Skip to main content

Three distinct recovery patterns following primary total knee arthroplasty: dutch arthroplasty register study of 809 patients

Knee Surgery, Sports Traumatology, Arthroscopy volume 29, pages 529–539 (2021)Cite this article

Abstract

Purpose

Total knee arthroplasty (TKA) is usually effective, although not all patients have satisfactory outcomes. This assumes distinct recovery patterns might exist. Little attention has been paid to determine which patients have worse outcomes. This study attempts to distinguish specific recovery patterns using the Oxford knee score (OKS) during the first postoperative year. The secondary aim was to explore predictors of less favourable recovery patterns.

Methods

Analysis of patients in the Dutch Arthroplasty Register (LROI) with unilateral primary TKA. Data collected up to one year postoperative was used. To identify subgroups of patients based on OKS, latent class growth modeling (LCGM) was used. Moreover, multivariable multinomial logistic regression analysis was used to explore predictors of class membership.

Results

809 Patients completed three OKS during the first year postoperative and were included. LCGM identified 3 groups of patients; ‘high risers’ (most improvement during first 6-months, good 12-month scores 77%), ‘gradual progressors’ (continuous improvement during the first year 13%) and ‘non responders’ (initial improvement and subsequent deterioration to baseline score 10%). Predictors of least favourable class membership (OR, 95%CI) are EQ-5D items: VAS health score (0.83, 0.73–0.95), selfcare (2.22, 1.09–4.54) and anxiety/depression (2.45, 1.33–4.52).

Conclusion

Three recovery patterns after TKA were distinguished; ‘high risers', ‘gradual progressors' and ‘non responders'. Worse score on EQ-5D items VAS health, selfcare, and anxiety/depression were correlated with the least favourable ‘non responders’ recovery pattern.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price includes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2

References

  1. Baker P, Petheram T, Jameson S, Reed M, Gregg P, Deehan D (2012) The association between body mass index and the outcomes of total knee arthroplasty. J Bone Joint Surg Am 94:1501–1508

    Article  Google Scholar 

  2. Baker PN, van der Meulen JH, Lewsey J, Gregg PJ, National Joint Registry for E, Wales (2007) The role of pain and function in determining patient satisfaction after total knee replacement. Data from the National Joint Registry for England and Wales. J Bone Joint Surg Br 89:893–900

    CAS  Article  Google Scholar 

  3. Berlin KS, Parra GR, Williams NA (2014) An introduction to latent variable mixture modeling (part 2): longitudinal latent class growth analysis and growth mixture models. J Pediatr Psychol 39:188–203

    Article  Google Scholar 

  4. Bourne RB, Chesworth BM, Davis AM, Mahomed NN, Charron KD (2010) Patient satisfaction after total knee arthroplasty: who is satisfied and who is not? Clin Orthop Relat Res 468:57–63

    Article  Google Scholar 

  5. Dawson J, Fitzpatrick R, Murray D, Carr A (1998) Questionnaire on the perceptions of patients about total knee replacement. J Bone Joint Surg Br 80:63–69

    CAS  Article  Google Scholar 

  6. Dowsey MM, Smith AJ, Choong PFM (2015) Latent Class Growth Analysis predicts long term pain and function trajectories in total knee arthroplasty: a study of 689 patients. Osteoarthritis Cartil 23:2141–2149

    CAS  Article  Google Scholar 

  7. Dumenci L, Perera RA, Keefe FJ, Ang DC, Slover J, Jensen MP et al (2019) Model-based pain and function outcome trajectory types for patients undergoing knee arthroplasty: a secondary analysis from a randomized clinical trial. Osteoarthritis Cartil. https://doi.org/10.1016/j.joca.2019.01.004

    Article  Google Scholar 

  8. Dutch Arthroplasty Register (in Dutch: LROI). Online LROI-Rapportage 2016: Blik op uitkomsten. https://www.lroi-rapportage.nl/media/pdf/PDF%20Online%20LROI-Rapportage%202016.pdf. Accessed 9 Jan 2020

  9. Dutch Arthroplasty Register (in Dutch: LROI). Online LROI annual report 2017. https://www.lroi-rapportage.nl/media/pdf/PDF%20LROI%20annual%20report%202017.pdf. Accessed 11 Nov 2019

  10. EuroQol G (1990) EuroQol–a new facility for the measurement of health-related quality of life. Health Policy 16:199–208

    Article  Google Scholar 

  11. Halawi MJ, Allen DA, Baron S, Savoy L, Williams VJ, Cote MP (2018) Tobacco smoking independently predicts lower patient-reported outcomes: new insights on a forgotten epidemic. J Arthroplast. https://doi.org/10.1016/j.arth.2018.10.036

    Article  Google Scholar 

  12. Jung T, Wickrama K (2008) An introduction to latent class growth analysis and growth mixture modeling. Soc Personal Psychol Compass 2:302–317

    Article  Google Scholar 

  13. Kuperman EF, Schweizer M, Joy P, Gu X, Fang MM (2016) The effects of advanced age on primary total knee arthroplasty: a meta-analysis and systematic review. BMC Geriatr 16:41

    Article  Google Scholar 

  14. Lindberg MF, Miaskowski C, RustoEn T, Rosseland LA, Cooper BA, Lerdal A (2016) Factors that can predict pain with walking, 12 months after total knee arthroplasty. Acta Orthop 87:600–606

    Article  Google Scholar 

  15. Nagin DS (2005) Group-based modeling of development. Harvard University Press, Harvard

    Book  Google Scholar 

  16. Nagin DS, Odgers CL (2010) Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 6:109–138

    Article  Google Scholar 

  17. Page MG, Katz J, Romero Escobar EM, Lutzky-Cohen N, Curtis K, Fuss S et al (2015) Distinguishing problematic from nonproblematic postsurgical pain: a pain trajectory analysis after total knee arthroplasty. Pain 156:460–468

    Article  Google Scholar 

  18. Rabin R, de Charro F (2001) EQ-5D: a measure of health status from the EuroQol Group. Ann Med 33:337–343

    CAS  Article  Google Scholar 

  19. Ram N, Grimm KJ (2009) Growth mixture modeling: a method for identifying differences in longitudinal change among unobserved groups. Int J Behav Dev 33:565–576

    Article  Google Scholar 

  20. Singh JA, Lewallen DG (2013) Medical and psychological comorbidity predicts poor pain outcomes after total knee arthroplasty. Rheumatol (Oxford) 52:916–923

    Article  Google Scholar 

  21. Singh JA, O'Byrne M, Harmsen S, Lewallen D (2010) Predictors of moderate-severe functional limitation after primary total knee arthroplasty (TKA): 4701 TKAs at 2-years and 2935 TKAs at 5-years. Osteoarthritis Cartil 18:515–521

    CAS  Article  Google Scholar 

  22. Tristaino V, Lantieri F, Tornago S, Gramazio M, Carriere E, Camera A (2016) Effectiveness of psychological support in patients undergoing primary total hip or knee arthroplasty: a controlled cohort study. J Orthop Traumatol 17:137–147

    CAS  Article  Google Scholar 

  23. van de Schoot R, Sijbrandij M, Depaoli S, Vermunt JK (2017) The GRoLTS-checklist: guidelines for reporting on latent trajectory studies. Struct Equ Model Multidiscip J 451–467

  24. van Steenbergen LN, Denissen GA, Spooren A, van Rooden SM, van Oosterhout FJ, Morrenhof JW et al (2015) More than 95% completeness of reported procedures in the population-based Dutch Arthroplasty Register. Acta Orthop 86:498–505

    Article  Google Scholar 

  25. Vissers MM, Bussmann JB, Verhaar JA, Busschbach JJ, Bierma-Zeinstra SM, Reijman M (2012) Psychological factors affecting the outcome of total hip and knee arthroplasty: a systematic review. Semin Arthritis Rheum 41:576–588

    Article  Google Scholar 

  26. Wickrama KAS, Lee TK (2016) Higher-order growth curves and mixture modeling with mplus: a practical guide.

  27. Zale EL, Ring D, Vranceanu AM (2018) The future of orthopaedic care: promoting psychosocial resiliency in orthopaedic surgical practices. J Bone Joint Surg Am 100:e89

    Article  Google Scholar 

  28. Zhao S, Chen F, Wang D, Wang H, Han W, Zhang Y (2019) Effect of preoperative smoking cessation on postoperative pain outcomes in elderly patients with high nicotine dependence. Medicine (Baltimore) 98:e14209

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank LROI for using the data. Moreover, we would like to thank the Van Rens Fonds for financially supporting this study.

Funding

This study was funded by the Van Rens Fonds Foundation (VRF2017-005), The Netherlands.

Author information

Authors and Affiliations

  1. Department of Orthopaedic Surgery, Reinier de Graaf Groep, Reinier de Graafweg 5, 2625 AD, Delft, The Netherlands

    Jeroen C. van Egmond, Brechtje Hesseling, Stephan B. W. Vehmeijer & Nina M. C. Mathijssen

  2. Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628 CE, Delft, The Netherlands

    Marijke Melles

  3. Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands

    Marijke Melles

  4. Dutch Arthroplasty Register (Landelijke Registratie Orthopedische Implantaten/LROI), Bruistensingel 230, 5232 AD, Hertogenbosch, The Netherlands

    Liza N. van Steenbergen

  5. Integrated Brain Health Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, One Bowdoin Square, Boston, MA, 02114, USA

    Jarry T. Porsius

  6. Department of Rehabilitation Medicine and the Department of Plastic and Reconstructive Surgery, Erasmus University Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands

    Jarry T. Porsius

Authors
  1. Jeroen C. van Egmond
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brechtje Hesseling
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marijke Melles
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Stephan B. W. Vehmeijer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liza N. van Steenbergen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Nina M. C. Mathijssen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jarry T. Porsius
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JE performed data-analysis, he wrote and revised the manuscript for important intellectual content. BH supported data-analysis and critically reviewed the manuscript for important intellectual content. MM designed the study and critically reviewed the manuscript for important intellectual content. SV designed the study and critically reviewed the manuscript for important intellectual content and wrote the funding application. LS designed the study, provided data from the Dutch Arthroplasty Register (LROI) and critically reviewed the manuscript for important intellectual content. NM designed the study, supported data analysis and critically reviewed the manuscript for important intellectual content. JP designed the study, supported data analysis, critically reviewed the manuscript for important intellectual content and wrote the funding application. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Jeroen C. van Egmond.

Ethics declarations

Conflict of interest

S.B.W. Vehmeijer has a consultancy contract with Zimmer Biomet.

Ethical approval

Not applicable.

Informed consent

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 25 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

van Egmond, J.C., Hesseling, B., Melles, M. et al. Three distinct recovery patterns following primary total knee arthroplasty: dutch arthroplasty register study of 809 patients. Knee Surg Sports Traumatol Arthrosc 29, 529–539 (2021). https://doi.org/10.1007/s00167-020-05969-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00167-020-05969-8

Keywords

  • Total knee arthroplasty
  • Latent class growth modeling
  • Trajectories
  • Patient-reported outcome measurements