Robot‑assisted knee surgery: precision without superiority in joint line–patella restoration

. Fellow

CarlosPeñaherrera-Carrillo1Emailcarlospenaherrerac@gmail.com

SusanaCabrera-Ávila2Emailsussieca@gmail.com

Fellow2

FranciscoEndara3

Urresta.Specialist3

inOrthopedics3Emailfren9123@hotmail.com

Traumatology.1

. Resident in

AlejandroBarros-Castro4

Orthopedics4

Traumatology.1

. Fellow

EduardoDurán-Arce1Emaileduardo_duran2@hotmail.com

. Fellow

AlejandroGuillermoGallegos-Tejeda1Emailalejandroxbc27@gmail.comEmailalexgalle994@gmail.com

Director

CarlosJavierPineda5Emailepineda@inr.gob.mx

CarlosSuarez-Ahedo6,7✉Emaildrsuarezahedo@gmail.com

1in Adult Hip and Knee ReconstructionNational Rehabilitation Institute of MexicoMexico CityMexico

2National Rehabilitation Institute of MexicoMexico CityMexico

Arthros Clinic. Quito-Ecuador

4Metropolitan HospitalInternational University of Ecuador

5general of National Rehabilitation Institute of MexicoMexico CityMexico

6Adult Hip and Knee Reconstruction DepartmentNational Rehabilitation Institute of MexicoMexico CityMexico

7Calzada México-Xochimilco #289, Colonia Arenal de GuadalupeAlcaldía Tlalpan14389

+525519513526

AUTHORS

Carlos Peñaherrera-Carrillo. Fellow in Adult Hip and Knee Reconstruction. National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: carlospenaherrerac@gmail.com. ORCID: 0000-0002-1474-5295

Susana Cabrera-Ávila. Fellow in Articular Surgery. National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: sussieca@gmail.com. ORCID: 0009-0000-2170-0768

Francisco Endara Urresta. Specialist in Orthopedics and Traumatology. Arthros Clinic. Quito-Ecuador. Email: fren9123@hotmail.com. ORCID: 0000-0002-7799-124X

Alejandro Barros-Castro. Resident in Orthopedics and Traumatology. Metropolitan Hospital. International University of Ecuador. Quito-Ecuador. Email: alejandroxbc27@gmail.com. ORCID: 0000-0001-8480-9218

Eduardo Durán-Arce. Fellow in Adult Hip and Knee Reconstruction. National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: eduardo_duran2@hotmail.com. ORCID: 0009-0007-3198-5075

Alejandro Guillermo Gallegos-Tejeda. Fellow in Adult Hip and Knee Reconstruction. National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: alexgalle994@gmail.com. ORCID: 0000-0003-2408-1143

Carlos Javier Pineda Villaseñor. Director general of National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: epineda@inr.gob.mx. ORCID: 0000-0003-0544-7461

Carlos Suarez-Ahedo*. Adult Hip and Knee Reconstruction Department. National Rehabilitation Institute of Mexico. Mexico City, Mexico. Email: drsuarezahedo@gmail.com. ORCID: 0000-0001-9766-2411

*Corresponding author.

Email: drsuarezahedo@gmail.com (C. Suarez-Ahedo)

Address: Calzada México-Xochimilco #289, Colonia Arenal de Guadalupe, Alcaldía Tlalpan. Zip Code: 14389

Author Contribution

**Author:** CPPCContribution: conception of work, data curation, research, formal analysis, drafting work, critically revised work for intellectual content, final approval for publication, agreement of accountability**Author:** MSCAContribution: conception of work, data curation, research, drafting work, final approval for publication, and agreement of accountability**Author:** FEUContribution: conception of work, research, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability**Author:** AXBCContribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability**Author:** EDAContribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability**Author:** AGGTContribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability**Author:** CSAContribution: conception of work, critically revised work for intellectual content, major revisions for intellectual content, final approval for publication, agreement of accountability**Author:** CJPVContribution: conception of work, critically revised work for intellectual content, major revisions for intellectual content, final approval for publication, agreement of accountability

Phone number: +525519513526

Contribution: conception of work, data curation, research, formal analysis, drafting work, critically revised work for intellectual content, final approval for publication, agreement of accountability

Author

María Susana Cabrera Ávila

Contribution: conception of work, data curation, research, drafting work, final approval for publication, and agreement of accountability

Author

Francisco Endara Urresta

Contribution: conception of work, research, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability

Author

Alejandro Xavier Barros Castro

Contribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability

Author

Eduardo Durán-Arce

Contribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability

Author

Alejandro Guillermo Gallegos-Tejeda

Contribution: conception of work, drafting work, critically revised work for intellectual content, final approval for publication, and agreement of accountability

Author

Carlos Enrique Suárez Ahedo

Contribution: conception of work, critically revised work for intellectual content, major revisions for intellectual content, final approval for publication, agreement of accountability

Author

Carlos Javier Pineda Villaseñor

Contribution: conception of work, critically revised work for intellectual content, major revisions for intellectual content, final approval for publication, agreement of accountability

Conflict of interest

None of the authors declare any conflicts of interest.

Financial funding

None of the authors declare any financial funding.

Robot‑assisted knee surgery: precision without superiority in joint line–patella restoration

Abstract

Materials and Methods

A retrospective study including 600 consecutives primary TKAs performed from 2015 to 2024 was conducted. Patients were allocated into robotic (n = 300) and manual (n = 300) groups. All procedures were performed by the same arthroplasty team using a standardized surgical protocol and identical prosthesis model. Radiographic assessment included femorotibial mechanical axis and patellar orientation at a minimum of 12 months. Alignment was considered adequate when the absolute angular discrepancy was ≤ 2°. Statistical analyses included χ² tests, Student’s t-tests, and equivalence testing with the Two One-Sided Tests (TOST) method. Results: Baseline demographics were comparable between groups. All knees achieved alignment within the ≤ 2° tolerance (100% vs. 100%). Mean angular discrepancy showed no significant differences (manual 0.52° vs. robotic 0.48°; p = 0.37). The robotic technique achieved a higher rate of exact matches (64% vs. 52%), while both remained within clinically accepted limits. Equivalence and non-inferiority analyses confirmed statistically and clinically equivalent outcomes between techniques. Conclusions: Robot-assisted TKA provides greater geometric precision; however, this advantage does not translate into measurable clinical or radiographic superiority when the manual technique is performed under a standardized protocol by experienced surgeons. Both methods demonstrated equivalent performance in restoring mechanical alignment and patellofemoral relationships.

Level of Evidence

III. Retrospective comparative study.

Keywords:

Arthroplasty, Replacement, Knee

Robotics

Knee Joint

Patella

Radiographic Image Interpretation, Computer-Assisted

Robot‑assisted knee surgery: precision without superiority in joint line–patella restoration

Introduction

Knee osteoarthritis (KOA) is a common condition in older adults due to progressive wear and destruction of articular cartilage, and is a degenerative joint disease resulting from many factors. As a result of factors such as increased life expectancy and obesity, its prevalence continues to rise. Depending on the source, prevalence estimates range from 10% to 13%, with a 40% prevalence in patients entering their seventh decade (1). It is estimated that KOA will affect 78.4 million Americans by 2040 (2). The prevalence of symptomatic gonarthrosis is estimated at 44.7%. (3) According to the Mexican government, the prevalence rate is 10.5%, with females predominating (11.7%) and males (8.71%). (4) A patient with KOA experiences pain, swelling, stiffness, and limitations in daily life. (1)

Treatment is determined by the severity of symptoms and the degree of joint wear, classified according to Kellgren–Lawrence (5). Among the nonsurgical and surgical options, total knee arthroplasty (TKA) is indicated in patients with severe degeneration and significant symptoms (6).

The number of TKAs performed in the United States has increased by 134% over 20 years. (7) Further studies predict that primary TKAs will increase by 139% by 2040 and by 469% by 2060. (7–9)

Despite being widely performed, well accepted, safe, and cost-effective, patient satisfaction rates remain between 82% and 89%. Dissatisfaction is caused by a variety of factors, including malalignment, incorrect prosthesis indication, soft-tissue imbalance, instability, high preoperative expectations, and altered joint line and patellar height (PH). (10–12)

After TKA, any change in the joint line affects the biomechanics. (13) This changes the center of rotation, the isometry of the medial collateral ligament (MCL), resulting in midflexion instability. (14, 15)

Furthermore, JL elevation reduces posterior condylar offset, negatively affecting flexion angle and extensor mechanism force. A reported postoperative JL elevation after primary TKA ranges between 1.1 and 5.6 millimeters. (16, 17)

Studies suggest functional impairments occur when JL elevation exceeds 3 to 5 millimeters compared with preoperative values. (18)

In response to dissatisfaction rates, robotic surgery has emerged as a potential solution. (19) Robotic knee arthroplasty (rTKA) has been shown to increase procedural precision. In comparison with conventional techniques, it achieves near-anatomical results in joint‑line position and has been reported to yield better functional outcomes. (20–24)

Because evidence remains limited, this investigation was undertaken to examine rTKA, its relationship with joint‑line height and patellar position, and its impact on medium‑term functional outcomes.

Materials and Methods

A retrospective study comparing robot-assisted (rTKA) and conventional manual knee arthroplasty techniques was performed. The study period was January 2015 to December 2024, at a single high-specialty hospital.

Population and Inclusion Criteria

Three hundred consecutive primary TKAs were included in each group (total = 600), all performed by the same surgical team:

Robotic group (n = 300): robot navigation and execution system-assisted.

Manual group (n = 300): conventional intramedullary/extramedullary mechanical guides.

Inclusion criteria: patients with primary knee osteoarthritis (Kellgren–Lawrence grade III or IV), tricompartmental disease, elective TKA indication, and a minimum radiographic follow‑up of 12 months. Exclusion criteria: prior peri‑articular fracture, revision surgery, non‑standard prosthesis, or deformities beyond 15°.

Ethical Considerations

The protocol was approved by the local Ethics and Research Committee and followed the principles of the Declaration of Helsinki. All patients provided informed consent for the procedure and anonymous use of their clinical data.

Surgical Technique

All surgeries followed a standardized protocol: regional anesthesia, medial parapatellar approach, distal femur and proximal tibia exposure, sequential soft tissue release, and extension/flexion gap balancing.

In the robotic group, a navigation system with intraoperative three‑dimensional mapping, anatomic point registration, and guided bone cuts was used.

In the manual group, cutting was done with standard extramedullary and intramedullary mechanical guides. In both groups, the same postero-stabilized (PS) prosthetic model was implanted, and the same cementing and postoperative rehabilitation protocols were applied.

Radiographic Evaluation and Measurements

Radiographs were obtained at 3, 6, and 12 months, and then annually, with a mean follow‑up of 24 ± 6 months. Measurements were made by two independent observers blinded to the surgical technique, using weight‑bearing anteroposterior and strict lateral radiographs. The following were determined:

Femoro‑tibial mechanical axis (Line Axis, LA).

Postoperative patellar orientation and position.

Absolute angular discrepancy between the two parameters, classified as:

− 0° (exact match),

− 1° (mild deviation),

− 2° (moderate discrepancy, clinically acceptable ≤ 2°).

Alignment was defined as adequate if the absolute discrepancy was ≤ 2°.

Statistical Analysis

Data were analyzed using SPSS v.27 (IBM Corp., Armonk, NY). Continuous variables are presented as mean ± standard deviation (SD) or median [interquartile range], depending on distribution. Categorical variables were compared using χ² test or Fisher’s exact test; continuous variables with Student’s t‑test or Mann–Whitney U test. Equivalence analyses used a predefined margin of ± 10% and bilateral non‑inferiority testing (margin 5%), using the Two One‑Sided Tests (TOST) approach. A p‑value < 0.05 was considered statistically significant.

Results

Patient Flow and Baseline Characteristics

Six hundred consecutive primary TKAs between January 2015 and December 2024 were analyzed, divided equally into robotic and manual groups (n = 300 each). Technique selection depended solely on robotic system availability, rather than on patient clinical characteristics, thereby avoiding indication bias. The same experienced arthroplasty team conducted all surgeries under a standardized protocol (medial parapatellar approach, distal femur/proximal tibia exposure, ligamentous release, gap balance, intra‑operative femoral rotation verification using epicondyles and Whiteside’s line, and final patellofemoral congruence check).

The robotic group used intraoperative 3‑D mapping and guided cuts; the manual group used traditional mechanical guides. The same PS prosthesis model and identical cementing and rehabilitation protocols were used.

Baseline demographics and clinical features were comparable: mean age 67.8 ± 8.9 years in manual vs. 66.5 ± 9.2 years in robotic (p = 0.21); female proportion 62% vs. 59% (p = 0.48); mean BMI 28.6 ± 4.3 vs. 28.9 ± 4.1 kg/m² (p = 0.63); prevalence of comorbidities (diabetes, hypertension, tricompartmental osteoarthritis, varus deformity > 10°) was similar (p > 0.05). Minimum radiographic follow‑up was 12 months, averaging 24 ± 6 months, during which there were no prosthetic loosening, revisions, or major complications influencing postoperative alignment. No patients were lost to follow‑up or excluded after surgery. (Table 1)

Table 1
Baseline characteristics of the cohort
Variable	Manual (n = 300)	Robotic (n = 300)	P Value
Age (years), mean ± SD	67.8 ± 8.9	66.5 ± 9.2	0.21
Sex female, n (%)	186 (62.0)	177 (59.0)	0.48
BMI (kg/m²), mean ± SD	28.6 ± 4.3	28.9 ± 4.1	0.63
Diabetes mellitus, n (%)	47 (15.7)	44 (14.7)	0.74
Hypertension, n (%)	179 (59.7)	182 (60.7)	0.82
Deformity > 10°, n (%)	38 (12.7)	41 (13.7)	0.73
PCL retention (CR), n (%)	300 (100)	300 (100)	–
Patellar component, n (%)	262 (87.3)	258 (86.0)	0.67

Concordance between the femoro‑tibial mechanical axis and post‑operative patellar position

Evaluation of postoperative concordance between the femoro‑tibial mechanical axis (LA) and patellar orientation showed comparable performance in both techniques. Defining adequate alignment as absolute discrepancy ≤ 2°, 100% of knees in both groups achieved this criterion (p = 1.000, Fisher’s exact test), demonstrating that robotic and manual surgeries attain clinically satisfactory patellofemoral alignment. This indicates that within the functionally accepted range (< 2°), the probability of correct alignment is equivalent for both methods. From a clinical and biomechanical perspective, no significant superiority of robotic assistance over manual technique is evident when the exact alignment and balancing principles are followed.

Distribution of Angular Discrepancy

To examine residual angular variability more closely, the absolute difference between the mechanical axis and patellar position was classified: 0° (exact match), 1° (mild deviation), and 2° (moderate discrepancy, still clinically acceptable). In the manual technique group, 52% of cases showed exact coincidence (0°), 44% a deviation of 1°, and 4% a discrepancy of 2°. In the robotic group, 64% had exact coincidence, 24% a 1° deviation, and 12% a 2° discrepancy. (Fig. 1)

Fig. 1

Distribution of angular discrepancy between the femorotibial mechanical axis and patellar position according to the surgical technique. Although the distributions differ in shape, all values remain within the clinical tolerance (≤ 2°).

Although the χ² test identified differences in distribution shape (p < 0.001), all measurements remained within the clinically accepted range for both groups. Mean angular values were similar: manual 0.52° vs. robotic 0.48° (difference = − 0.04°; p = 0.37). Medians were 0° in both groups, with identical IQRs (0–1°), confirming low and equivalent angular dispersion. (Fig. 2)

Fig. 2

Boxplots of absolute discrepancy. Both groups show overlapping medians and low dispersion, with no significant differences (p > 0.05).

Geometrically, the robotic technique showed a more ‘polarized’ pattern, a higher rate of exact matches, but a slight increase in 2° deviations. In contrast, the manual technique concentrated more cases at 1°, suggesting a centralized but equally controlled variability. None of these patterns implied behavior outside the optimal functional alignment range. (Table 2)

Table 2
Postoperative angular outcomes
Variable	Manual (n = 300)	Robotic (n = 300)	Difference (IC 95%)	P Value
Exact match (0°), n (%)	156 (52.0)	192 (64.0)	+ 12.0 (+ 0.8 a + 22.9)	0.0029
Mild deviation (1°), n (%)	132 (44.0)	72 (24.0)	–20.0 (–29.5 a − 10.6)	< 0.001
Moderate discrepancy (2°), n (%)	12 (4.0)	36 (12.0)	+ 8.0 (+ 2.8 a + 13.2)	0.001
Within tolerance (≤ 2°), n (%)	300 (100)	300 (100)	0.0 (–2.1 a + 2.1)	1.000
Mean discrepancy (°) ± DE	0.52 ± 0.63	0.48 ± 0.71	–0.04 (–0.15 a + 0.23)	0.37
Median [IQR] (°)	0 [0–1]	0 [0–1]	–	–

Equivalence and Non‑Inferiority Analysis

An equivalence analysis with a ± 10% margin in the proportion of knees aligned within ± 2° was performed. The 95% confidence interval (CI) for the difference in proportions (0.0%; 95% CI − 2.1% to + 2.1%) lay entirely within the predefined margin, demonstrating both clinical and statistical equivalence between the techniques. (Fig. 3)

Fig. 3

Two-one-sided equivalence test (TOST) for the proportion of alignments within ± 2°. The observed difference (0%) and its 95% CI (–2.1 to + 2.1) lie entirely within the ± 10% margin, confirming clinical equivalence between robotic and manual surgery.

Additionally, a bilateral non‑inferiority analysis (margin 5%) confirmed that neither method was inferior (p < 0.001 for both TOST contrasts), consolidating the conclusion of equivalent performance. Sensitivity analyses—excluding cases with deformities > 10°, BMI > 35 kg/m², or non‑standard prostheses—maintained identical results (100% within ± 2° in both cohorts). (Table 3)

Table 3
Equivalence and non-inferiority analysis
Comparation	Observed difference (%)	Equivalence margin (%)	95% CI of the difference	Result
Proportion within ± 2° (Robotic – Manual)	0.0	± 10	[–2.1, + 2.1]	Equivalent
Idem (margin ± 5%)	0.0	± 5	[–2.1, + 2.1]	Equivalent
Two-sided non-inferiority test (5% margin)	0.0	5	[–2.1, + 2.1]	Non-inferiority demonstrated
Sensitivity analysis (excluding BMI > 35 or deformity > 10°)	0.0	± 10	[–2.4, + 1.8]	Unchanged result
Abbreviation

Clinical Interpretation

Overall, the results demonstrate that under standardized operative conditions and controlled execution, robot‑assisted and conventional manual TKA achieve equivalent patellofemoral alignment. Every case in both cohorts fell within the clinically acceptable tolerance (< 2°), without increased angular dispersion or a higher malalignment rate. Although the robotic technique achieved a greater proportion of exact 0° coincidences, this reflects increased mathematical precision rather than a tangible clinical benefit. The slight variability observed in the manual technique falls within the expected measurement precision of radiographic methods and has no functional consequences. Consequently, evidence suggests that in the hands of experienced surgeons following a reproducible surgical protocol, robot‑assisted TKA does not offer significant clinical advantages over manual technique with respect to mechanical axis alignment or patellofemoral congruence. In summary, both approaches demonstrated equivalent biomechanical and functional behavior, with consistent, reproducible, and clinically satisfactory results, supporting the absence of a significant difference between the two surgical modalities.

Discussion

Robot-assisted total knee arthroplasty (rTKA) has emerged as a technological alternative to the conventional manual technique (mTKA) in advanced gonarthrosis. In our study, both groups achieved mechanical alignment and patellofemoral congruence within the clinically acceptable range, with no significant functional differences between techniques. This finding is consistent with a recent meta-analysis showing that although rTKA achieves better postoperative alignment, it does not translate into clear clinical or functional improvements in the short to mid-term (25–27).

From a biomechanical perspective, accuracy in implant positioning and restoration of the joint line are essential to prevent instability, ligament-muscular imbalance, or alterations in the extensor mechanism. Several studies indicate that rTKA reduces the rate of out-of-range cases in the mechanical axis (HKA) and other complementary implant-related angles (26, 28). However, improvements in precision have not consistently translated into greater satisfaction or increased range of motion at one year postoperatively. This may be explained by the high proficiency achieved by experienced surgeons using the manual technique, or by the influence of other factors (such as soft-tissue balancing, rehabilitation protocols, or patient expectations), which may play a role as important as geometric accuracy.

In the context of severe deformities, altered joint lines, or revision cases, rTKA may offer a more evident advantage. Recent studies support that the greater investment in technology is justified when anatomy presents major challenges or when a minimal margin of error is required (29, 30). For primary procedures without added complexity, however, the equivalent clinical outcomes suggest that the manual technique remains a valid and efficient option.

Methodologically, the current trend in comparing surgical techniques is to use equivalence or non-inferiority designs rather than simply demonstrating superiority. Several studies have emphasized that reproducibility and standardization of the surgical protocol—rather than mere technological adoption—are key to optimizing outcomes (31). This aligns with our findings: the experience of the surgical team, a standardized robotic assistance system, and appropriate patient selection can level the field between both techniques.

Finally, several limitations of our study must be acknowledged. First, the retrospective design reduces the ability to establish causality and may introduce selection bias, although both groups were comparable in baseline variables. Secondly, the follow-up period, although adequate to evaluate functional outcomes and mid-term alignment, does not allow conclusions regarding implant durability or long-term complications. Additionally, the study was conducted in a single center with a single surgical team, which enhances technical homogeneity but limits the generalizability of the findings to settings with different learning curves or technological resources. Cost-effectiveness, operative time, and the robotic learning curve were also not analyzed, despite being decisive factors in clinical implementation. In this sense, although the findings provide internal robustness, they should be interpreted with caution regarding their broader applicability.

Conclusions

Robot-assisted total knee arthroplasty provides superior geometric precision in restoring the joint line and patellofemoral alignment; however, this accuracy does not translate into significant clinical benefits when manual surgery is performed under a standardized protocol by experienced surgeons.

Both techniques demonstrated safety, reproducibility, and equivalent functional outcomes, confirming the clinical non-inferiority of the manual technique compared with the robotic one.

The use of assisted technology should be reserved for cases with high anatomical complexity or severe deformities, prioritizing treatment individualization and optimization of surgical resources.

References

Hsu H, Siwiec RM, Knee O (2023) Jun 26. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan–. PMID: 29939661

Hootman JM, Helmick CG, Barbour KE et al (2016) Updated projected prevalence of self-reported doctor-diagnosed arthritis and arthritis-attributable activity limitation among US adults, 2015–2040. Arthritis Rheumatol Hoboken NJ 68:1582–1587

Murphy L, Schwartz TA, Helmick CG et al (2008) Lifetime risk of symptomatic knee osteoarthritis. Arthritis Rheum 59:1207–1213

Espinosa MR, Arce SCA, Cajigas MJC, Esquivel VJA, Gutiérrez GJJ, Martínez HJL et al (2013) Reunión multidisciplinaria de expertos en diagnóstico y tratamiento de pacientes con osteoartritis. Actualización basada en evidencias. Med Int Mex 29(1):67–92

Kellgren J, Lawrence J (1957) Radiological Assessment of Osteo-Arthrosis. Ann Rheum Dis 16(4):494–502. 10.1136/ard.16.4.494

Aweid O, Haider Z, Saed A, Kalairajah Y (2018 May-Aug) Treatment modalities for hip and knee osteoarthritis: A systematic review of safety. J Orthop Surg (Hong Kong) 26(3):2309499018808669

Home | Agency for Healthcare Research and Quality (2022) https://www.ahrq.gov/ (Accessed 20 Nov

Shichman I, Roof M, Askew N, Nherera L, Rozell JC, Seyler TM, Schwarzkopf R (2023) Projections and Epidemiology of Primary Hip and Knee Arthroplasty in Medicare Patients to 2040–2060. JB JS Open Access. ;8(1):e22.00112. 10.2106/JBJS.OA.22.00112. PMID: 36864906; PMCID: PMC9974080

Kahlenberg CA, Nwachukwu BU, McLawhorn AS, Cross MB, Cornell CN, Padgett DE (2018) Patient satisfaction after total knee replacement: a systematic review. HSS J 14:192–201

10.

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

11.

Lording T, Lustig S, Neyret P (2017) Coronal alignment after total knee arthroplasty. EFORT Open Rev 1:12–17

12.

Matsuda S, Kawahara S, Okazaki K, Tashiro Y, Iwamoto Y (2013) Postoperative alignment and ROM affect patient satisfaction after TKA. Clin Orthop Relat Res 471:127–133

13.

van Lieshout KP, van Koen E-J, van Gino G (2018) The negative effect of joint line elevation after total knee arthroplasty on outcome. Knee Surgery, Sports Traumatology, Arthroscopy. ;27(5):1477–86

14.

Luyckx T, Vandenneucker H, Ing LS, Vereecke E, Ing AV, Victor J (2018) Raising the Joint Line in TKA is Associated With Mid-flexion Laxity: A Study in Cadaver Knees. Clin Orthop Relat Res 476(3):601–611

15.

Georg Matziolis, Brodt S, Windisch C, Roehner E (2017) Changes of posterior condylar offset results in midflexion instability in single-radius total knee arthroplasty. Arch Orthop Trauma Surg 137(5):713–717

16.

Selvarajah E, Hooper G (2009) Restoration of the Joint Line in Total Knee Arthroplasty. J Arthroplast 24(7):1099–1102

17.

Snider MG, MacDonald SJ (2009) The Influence of the Posterior Cruciate Ligament and Component Design on Joint Line Position After Primary Total Knee Arthroplasty. J Arthroplast 24(7):1093–1098

18.

Koshire S, Mohanty SS, Keny SA, Rai AK, Rathod TN, Kamble P (2022) The influence of joint line restoration on functional outcome after primary total knee arthroplasty: A prospective study. J Clin Orthop Trauma 34:102023

19.

St Mart JP, Goh EL (2021) The current state of robotics in total knee arthroplasty. EFORT Open Rev 6(4):270–279. 10.1302/2058-5241.6.200052PMID: 34040804; PMCID: PMC8142057

20.

Agrawal VO, Gadekar AP, Vaidya N (2022) Does robotic technology successfully restore the joint line after total knee arthroplasty? A retrospective analysis. Arthroplasty. ;4(1)

21.

Gaillard R, Bankhead C, Budhiparama NC, Cécile Batailler E, Servien LS (2019) Influence of Patella Height on Total Knee Arthroplasty: Outcomes and Survival. J Arthroplasty 34(3):469–477

22.

Nakano N, Kuroda Y, Masanori Tsubosaka T, Kamenaga, Ishida K, Hayashi S et al (2023) The influence of patellar height on patellofemoral contact force during total knee arthroplasty. J Joint Surg Res 1(1):186–191

23.

Jobe Shatrov M, Khasian, Lording T, Monk AP, Parker D, Lustig S (2024) Robotic assessment of patella tracking in total knee arthroplasty. J ISAKOS Joint Disorders Orthop Sports Med 9(5):100287–100287

24.

Mayne AI, Harshadkumar Rajgor C, Munasinghe, Agrawal Y, Pagkalos J, Davis ET et al (2024) The ROSA robotic-arm system reliably restores joint line height, patella height and posterior condylar offset in total knee arthroplasty. Knee 48:1–7

25.

Alrajeb R, Zarti M, Zakaria Shuia O, Alzobi, Ahmed G, Aissam E Robotic-assisted versus conventional total knee arthroplasty: a systematic review and meta-analysis of randomized controlled trials. Eur J Orthop Surg Traumatol. 2023;PubMed

26.

Riantho A, Christian J, Fidiasrianto K, Elson E, Irvan I, Handy H et al (2023) Radiographic Outcomes of Robot-Assisted Versus Conventional Total Knee Arthroplasty, vol 8. JB & JS Open Access, 2

27.

Fu X, She Y, Jin G, Liu C, Liu Z, Li W et al (2024) Comparison of robotic-assisted total knee arthroplasty: an updated systematic review and meta-analysis. J Robotic Surg. ;18(1)

28.

Sun C, Ma Q, Zhang X et al (2025) Improved alignment accuracy but similar early clinical outcomes with NAVIO imageless robotic-assisted vs. conventional total knee arthroplasty: a meta-analysis. J Orthop Surg Res 20:619. https://doi.org/10.1186/s13018-025-06013-6

29.

Xing P, Qu J, Feng S et al (2024) Comparison of the efficacy of robot-assisted total knee arthroplasty in patients with knee osteoarthritis with varying severity deformity. J Orthop Surg Res 19:872. https://doi.org/10.1186/s13018-024-05372-w

30.

Chen J, Loke RWK, Lim KKL et al (2025) Survivorship in robotic total knee arthroplasty compared with conventional total knee arthroplasty: A systematic review and meta-analysis. Arthroplasty 7:21. https://doi.org/10.1186/s42836-025-00304-3

31.

Ümit M, Khasawneh Moh’dY, Ghandour M, Zuabi AA, Horst K, Hildebrand F et al (2025) Comparative Efficacy and Precision of Robot-Assisted vs. Conventional Total Knee Arthroplasty: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. J Clin Med J Clin Med 14:3249. https://doi.org/10.3390/jcm14093249

Tables

standard deviation

BMI

body mass index

PCL

posterior cruciate ligament

cruciate retaining

confidence interval

Yes

Abstract

Introduction: Robot-assisted total knee arthroplasty (rTKA) has been proposed to improve precision in implant positioning and joint line restoration compared with manual TKA (mTKA). However, it remains unclear whether this increased accuracy results in superior functional or radiographic outcomes. This study aimed to compare mechanical alignment and patellofemoral restoration between robotic and manual techniques. Materials and Methods: A retrospective study including 600 consecutives primary TKAs performed from 2015 to 2024 was conducted. Patients were allocated into robotic (n=300) and manual (n=300) groups. All procedures were performed by the same arthroplasty team using a standardized surgical protocol and identical prosthesis model. Radiographic assessment included femorotibial mechanical axis and patellar orientation at a minimum of 12 months. Alignment was considered adequate when the absolute angular discrepancy was ≤2°. Statistical analyses included χ² tests, Student’s t-tests, and equivalence testing with the Two One-Sided Tests (TOST) method. Results: Baseline demographics were comparable between groups. All knees achieved alignment within the ≤2° tolerance (100% vs. 100%). Mean angular discrepancy showed no significant differences (manual 0.52° vs. robotic 0.48°; p=0.37). The robotic technique achieved a higher rate of exact matches (64% vs. 52%), while both remained within clinically accepted limits. Equivalence and non-inferiority analyses confirmed statistically and clinically equivalent outcomes between techniques. Conclusions: Robot-assisted TKA provides greater geometric precision; however, this advantage does not translate into measurable clinical or radiographic superiority when the manual technique is performed under a standardized protocol by experienced surgeons. Both methods demonstrated equivalent performance in restoring mechanical alignment and patellofemoral relationships.