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Abstract

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

Objective

To examine racial differences in surgical complications, mortality, and revision rates after total knee arthroplasty.

Methods

We studied patients undergoing primary total knee arthroplasty using 2001–2007 Pennsylvania Health Care Cost Containment Council data. We conducted bivariate analyses to assess the risk of complications such as myocardial infarction, venous thromboembolism, wound infections, and failure of prosthesis, as well as 30-day and 1-year overall mortality after elective total knee arthroplasty, between racial groups. We estimated Kaplan-Meier 1- and 5-year surgical revision rates, and fit multivariable Cox proportional hazards models to compare surgical revision by race, incorporating 5 years of followup. We adjusted for patient age, sex, length of hospital stay, surgical risk of death, type of health insurance, hospital surgical volume, and hospital teaching status.

Results

In unadjusted analyses, there were no significant differences by racial group for either overall 30-day or in-hospital complication rates, or 30-day and 1-year mortality rates. Adjusted Cox models incorporating 5 years of followup showed an increased risk of revisions for African American patients (hazard ratio [HR] 1.39, 95% confidence interval [95% CI] 1.08–1.80), younger patients (HR 2.30, 95% CI 1.96–2.69), and lower risk for female patients (HR 0.81, 95% CI 0.71–0.92).

Conclusion

In this sample of patients who underwent knee arthroplasty, we found no significant racial differences in major complication rates or mortality. However, African American patients, younger patients, and male patients all had significantly higher rates of revision based on 5 years of followup.


INTRODUCTION

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

Total knee arthroplasty (TKA) is an effective treatment option for end-stage knee osteoarthritis (OA) and has been shown to improve quality of life and reduce the risk of disability and pain for those with knee OA (1–3). Despite the effectiveness and widespread availability of this procedure, there are marked variations in the utilization of TKA, where minority patients are significantly less likely than white patients to undergo TKA (4, 5). For instance, in 2006, TKA rates were 39% lower among African Americans compared to whites in all 50 states, with Pennsylvania having one of the largest racial variations (49%) (5). The reasons for these marked racial variations remain unclear. There is evidence demonstrating racial differences in patient preference for joint arthroplasty, with minority patients expressing lower preference rates (6–8). However, patient preference for joint arthroplasty is largely shaped by expectations of surgical outcomes after joint arthroplasty, which also varies by race (6, 7, 9). Several studies have demonstrated that African American patients have lower expectations for TKA (9), and are more likely to expect a longer length of stay (LOS), have more pain, and have more trouble ambulating after the procedure (6, 7).

Furthermore, it is likely that outcomes after arthroplasty influence patients' decisions to use the procedure. Relatively few studies have examined racial differences in surgical outcomes after knee arthroplasty and even fewer have examined racial variations in revision rates after TKA (10, 11). Of 3 studies that have looked at mortality, there were mixed results on racial differences (12–14). One study evaluating Veterans Affairs (VA) patients showed increased risks of postoperative infection and noninfection-related complications for African American patients (14). Another study using Medicare data showed an increased rate of readmissions to acute care facilities within 90 days after arthroplasty and an increased rate of postoperative wound infection (12). Other studies found increased risks of pulmonary embolism (13) and an elevated risk for revision for African American patients (11).

To address this knowledge gap, we used the Pennsylvania Health Care Cost Containment Council (PHC4) database, a large regional data set, to examine the presence and the magnitude of racial differences in surgical outcomes after TKA. The objective of this study was to investigate the role of race on key postsurgical outcomes: myocardial infarction, venous thromboembolism (VTE), surgical wound infections, prosthetic device failure, overall mortality at 30 days and at 1 year, and revision rates incorporating 5 years of followup data, among patients undergoing elective TKA in Pennsylvania.

Significance & Innovations

  • Disparities of care between white and African American patients with knee osteoarthritis are well documented for utilization of total joint arthroplasty as treatment. Racial inequalities for postarthroplasty outcomes are less well known, and this study attempts to evaluate for this.

  • The key findings are that African American patients, compared to white patients, younger patients, and male patients, have a higher risk of revision at 5 years.

  • These findings add to a national effort to define and intervene upon racial variation in access to and utilization of joint arthroplasty.

MATERIALS AND METHODS

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

Study sample.

We used the PHC4 database to identify patients ages >18 years undergoing TKA as the primary procedure by the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 81.54, from the third and fourth quarters of 2001 and the first and second quarters of 2002, as outlined by the flow chart in Supplementary Figure 1 (available in the online version of this article at http://onlinelibrary.wiley.com/doi/10.1002/acr.21834/abstract). Ascertainment of patient-level events was obtained through 2007. The PHC4 collects more than 4.5 million inpatient hospital discharge and ambulatory/outpatient procedure records yearly from hospitals and freestanding ambulatory surgery centers throughout Pennsylvania. The data include hospital charge and treatment information that is collected on a quarterly basis (15).

Patients were excluded if LOS was greater than 14 days, race was indicated as other, or the index hospitalization included procedure codes for knee revision (ICD-9-CM codes 81.55, 0080, 0082, 0083, and 0084) or a hip-related procedure (ICD-9-CM codes 81.51, 81.53, 0070, 0071, 0072, and 0073) in addition to the primary TKA. Patients were also excluded if they were duplicated index cases or if they died the same day, or had missing key data including identification, sex, and teaching status for the hospital. The final analysis cohort contained 17,385 patients. The study was approved by the Institutional Review Board at the University of Pennsylvania.

Study outcomes.

The primary outcomes of interest were occurrence of the following: 1) any major complication within 30 days, 2) in-hospital major complications, 3) death within 30 days and 1 year, and 4) revisions at 1 and 5 years. Major complications were defined as occurrence of one or more of the following: 1) myocardial infarction (ICD-9-CM codes: 410.00, 410.01, 410.10, 410.11, 410.20, 410.21, 410.30, 410.31, 410.40, 410.41, 410.50, 410.51, 410.60, 410.61, 410.70, 410.71, 410.80, 410.81, 410.90, and 410.91); 2) VTE (ICD-9-CM codes: 415.1, 415.11, 415.19, 451.11, 451.19, 451.2, 451.81, 451.9, 453.40, 453.41, 453.42, 453.8, and 453.9); 3) wound infection (ICD-9-CM codes: 682.5, 682.6, 682.8, 682.9, 998.51, and 998.59); and 4) prosthesis failure or device defect (ICD-9-CM codes: 996.4, 996.40, 996.41, 996.42, 996.43, 996.46, 996.47, and 996.49). Mortality rates were evaluated at 30 days and at 1 year, and revision rates at 1 and at 5 years.

Study measures.

The primary independent variable was race. Race was defined as African American, white, and other. We excluded “other” race from all analyses as our main focus was to compare African American and white racial groups. We included potential confounders in the model to adjust for bias due to differences in risk factors between race groups. Covariates included in the model were age (defined as ages 18–64 years versus ages >64 years), sex, LOS (defined as 0–3 days versus 4–14 days), surgical risk of death, insurance type (defined as Medicaid/unknown versus government [Medicare]/private), hospital volume (defined as 0–100 knee arthroplasty surgeries versus >100 surgeries), and hospital teaching status (teaching versus nonteaching). Surgical risk of death was defined by the 3M All Patient Refined Diagnosis Related Group (APR-DRG) risk of mortality score. This risk-adjustment tool provides a categorical risk assessment based on interactions of age, type of surgical procedure, comorbidity, and the principal diagnosis and has been previously validated (16–19). The 3M APR-DRG risk of mortality score assigns a risk of death to each patient for a specified surgical procedure as minor, moderate, major, or extremely likely. Based on preliminary analysis, we combined risk categories because of the small numbers of patients who experienced rare study outcomes in the unknown and extremely likely risk groups. As a result, we considered surgical risk of death as a 3-level variable, with levels corresponding to “minor/unknown,” “moderate,” and “major/extremely likely.”

Statistical analysis.

Descriptive statistics for patient characteristics and study outcomes were calculated for the study sample overall and by race group. Comparisons of patient and hospital characteristics were tested using chi-square tests. Unadjusted associations between race and complication outcomes, and race and mortality outcomes, were assessed using Fisher's exact test. Adjustment variables for multivariable models were determined a priori based on clinical considerations and availability of data in the PHC4 database. We analyzed the occurrence of any major complication in 30 days for African American versus white race, and included age, sex, surgical risk of death, insurance type, LOS, teaching status, and hospital volume in an additive logistic regression model, using generalized estimating equations to accommodate the clustering within hospitals (20). We repeated this analysis, excluding patients who died within the 30-day followup period, as a sensitivity check. The relatively small number of patients who died within 30 days, experienced in-hospital complications, or experienced individual complication outcomes in 30 days precluded multivariable modeling of these outcomes.

We determined revision rates using Kaplan-Meier survival models for TKA revision within 1 and 5 years. In survival models stratified by race, we assessed unadjusted differences by race and constructed Kaplan-Meier survival plots stratified by race. We tested for equality of survival by race using the log rank test. To compare risk of surgical revision by race, adjusted for the same covariates, we fit Cox proportional hazards models, incorporating 5 years of followup, and censored patients at death or at the end of followup. We checked the proportional hazards assumption and accounted for clustering of observations within hospitals with the robust covariance method of Lin and Wei (21). All analyses were performed with SAS, version 9.2.

RESULTS

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

Study sample characteristics.

There were 17,385 patients in the final analysis cohort who underwent TKA as the index procedure. Most patients were white (n = 16,436). Table 1 summarizes differences between racial groups.

Table 1. Clinical and demographic characteristics by race
CharacteristicTotal, no. (%) (n = 17,385)White, no. (%) (n = 16,436)African American, no. (%) (n = 949)P
  • *

    There was only one patient whose 3M All Patient Refined Diagnosis Related Group risk of mortality score could not be assigned, which was thus classified as “unknown.”

Sex    
 Female11,325 (65.1)10,594 (64.5)731 (77.0)< 0.0001
 Male6,060 (34.9)5,842 (35.5)218 (23.0) 
Age, years    
 18–646,107 (35.1)5,602 (34.1)505 (53.2)< 0.0001
 ≥6511,278 (64.9)10,834 (65.9)444 (46.8) 
Length of stay, days    
 0–39,822 (56.5)9,326 (56.7)496 (52.3)0.0069
 4–147,563 (43.5)7,110 (43.3)453 (47.7) 
Surgical risk of death    
 Minor/unknown*13,961 (80.3)13,152 (80.0)809 (85.2)0.0003
 Moderate2,765 (15.9)2,648 (16.1)117 (12.3) 
 Major/extremely likely659 (3.8)636 (3.9)23 (2.4) 
Insurance    
 Medicaid/unknown467 (2.7)339 (2.1)128 (13.5)< 0.0001
 Government/private16,918 (97.3)16,097 (97.9)821 (86.5) 
Hospital volume    
 1–1004,057 (23.3)3,738 (22.7)319 (33.6)< 0.0001
  >10013,328 (76.7)12,698 (77.3)630 (66.4) 
Hospital teaching status    
 Teaching hospital4,346 (25.0)3,833 (23.3)513 (54.1)< 0.0001
 Nonteaching hospital13,039 (75.0)12,603 (76.7)436 (45.9) 

Unadjusted and adjusted complication and mortality rates.

Approximately 5.5% of patients undergoing TKA had a complication within 30 days of the procedure, and 1.7% had a complication while in the hospital (Table 2). The most frequent 30-day complications were VTE (2.6%) and wound infections (2.3%), while the most common in-hospital complication was VTE (0.97%). There were no significant differences by racial group for either overall 30-day or in-hospital complication rates. Death by 30 days occurred in approximately 0.3% of patients and by 1 year in 1.3%. There were no differences by racial group for either of these measures.

Table 2. Unadjusted major complications, mortality, and revision rates by race
 Total, no. (%) (n = 17,385)White, no. (%) (n = 16,436)African American, no. (%) (n = 949)P
  • *

    Calculated as number of patients with occurrence of any of the 4 specific complications listed.

  • Revision rates were determined using Kaplan-Meier survival analysis.

30-day complications    
 Overall complications*948 (5.5)895 (5.4)53 (5.6)0.83
 Myocardial infarction81 (0.5)79 (0.5)2 (0.2)0.33
 Venous thromboembolism452 (2.6)431 (2.6)21 (2.2)0.53
 Wound infection399 (2.3)371 (2.3)28 (3.0)0.18
 Prosthesis failure or device defect54 (0.3)50 (0.3)4 (0.4)0.54
In-hospital complications    
 Overall complications*304 (1.7)295 (1.8)9 (0.9)0.06
 Myocardial infarction53 (0.3)51 (0.3)2 (0.2)1.00
 Venous thromboembolism169 (1.0)166 (1.0)3 (0.3)0.03
 Wound infection60 (0.3)58 (0.4)2 (0.2)0.77
 Prosthesis failure or device defect29 (0.2)27 (0.2)2 (0.2)0.67
Surgical outcome    
 30-day mortality46 (0.3)43 (0.3)3 (0.3)0.74
 1-year mortality220 (1.3)207 (1.3)13 (1.4)0.77
 1-year revision276 (1.6)251 (1.6)25 (2.7)0.009
 5-year revision907 (5.7)831 (5.5)76 (8.9)< 0.0001

In adjusted analysis, there was no significant difference between white and African American patients for the occurrence of any complication within 30 days (odds ratio [OR] 0.96, 95% confidence interval [95% CI] 0.71–1.29), and the results were identical when patients who died within 30 days were excluded from the analysis. Adjusted analysis evaluating mortality at 1 year showed an increased risk of death for African American patients; however, it was not significant (OR 1.45, 95% CI 0.86–2.47).

Unadjusted and adjusted 1- and 5-year revision rates.

Revision probabilities calculated by Kaplan-Meier revealed 1-year risk of 1.62% (95% CI 1.44–1.82) and 5-year risk of 5.71% (95% CI 5.37–6.07) (Figure 1). Among white patients, the revision rate at 1 year was 1.56% (95% CI 1.38–1.76) compared to African American patients at 2.66% (95% CI 1.80–3.91) (log rank P = 0.009). At 5 years, the revision rate for white patients was 5.52% (95% CI 5.18–5.89) compared to 8.93% (95% CI 7.26–10.97) for African American patients (log rank P < 0.0001). The adjusted Cox proportional hazards models showed an increased risk of 5-year revisions for African American patients (hazard ratio [HR] 1.39, 95% CI 1.08–1.80), younger patients (HR 2.30, 95% CI 1.96–2.69), and a lower risk for female patients (HR 0.81, 95% CI 0.71–0.92) (Table 3).

thumbnail image

Figure 1. Kaplan-Meier curves showing the probability of knee arthroplasty survival (proportion not revised) over time for African American and white patients (log rank P < 0.0001).

Download figure to PowerPoint

Table 3. Cox proportional hazard results: risk factors for 5-year revision after TKA*
5-year variableHR (95% CI)P
  • *

    TKA = total knee arthroplasty; HR = hazard ratio; 95% CI = 95% confidence interval.

African American race (reference: white)1.39 (1.08–1.80)0.01
Ages 18–64 years (reference: age ≥65 years)2.30 (1.96–2.69)< 0.0001
Female sex (reference: male)0.81 (0.71–0.92)< 0.01
Surgical risk of death: major/extremely likely (reference: minor/unknown)1.17 (0.80–1.70)0.42
Surgical risk of death: moderate (reference: minor/unknown)1.02 (0.82–1.26)0.87
Insurance: government/private (reference: Medicaid/unknown)0.87 (0.62–1.21)0.40
Length of stay: 0–3 days (reference: 4–14 days)0.99 (0.85–1.14)0.88
Teaching status: nonteaching (reference: teaching)0.93 (0.74–1.18)0.57
Hospital procedure volume: 1–100 (reference: >100)0.99 (0.82–1.19)0.88

DISCUSSION

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

In this sample of patients from 170 hospitals in the state of Pennsylvania, we found that African American and white patients have similar unadjusted rates of major 30-day complications: myocardial infarction, wound infection, and prosthetic device failure; however, white patients had higher unadjusted rates of in-hospital VTE compared to African American patients. Due to a small number of events, we were unable to perform adjusted analyses of complications other than for 30-day overall complications, where we found no significant difference between white and African American patients. The unadjusted rates for 30-day and 1-year mortality were also similar for both racial groups. We did find that there were significant racial differences in both 1- and 5-year revision rates after TKA, with African American patients having higher rates of revision compared to white patients, and an independently higher risk of revision at 5 years of followup.

We were surprised to find our study results showed no significant racial differences in 30-day complications. Our results are consistent with one other report of VA patients showing no significant differences in the rates of infection or noninfection-related complications post–knee arthroplasty (22). Other studies, however, have documented that following TKA, racial/ethnic minority patients are at higher risk for postoperative complications including longer LOS, 30- and 90-day infection, and noninfection complications, and higher rates of readmissions and infection following the procedure (12–14, 22, 23).

The reason for the disagreement between previous studies and our study may be due to multiple factors. Some of these studies used data from an earlier period of time (22, 23). Several studies used data that were isolated to only VA data (2, 23), Medicare data (12), or state-specific data (13), reflective of possibly different unmeasured characteristics from our study population. One study used a broader definition of complications, which included readmissions and pneumonia not included in our definition (12), and another study included minor complications such as urinary tract infection in a composite outcome for complications (22). Another possible reason for the lack of association in our study is the baseline differences between the African American and white subjects. There were younger and relatively healthier African American patients undergoing knee arthroplasty compared to white patients. While this is counterintuitive, it may speak to a selection bias present for patients undergoing knee arthroplasty. While our multivariable model adjusted for both age and surgical risk, as well as other patient and hospital characteristics, it is possible that residual bias or bias due to additional unobserved confounders limited our ability to detect racial differences. However, given the relatively large P values for these associations, this seems unlikely, or at least suggests a relatively weak association between these outcomes and race. Finally, since our data used only PHC4-related inpatient records, events may have been missed if patients were not admitted to a PHC4 hospital during followup or were treated as an outpatient for complications.

Fewer studies have examined racial differences in mortality after arthroplasty. One study found an increased risk for 90-day mortality for African American patients compared to white patients after TKA (OR 1.4, 95% CI 1.0–1.8), while another study found no association at 90 days (OR 0.98, 95% CI 0.74–1.29) (12, 13). A study that evaluated mortality within 30 days after knee arthroplasty also showed no difference between African American and white patients (0.4%, 95% CI 0.1–0.9 versus 0.7%, 95% CI 0.5–0.8, respectively) (14). Our findings show that there were no racial differences in unadjusted rates of mortality at 30 days and 1 year, and no significantly increased risk of 1-year mortality for African American patients, and overall is consistent with these other published data.

Our overall revision rate at 5 years (5.7%) for the entire sample is higher than what was reported for a Medicare sample (2.8% at 5 years) (11). A report from Australia reported a 5-year rate of 3.6%, and this study included all-comers rather than only patients ages >65 years (24). It is conceivable that revision rates are higher in our sample because our study included patients of all ages and younger patients who may be more likely to undergo revision arthroplasty (11, 25–27). In the Finnish Arthroplasty Register, age <55 years was associated with a 5-year TKA survival rate of 92% compared to a survival rate of 97% in patients ages >65 years (27). While the complication results were negative, a strong signal emerged in spite of this to demonstrate a marked racial variation in revision rates and risk for revision. These data are in keeping with other published data that used a 5% national sample of the Medicare claims database (11). They found that younger age (65–69 years), male sex, African American race, and higher disease severity scores were predictors of revision for knee arthroplasty.

While there were more young patients in our African American race group, it is plausible that younger age and male sex are only part of why revision rates are higher. In general, infection and instability are common causes of revisions within the first 2 years, while aseptic loosening or mechanical failure tends to occur after 5 years (28). It is not known whether there are race- or ethnic-specific differences among these causes of failure. It is reasonable to postulate that factors other than those biologic may affect revision risk and should be considered. One factor that may affect the potential for revision is the rehabilitation that occurs postarthroplasty. Postarthroplasty care has been shaped by a decreased LOS (18, 29), driven by multiple factors including the use of clinical care pathways and changes in reimbursement schedules (30). While the LOS has decreased, the proportion of patients being admitted to extended care facilities has increased from 17.1% in 1993 to 54.6% in 2003 (18). The burden of postoperative care has shifted to postacute care facilities such as inpatient rehabilitation facilities, skilled nursing facilities, and home health agencies. Factors associated with discharge to an extended care facility for TKA patients include older age, a higher American Society of Anesthesiology class, female sex, Medicare insurance, and region of country (18); a recent study using state hospital discharge data of patients after joint arthroplasty showed racial and socioeconomic disparities in the use of more versus less intensive utilization of rehabilitation services that also differed by state (31).

Our study used hospital volume as a surrogate marker of quality; however, we did not observe a difference between volume and outcomes measured. These findings are counter to other studies showing a strong relationship between hospital and surgeon procedure volume and patient outcomes in joint arthroplasty (32, 33). In this case, hospital volume was defined as number of knee arthroplasty surgeries; we did not have information about all surgical procedures. In addition, the variable was broken up by 1–100 versus >100, which may not have been sensitive to changes in outcomes. Another recent study using this same database during the same period of time, however, using different cut points for hospital procedure volume and using both knee and hip replacement procedures combined, did show that there was a relationship between hospital volume and surgical outcomes (34).

Our study has some important limitations. First, we used an administrative database with limited clinical and demographic information. For instance, we do not have information on body mass index, other comorbid conditions, and the type of prosthesis used, which may affect risk of revision or the type of revision procedure performed. In addition, while these procedures were elective and assumed to be mostly due to OA given the prevalence of disease, we did not have the reasons for why the joint arthroplasty was performed, nor did we have information on function after arthroplasty. Second, while we intended to analyze major complications, mortality, and surgical revision through multivariable analyses as part of objectives, the relatively low frequencies of these outcomes precluded multivariable modeling for all but 30-day overall complications, 1-year mortality, and revision. This limitation could be overcome by using a larger, more geographically representative database such as the Medicare 5% sample. Next, as mentioned previously, this database may not capture all potential postoperative complications. And finally, our data reflect patients hospitalized in Pennsylvania and may not be generalizable to the rest of the US population. However, we believe it is fairly representative based on the sex and racial similarities to the Medicare population in the study by Ong et al (11); we report 65.1% females, similar to 65.2% reported by Ong et al, and we report 94.5% white, just slightly higher than the 92.3% reported by Ong et al.

In conclusion, in this sample of patients who underwent TKA in Pennsylvania, we found no significant racial differences in 30-day major complications or 1-year mortality after adjustment. However, we found significant racial differences in adjusted risk of revision over a 5-year followup period. The reasons for these differences remain unclear, and the role of other demographic and disease-specific factors has not been sufficiently evaluated yet. Because revision surgeries carry a higher risk for complications and costs to both the individual and society (35), further studies are necessary to evaluate the reasons for these racial differences in revision rates and the role of postsurgical care in this disparity.

AUTHOR CONTRIBUTIONS

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

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

Study conception and design. Blum, Singh, Ibrahim.

Acquisition of data. Chen, Ibrahim.

Analysis and interpretation of data. Blum, Singh, Lee, Richardson, Chen, Ibrahim.

REFERENCES

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

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

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

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ACR_21834_sm_SupplFig1.doc26KSupplementary Figure 1

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