| Literature DB >> 35628963 |
Filippo Migliorini1, Nicola Maffulli2,3,4, Francesco Cuozzo2, Karen Elsner1, Frank Hildebrand1, Jörg Eschweiler1, Arne Driessen1.
Abstract
INTRODUCTION: Whether mobile-bearing (MB) unicompartmental knee arthroplasty (UKA) performs better than fixed-bearing (FB) implants in patients with monocompartmental osteoarthritis (OA) still remains unclear. Therefore, a meta-analysis comparing MB versus FB for UKA was conducted to investigate the possible advantages of MB versus FB in patient-reported outcome measures (PROMs), range of motion (ROM), and complications. We hypothesised that the MB design performs better than FB.Entities:
Keywords: fixed bearing; mobile bearing; unicompartmental knee arthroplasty
Year: 2022 PMID: 35628963 PMCID: PMC9143434 DOI: 10.3390/jcm11102837
Source DB: PubMed Journal: J Clin Med ISSN: 2077-0383 Impact factor: 4.964
Figure 1Flow chart of the literature search.
Figure 2Risk of bias assessment. The risk of bias tool assessed the risk of bias (low, unclear, or high) per each risk of bias item presented as percentages across all included studies. The risk of selection bias evaluated the random sequence generation and the allocation concealment. The risk of detection bias assessed the blinding procedure during the outcome assessment. The risk of attrition bias refers to incomplete outcome data during study enrollment or analysis. The risk of reporting bias analyses the selective publication of results based on their statistical or clinical relevance. If the authors identified additional risks of bias, these were considered as “other bias”.
Figure 3Funnel plot. The funnel plot charted the standard error (SE) of the log odds ratio (Log OR) versus its odd ratio. The degree of asymmetry of the plot is directly proportional to the degree of bias.
Generalities and patient baseline of the included studies (MB: mobile bearing; FB: fixed bearing).
| Author, Year | Journal | Design | Follow-Up (Months) | Bearing | Procedures ( | Mean Age | Women ( |
|---|---|---|---|---|---|---|---|
| Artz et al., 2015 [ |
| Randomised | 24 | MB | 205 | 62.0 | 50% |
| FB | 284 | 71.4 | 44% | ||||
| Bhattacharya et al., 2012 [ |
| Retrospective | 44.7 | FB | 91 | 67.7 | 58% |
| MB | 49 | 68.8 | 47% | ||||
| Biau et al., 2013 [ |
| Retrospective | 24 | MB | 33 | 67.7 | 59% |
| FB | 57 | 68.8 | 51% | ||||
| Catani et al., 2011 [ |
| Retrospective | 12 | MB | 10 | 70.3 | 80% |
| FB | 10 | 70.3 | 60% | ||||
| Confalonieri et al., 2004 [ |
| Randomised | 68.4 | MB | 20 | 71.0 | 45% |
| FB | 20 | 69.5 | 60% | ||||
| Emerson et al., 2002 [ |
| Prospective | 81.6 | MB | 50 | 63.0 | 56% |
| FB | 51 | 63.0 | 66% | ||||
| Forster et al., 2007 [ |
| Prospective | 24 | FB | 17 | 75.0 | 69% |
| MB | 13 | 55.0 | 42% | ||||
| Gilmour et al., 2018 [ |
| Prospective | 24 | FB | 58 | 61.8 | 45% |
| MB | 54 | 62.6 | 45% | ||||
| Gleeson et al., 2004 [ |
| Randomised | 24 | FB | 57 | 66.7 | 41% |
| MB | 47 | 64.7 | 60% | ||||
| Inoue et al., 2016 [ |
| Retrospective | 27.3 | FB | 24 | 75.0 | 76% |
| MB | 28 | 73.3 | 76% | ||||
| Kayani et al., 2019 [ |
| Prospective | 3 | MB | 73 | 66.1 | 53% |
| FB | 73 | 65.3 | 56% | ||||
| Kazarian et al., 2020 [ |
| Retrospective | 44.4 | FB | 162 | 63.2 | 59% |
| MB | 91 | 62.2 | 52% | ||||
| Kim et al., 2016 [ |
| Retrospective | 94 | MB | 1441 | 62.0 62.0 | 91% 91% |
| FB | 135 | ||||||
| Kim et al., 2020 [ |
| Retrospective | 60 | FB | 58 | 61.3 | 93% |
| MB | 57 | 60.7 | 84% | ||||
| Koppens et al., 2019 [ |
| Randomised | 24 | MB | 33 | 64.0 | 52% |
| FB | 32 | 61.0 | 47% | ||||
| Li et al., 2006 [ |
| Randomised | 24 | FB | 28 | 70.0 | 32% |
| MB | 28 | 74.0 | 29% | ||||
| Neufeld et al., 2018 [ |
| Retrospective | 120 | MB | 38 | 60.3 | 58% |
| FB | 68 | 64.6 | 50% | ||||
| Ozcan et al., 2018 [ |
| Retrospective | 28.8 | FB | 153 | ||
| MB | 171 | ||||||
| Paratte et al., 2011 [ |
| Retrospective | 180 | FB | 79 | 62.8 | 63% |
| MB | 77 | 63.4 | 68% | ||||
| Patrick et al., 2020 [ |
| Retrospective | 14.4 | MB | 150 | 68.6 | 53% |
| FB | 44 | 67.7 | 86% | ||||
| Pronk et al., 2020 [ |
| Retrospective | 12 | MB | 66 | 61.4 | 47% |
| FB | 97 | 61.2 | 44% | ||||
| Seo et al., 2019 [ |
| Retrospective | 120 | MB | 36 | 64.5 | 97% |
| FB | 60 | 61.8 | 95% | ||||
| Tecame et al., 2018 [ |
| Retrospective | 42 | MB | 9 | 47.8 | 17% |
| FB | 15 | 48.4 | |||||
| Verdini et al., 2017 [ |
| Prospective | 20 | MB | 7 | 68.0 | 60% |
| FB | 8 | 67.0 | 40% | ||||
| Whittaker et al., 2010 [ |
| Retrospective | 3.6 | FB | 150 | 68.0 | 53% |
| MB | 79 | 63.0 | 48% |
Main results of the meta-analyses. The final effect was evaluated as odds ratio for binary data and as mean difference for continuous data (MB: mobile bearing; FB: fixed bearing; CI: confidence interval).
| Endpoint | MB | FB | Model | 95% CI | Final Effect |
| I2 ( |
|---|---|---|---|---|---|---|---|
| ROM | 243 | 249 | Fixed | −4.37, −0.04 | −2.21 | 0.05 | 0 |
| KSS | 487 | 548 | Random | −6.38, 5.64 | −0.37 | 0.9 | 99 |
| KSFS | 176 | 241 | Fixed | −1.92, 0.31 | −0.81 | 0.2 | 0 |
| OKS | 97 | 95 | Random | −11.56, 4.44 | −3.56 | 0.4 | 95 |
| Revision | 2353 | 1148 | Random | 0.82, 3.20 | 1.62 | 0.2 | 52 |
| Aseptic Loosening | 1810 | 658 | Random | 0.16, 7.96 | 1.12 | 0.9 | 89 |
| Deep Infections | 1781 | 404 | Fixed | 0.28, 3.47 | 0.99 | 0.99 | 0 |
| Fractures | 1679 | 277 | Random | 0.08, 4.85 | 0.61 | 0.6 | 62 |
| OA Progression | 1752 | 602 | Fixed | 0.81, 2.60 | 1.45 | 0.2 | 3 |