Elsevier

The Journal of Arthroplasty

Volume 35, Issue 1, January 2020, Pages 121-126.e6
The Journal of Arthroplasty

Primary Arthroplasty
Using Cluster Analysis to Identify Patient Factors Linked to Differential Functional Gains After Total Knee Arthroplasty

https://doi.org/10.1016/j.arth.2019.08.039Get rights and content

Abstract

Background

The basis of poor outcomes following total knee arthroplasty (TKA) is multifactorial. Previous research aimed at predicting outcome following TKA focuses largely on outcomes measured between two specific time points (pre-to post-TKA). Analysis of outcomes measured over multiple time points (trajectory) may expose relationships between patients’ characteristics and longitudinal outcome patterns that may otherwise remain obscured.

Methods

The current study analyzed Short Form 36 Physical Component Score (PCS) trajectories of 656 patients composed of 3 time points over a 1-year period. Clusters were constructed utilizing MultiExperiment Viewer hierarchical clustering algorithm. Statistical significance of these clusters was assessed using MeV’s built-in bootstrapping method. Patient characteristics of the resulting statistically conserved clusters were summarized and compared using Wilcoxon rank-sum test or chi-squared test as appropriate.

Results

Two distinct clusters of outcome trajectory were identified. Cluster 1 included 550 patients (84%) who demonstrated persistent PCS improvement at 6 and 12 months. Cluster 2 included 106 patients (16%) who demonstrated decline in PCS at 6 months followed by improvement at 12 months. Cluster 1 achieved earlier success, greater absolute mental and physical health scores as compared to Cluster 2 (P < .05), and demonstrated higher baseline mental health scores, lower baseline PCS, and a significantly higher proportion of non-Hispanic Whites (P ≤ .05).

Conclusion

Cluster analysis identified distinct functional outcome trajectories following TKA. Specific differentiating patient factors were associated with differing trajectories. Future studies should focus on this method’s ability to inform predictive models regarding patient outcomes.

Section snippets

Data Sources

This is a prospective cohort study. FORCE-TJR (Functional and Outcomes Research for Comparative Effectiveness in Total Joint Replacement), centered at the University of Massachusetts Medical School, is a national, prospective, cohort of total joint arthroplasty patients [30], [31]. Parallel to the current US surgical practice, 75% of patients are enrolled from community-based surgeons, including fellowship-trained and general orthopedists in urban and rural locations, as well as teaching and

Results

Hierarchical clustering yielded 2 statistically significantly distinct clusters among the 656 total patients at a between-cluster distance of −0.15 (Pearson correlation coefficient). Cluster 1 contained 550 patients (84% of the cohort) and, on average, exhibited a clinically important improvement in PCS at 6 months postoperatively followed by no further improvement at 12 months postoperatively (Table 2, Fig. 2) [36]. Cluster 2 contained 106 patients (16% of the cohort) and, on average,

Discussion

This study identified 2 significantly different physical function outcome trajectories within the first year following TKA, in the patient cohort analyzed. One trajectory was marked by sustained functional gains, and the other was marked by delayed functional gains. We demonstrated the efficacy of cluster analysis in identifying post-TKA outcome trajectories, which has not been reported previously to our knowledge. In addition, we were able to demonstrate that the identified outcome

References (53)

  • P.D. Franklin et al.

    Incorporating patient-reported outcomes in total joint arthroplasty registries: challenges and opportunities

    Clin Orthop Relat Res

    (2013)
  • P.D. Franklin et al.

    The Chitranjan Ranawat Award: functional outcome after total knee replacement varies with patient attributes

    Clin Orthop Relat Res

    (2008)
  • D.C. Ayers et al.

    Total knee replacement outcome and coexisting physical and emotional illness

    Clin Orthop Relat Res

    (2005)
  • D.C. Ayers et al.

    Patient-reported outcomes after total knee replacement vary on the basis of preoperative coexisting disease in the lumbar spine and other nonoperatively treated joints: the need for a musculoskeletal comorbidity index

    J Bone Joint Surg Am

    (2013)
  • A. Escobar et al.

    Effect of patient characteristics on reported outcomes after total knee replacement

    Rheumatology (Oxford)

    (2007)
  • C.E. Scott et al.

    Predicting patient dissatisfaction following total knee replacement: a prospective study of 1217 patients

    J Bone Joint Surg Br

    (2010)
  • R.B. Bourne et al.

    Patient satisfaction after total knee arthroplasty: who is satisfied and who is not?

    Clin Orthop Relat Res

    (2010)
  • M. Sloan et al.

    Projected volume of primary total joint arthroplasty in the U.S., 2014 to 2030

    J Bone Joint Surg Am

    (2018)
  • A. Husain et al.

    Establishing realistic patient expectations following total knee arthroplasty

    J Am Acad Orthop Surg

    (2015)
  • M. Khan et al.

    The epidemiology of failure in total knee arthroplasty avoiding your next revision

    Bone Joint J

    (2016)
  • H.M. Kremers et al.

    Comparative survivorship of different tibial designs in primary total knee arthroplasty

    J Bone Joint Surg Am

    (2014)
  • T. Borus et al.

    Unicompartmental knee arthroplasty

    J Am Acad Orthop Surg

    (2008)
  • O. Furnes et al.

    Failure mechanisms after unicompartmental and tricompartmental primary knee replacement with cement

    J Bone Joint Surg Am

    (2007)
  • J.N. Katz et al.

    Association between hospital and surgeon procedure volume and the outcomes of total knee replacement

    J Bone Joint Surg Am

    (2004)
  • N. Shervin et al.

    Orthopaedic procedure volume and patient outcomes: a systematic literature review

    Clin Orthop Relat Res

    (2007)
  • J. Julin et al.

    Younger age increases the risk of early prosthesis failure following primary total knee replacement for osteoarthritis. A follow-up study of 32,019 total knee replacements in the Finnish Arthroplasty Register

    Acta Orthop

    (2010)
  • Cited by (8)

    • Relationship Between Preoperative and Postoperative Motion After Four-Corner Wrist Fusion for Osteoarthritis: Clustering and Regression Analyses

      2022, Journal of Hand Surgery
      Citation Excerpt :

      Cluster analyses make it possible to determine groups along with continuous variables, unlike arbitrary groups, which may divide and eliminate statistically significant data. Cluster analyses have been previously used in orthopedic studies to assess preoperative and postoperative ROM.9,20,21 For example, Ritter et al,20 through their cluster analysis of 4727 total knee arthroplasties, found that the principal predictive factor of postoperative ROM was preoperative ROM.

    View all citing articles on Scopus

    Investigation was performed at the University of Massachusetts Medical School, Worcester, MA

    Ethical Approval: This study was approved by the UMass Medical School Institutional Review Board, Docket #H00008642.

    One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2019.08.039.

    View full text