Postoperative knee instability is one of the major reasons accounting for unsatisfactory outcomes, as well as a major failure mechanism leading to revision surgery after primary total knee arthroplasty (TKA). However, postoperative knee instability is not well defined clinically, and the boundaries between stable and unstable TKA knees are still poorly understood. This lack of understanding is likely due to the multitude of factors that are associated with knee instability, including inadequate soft-tissue balancing (Hosseini Nasab et al., 2019; Song et al., 2014), loss of ligamentous integrity (Nagle and Glynn, 2020), and improper component sizing (Nagle and Glynn, 2020; Parratte and Pagnano, 2008).

Clinical assessment of joint stability relies on passive laxity examinations and patient-reported outcome measures (PROMs). Manual stress tests, including the anterior/posterior drawer, Lachman, and varus/valgus tests, as well as questionnaires such as the Knee injury and Osteoarthritis Outcome Score (KOOS) (Roos et al., 1998), Oxford Knee Score (OKS) (Dawson et al., 1998), University of California and Los Angeles (UCLA) Activity Scale (Zahiri et al., 1998), and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (Bellamy et al., 1988) are widely used in clinical practice to assess knee instability after TKA. However, such clinical assessments are highly subjective with large inter-rater variability (Mears et al., 2022). With the goal to objectively investigate knee instability, methods for quantifying passive knee laxity such as the KT-1000/2000 (White et al., 1991; Ishii et al., 2005), Telos (Murer et al., 2021; Moser et al., 2022; Jung et al., 2006), Rotometer (Moewis et al., 2016; Lorbach et al., 2012), and Rolimeter (Schuster et al., 2011) devices, all generally combined with stress radiography, have been presented. Studies using these techniques have demonstrated that passive knee laxity plays a key role for functional outcomes and patient satisfaction after TKA (Oh et al., 2015; Jones et al., 2006). Nevertheless, it remains unclear whether self-reported instability after TKA is reflected in implant kinematics in vivo during functional activities of daily living. Specifically, both downhill walking and stair descent are considered as challenging tasks for subjects with knee pathologies (Stacoff et al., 2005; Simon et al., 2018), and could therefore present relevant activities for provoking feelings of instability.

As the primary actuators of the locomotion system, muscles play a critical role in guiding motor functionality as well as supporting stability of the knee joint. Muscular deficits are often observed after TKA and closely correlate with physical impairment and limitations in daily activities (Berman et al., 1991; Walsh et al., 1998). Well-coordinated muscular activity is thought to be necessary for normal gait patterns (Berman et al., 1991). Here, adaptation of muscle recruitment patterns in the early postoperative phase, where increased knee extensor (quadriceps) and flexor (hamstrings) co-activation has generally been observed, is thought to enhance knee stability (Lundberg et al., 2016; Benedetti et al., 2003). However, whether such muscular adaptation is temporary and can be reversed in the long term after TKA remains controversially discussed (Benedetti et al., 2003; Thomas et al., 2014). Moreover, it remains unknown whether such adaptive strategies persist in unstable knees, or whether different lower limb muscle synergy patterns develop to compensate for deficits in knee stability.

While the accurate assessment of tibiofemoral kinematics during functional activities is challenging, the recent development of dynamic video-fluoroscopy systems now provides access to implant kinematics with a high level of accuracy and without soft-tissue artefact throughout consecutive cycles of gait activities (Taylor et al., 2017; Schütz et al., 2019b; Schütz et al., 2019a; List et al., 2020). Such systems have recently allowed investigations into the impact of activity (Schütz et al., 2019a) and implant geometry (Schütz et al., 2019b; List et al., 2020) on tibiofemoral kinematics during functional activities such as level walking, downhill walking, and stair descent, and can be combined with electromyography (EMG) to assess muscle activation synergies and its role on modulating joint kinematics (Benedetti et al., 2003; Taylor et al., 2017; Ardestani et al., 2017). As such, the application of these approaches to subjects with stable and unstable knees after TKA could establish whether compensation mechanisms continue to occur, but also elucidate the role of neuromuscular activation and coordination on kinematic adaptations in the joint.

To understand tibiofemoral kinematics in unstable TKA knees and its interaction with muscle activation strategies, the objective of this study was to investigate in vivo tibiofemoral implant kinematics and muscle synergy patterns in subjects with stable and self-reported unstable knees after TKA during functional activities of daily living using dynamic video-fluoroscopy and EMG. Specifically, we aimed to establish whether unstable knees exhibit higher levels of relative tibiofemoral motion and distinct muscle synergy patterns/strategies than their stable counterparts.

Knee instability is one of the most common reasons for unsatisfactory outcomes after TKA, accounting for up to 26% of revisions (Parratte and Pagnano, 2008; Wilson et al., 2017). However, the relationships between self-reported assessment of instability and knee functionality in daily living remain unclear. Using moving video-fluoroscopy and EMG, we compared kinematic parameters of knee joint stability, as well as muscle synergy patterns, between subjects who had expressed concern at the stability of their knee, and those who were happy with its functional performance. Our results indicate that kinematic parameters, including A-P translations and knee rotations, as well as their RoMs during functional activities, were generally comparable between stable and unstable TKA knees. However, increased heterogeneity in muscle synergy patterns between subjects and across activities, especially during challenging tasks such as stair descent, as well as prolonged activation of the classified knee flexor synergy, were observed in the unstable group. These differences between groups plausibly reveal long-lasting muscular adaptation strategies that develop as a compensation mechanism for feelings of joint instability and serve to prevent possible unstable events. Despite these modifications in muscular strategies, however, specific cases of acute instability were still reported by some subjects during the measurements, and analysis of their data revealed clear deviations in kinematic patterns from those of both the stable and unstable groups. These observations suggest that accurate movement analysis might be highly sensitive for detecting acute instability events, but might be less robust in identifying general joint instability.

The range of A-P translation in both groups studied here was comparable to previous studies during functional activities in good outcome TKAs with similar UC inlay geometries (Schütz et al., 2019b; Roberti di Sarsina et al., 2022; Cardinale et al., 2020). The so-called ‘paradoxical anterior translation’ pattern that is commonly observed in tibiofemoral kinematics after TKA (Dennis et al., 2003) was also observed in both groups during level walking and became even more evident during downhill walking and stair descent. Interestingly, while the stable and unstable groups showed comparable A-P translation RoMs on both condyles (Table 2), the assessment of subject-specific tibiofemoral kinematics was capable of identifying acute instability events. In vivo kinematics of three unstable knees who reported instability during downhill walking and stair descent showed distinct A-P motion patterns, with an early, rapid condylar posterior translation followed by an additional anterior translation in the early/mid-swing phase (Figure 3). Such kinematic patterns stand out from those of both the stable cohort and even the unstable knees that did not report instability during the measured activities. Although our findings suggest that the accurate assessment of tibiofemoral kinematics has the potential to identify acute instability events, we have not been able to detect a common distinct kinematic pattern throughout the cohort of unstable knees.

Extensive efforts have been made to understand kinematic adaptations in knee pathologies including osteoarthritis (OA) and posterior cruciate ligament deficiency (PCLD). However, no significant differences have yet been found between PCLD and healthy knees in abduction/adduction or in internal/external rotation (Fontboté et al., 2005), nor in knee flexion/extension between OA knees and healthy controls (Na et al., 2018) during level gait. During more challenging activities such as stair descent, the differences in knee flexion angle and extensor torque between PCLD and healthy knees have been found to be statistically significant but presented no outstanding clinical consequences (Hooper et al., 2002). Interestingly, the structural deficits presented in such cases did not seem to result in clear kinematic deviations. Similarly in our study of knee joint instability, it seems that tibiofemoral movement patterns become well-compensated/controlled, plausibly through altered muscular control mechanisms.

It was previously found that unsatisfactory TKA knees present fewer muscle synergies for locomotion compared to satisfactory TKA knees and healthy controls (Ardestani et al., 2017). However, our results suggest that more heterogenous synergy patterns were developed in the unstable compared to the stable knees in the long term, albeit with a comparable number of synergies extracted from both groups in all activities. A higher number of non-classifiable, subject-specific muscle synergies was identified in the unstable compared to the stable group during level walking, and this number further increased during the more demanding activities of downhill walking and stair descent. This finding suggests that more challenging locomotor activities have a greater potential for provoking knee instability, which is plausibly linked to the requirement for a specific or individual response to each unstable situation or musculoskeletal deficit. Higher FWHM in the knee-/dorsiflexor-controlled activation patterns were observed in the unstable knees compared to their stable counterparts during stair descent, which further indicates that the feeling of instability can permanently trigger prolonged activation of flexor muscle groups. This finding is in line with previous studies reporting the widening of muscle activation patterns in pathologies (Cappellini et al., 2016; Martino et al., 2015; Janshen et al., 2020), early developmental stage (Cappellini et al., 2016; Dominici et al., 2011), ageing (Santuz et al., 2020; Dewolf et al., 2021), and presence of external mechanical perturbations (Santuz et al., 2018a). A possible explanation for this peculiar behaviour can be found in mouse studies, where similar temporal modifications of muscle activity have been associated with a lack of sensory feedback from proprioceptors (Akay et al., 2014; Mayer and Akay, 2018; Santuz et al., 2019). Interestingly, our results showed that knee extensor–flexor co-activation was present throughout the stance phase of the gait cycle in both TKA groups in all activities. However, this co-activation pattern was generally not reported in healthy stable knees (Santuz et al., 2018a; Cappellini et al., 2006; Lacquaniti et al., 2012). This finding shows that co-activation of knee extensors and flexors appears after TKA and persists in the long term. Moreover, we found a major involvement in TKA knees of knee flexors in the propulsion/early-swing phase during all activities, contrary to what is typically found in healthy subjects (Santuz et al., 2020; Santuz et al., 2018a; Cappellini et al., 2006; Lacquaniti et al., 2012). These activation bursts of the knee flexors possibly serve as an additional adaptive strategy to ensure joint stability during daily activities (Benedetti et al., 2003; Hirokawa et al., 1991).

There are some limitations to this retrospective observational study. Firstly, only small sample sizes were considered, which consisted of 70% male in the stable group but >60% female in the unstable group. Since subjective differences in soft-tissue properties are known to exist between males and females, it is possible that gender imbalance could have influenced the results of the passive laxity tests presented. Even though no statistical differences were found between our study groups, a more balanced cohort should be investigated in future to confirm the findings of this study. Moreover, self-reported instability is highly subjective and activity dependent, which is visible in the high inter-subject kinematic variability, and not all patients in the unstable group reported a feeling of instability during measurement. Our analyses have, therefore, not been able to capture all the characteristics of self-reported instability, but have rather been able to make progress in understanding the relationships between several important confounding factors, as well as the individual compensation mechanisms that have developed due to joint instability. The unstable knees in this study demonstrated highly heterogenous, unclassifiable muscle synergies with variable activation patterns, suggesting patient-specific muscular strategies. However, it remains unclear whether the observed synergy patterns are a hallmark for classifying knee stability. Lastly, only a single implant type was examined in this study. Here, we acknowledge that considerable further investigation would be required to establish whether the same or similar results are observed in subjects with other implants. Moreover, it is likely that more challenging tasks (e.g. stop-and-go activities) could expose the subjects to more frequent instability events than the daily activities investigated in our study, but such tasks are hard to standardize for reliable assessment of kinematic instability.

Source Data files and related codes have been provided for all Figures and Tables in the supplementary and can be found here: https://doi.org/10.3929/ethz-b-000584582.

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Author details

1. Longfeng Rao

   Laboratory for Movement Biomechanics, Institute for Biomechanics, Zurich, Switzerland

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2139-4972

2. Nils Horn

   Department of lower extremities, Schulthess Clinic Zurich, Zurich, Switzerland

   Contribution

   Conceptualization, Resources, Data curation, Supervision, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Nadja Meister

   Laboratory for Movement Biomechanics, Institute for Biomechanics, Zurich, Switzerland

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

4. Stefan Preiss

   Department of lower extremities, Schulthess Clinic Zurich, Zurich, Switzerland

   Contribution

   Conceptualization, Resources, Supervision, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

5. William R Taylor

   Laboratory for Movement Biomechanics, Institute for Biomechanics, Zurich, Switzerland

   Contribution

   Conceptualization, Resources, Supervision, Validation, Visualization, Methodology, Project administration, Writing – review and editing

   For correspondence

   bt@ethz.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4060-4098

6. Alessandro Santuz

   1. Laboratory for Movement Biomechanics, Institute for Biomechanics, Zurich, Switzerland
   2. Max Delbrück Center for Molecular Medicine, Berlin, Germany

   Contribution

   Software, Formal analysis, Validation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

7. Pascal Schütz

   Laboratory for Movement Biomechanics, Institute for Biomechanics, Zurich, Switzerland

   Contribution

   Conceptualization, Resources, Software, Supervision, Validation, Investigation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1711-7881

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