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58 (); 154-160
doi:
10.1016/j.jor.2024.07.011

The influence of implant factors on patient outcomes in primary total knee arthroplasty

, , , , , ,
a Sydney Orthopaedic Trauma and Reconstructive Surgery (SOTRS), Sydney, Australia
b Department of Orthopaedics, University Hospital of Ghent, Ghent, Belgium
c School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Australia
d South Australian Health & Medical Research Institute (SAHMRI), Australia
e Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR), Australia
f Queensland University of Technology (QUT - Gardens Point), Australia
g St. George and Sutherland Hospitals, Sydney, Australia
h St. George and Sutherland Clinical School, UNSW, Australia

⁎Corresponding author: Jan Peter Van Meirhaeghe. Jan.vanmeirhaeghe@uzgent.be

Received: , Accepted: ,
Professor P K Surendran Memorial Education Foundation
Disclaimer:
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Abstract

The influence of implant factors on patient-reported outcome measures (PROMS) after total knee arthroplasty (TKA) has previously been studied but findings are often inconsistent, restricted in scope and biased by confounding factors. This study aims to determine the association between implant-related factors and early post-operative PROMs after TKA.

Using data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) PROMs program, the study included 9487 primary TKA procedures performed in 43 hospitals from July 31, 2018 to December 31, 2020. Data included baseline demographic data, surgical details and PROMs collected pre- and 6 months post-operatively. Seven prosthesis characteristics were incorporated in the multivariable model, with proportional odds ordinal regression analysis used to assess their effects on post-operative Oxford knee score (OKS) and joint pain. Adjustments were made for pre-operative OKS and joint pain, as well as potential patient confounders.

At six months, fixed bearing implants showed higher odds of better OKS compared to mobile bearing implants (odds ratio [OR] = 1.20, 95 % confidence interval [CI] 1.06–1.37. p < 0.004). Similar findings were found with the use of image derived instrumentation (IDI) (OR = 1.27, 95 % CI 1.11–1.46, p < 0.001), robotic assisted vs. non-navigated knees (OR = 1.21, 95 % CI 1.06–1.38, p < 0.005) and no patella resurfacing (OR = 1.10, 95 % CI 1.01–1.20, p < 0.032). For lower pain scores at six months, the use of highly crosslinked polyethylene (OR = 1.12, 95 % CI 1.02–1.22, p < 0.015), cemented femoral components (OR = 1.11, 95 % CI 1.01–1.22, p < 0.024), IDI (OR = 1.20, 95 % CI 1.05–1.37, p < 0.009) or no patella resurfacing (OR = 1.10, 95 % CI 1.01–1.20, p < 0.034) were associated.

Utilizing a fixed bearing or robotic assistance correlated with improved OKS scores, whereas highly crosslinked polyethylene or cemented femoral components were associated with improved pain scores. At six months, the use of IDI compared to non-navigated TKA, and patellar resurfacing showed both improved OKS and pain scores.

Keywords

Primary knee arthroplasty
PROMs
Implant characteristics
Outcomes
1

1 Introduction

The influence of implant characteristics on patient-reported outcomes has frequently been studied in the literature. However, the findings are often inconsistent, restricted in scope and biased by confounding factors. This study investigates the effect of multiple implant-related factors on early post-operative patient reported outcome measures (PROMs).

Cruciate retaining (CR), posterior stabilised (PS) and medial stabilised (MS) TKA are widely used for TKA. Recent studies comparing implant designs show conflicting evidence for improvement in outcome measures. Most studies show no difference between different implants after 2–10 years of follow-up.1–6

Highly crosslinked polyethylene is now widely established and safely used in total knee arthroplasty. However, current literature does not show differences in clinical and radiological outcomes compared to conventional polyethylene..7–13 The maximum follow-up of these studies was 12 years. Longer follow-up will be necessary to determine long term effects. Some studies suggest lower revision rates for crosslinked polyethylene14,15.

The most common method of fixation in total knee arthroplasty (TKA) is cementing both the tibial and femoral components. About 10 % of TKA performed in Australia use cementless fixation.16 This rate is higher than other countries and compares with 8.4 % in USA,7.3 % in Sweden, 5 % in NZ, and 2 % in the UK. There is a renewed interest in cementless fixation due to advances in component design, metallurgy and improved surface fixation..17 A recent overview of 27 randomised controlled trials (RCT) in TKA showed no significant differences in multiple outcome measures when comparing cemented vs uncemented fixation.18

The mobility of the prosthesis has not been associated with patient reported outcomes.19–24 Range of motion improves quicker in mobile bearing designs, but at 2 years this difference was not significant.25

Patella resurfacing and the need for it has been a controversy since the start of total knee replacement surgery. Surgeons who prefer to retain the patella assume resurfacing causes more complications with less favorable outcomes.26 Other surgeons use it to diminish anterior knee pain caused by patellofemoral articulation of the native patella and the implant.27 Two recent meta-analysis of RCT studies showed conflicting evidence. An analysis by Longo et al. showed better outcome scores for patella resurfacing compared to retention.28 A meta-analysis from Grassi et al. showed comparable subjective outcome scores (function and pain) between both.29 Most current studies do not show a significant association between patient reported outcome and patella resurfacing.29–31

Over the last 2 decades there has been a clear rise in the use of navigation, image derived instrumentation (IDI) and robotics for TKA, shown by the recent annual 2023 report of the AOANJRR.32 Although improvements in radiological outcomes, especially in the coronal plane, have been seen, a clinical meaningful change in long term PROMs has not.33–36 Computer assisted and robotic assisted arthroplasty show promising results in short-term outcome data, but medium to long term data show no differences. 37–43 These better early PROMs could be explained by high early expectation fulfillment scores.44 With some studies proposing an advantage in early OKS,45 IDI has not shown to improve (early) PROMs, surgery time and complication rates, stipulated by a recent meta-analysis of Kizaki et al. and confirmed by others.46–50

The purpose of this study was to evaluate the difference in PROMS between multiple TKA implant characteristics using methods to adjust for known and unknown confounders.

2

2 Material and methods

2.1

2.1 Study design

Data from the Australia Orthopaedic Association National Joint Replacement Registry (AOANJRR) was used. Data included demographic details, health and functional scores, re-admission data, surgical data (including implant type, design and whether concomitant patella resurfacing was performed), and patient reported outcome measures (PROMs) at 6 months post-operatively. The registry only collects 6 months data. The analysis was restricted to patients undergoing primary total knee replacement performed for osteoarthritis that completed both preoperative and 6-month postoperative PROMS. Inclusion/exclusion criteria are mentioned in the flowchart underneath (Fig. 1).

Flowchart of patient cohort after applying inclusion/exclusion criteria.
Fig. 1 Flowchart of patient cohort after applying inclusion/exclusion criteria.

The model included 10,301 potential eligible patients. After adjusting for inclusion and exclusion criteria 9487 eligible patients were analysed. The men/women ratio was 43.9 %/56.1 % with a mean age of 67.3 years (standard deviation (SD): 8.7) and a mean BMI of 32.4 (SD: 6.3). The cohort consisted of primary TKAs performed between July 31, 2018 and December 31, 2020. Two thirds of femoral components were cemented (66.6 %), compared to 87.1 % of tibial components. In Australia, almost a quarter of surgeons use no resurfacing of the patella and CR designs are most widely used (79.1 %). Further details can be found in Table 1.

Table 1 Summary of primary total knee replacement procedures (primary diagnosis OA).
Variable Stats/Values Freqs (% of Valid)
Age Mean (sd): 67.3 (8.7) min < med < max: 30 < 68 < 95IQR (CV): 12 (0.1) 63 distinct values
Sex 1Men2Women 4169 (43.9 %)5318 (56.1 %)
Femoral cement 1Cementless2Cemented 3170 (33.4 %)6317 (66.6 %)
Tibial cement 1Cementless2Cemented 1220 (12.9 %)8267 (87.1 %)
Patella usage 1Patella Used2No Patella 7225 (76.2 %)2262 (23.8 %)
Prosthesis stability 1Medial Pivot Design2Minimally Stabilised3Posterior Stabilised 496 (5.2 %)7507 (79.1 %)1484 (15.6 %)
Polyethylene type 1Non XLPE2XLPE 2864 (30.2 %)6623 (69.8 %)
Prosthesis mobility 1Fixed2Rotating 8630 (91.0 %)857 (9.0 %)
Navigation 1Computer Navigated2IDI3Robotic4Non-Navigated 2974 (31.3 %)833 (8.8 %)1032 (10.9 %)4648 (49.0 %)
Oxford Knee Score (pre-operative) Mean (sd): 22.3 (8.2) min < med < max: 0 < 22 < 48IQR (CV): 12 (0.4) 49 distinct values
American Society of Anesthesiologist (ASA) score [ordered factor] 11223344 466 (4.9 %)5134 (54.1 %)3805 (40.1 %)82 (0.9 %)
Body Mass Index (BMI) Mean (sd): 32.4 (6.3) min < med < max: 11.6 < 31.6 < 50IQR (CV): 8.3 (0.2) 324 distinct values
Expected pain in 6 months Mean (sd): 2.1 (2.6) min < med < max: 0 < 1 < 10IQR (CV): 3 (1.3) 11 distinct values
Expected health in 6 months Mean (sd): 84.5 (16.8) min < med < max: 0 < 90 < 100IQR (CV): 19 (0.2) 97 distinct values
Expected mobility in 6 months 1122334455 5525 (58.2 %)2935 (30.9 %)766 (8.1 %)236 (2.5 %)25 (0.3 %)
Joint pain (pre-operative) Mean (sd): 6.72 min < med < max: 0 < 7 < 10IQR (CV): 3 (0.3) 11 distinct values
Back pain (pre-operative) Mean (sd): 3.33 min < med < max: 0 < 3 < 10IQR (CV): 6 (0.9) 11 distinct values
Oxford Knee Score 6 months post-surgery Mean (sd): 37.6 (7.9) min < med < max: 0 < 39 < 48IQR (CV): 11 (0.2) 47 distinct values
Pain level 6 months post-surgery Mean (sd): 2.3 (2.4) min < med < max: 0 < 2 < 10IQR (CV): 41 11 distinct values

The two outcomes of interest were Oxford Knee Score at 6 months (a summary score ranging from 0 to 48, with higher scores indicating less symptoms) and patient pain levels, measured on a numeric rating scale of 0–10, with 0 being no pain at all and 10 being the worst pain imaginable. These outcomes were chosen as they are widely used, validated arthroplasty outcome tools, are routinely collected by the AOANJRR and were thought to be most sensitive to implant characteristics. Seven prosthesis characteristics were investigated: stability (minimally stabilised, posterior stabilised, medial pivot design), polyethylene type (non cross-linked polyethylene, cross-linked polyethylene), cement use for the femoral component (cemented or cementless), cement use for the tibial component (cemented or cementless), bearing mobility (fixed or rotating), patella component usage (patella used or no patella used) and surgical technique (computer navigated, image derived instrumentation, robotic assistance, or non-navigated).

2.2

2.2 Statistical analysis

Proportional odds ordinal regression was used to model the effect of prosthesis characteristics on1 the OKS 6 months after surgery, and2 pain 6 months post-surgery. The models were adjusted for pre-operative OKS and joint pain, as well as potential patient confounders (age, sex, ASA, BMI, and pre-operative expectations of mobility, health and pain 6 months from surgery). All continuous variables were modelled with restricted cubic splines with three knots to allow for a non-linear relationship with the outcome. A summary of the outcomes and variables included in the analysis is provided in Table 1.

Statistical analysis was performed using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria) with package rms.

2.3

2.3 Ethics

AOANJRR collection of joint replacement and PROMs data are approved by the Commonwealth of Australia as a Federal Quality Assurance Activity (F2022L00986) Part VC of the Health Insurance Act 1973 (HIA) and Part 10 of the Health Insurance Regulations 2018. All AOANJRR studies are conducted in accordance with ethical principles of research (the Helsinki Declaration II). All patients undergoing joint replacement in Australia provide consent for routine AOANJRR data collection on an opt-out basis. Additional informed consent was obtained from all participants in the PROMs program.

3

3 Results

Oxford Knee Score increased from 22.8 (SD: 8.2) pre-operatively to 37.6 (SD: 7.9) 6 months postoperatively, where-as joint pain diminished from 6.7 (SD:2) to 2.3 (SD: 2.4). The latter was very close to the expected pain level after 6 months pre-operatively (2.1, SD: 2.6).

In order to keep interpretation consistent for both outcomes (OKS and pain), the odds ratio has been coded such that an OR>1 indicates a better outcome.

For Oxford Knee Score, OR>1 indicates increased odds of a higher score. For pain, the scale was inverted so that OR>1 indicates increased odds of a lower pain score.

At six months, there was a higher odds of improved OKS with fixed vs. mobile bearing implants (odds ratio [OR] = 1.20, 95 % confidence interval [CI] 1.06–1.37. p < 0.004), use of image derived instrumentation (IDI) (OR = 1.27, 95 % CI 1.11–1.46, p < 0.001), robotic assisted vs. non-navigated knees (OR = 1.21, 95 % CI 1.06–1.38, p < 0.0051), and no patella vs. patella resurfacing (OR = 1.10, 95 % CI 1.01–1.20, p < 0.032). (Table 2).

Table 2 Odds Ratios of Prosthesis Factors for outcome of Oxford Knee Score 6 Months Post-Surgery.
Prosthesis Factor Odds Ratio 95 % CI p-value
Fixed vs Rotating 1.20 (1.06, 1.37) 0.004
Medial Pivot Design vs Minimally Stabilised 0.93 (0.78, 1.11) 0.4428
Posterior Stabilised vs Minimally Stabilised 1.11 (1.00, 1.23) 0.0580
Non XLPE vs XLPE 0.95 (0.87, 1.04) 0.2634
Cementless vs Cemented Tibial Component 1.04 (0.92, 1.19) 0.4985
Cementless vs Cemented Femoral Component 0.92 (0.84, 1.01) 0.0993
Computer Navigated vs Non-Navigated 1.06 (0.97, 1.15) 0.1856
IDI vs Non-Navigated 1.27 (1.11, 1.46) <0.001
Robotic vs Non-Navigated 1.21 (1.06, 1.38) 0.0051
No Patella vs Patella Used 1.10 (1.01, 1.20) 0.0324

At six months, there was a higher odds of lower pain scores with the use of highly crosslinked polyethylene, cemented femoral components, IDI, and no patella resurfacing. No significant differences were found for other implant factors (Table 3).

Table 3 Odds ratios for primary total knee replacement outcome of pain 6 Months post-surgery (primary diagnosis OA).
Prosthesis Factor Odds Ratio 95 % CI P-Value
Rotating vs Fixed 0.89 (0.78, 1.01) 0.0759
Medial Pivot Design vs Minimally Stabilised 0.87 (0.73, 1.04) 0.1323
Posterior Stabilised vs Minimally Stabilised 1.08 (0.97, 1.20) 0.1762
Non XLPE vs XLPE 0.89 (0.82, 0.98) 0.0153
Cementless vs Cemented Tibial Component 1.00 (0.88, 1.13) 0.9786
Cementless vs Cemented Femoral Component 0.90 (0.82, 0.99) 0.0246
Computer Navigated vs Non-Navigated 0.96 (0.88, 1.05) 0.3779
IDI vs Non-Navigated 1.20 (1.05, 1.37) 0.0094
Robotic vs Non-Navigated 1.08 (0.94, 1.23) 0.2809
No Patella vs Patella Used 1.10 (1.01, 1.20) 0.0347
4

4 Discussion

We have demonstrated that a number of implant associated factors do appear to be associated with differences in early PROMS outcomes. Enhanced OKS scores were associated with fixed bearing implants and robotic assistance, while lower pain scores were observed with highly crosslinked polyethylene and cemented femoral implants. Notably, omitting patella resurfacing and utilizing IDI instead of non-navigated TKA also improve outcome scores. However, it is important to note that the strength of these findings was variable, and some factors may serve as proxies rather than definitive influencers of outcome.

Current literature suggests that stability design does not influence patient outcomes.1–6 A recent meta-analysis from Nisar et al.51 shows comparable results in both patient and clinical outcomes, suggesting implant design alone may not further improve patient outcome. Other studies show favorable results in range of motion for PS compared to CR designs,52 or superior patient satisfaction and expectation in MS compared to PS designs.53 We did not find any difference in PROMs when looking at stability designs. Data on range of motion or patient satisfaction was not included in our study.

Highly crosslinked polyethylene shows better pain scores in our study compared to non cross-linked polyethylene. This is different from previous studies that show no correlation. 7–13 This difference is likely implant- or surgeon dependent as it would be difficult to offer a reason why the presence of highly crosslinked polyethylene would influence PROMS at such short term follow-up. We did not differentiate for specific implant brands, so it is possible that this finding may be explained by other prosthesis-specific characteristics. We found no evidence supporting a difference in PROMs comparing implant brands.54,55

In a recent overview of randomised controlled trials (RCT) in TKA, cemented vs uncemented fixation was compared in 27 RCTs. None of these RCTs showed significant differences in multiple outcome measures.18 A New Zealand Joint Registry (NZJR) study showed no difference in implant survival between cemented and uncemented TKA in people aged over 64. There was, however, lower implant survival in uncemented TKA under 65 years of age.56 Although early failure has been seen in uncemented tibial components,57 the interest in uncemented implants is growing. For tibial components, our study did not show a significant difference, which is consistent with current literature.18

A higher odds of lower pain scores was found when comparing cemented and uncemented femoral implants. This is different from previous studies that suggest no significant difference58,59. When looking for a reason for this variation, we hypothesize that uncemented femoral components may take longer to achieve stable fixation, although these differences have not been proven in literature.

We found improved odds for better OKS after the use of a fixed bearing compared to a mobile bearing implant, where most literature suggests there is no difference. 19–23 A study from Lizaur-Utrilla et al. shows better perception and satisfaction in mobile bearing designs in older patients, possibly due to earlier regained flexion, but their cohort only consisted of 61 mobile bearing and 58 fixed bearing primary TKA's.60 Mobility of the implant has no impact on pain at 6 months.

In our research, better OKS and pain scores were found without patella resurfacing. This may represent a direct effect or may be due to unmeasured confounding and the clinical importance of a 10 % increase in the odds of a higher OKS and a CI of 1.01 is unclear. Conflicting evidence whether to resurface or not has been suggested in the past.28 Baker et al. used National joint registry data from the UK which showed no significant difference between resurfacing and retention for improvement in knee function or anterior knee specific function and showed a large variation in proportion of patella resurfacing between different implants.31 A prospective randomized study of Deroche et al. showed no superiority between both in terms of clinical and radiological outcomes at mid-term.30

Although early outcome scores show promising results with robotic assistance, medium to long term data shows no differences.37–43 Our study shows similar findings, with improved OKS at 6 months with the use of robotics. For IDI, current literature does not show any differences in early outcome.46–50 In our research, it performs well for both improvement of pain and OKS scores after 6 months when compared to non navigated TKA, which is consistent with a recent study of Nabavi et al..45 We did not find any significant difference with the use of navigation versus non navigated TKA, which is similar to current literature.

The main strength of this study is the use of a proportional odds ordinal regression analysis to account for multiple confounding factors. The models were adjusted for pre-operative Oxford Knee score and joint pain, as well as potential patient confounders (age, sex, ASA, BMI, and pre-operative expectations of mobility, health and pain 6 months from surgery). The large cohort of almost 10,000 patients is likely to be representative of the population.61

The main limitation is the short follow up period (6 months). Previous studies have suggested 1-year OKS should be used.62,63 On the other hand, studies report that most of the improvement in PROMs occur in the first 6 months post-operatively.64,65 Reducing data collection frequency and obtaining data earlier can enhance the affordability and feasibility of maintaining a registry, hereby encouraging more centers to participate. Taking advantage of higher response rates within the initial 6 months and considering higher attrition rates beyond this timeframe, limiting PROMS collection at the 6-month mark also proves to be a more cost-effective strategy.64 Another limitation of this study is the observational design. Patient satisfaction or range of motion was not included. A subgroup analysis comparing a combination of implant factors or comparing different implant design/brand was also not performed, which could be a scope for further studies.

5

5 Conclusion

Our study suggests that specific implant factors may indeed influence clinical outcomes in the short term. The strength of these findings is variable. Further studies are needed to see if these factors remain important in longer term follow-up and which factors are independently important as opposed to those that may be associated with other, yet undefined factors associated with the surgery.

Conflict of interest statement

No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.

Ethical statement

AOANJRR collection of joint replacement and PROMs data are approved by the Commonwealth of Australia as a Federal Quality Assurance Activity (F2022L00986) Part VC of the Health Insurance Act 1973 (HIA) and Part 10 of the Health Insurance Regulations 2018. All AOANJRR studies are conducted in accordance with ethical principles of research (the Helsinki Declaration II).

Funding statement

The authors received no funding for this study.

Patient consent

All patients undergoing joint replacement in Australia provide consent for routine AOANJRR data collection on an opt-out basis. Additional informed consent was obtained from all participants in the PROMs program.

CRediT authorship contribution statement

Jan Peter Van Meirhaeghe: Writing – original draft, Writing – review & editing, Visualization. Ian A. Harris: Writing – review & editing, Conceptualization, Supervision. Alana Cuthbert: Methodology, Formal analysis, Data curation. Michelle Lorimer: Methodology, Formal analysis, Data curation. Michael McAuliffe: Writing – review & editing, Data curation. Sam Adie: Writing – review & editing. Robert Molnar: Conceptualization, Writing – review & editing, Visualization, Supervision.

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