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71 (); 8-15
doi:
10.1016/j.jor.2025.08.037

Correlation between functional outcome and alterations of aHKA, PCOR, and Caton-Deschamps index following image-based robotic TKA in varus knees

, , , , ,
a Department of Orthopaedics and Sports Orthopaedics, TUM Klinikum Rechts der Isar, Technical University Munich, Ismaningerstr. 22, 81675, Munich, Germany
b Department of Trauma and Orthopedic Surgery, Berufsgenossenschaftliche Unfallklinik Murnau, Prof. Küntscher Str. 8, 82418, Murnau, Germany
c Department of Personalised Orthopaedics (PersO) at Privatklinik Siloah, Worbstrasse 316, 3073, Gümligen, Switzerland

⁎Corresponding author: Claudio Glowalla. claudio.glowalla@tum.de

Received: , Accepted: ,
The Authors
Disclaimer:
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Abstract

This study evaluated the relationship between functional outcomes and radiographic parameter changes in coronal and sagittal planes after robotic-assisted TKA in varus knees.

Between May 2020 and December 2022, all patients who underwent robotic-assisted total knee arthroplasty (RaTKA) using Functional Alignment technique (Mako, Stryker) and met predefined inclusion and exclusion criteria were enrolled in this study. A total of 115 patients (mean age 69.7 years; BMI 27.9; ASA 2.1) with varus knee morphology (defined as an arithmetic hip-knee-ankle angle [aHKA] < 0°) and complete datasets were included in the final analysis.

For analysis pre- and postoperative full-length weight-bearing radiographs and lateral knee views were obtained, and the Medial Proximal Tibial Angle (MPTA) and mechanical Lateral Distal Femoral Angle (mLDFA) in the coronal plane, as well as the Posterior Condylar Offset Ratio (PCOR) and Caton-Deschamps -Index in the sagittal plane were assessed. Based on the differences between pre- and postoperative values of the key parameters, patients were classified into two groups: Collective A, showing no deviation from preoperative alignment, and collective B, exhibiting a deviation in at least one parameter according to predefined thresholds.

Clinical outcome, and patient satisfaction 2 months postoperatively using validated patient-reported outcome measures (PROMs) were compared between the collectives.

No significant differences were observed between the collectives regarding demographics and preoperative clinical parameters. 47 patients were assigned to Collective A, 68 to Collective B. Collective A showed significantly better OKS (26.2 vs. 29.9; p = 0.037∗), EQ-VAS (75.0 vs. 67.2; p = 0.014∗), EQ-5D (0.87 vs. 0.80; p = 0.005∗), and ROM (+4.7° vs. −9.2°; p = 0,007∗), whereas FJS was non-significantly higher in A (44.5 vs. 34.1; p = 0.062).

Anatomic bony restoration in the coronal and sagittal plane was associated with better early outcomes. Even single-parameter deviations may impair results, underscoring the importance of accurate reconstruction in robotic TKA.

Keywords

Robotic assisted total knee arthroplasty
Functional alignment
Kinematic alignment
Varus alignment
Outcome
1

1 Introduction

Although total knee arthroplasty (TKA) performed with mechanical alignment (MA) has been established as Golden Standard, 10–20 % of patients remain dissatisfied with postoperative outcomes.1–3 To address this issue, several new alignment philosophies have been introduced all aiming for a more personalized approach.4–8 However, until now it remains unclear which alignment strategy yields superior results in terms of patient satisfaction, patient-reported outcome measures (PROMs), and range of motion (ROM) —or whether it might be more advisable to select a philosophy specifically for each patient based individual patient anatomy and pathology.

Kinematic alignment (KA) follows a true resurfacing principle, aiming to restore native joint geometry based exclusively on bony landmarks, with the intent of re-establishing physiological soft-tissue balance.5 However, several studies have demonstrated that KA may nonetheless often compromise soft-tissue balance. Shatrov et al. reported flexion gap imbalance in over 50 % of KA cases. Furthermore, it has been shown that different alignment strategies significantly affect femoral and tibial resection planes, thereby altering soft-tissue tension.8–10

In contrast, functional or inverse kinematic alignment (FA/iKA), as described by Lustig and de Grave use intraoperative ligament tension as an important reference for component positioning, typically within predefined adjustment boundaries.4,7 However, soft-tissue balancing remains challenging due to substantial inter-individual variability in laxity phenotypes. This underscores the limitations of systematic approaches for balancing goals in general.8,11 Increasing evidence suggests that achieving optimal ligament balance may be more critical to functional outcomes than strict anatomical restoration of bone geometry.12–14

Although alignment optimization has gained increasing attention, the correlation between radiographic alignment parameters and clinical-functional outcomes remains poorly studied. Most existing investigations have been limited to the coronal plane, neglecting the inherently 3-dimensional nature of lower limb alignment.7,12,15,16 Given the critical role of the sagittal plane—particularly in flexion gap control—its relevance deserves systematic evaluation, as it may provide additional insights into functional outcomes.

The aim of this study is to assess the correlation between functional outcomes and alterations in radiographic key parameters in both the coronal and sagittal planes. This analysis is conducted in patients with varus alignment undergoing image-based robotic assisted total knee arthroplasty (RaTKA) using a functional alignment technique.

To the best of our knowledge, this is the first study to investigate the association between multiplanar alignment changes and patient-reported functional outcomes within a functional alignment framework.

It is hypothesized that accurate restoration of coronal (arithmetic hip-knee-ankle [aHKA]) and sagittal (posterior condylar offset ratio [PCOR], Caton-Deschamps Index [CDI]) alignment key parameters would be associated with superior functional outcomes following image-based RaTKA in patients with varus alignment.

2

2 Methods

2.1

2.1 Patients and data collection

Between May 2020 and December 2022, this prospective, monocentric study included all primary TKA performed using an image-based robotic-assisted system (MAKO, Stryker Corp., USA) in patients with end-stage osteoarthritis and varus limb alignment (aHKA <0°). All procedures were performed by two experienced surgeons using FA technique. The same implant design (Triathlon PS, Stryker Corp., USA) was used in all cases to ensure consistency.

Patients aged ≥18 years with ASA scores of 1–3, sufficient German language skills, and written informed consent were included if follow-up at the study center was planned. Exclusion criteria included prior joint infection, trauma, or surgery (except arthroscopy), metal hypersensitivity (nickel, cobalt, or chromium), legal incapacity, or any condition impairing study comprehension. Dropout was defined as loss to follow-up or incomplete datasets.

2.2

2.2 Alignment strategies

Patients were treated according to FA philosophy, in which individual bony anatomy and pre-arthritic deformity were considered during implantation, and soft tissue tension was balanced by adjusting the implant position within predefined limits to achieve a maximum gap difference of 1 mm between the medial and lateral compartments in both extension and flexion, allowing for slight lateral laxity in flexion.7 Planning was carried out on a patient-specific, CT-based 3D model of the knee joint using image-based RaTKA. The anatomical landmarks were used to determine the size and position of the femoral and tibial implants in the coronal and sagittal planes in a first step. All osteophytes and menisci were removed prior to implant planning.

Then the tibial cut was set to the individual medial proximal tibial angle (MPTA), by that the joint line obliquity (JLO) was restored within defined limits (MPTA 87–90°). The tibial slope was between 0°at 3° as a consequence of the applied PS design, and the rotation corresponded to the Akagi line.17 The femoral component was positioned according to the mechanical lateral distal femoral angle (mLDFA) and the posterior condylar axis (PCA) and then adjusted to balance the extension and flexion gaps, without attempting soft tissue release, which is the primary goal of this FA technique. Adjustments were primarily made to the femoral components within certain limits (MPTA 87–90°, mLDFA 87–93°, HKA: 174–180°, PCA 3°external rotation - 3° internal rotation)) with the goal of achieving a maximum gap difference of 1 mm between the medial and lateral compartments in both extension and flexion, allowing for slight lateral laxity in flexion. The primary goal was achieving optimal soft-tissue balance rather than strict adherence to anatomical resections. In cases of flexion–extension gap asymmetry, particularly with a larger flexion gap, a deviation from the pre-arthritic bone anatomy was accepted and adjusted component positioning—such as femoral rotation or flexion—within the predefined limits rather than modifying resection depth alone.

The planned 3D alignment was then realized with the robot-assisted system's integrated oscillating saw.

2.3

2.3 Data analysis

Data assessment was conducted before surgery and at two months postoperatively by a study physician and a study nurse. This included clinical and radiological examinations, as well as the collection of validated PROMs like the Oxford Knee Score (OKS), the Forgotten Joint Score (FJS), EQ-VAS and EQ-5D.18–21 In addition, patients’ demographic data were recorded and analyzed.

2.4

2.4 Radiographic analysis

To analyze the alignment and radiological results long leg radiographs under weight-bearing, in anterior-posterior, and knee lateral direction were obtained pre- and postoperatively. All radiographic measurements were carried out by an experienced study physician using a digital AGFA software.

In various studies, key radiographic parameters used to describe and define alignment include the mLDFA, MPTA, and JLO in the coronal plane, as well as the PCOR, tibial slope, and the patellar height in the sagittal plane, which can be assessed using the Caton-Deschamps Index.8,22–25 For the evaluation of bony alignment, the following key parameters and their corresponding threshold values were selected:

In the coronal plane, the aHKA angle was calculated as the difference between the MPTA and the mLDFA. A negative value indicates a varus morphology, while a positive value indicates a valgus morphology.26 The Change between the aHKA pre-vs. postoperatively (ΔaHKA) was selected with a tolerance limit of 3°, as both mLDFA and MPTA were intraoperatively adjusted based on individual ligament tension to achieve balanced flexion and extension gaps. This threshold corresponds to the boundary defined in the phenotype classification by MacDessi.23

In the sagittal plane, the PCOR was calculated as the ratio between the maximum posterior condylar offset and the diameter of the femoral shaft, measured along the posterior femoral cortex.27 For the difference between preoperative and postoperative PCOR values (ΔPCOR), a tolerance limit of 0.1 was defined, based on findings that changes of 4–6 mm are associated with reduced knee flexion and mid-range instability.28,29

Also in the sagittal plane, the CDI was measured on a lateral radiograph at 30° knee flexion, calculated as the ratio between the distance from the anterior tibial plateau to the inferior end of the patellar articular surface and the length of the patellar articular surface.30,31 To determine the postoperative CDI, the most cranial point of the tibial implant was used as reference, including the polyethylene inlay height. The difference between the preoperative and postoperative CDI values (ΔCDI) was calculated as a measure of patellar height shift and joint line change. A threshold of 0.2 for the ΔCDI was defined based on the findings of Suthar et al., which demonstrated that a reduction in the patella index is associated with decreased range of motion and poorer functional outcomes.32

These radiological key parameters were integrated into a classification algorithm to stratify patients into two groups. The Classification was based on the differences between pre- and postoperative values of the arithmetic hip-knee-ankle angle (ΔaHKA), posterior condylar offset ratio (ΔPCOR), and Caton-Deschamps Index (ΔCDI), using predefined tolerance thresholds derived from the literature (see Fig. 1). Patients were allocated to Collective A if all three parameters remained within the defined limits, indicating accurate anatomical bony restoration. Collective B included all patients in whom at least one parameter exceeded the accepted threshold, reflecting a deviation from the preoperative alignment.

Algorithm to classify patients into two groups by quantifying changes in the radiological key parameters (arithmetic hip-knee-ankle angle (ΔaHKA), posterior condylar offset ratio (ΔPCOR), and Caton-Deschamps Index (ΔCDI)), using predefined thresholds to assess alignment deviations in the coronal and sagittal planes.
Fig. 1 Algorithm to classify patients into two groups by quantifying changes in the radiological key parameters (arithmetic hip-knee-ankle angle (ΔaHKA), posterior condylar offset ratio (ΔPCOR), and Caton-Deschamps Index (ΔCDI)), using predefined thresholds to assess alignment deviations in the coronal and sagittal planes.
2.5

2.5 Statistical analysis

Statistical analyses were performed using IBM SPSS software (version 28.0.1.0, build 142). Data normality was assessed using the Shapiro–Wilk test. All tests were two-tailed, and p-values <0.05 were considered statistically significant. For normally distributed variables, comparisons within groups (pre-vs. postoperative) were conducted using the paired t-test, and between groups using the independent samples t-test. For non-normally distributed data, within-group comparisons were analyzed using the Wilcoxon signed-rank test, and between-group comparisons with the Mann–Whitney U test. Categorical variables were analyzed using the chi-square (χ2) test. In cases involving multiple group comparisons across two time points, ANOVA was applied for normally distributed data, and the Kruskal–Wallis test for non-normally distributed data.

2.6

2.6 Ethics

All patients gave written consent for their data and images to be used for research and publication purposes. All procedures and data analysis were performed in accordance with all ethical guidelines of the Ethics Committee of the TUM Klinikum rechts der Isar, Munich (409/20S-KH) and with strict consent for data protection.

3

3 Results

A total of 115 patients with complete clinical and radiographic datasets at 2 months postoperatively were included in the final analysis.

3.1

3.1 Radiographic analysis

Based on the radiological analysis and the applied algorithm, n = 47 patients were assigned to Collective A, while n = 68 patients were classified into Collective B (Fig. 1).

The algorithm shows where key parameters deviated: In 81 patients, ΔaHKA was changed by less than 3°. In 73 patients, the PCOR was reconstructed with a deviation of less than 0.1 and in 47 patients, the CDI was restored with a change of less than 0.2, so that all 3 key parameters were achieved in a total of 47patients (Collectiv A). In the remaining 68 patients, at least one of the key parameters deviated from the limits, so these patients were assigned to Collective B.

3.2

3.2 Demographics & clinical parameters

The statistical analysis of the demographic data and the clinical parameters showed no significant differences between Collective A and Collective B (Table 1). The complications were categorized into minor complications (fall with wound dehiscence, superficial wound healing disorder, superficial vein thrombosis) and major complication (arthrofibrosis).

Table 1 Patient demographics and clinical parameters of the Collectives A and B with corresponding p-values for group comparison (ASA = American Society of Anesthesiologists, BMI= Body mass index).
Collective A + B Collective A Collective B p-value A vs. B
Cases 115 47 68
Gender
Female 43 13 30
Male 72 34 38
Age (years) 69.7 ± 8.4 70.5 ± 7.2 69.1 ± 9.1 0.39
BMI (kg/m2) 27.9 ± 4.7 27.9 ± 4.5 27.9 ± 4.9 1.00
ASA- Score 2.1 ± 0.5 2.1 ± 0.5 2.1 ± 0.5 0.567
Surgical time (minutes) 95.2 ± 17.0 92.4 ± 14.4 97.1 ± 18.5 0.15
Follow- Up (days) 63.6 ± 38.0 65.8 ± 35.1 62.0 ± 40.1 0.61
Complications 6 2 4 0.71
Major 1 0 1
Minor 5 2 3
Soft tissue release 25 9 16 0.58
3.3

3.3 PROMs

The evaluation of PROMs within each group revealed statistically significant improvements from preoperative to postoperative assessments in both collectives across all recorded scores (OKS, FJS, EQ-5D, and EQ-VAS). In contrast, ROM improved significantly in Collective A, whereas a significant deterioration in ROM was observed in Collective B (Table 2).

Table 2 Comparison of preoperative and 2-month postoperative functional outcomes (PROMs and ROM) within each Collective (mean ± SD). (OKS = Oxford Knee Score, OKS lower value indicates better outcome, FJS = Forgotten Joint Score, ROM = Range of Motion).
Collective A Collective B
PROM/Function Preoperative Postoperative p-value Preoperative Postoperative p-value
OKS 33.9 ± 8.4 26.2 ± 9.2 <0.001∗ 35.3 ± 7.8 29.9 ± 9.3 <0.001∗
FJS 18.7 ± 18.0 44.5 ± 29.1 <0.001∗ 15.7 ± 16.2 34.1 ± 29.5 <0.001
EQ-5D 0.69 ± 0.18 0.87 ± 0.11 <0.001∗ 0.68 ± 0.21 0.80 ± 0.16 0.003∗
EQ-VAS 66.0 ± 17.7 75.0 ± 14.5 0.003∗ 60.0 ± 18.9 67.2 ± 17.6 0.011∗
ROM 111.3° ± 15.1 116.1° ± 12.5 0.025∗ 117.4° ± 11.6 108.2° ± 16.5 <0.001∗

The comparison of the two groups (collective A and B) shows that the preoperative PROMs do not differ significantly, but the postoperative PROMs show a significant difference with better results for group A on OKS, EQ-VAS and EQ-5D. The FJS trended higher in A, but reached not a significance level. Although Collective B demonstrated significantly greater preoperative ROM compared to Collective A, postoperative measurements revealed a reversal, with Collective B showing significantly reduced ROM in comparison to Collective A (Fig. 2).

Boxplots showing preoperative and 2-months postoperative PROM and Range of motion values for Collectives A and B, including p-values for each comparison: A) No differences in preoperative OKS (p = 0.367), but a significant difference (p = 0.037∗) in postoperative OKS, with better results in the A collective (lower value means better outcome). B) No significant difference in preoperative FJS (p = 0.352). Postoperatively, FJS scores were higher in Collective A; however, the difference did not reach statistical significance (p = 0.062). C) No differences in preoperative EQ-5D (p = 0.907), but a significant difference (p = 0.005∗) in postoperative EQ-5D, with better results in the A collective. D) No differences in preoperative EQ-VAS (p = 0.086), but a significant difference (p = 0.014∗) in postoperative EQ-VAS, with better results in the Collective A. E) Significant difference in preoperative ROM (p = 0.015∗) with greater ROM in Collective B compared to Collective A, postoperative measurements revealed a reversal, with Collective B showing significantly reduced ROM in comparison to Collective A (p = 0.007∗). (∗statistically significant).
Fig. 2 Boxplots showing preoperative and 2-months postoperative PROM and Range of motion values for Collectives A and B, including p-values for each comparison: A) No differences in preoperative OKS (p = 0.367), but a significant difference (p = 0.037∗) in postoperative OKS, with better results in the A collective (lower value means better outcome). B) No significant difference in preoperative FJS (p = 0.352). Postoperatively, FJS scores were higher in Collective A; however, the difference did not reach statistical significance (p = 0.062). C) No differences in preoperative EQ-5D (p = 0.907), but a significant difference (p = 0.005∗) in postoperative EQ-5D, with better results in the A collective. D) No differences in preoperative EQ-VAS (p = 0.086), but a significant difference (p = 0.014∗) in postoperative EQ-VAS, with better results in the Collective A. E) Significant difference in preoperative ROM (p = 0.015∗) with greater ROM in Collective B compared to Collective A, postoperative measurements revealed a reversal, with Collective B showing significantly reduced ROM in comparison to Collective A (p = 0.007∗). (∗statistically significant).
4

4 Discussion

The findings of this study support the initial hypothesis that in a FA alignment workflow accurate bony restoration of coronal (aHKA) and sagittal (PCOR, CDI) alignment key parameters is associated with improved functional outcomes following image-based RaTKA in patients with varus alignment.

The first key finding of this study is that, when applying functional alignment (FA) with strict adherence to predefined soft-tissue balancing targets, a considerable number of patients exhibited deviations from their native bony anatomy. This reflects the competing priorities of bony alignment and ligamentous balance inherent to FA: by rating a specific balancing goal higher often compromises in coronal or sagittal component positioning are required, particularly if soft tissue release is avoided.

Based on radiological analysis, 47 patients (Collective A) met preoperative Alignmemt in all three criteria (ΔaHKA, ΔPCOR, ΔCDI), whereas 68 patients (Collective B) had a deviation in at least one parameter. Notably, if only the coronal plane (ΔaHKA) had been considered, 81 knees would have appeared anatomically restored. The addition of sagittal parameters, however, revealed 40 further deviations—highlighting the critical value of multiplanar assessment in accurately identifying anatomical alterations.

This suggests that in FA-based TKA, achieving soft tissue balance without release may inherently limit the extent to which native anatomy can be restored, despite advanced intraoperative technologies.

The second key finding is that patients with accurate restoration of both coronal and sagittal alignment parameters (ΔaHKA, ΔPCOR, ΔCDI) reported significantly better early outcomes in PROMs, including OKS, EQ-5D, and EQ-VAS, compared to those with deviations beyond predefined thresholds—thus supporting the initial hypothesis that precise anatomical reconstruction correlates with improved functional outcome.

A third key finding of this study is the high external validity of the TUM TKA cohort in comparison to national registry data and published literature. To contextualize the functional outcomes, results were compared with studies utilizing similar alignment strategies or robotic-assisted techniques. However, most of these studies report follow-up periods of 3–12 months, whereas the present data reflect an early follow-up at 2 months. Given the known progression of functional recovery within the first 6 months, this temporal discrepancy must be considered when interpreting outcome comparisons (Table 3).

Table 3 Comparison of the pre- and postoperative Oxford Knee Score (OKS), Forgotten Joint Score (FJS), EQ-VAS, EQ-5D and Range of motion (ROM) with Reference Values from the Literature and Registers (mean ± SD). TUM = Technical University of Munich, LROI = Dutch Arthroplasty Register, TNZJ = National Joint Registry United Kingdom, AOANJRR= Australian Orthopaedic Association National Joint Replacement Registry, FA = Functional Alignment, riKA = restricted inverse Kinematic Alignment, MA = Mechanic Alignment, RaTKA = Robotic assisted Total Knee Arthroplasty, MaTKA = Manual Total Knee Arthroplasty, NaTKA= Navigation assisted Total Knee Arthroplasty, n.s. = not specifie
Group/Literature OKS FJS EQ-VAS EQ-5D ROM Follow up (months) Alignment Technique
pre post pre post pre post pre post pre post
TUM TKA
Collective A + B 34.7 ± 8.1 28.4 ± 9.4 16.9 ± 16.9 38.4 ± 29.6 62.5 ± 18.6 70.4 ± 16.8 0.69 ± 0.2 0.83 ± 0.2 111.4° ± 15.4 114.9° ± 13.4 2 FA RaTKA
Collective A 33.9 ± 8.4 26.2 ± 9.2 18.7 ± 18.0 44.5 ± 29.1 66.0 ± 17.7 75.0 ± 14.5 0.69 ± 0.2 0.87 ± 0.1 111.3° ± 15.1 116.1° ± 12.5 2 FA RaTKA
Collective B 35.3 ± 7.8 29.9 ± 9.3 15.7 ± 16.2 34.1 ± 29.5 60.0 ± 18.9 67.2 ± 17.6 0.68 ± 0.2 0.80 ± 0.2 117.4° ± 11.6 108.2° ± 16.5 2 FA RaTKA
Kenanidis et al. (2023)33 46.1 ± 4.7 32.8 ± 3 3 MA RaTKA
22.2 ± 3.8 71.6 ± 8.3 6 MA RaTKA
44.2 ± 5.2 34.1 ± 3.3 3 MA MaTKA
25.2 ± 4 61.9 ± 8.1 6 MA MaTKA
Winnock de Grave et al. (2022)4 33.7 ± 6.4 15.2 ± 3.5 12 riKA RaTKA
Choi et al. (2023)34 39.3 ± 35.6 3 FA RaTKA
Singh et al. (2021)35 26.5 ± 23.5 3 MA MaTKA
22.3 ± 19.4 3 MA NaTKA
20.6 ± 20.6 3 MA RaTKA
LROI Register (2024)36 36.3 22.5 0.79 6 n.s. n.s.
20.1 12 n.s. n.s.
TNZJ Register (2024)37 21.6 6 n.s. n.s.
AOANJRR Register (2024)38 22.2 80.1 ± 15.4 0.76 6 n.s. n.s.
Golinelli et al. (2025)39 73.1 ± 14.5 0.83 ± 0.15 6 FA RaTKA
Fary et al. (2023)40 0.8 ± 0.17 116.1° 116° 3 MA RaTKA
0.8 ± 0.2 114.6° 118.9° 3 MA MaTKA
Moret et al. (2021)41 78 ± 17.6 0.82 ± 0.16 4 MA MaTKA
84 ± 10.5 0.91 ± 0.11 12 MA MaTKA
Held et al. (2021)42 112° ± 11 114° ± 11 3 n.s. MaTKA
109° ± 14 116.9° ± 9 3 n.s. RaTKA
Adamska et al. (2023)43 114.8° ± 10.4 124.3° ± 12.6 12 MA MaTKA
111.2° ± 10.4 126.3° ± 14.2 12 MA RaTKA
Kafelov et al. (2023)12 117.5° ± 12.5 124.2° ± 8.8 12 riKA RaTKA
120.3° ± 12.9 123.4° ± 10.4 12 riKA MaTKA

When summarizing all findings, it becomes evident that compromises made to achieve soft-tissue balance—despite robotic precision and adherence to FA principles—are associated with inferior functional outcomes when native anatomy is not fully restored. This suggests that the balance between ligament tension and bony alignment remains a limiting factor in current FA protocols. Given the superior outcomes in patients with accurate multiplanar reconstruction, it may be necessary to reconsider whether controlled compromise in balancing can be accepted to achieve more consistent anatomical restoration. However, this hypothesis needs to be proven in a separate study.

4.1

4.1 Data quality

This study is distinguished by high data quality, as all pre- and postoperative full-leg weight-bearing and lateral knee radiographs used to determine radiological key parameters in both the coronal and sagittal planes were assessed by an experienced, trained radiological examiner. All surgical procedures were performed by two board-certified senior surgeons using a consistent surgical technique and alignment philosophy. Functional outcomes were evaluated using multiple validated PROMs, including the OKS, FJS, while the EQ-5D and EQ-VAS were employed to assess health-related quality of life.

4.2

4.2 Limitations

The limitations of the study are the number of study participants (n = 115), and the short follow-up period of 2 months. A larger number of patients and a longer follow-up will be assessed in ongoing studies.

5

5 Conclusion

This study demonstrates two main findings with relevant implications for alignment strategies in RaTKA.

First, due to strict adherence to a standardized FA protocol with clearly defined balancing targets, it is possible only a subset of patients to achieve accurate restoration of native bony anatomy in both coronal and sagittal planes. This highlights the intrinsic conflict between achieving soft tissue balance and preserving anatomical bony alignment—particularly in FA, which avoids soft tissue release and prioritizes gap symmetry.

Second, patients in whom all three radiological parameters (aHKA, PCOR, CDI) remained within predefined limits showed significantly better early functional outcomes, including OKS, EQ-5D, EQ-VAS, and ROM. Notably, even a single deviation from these thresholds was associated with inferior outcomes.

These results confirm the initial hypothesis that precise multiplanar anatomical reconstruction correlates with superior functional recovery.

To the best of our knowledge, this is the first study to systematically correlate early clinical outcomes with a combined assessment of coronal and sagittal alignment parameters following robotic-assisted TKA performed using a functional alignment approach.

These findings raise the question whether a more bony anatomy-oriented strategy—potentially accepting minor asymmetries in soft tissue balance—may allow for more consistent restoration of native joint geometry. Future studies with larger patient number and longer follow-up need to be awaited before a final conclusion can be made.

Author contributions according to CRediT taxonomy

a. Conceptualization: CG, HG, RvE

b. Data curation: CG, LF, PS, SH

c. Formal analysis: CG, LF, PS, SH

d. Funding acquisition: RvE

e. Investigation: CG, LF, PS, SH, RvE

f. Methodology: CG, RvE

g. Project administration: CG, RvE

h. Resources: CG, RvE

i. Software:

j. Supervision: CG, RvE

k. Validation: CG, RvE

l. Visualization: CG, LF, PS, SH

m. Writing – original draft: CG, LF, PS, SH, HG

n. Writing – review & editing: CG, HG, RvE.

Data availability statement

Data is available on reasonable request by contacting the corresponding author.

Permission to reproduce material from other sources

Not applicable.

Ethical statement

Written informed consent was obtained from all individual participants included in the study. The study was approved by the Ethics Committee of the TUM Klinikum rechts der Isar, Munich (409/20S-KH)

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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