okroj KT, Rogers T, Della Valle CJ, Sporer SM. Nephrotoxicity After the Treatment of Periprosthetic Joint Infection With Antibiotic-Loaded Cement Spacers. J Arthroplasty 33(7): 2225, 2018 41. Patel RA, Baker HP, Smith SB. Acute Renal Failure due to a Tobramycin and Vancomycin Spacer in Revision Two-Staged Knee Arthroplasty. Case Rep Nephrol 2018: 6579894, 2018
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Table 1. Use of antibiotic-loaded bone cement by study variables; row percentages.
66 (59-73)
66 (59-74)
201,794 120,682
540,453 321,341
250,718 26,270 45,488
665,654 63,773 132,367
27.4% 29.2% 25.6%
307,120 27,779 491,444 3,203 32,248
STD
0.011 0.003
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27.2% 27.3%
26,732 295,744
98,300 763,494
21.4% 27.9%
92,698 113,072 116,706
222,805 288,794 350,195
29.4% 28.1% 25.0%
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27.5% 24.2% 27.3% 26.1% 25.7%
116,375 8,856 184,950 1,132 11,163
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DEMOGRAPHICS Age* Sex Female Male Race White Black Other Insurance Type Commercial Medicaid Medicare Uninsured Unknown HEALTHCARE-RELATED Hospital Location Rural Urban Hospital Size Small (<300 beds) Medium (300-499 beds) Large (≥500 beds) Hospital Teaching Status Non-Teaching Teaching No. of Annual Knee Arthroplasties Per Hospital* PROCEDURE-RELATED Year of Procedure 2006 2007 2008 2009 2010 2011
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Antibiotic-Loaded Bone Cement Yes No (N=322,476) (N=861,794) N* N* % Use
0.043
0.033
0.105
0.095
0.006
190,010 132,466
510,469 351,325
27.1% 27.4%
409 (243-662)
402 (232671)
-
0.042
0.164 12,670 18,289 21,054 25,474 31,121 32,884
60,582 60,932 63,068 68,109 71,824 77,083
17.3% 23.1% 25.0% 27.2% 30.2% 29.9%
34,431 35,479 36,798 38,497 35,779
85,272 89,570 91,777 99,397 94,180
28.8% 28.4% 28.6% 27.9% 27.5%
220,767 74,797 63,670
573,565 176,906 201,415
53,473 99,934 134,438 7,455 48,489 41,599 134,639 59,734
160,696 250,188 325,391 20,387 119,128 77,343 342,569 130,122
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172,265 95,508 33,632 21,071 74,786 80,324
0 (0-1)
0.041 0.065 0.088
28.5% 29.2% 26.8% 28.9% 35.0% 28.2% 31.5%
0.054 0.043 0.080 0.004 0.035 0.035 0.041 0.092
-
0.086
0.087 495,164 239,790 80,380 46,460 180,527 203,179
STD: standardized difference *Median and interquartile range instead of N and %
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27.8% 29.7% 24.0% 25.0%
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2012 2013 2014 2015 2016 Anesthesia Type General Neuraxial Unknown Patient Controlled Analgesia NSAIDs Cox-2 Inhibitors Ketamine Gabapentin Pregabalin Acetaminophen Peripheral Nerve Block COMORBIDITIES Deyo-Charlson Comorbidity Index (continuous)* Deyo-Charlson Comorbidity Index (categorized) 0 1 2 2+ Smoking Obesity
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25.8% 28.5% 29.5% 31.2% 29.3% 28.3%
0.054 0.031
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Table 2. Outcomes by use of antibiotic-loaded bone cement; column percentages
0.47
3966
5833 10634 15730 599 10127
1.81 3.30 4.88 0.19 3.14
1276
0.40
RESOURCE UTILIZATION Length of Stay* 3 Cost of $16,251 Hospitalization*
2-3 $13,501$20,128
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STD: standardized difference *Median and interquartile range instead of N and %
STD
0.46
0.001
12796 29538 42908 1456 23654
1.48 3.43 4.98 0.17 2.74
0.026 0.007 0.005 0.004 0.023
3072
0.36
0.006
2-3 $12,873$19,598
0.009
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CLINICAL OUTCOMES Early postoperative Infection Acute Renal Failure 30-Day Readmission 90-Day Readmission Acute Dialysis Allergic Complications Microbiome Disruption
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Antibiotic-Loaded Bone Cement Yes (N=322,476) No (N=861,794) N* % N* %
3
$15,698
0.111
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Instrumental variable analysis (n=1,184,270)
Restricted cohort analysis (n=825,862)
OR or % change
95% CI
OR or % change
0.90
0.83
0.96
0.97
1.06* 0.97 0.98 1.09 1.01 1.04
1.02 0.94 0.96 0.97 0.98 0.97
1.11 1.01 1.01 1.23 1.04 1.13
1.07* 0.91* 0.96* 0.93 1.01 1.07
RESOURCE UTILIZATION Length of Stay Cost of Hospitalization
0.5%* 3.5%*
0.2% 0.7% 0.9%* 3.2% 3.8% 2.1%*
1.06
1.02 0.88 0.93 0.82 0.97 0.10
1.12 0.94 0.98 1.07 1.04 1.16
95% CI
0.93
0.86
1.00
1.05* 0.97 0.97* 1.11 1.01 1.03
1.01 0.94 0.95 0.98 0.98 0.95
1.10 1.00 1.00 1.25 1.04 1.11
0.6% 1.2% 0.5%* 1.8% 2.5% 3.5%*
0.2% 0.7% 3.2% 3.8%
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0.89*
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Main analysis (n=1,184,270) OR or % change 95% CI CLINICAL OUTCOMES Early Postoperative infection Acute Renal Failure 30-Day Readmission 90-Day Readmission Acute Dialysis Allergic Complications Microbiome Disruption
*P<0.05
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Table 3. Results from multivariable analysis assessing the association between use of antibiotic-loaded bone cement (reference = no use) and outcomes; % change (instead of OR) for continuous outcomes (length of stay and cost of hospitalization)
Models adjusted for age, sex, insurance type, hospital location, size, teaching status and annual TKA volume, year of procedure, anesthesia type, use of patient controlled analgesia, NSAIDs, COX-2 inhibitors, ketamine, pregabalin, gabapentin, acetaminophen, peripheral nerve blocks, Deyo-Charlson comorbidities, smoking and obesity.
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Figure 1. Study flow diagram
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Figure 2. Trends in utilization of antibiotic-loaded bone cement stratified by hospital characteristics
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Appendix I Definitions of outcome variables Postoperative infection
ICD-9 996.66 and 998.59 ICD-9 584.9 Items selected from inpatient billing file: ‘HEMODIALYSIS SERVICES’ ICD-9 693.0 Dermatitis due to drugs/medicine ICD-9 995.0 Anaphylaxis ICD-9 708.0 Allergic urticaria ICD-9 995.1 Angioneurotic edema ICD-9 995.2 Unspecified adverse effect due to unspecified drug ICD-9 995.3 Allergy unspecified ICD-9 698.8 Specified pruritus ICD-9 698.9 Unspecified pruritis ICD-9 782.1 Rash ICD-9 708.9 Urticaria unspecified ICD-9 708.0 Allergic urticaria ICD-9 288.3 Eosinophilia ICD-9 695.9 Red man syndrome ICD-9 008.45 Clostridium difficile infection ICD-9 009.0 Intestinal infection ICD-9 787.91 Diarrhea ICD-9 112.1/112.9 Yeast infection
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Acute renal failure Dialysis need
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Allergic complications
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Complications related to microbiome disruption