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An orthopaedic intelligence application successfully integrates data from a smartphone-based care management platform and a robotic knee system using a commercial database

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Abstract

Purpose

To evaluate the feasibility of using a smartphone-based care management platform (sbCMP) and robotic-assisted total knee arthroplasty (raTKA) to collect data throughout the episode-of-care and assess if intra-operative measures of soft tissue laxity in raTKA were associated with post-operative outcomes.

Methods

A secondary data analysis of 131 patients in a commercial database who underwent raTKA was performed. Pre-operative through six week post-operative step counts and KOOS JR scores were collected and cross-referenced with intra-operative laxity measures. A Kruskal–Wallis test or a Wilcoxon sign-rank was used to assess outcomes.

Results

There were higher step counts at six weeks post-operatively in knees with increased laxity in both the lateral compartment in extension and medial compartment in flexion (p < 0.05). Knees balanced in flexion within < 0.5 mm had higher KOOS JR scores at six weeks post-operative (p = 0.034) compared to knees balanced within 0.5–1.5 mm.

Conclusion

A smartphone-based care management platform can be integrated with raTKA to passively collect data throughout the episode-of-care. Associations between intra-operative decisions regarding laxity and post-operative outcomes were identified. However, more robust analysis is needed to evaluate these associations and ensure clinical relevance to guide machine learning algorithms.

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Data availability

Access to the data is limited by the privacy and data processing teams. Requests to review the raw data will be reviewed on an individual basis.

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Funding

This work was supported by Zimmer Biomet, Inc.

Author information

Authors and Affiliations

  1. Rothman Orthopaedic Institute, Philadelphia, PA, USA

    Jess H. Lonner

  2. Zimmer Biomet, Warsaw, IN, USA

    Mike B. Anderson, Roberta E. Redfern & Dave Van Andel

  3. Regnerative Orthopedic Center, Portland, OR, USA

    James C. Ballard

  4. Department of Orthopaedic Surgery, International Knee and Joint Centre, Abu Dhabi, United Arab Emirates

    Sébastien Parratte

  5. Institute for Locomotion, Aix-Marseille University, Marseille, France

    Sébastien Parratte

Authors
  1. Jess H. Lonner
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  2. Mike B. Anderson
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  3. Roberta E. Redfern
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  4. Dave Van Andel
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  6. Sébastien Parratte
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Roberta Redfern and Mike B. Anderson. The first draft of the manuscript was written by Roberta Redfern and Mike B. Anderson and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sébastien Parratte.

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Ethical approval

The data was completely anonymized and access to data was restricted by the entity’s privacy and data processing teams. As such, the study does not meet the criteria for human subject research; regardless, an institutional review board approved the study with a waiver of consent and authorization (IRB # 20222582).

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Not applicable.

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Not applicable.

Conflict of interest

Jess Lonner—Royalties, paid consultant, research support: Zimmer Biomet and Smith and Nephew; paid consultant, stock or stock options, research support: Force Therapeutics. Roberta E. Redfern—employee of Zimmer Biomet. Mike B. Anderson—employee Zimmer Biomet; OrthoGrid Systems Stock or Stock Options. Dave Van Andel—employee of Zimmer Biomet. James Ballard—paid consultant; paid presenter or speaker Zimmer Biomet. Sebastien Parratte—Royalties: Zimmer Biomet and Newclip Technics, paid consultant: Zimmer Biomet.

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Lonner, J.H., Anderson, M.B., Redfern, R.E. et al. An orthopaedic intelligence application successfully integrates data from a smartphone-based care management platform and a robotic knee system using a commercial database. International Orthopaedics (SICOT) 47, 485–494 (2023). https://doi.org/10.1007/s00264-022-05651-3

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