Deviation from Native Posterior Tibial Slope and Dose‒Response Relationships with Forgotten Joint Score-12 in Robot-Assisted Total Knee Arthroplasty: A Retrospective Study

Deviation from Native Posterior Tibial Slope and Dose‒Response Relationships with Forgotten Joint Score-12 in Robot-Assisted Total Knee Arthroplasty: A Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Deviation from Native Posterior Tibial Slope and Dose‒Response Relationships with Forgotten Joint Score-12 in Robot-Assisted Total Knee Arthroplasty: A Retrospective Study Chen Boyi, Jing Lin, Zhang Hongmei, Yan Qi, Li Yuanyuan, Liu Siye, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9392901/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract Background Under the premise of high-precision osteotomy enabled by robot-assisted total knee arthroplasty (TKA), this study compared functional outcomes between a population-wide optimal posterior tibial slope (PTS) target and individualized restoration of the native anatomical PTS. It also quantified the dose‒response relationship between PTS deviation from the native angle and the Forgotten Joint Score-12 (FJS-12). Methods This retrospective analysis included 240 patients who underwent primary unilateral TKA in our hospital from August 2021 to June 2024. Patients were divided into conventional and robot-assisted groups (120 patients each) according to surgical method. All patients received the same brand of posterior-stabilized prosthesis. The PTS was measured on pre- and postoperative CT scans, and the osteotomy error (|actual PTS – target PTS|) was calculated. At the 1-year follow-up, the primary outcomes were the maximum active flexion angle and FJS-12 score; the secondary outcomes included the Knee Society Score, Oxford Knee Score, WOMAC score, anterior knee pain VAS score, tibial anterior translation distance, and complication rate. Multivariate linear and quadratic regression models were used to assess associations between postoperative PTS and clinical function, adjusting for age, sex, BMI, and preoperative flexion. Results Baseline characteristics were comparable between the groups (P > 0.05). The incidence of osteotomy error was significantly lower in the robot-assisted group (P < 0.05). At 1 year, the robot-assisted group achieved greater maximum flexion (121.5° ± 9.2° vs 118.3° ± 10.1°) and FJS-12 (68.7 ± 15.8 vs 64.2 ± 16.3) than did the conventional group (both P < 0.05). Multivariate regression revealed a positive linear correlation between postoperative PTS and maximum flexion (β = 1.9, 95% CI 1.2–2.6, P < 0.05) and a significant quadratic (inverted U-shaped) relationship between PTS and FJS-12, peaking at approximately 5.3°. Subgroup analysis indicated that patients with |actual PTS – native PTS| ≤ 2° had markedly higher FJS-12 scores than those with > 2° deviation (P < 0.05). Conclusions Under precise osteotomy conditions, the postoperative PTS is nonlinearly associated with subjective functional outcomes, with a population-level optimum of approximately 5.3°. For patients whose native PTS approximates this value, population-based and individualized targets converge; however, greater PTS deviation from native anatomy independently impairs FJS-12 scores, suggesting that individualized native PTS restoration is prioritized to improve patient satisfaction. These findings warrant validation in prospective randomized controlled trials. Total knee arthroplasty Posterior tibial slope Robot-assisted surgery Forgotten joint score Individualized reconstruction Regression analysis Introduction In modern artificial joint surgery, the ultimate clinical goal of total knee arthroplasty (TKA) has evolved from simply pursuing prosthesis survival to achieving excellent functional recovery and patient satisfaction. Although prosthesis design and surgical techniques have matured, approximately 15–20% of patients remain dissatisfied with their prognosis. This “subjective dissatisfaction” is typically attributed to loss of proprioception, limited flexion, or heightened self-awareness during joint motion (i.e., “foreign body sensation”) [ 1 ]. Among the parameters regulating postoperative kinematics, the posterior tibial slope (PTS) has emerged as a core research focus because of its decisive role in flexion-gap capacity, the femoral rollback trajectory, and extension-flexion balance. PTS is defined as the posterior tilt angle of the tibial plateau relative to the tibial mechanical axis in the sagittal plane. Previous biomechanical studies have shown that a moderate PTS increase effectively enlarges the flexion gap and improves the knee range of motion (ROM); however, excessive posterior tilt may reduce mid-flexion stability and increase the risk of prosthesis wear and loosening, whereas insufficient PTS reconstruction often leads to a tight flexion gap and restricted motion [ 2 , 3 ]. Therefore, precise intraoperative PTS reconstruction is critical for optimizing postoperative function. In conventional TKA, the PTS relies heavily on mechanical guidance and surgeon experience and is markedly affected by anatomical variation, frequently resulting in significant osteotomy deviation. Robot-assisted total knee arthroplasty (RATKA) substantially improves osteotomy accuracy through digital modeling and haptic limiting technology; this advantage has been widely confirmed [ 4 ]. However, even when the technical precision reaches submillimeter levels, the optimal PTS target remains controversial: should a biomechanically derived population-optimal angle be pursued, or should native anatomy be individually reconstructed? Moreover, whether PTS reconstruction deviation independently influences patients’ subjective functional experience has not been systematically investigated. With the increasing importance of patient-reported outcome measures (PROMs) in joint surgery evaluation, the Forgotten Joint Score-12 (FJS-12) has become a key indicator of TKA postoperative function. By quantifying how often patients “forget” the artificial joint in daily life, the FJS-12 is considered more sensitive than traditional scores for detecting proprioceptive recovery and psychological integration. Therefore, on the basis of a retrospective cohort, this study aims to elucidate the dose‒response relationship between PTS reconstruction accuracy and FJS-12 scores and to explore whether the precision boundary provided by robotic technology can substantially improve patients’ postoperative subjective “forgotten” experience by precisely restoring the individualized native PTS and crossing the minimal clinically important difference (MCID) threshold. Methods Study Design This investigation adhered to a single-center retrospective cohort design and was approved by the hospital’s ethics committee. Patient data from patients who underwent primary unilateral TKA from August 2021 to June 2024 were retrospectively analyzed. Inclusion criteria (1) Primary knee osteoarthritis with Kellgren–Lawrence grade III–IV [ 5 ]; (2) primary unilateral TKA; (3) age 50–80 years; (4) preoperative flexion contracture < 15°; (5) complete preoperative and postoperative imaging follow-up data. Exclusion criteria (1) History of ipsilateral knee surgery; (2) inflammatory arthropathy (e.g., rheumatoid arthritis); (3) severe osteoporosis or neuromuscular disease; (4) posterior cruciate ligament (PCL) insufficiency; (5) missing follow-up data. A total of 240 patients met the inclusion criteria and were included. Surgical technique The enrolled patients were divided into a conventional group (n = 120) and a robot-assisted group (n = 120). Grouping decisions were based on patients’ personal preferences and the availability of intraoperative resources; patients in the robot-assisted group actively chose to undergo the robot-assisted surgery system (RATKA), while the remaining patients entered the conventional surgery control group. This study was a nonrandomized retrospective study. All surgeries were performed by the same senior joint surgery team. A midline knee incision and the medial parapatellar approach were used uniformly [ 6 ]. Femoral osteotomy was completed with intramedullary guidance and a preset external rotation angle of 3° [ 7 ]. For tibial osteotomy, standard extramedullary positioning instruments were used for osteotomy in the conventional group. The robot-assisted group utilized the robotic navigation system to complete preoperative three-dimensional digital modeling and personalized planning, and under real-time optical navigation feedback during surgery, the haptic limiting technology of the robotic arm was used to precisely execute the osteotomy plan [ 8 ]. Both groups of patients received the same brand of posterior-stabilized (Posterior-Stabilized, PS) prosthesis, which was fixed with bone cement for biological fixation. Postoperative Rehabilitation Both groups followed a standardized perioperative pathway, including multimodal analgesia and routine thromboprophylaxis [ 9 ]. Quadriceps isometric exercises began on postoperative day 1; partial weight-bearing with a walker started on day 2. Progressive ROM training was supervised by rehabilitation therapists thereafter. Outcome Measures Primary outcome measures Maximum active knee flexion angle and FJS-12 score at 1 year post-operatively. Flexion angle measurement: The measurement was performed independently by two senior physicians who did not participate in the surgery via a standard goniometer (range 0–180°, precision 1°). During measurement, the subject was placed in the supine position, and the affected knee was actively flexed to the limit angle, with the readings recorded. For each patient, each of the two physicians repeated the measurement 3 times; the mean of each physician’s measurements was taken, and then the average between the two physicians was calculated as the final outcome data. Reliability testing: To verify the consistency of the measurements, 30 cases were randomly selected (approximately 12.5% of the total number of follow-up cases). The above two physicians performed independent measurements after a 1-week interval. The intraclass correlation coefficient (ICC) was used to assess test‒retest reliability. According to the evaluation criteria, an ICC value > 0.75 indicates good reliability, whereas 0.50–0.75 indicates moderate reliability. Forgotten Joint Score: The Chinese version of the FJS-12 scale was used to evaluate postoperative proprioceptive recovery. The scale contains 12 items, with a total score ranging from 0 to 100 points. A higher score indicates lower postoperative joint awareness, that is, a better “forgotten” state. The FJS-12 has been validated in multiple cultural backgrounds, demonstrating excellent reliability and validity with a lower ceiling effect; its minimal clinically important difference (MCID) is defined as 13.7–16.6 points. Secondary outcome measures KSS, OKS, WOMAC index, anterior knee pain VAS, tibial anterior translation (stability), and perioperative/follow-up complication rates. Assessment of Osteotomy Accuracy The actual PTS was measured on postoperative CT. Osteotomy error (absolute error) = |actual PTS – target PTS|, with the target PTS determined from preoperative digital planning. Statistical Analyses IBM SPSS 26.0 was used. Continuous variables are presented as the means ± SDs and were compared with independent-samples t tests; categorical variables are presented as frequencies (percentages) and were compared with χ² tests or Fisher’s exact tests. P < 0.05 was considered statistically significant. Propensity score matching (PSM): To balance baseline covariates between groups and reduce selection bias, PSM was performed at a 1:1 ratio to match the conventional and robot-assisted groups [ 10 ]. The propensity score model included age, sex, BMI, preoperative KSS score, preoperative flexion angle, degree of preoperative deformity, and preoperative native posterior tibial slope. Nearest-neighbor matching was used, with the caliper value set at 0.02. Balance after matching was assessed via the standardized mean difference (SMD), with SMD < 0.10 considered indicative of good balance between groups. Minimal clinically important difference (MCID): This study introduced the MCID as the threshold for clinical efficacy evaluation to distinguish statistical significance from clinical relevance. In accordance with previous studies, the MCID for FJS-12 was set at 12 points [ 11 ], and the MCID for the maximum active knee flexion angle was set at 5°. Core variable construction and regression analysis: To quantitatively evaluate the effect of deviation between actual osteotomy values and anatomical morphology on postoperative function, the core index deviation (Deviation) was calculated as Deviation = |Actual PTS − Native PTS|. Multivariate linear regression was used to analyze the influencing factors of functional outcomes, with the FJS-12 score as the dependent variable. The independent variables of the model included (1) actual postoperative PTS (containing both linear and quadratic terms to capture potential nonlinear effects); (2) deviation (continuous variable); and (3) covariates (age, sex, BMI, preoperative flexion angle, and surgical method). The partial regression coefficients (β) and their significance levels for each variable were used to explore the independent contributions of “population-wide target value” and “individualized native restoration” to patients’ subjective “forgotten” joint experience [ 12 ]. Sensitivity analysis: To further assess the potential independent interference of coronal alignment on clinical function and to verify the robustness of the model conclusions, postoperative lower-limb alignment deviation (the absolute value of the HKA angle deviation from the neutral position) was added as an additional control variable into the regression equation for sensitivity analysis [ 13 ]. Reliability testing: The intraclass correlation coefficient (ICC) was used to evaluate the test-retest reliability of knee flexion angle measurements, with an ICC > 0.75 considered indicative of good reliability [ 14 ]. Results Patient Demographics There were no significant differences in age, sex, BMI, preoperative flexion, KSS score, OKS score, WOMAC score, deformity, or native PTS (all P > 0.05) among the 240 patients (120 per group) (Table 1 ). Table 1 Patient baseline characteristics (mean ± SD) Indicator Conventional(n = 120) Robot-assisted(n = 120) t/χ² P Age(years) 67.5 ± 7.9 67.9 ± 8.1 0.38 0.704 Sex(male/female) 48/72 52/68 0.27 0.603 BMI(kg/m²) 27.4 ± 3.7 27.7 ± 3.8 0.62 0.536 Preoperative flexion(°) 108.3 ± 10.5 109.1 ± 10.8 0.58 0.562 Preoperative KSS 48.3 ± 12.1 49.0 ± 12.5 0.44 0.660 Preoperative OKS 24.2 ± 5.5 24.6 ± 5.8 0.55 0.583 Preoperative WOMAC 52.5 ± 11.3 53.1 ± 11.8 0.40 0.689 Preoperative deformity(°) 8.6 ± 3.7 8.9 ± 3.9 0.61 0.542 Native PTS(°) 6.1 ± 2.3 6.3 ± 2.4 0.66 0.510 Osteotomy Accuracy The preoperative target PTS did not differ significantly (5.8° ± 1.2° vs 6.1° ± 1.3°, P = 0.065). The actual postoperative PTS was 6.8° ± 2.5° (conventional) vs 6.5° ± 1.8° (robot-assisted) (P = 0.290). The absolute error was 2.8° ± 1.6° vs 1.2° ± 0.9° (t = 9.46, P < 0.001) (Table 2 ). Table 2 Osteotomy accuracy comparison (mean ± SD) Indicator Conventional(n = 120) Robot-assisted(n = 120) t P Target PTS(°) 5.8 ± 1.2 6.1 ± 1.3 1.85 0.065 Actual PTS(°) 6.8 ± 2.5 6.5 ± 1.8 1.06 0.290 Osteotomy error(°) 2.8 ± 1.6 1.2 ± 0.9 9.46 < 0.001 Reliability of the Flexion Angle Measurement For 30 patients, the interrater ICC was 0.89 (95% CI: 0.82–0.94); the intrarater ICCs were 0.92 (Physician A) and 0.91 (Physician B) (Table 3 ). Table 3 Flexion angle measurement reliability Reliability type ICC 95% CI Rating Interrater 0.89 0.82–0.94 Good Intrarater (Physician A) 0.92 0.86–0.96 Good Intrarater (Physician B) 0.91 0.85–0.95 Good Clinical functional outcomes at 1 year post-surgery The robot-assisted group had greater maximum flexion (121.5° ± 9.2° vs 118.3° ± 10.1°, P = 0.011) and FJS-12 (68.7 ± 15.8 vs 64.2 ± 16.3, P = 0.030) values. No significant differences were found in the KSS, OKS, WOMAC, tibial translation score, or anterior knee pain VAS score (all P > 0.05) (Table 4 ). Table 4 1-year clinical outcomes (mean ± SD) Indicator Conventional(n = 120) Robot-assisted(n = 120) t P Maximum flexion (°) 118.3 ± 10.1 121.5 ± 9.2 2.55 0.011 FJS-12 64.2 ± 16.3 68.7 ± 15.8 2.18 0.030 KSS 85.3 ± 11.5 86.9 ± 11.8 1.06 0.290 OKS 40.1 ± 5.8 41.3 ± 5.9 1.58 0.115 WOMAC 19.8 ± 8.7 18.5 ± 8.4 1.18 0.239 Tibial anterior translation (mm) 5.6 ± 2.0 5.4 ± 1.9 0.80 0.424 Anterior knee pain VAS 1.4 ± 1.7 1.3 ± 1.6 0.47 0.639 Multivariate linear regression After adjusting for age, sex, BMI, and preoperative flexion, (1) PTS and flexion were positively linearly correlated (β = 1.9, 95% CI: 1.2–2.6, P = 0.008). (2) PTS and FJS-12: quadratic relationship (quadratic term β = − 0.95, 95% CI: − 1.58 to − 0.32, P = 0.012); peak at PTS = 5.3°. (3) Deviation and FJS-12 score: negative correlation (β = − 2.4, 95% CI: − 3.8 to − 1.0, P = 0.006). (4) Sensitivity analysis for lower-limb alignment deviation (HKA): Postoperative HKA deviation was included in the model as an additional covariate. The results revealed that a quadratic relationship between actual PTS and the FJS-12 score (β = -0.89, P = 0.018) and a negative correlation between deviation and the FJS-12 score (β = -2.1, P = 0.012) still existed. In addition, HKA deviation was negatively correlated with the FJS-12 score (β = -1.8, 95% CI: -3.1 to -0.5, P = 0.009). Since the intraoperative soft-tissue pressure distribution was not quantified, this factor was not included in the model. (5) Group differences did not exceed MCID thresholds (flexion difference 3.2° < 5° MCID; FJS-12 difference 4.5 points < 12 points MCID). Subgroup analysis: stratified influence of PTS deviation (Δ) The Δ ≤ 2° group (n = 102) had greater FJS-12 scores (71.2 ± 15.6 vs 63.8 ± 16.2, P 2° group (n = 138); there were no differences in flexion, KSS, or tibial translation (Table 5 ). Table 5 Clinical outcomes stratified by the Δ (mean ± SD) Indicator Δ ≤ 2° (n = 102) Δ > 2° (n = 138) t P Maximum flexion (°) 120.8 ± 9.5 119.2 ± 10.0 1.27 0.205 FJS-12 71.2 ± 15.6 63.8 ± 16.2 3.56 < 0.001 KSS 86.5 ± 11.3 85.2 ± 11.9 0.86 0.390 Tibial anterior translation (mm) 5.3 ± 1.8 5.7 ± 2.1 1.56 0.120 In the Δ ≤ 2° group, the proportion of robot-assisted procedures was 87.3% (89/102), whereas the proportion of conventional procedures was 12.7% (13/102); in the Δ > 2° group, the proportion of robot-assisted procedures was 21.7% (30/138), whereas the proportion of conventional procedures was 78.3% (108/138). The difference in the distribution of surgical methods between the groups was statistically significant (χ² = 108.5, P 2° (n = 138) Total χ² P Conventional 13 (12.7) 108 (78.3) 121 108.5 0.05) (Table 7 ). Table 7 Adverse events [n (%)] Event Conventional(n = 120) Robot-assisted(n = 120) χ² P Infection 2 (1.7) 1 (0.8) 0.34 0.560 Deep vein thrombosis 2 (1.7) 2 (1.7) 0.00 1.000 Stiffness 4 (3.3) 3 (2.5) 0.15 0.699 Total 8 (6.7) 6 (5.0) 0.31 0.578 Discussion This retrospective cohort study compared conventional and robot-assisted TKA with respect to PTS reconstruction accuracy and examined the relationship between postoperative PTS and clinical function. Robot-assisted surgery significantly reduced the osteotomy error (1.2° ± 0.9° vs 2.8° ± 1.6°, P < 0.001), which is consistent with prior reports [ 15 , 16 ]. The advantage extends beyond sagittal PTS to coronal alignment, femoral rotation, and soft-tissue balance. Conventional techniques rely on intramedullary or extramedullary references and are strongly affected by anatomical variation, whereas the robotic system achieves higher prosthesis implantation accuracy through preoperative three-dimensional digital modeling and intraoperative real-time optical navigation feedback [ 15 ]. While FJS-12 scores were superior in the robot-assisted group, traditional objective scores (KSS, OKS, and WOMAC) showed no difference, suggesting that robotic benefits are most evident in subjective joint awareness rather than all functional domains [ 12 ]. Regression confirmed an independent PTS contribution to FJS-12 even after HKA adjustment. Notably, owing to the limitations of the retrospective design, this study failed to include dynamic mechanical parameters such as intraoperative soft-tissue pressure distribution in the model, which may constitute a potential confounding factor. The linear relationship between the postoperative PTS and knee flexion range of motion regression analysis revealed that for every 1° increase in the postoperative PTS, the maximum flexion angle increased by approximately 1.9° (β = 1.9). This conclusion validates the regulatory role of the PTS in the knee flexion dimension: increasing the posterior slope can effectively enlarge the flexion gap and reduce posterior bony impingement between the femur and tibia, thereby improving flexion activity. Biomechanical and finite element analyses also support this view, considering that a moderate increase in PTS is a key means to increase the postoperative flexion range (ROM) of PS-type prostheses [ 18 ]. A quadratic (inverted U) relationship was found between PTS and FJS-12 (peak at 5.3°), aligning closely with the cohort’s mean native PTS (≈ 6°). This finding indicates an optimal subjective “forgotten” experience when PTS approaches native anatomy [ 12 ]. Although the robot-assisted group had a significantly greater FJS-12 score, the 4.5-point difference did not exceed the MCID (≈ 10–14 points), implying limited gain in clinical perception. Deviation analysis revealed that greater PTS deviation from native anatomy independently lowered FJS-12 scores (β = − 2.4), independent of the absolute PTS value. The subgroup results reinforced that Δ ≤ 2° yields markedly better subjective outcomes. Therefore, clinical decision-making should tend toward precise replication of individualized native PTSs rather than blindly pursuing a certain fixed angle [ 12 ]. Hierarchical influence of the PTS deviation amplitude (Δ) on subjective perception The results of the subgroup stratified analysis revealed that when the postoperative PTS deviation was controlled within 2° (Δ ≤ 2°), patients’ FJS-12 scores exhibited a significant hierarchical advantage. This finding defines the “precision threshold window” for subjective functional benefit and confirms that the anatomical reduction accuracy of PTS is the key factor determining the postoperative “natural feel.” The extremely high achievement rate of the robot-assisted group within this window (87.3%) provided empirical support for its significant advantage in FJS-12 scores. Although the 2° threshold was set on the basis of clinical experience, its mutual corroboration with the continuous-variable regression results further reveals the value of “anatomical reconstruction” in subjective functional recovery [ 12 ]. Anatomical and biomechanical value of restoring the native posterior tibial slope This study revealed that the FJS-12 score in the Δ ≤ 2° group was significantly superior, indicating that precise anatomical alignment can more effectively place subjects into the “subjective functional benefit window.” From a biomechanical perspective, restoring the PTS close to the physiological state helps preserve joint proprioception and enhances patients’ bodily cognition of the artificial prosthesis. Given the significant anatomical heterogeneity of the native PTS in the population, compared with pursuing a population-wide target value, precise reconstruction based on individualized anatomical features has far-reaching clinical significance for maintaining the native kinematic characteristics of the knee joint and improving mid- to long-term postoperative function [ 12 ]. Analysis of inconsistency between primary and secondary outcome indicators In this study, secondary outcome indicators, such as the KSS score, Oxford Knee score (OKS), and WOMAC, showed no statistically significant intergroup differences, which is in sharp contrast with the positive findings in the primary outcomes (FJS-12 score and flexion angle). The potential mechanisms may include the following: (1) FJS-12 has greater detection sensitivity for subtle differences in joint perception, whereas traditional functional scales are limited by the “ceiling effect,” making it difficult to distinguish microdifferences among high-functioning patients [ 17 ]; (2) the clinical benefits of robot-assisted technology have certain functional specificity, mainly manifested in the patients’ subjective perception dimension rather than comprehensive objective functional domain improvement. In addition, this finding also suggests that within the retrospective study framework, differences in FJS-12 scores may be influenced by potential confounders such as selection bias, and causal inference should be interpreted with caution. Study limitations This study has the following limitations: (1) Retrospective design and selection bias: nonrandomized grouping driven by patients’ socioeconomic status and high functional expectations may introduce a “placebo effect,” weakening the causal inference power of the conclusions. (2) Follow-up period limitations: the 1-year follow-up reflects only short-term efficacy and cannot yet assess long-term prosthesis survival, periprosthetic bone density changes, or long-term polyethylene liner wear. (3) Single prosthesis design: This study included only posterior-stabilized (PS) prostheses; the generalizability of the conclusions to cruciate-retaining (CR) and other prostheses with different mechanical designs needs further verification. (4) Multidimensional confounding interference: Although this study adjusted for HKA deviation, it did not quantify dynamic mechanical indicators such as soft-tissue balance. Given that robot-assisted surgery has systemic technical advantages (such as femoral rotation positioning optimization), it is difficult to completely isolate the independent contribution of PTS to FJS-12 scores. Clinical Implications and Future Directions Surgeons should measure native PTS preoperatively via 3D imaging and leverage robotic precision to achieve Δ ≤ 2° reconstruction, aiming to cross MCID thresholds. Future prospective RCTs stratified by native PTS, incorporating coronal alignment, sagittal PTS, and multidimensional soft-tissue data, are warranted. Artificial intelligence-assisted planning systems may further optimize individualized strategies. Conclusions In summary, under precise robotic osteotomy, the postoperative PTS is significantly nonlinearly related to the FJS-12 score, with an optimal population-level value of approximately 5.3°. PTS deviation from native anatomy is an independent predictor of FJS-12 score, underscoring the value of individualized native PTS restoration—particularly in patients with marked anatomical variation. However, the observed FJS-12 score improvement did not exceed the MCID, and most secondary outcomes were negative; therefore, the clinical significance of this finding requires cautious interpretation. Large-scale prospective RCTs are needed to confirm the long-term benefits of individualized PTS reconstruction. Abbreviations BMI Body mass index FJS-12 Forgotten Joint Score-12 HKA Hip-knee-ankle ICC Intraclass correlation coefficient KSS Knee Society score MCID Minimal clinically important difference OKS Oxford Knee Score PCL Posterior cruciate ligament PS Posterior stabilized PSM Propensity score matching PTS Posterior tibial slope RATKA Robot-assisted total knee arthroplasty ROM Range of motion SMD Standardized mean difference TKA Total knee arthroplasty VAS Visual analog scale WOMAC Western Ontario and McMaster Universities Osteoarthritis Index Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Wangjing Hospital, China Academy of Chinese Medical Sciences (approval numbers: WJEC-KT-2021-035-P003, WJEC-KT-2021-035-P004, WJEC-KT-2021-035-P005; dates of approval: July 15, 2021; July 28, 2022; July 24, 2023). Informed consent was obtained from all participants involved in the study. Consent for publication Written informed consent for publication was obtained from each patient. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors' contributions Chen Boyi: Conceptualization, methodology, formal analysis, data curation, writing—original draft, writing—review & editing. Yan Qi, Li Yuanyuan, Liu Siye, Yu Ximing: Investigation, Data curation, Validation. Jing Lin, Zhang Hongmei: Supervision, Project administration, Writing—review & editing. All the authors have read and agreed to the published version of the manuscript. Acknowledgments Not applicable. Authors' information (Not applicable) References Gunaratne R, et al. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9392901","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633381452,"identity":"888cbea7-fc63-4038-b7a5-a4df7ae1d426","order_by":0,"name":"Chen Boyi","email":"","orcid":"","institution":"Beijing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Boyi","suffix":""},{"id":633381453,"identity":"b25c60ac-bf49-4160-840b-0bc8ce171135","order_by":1,"name":"Jing Lin","email":"","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Lin","suffix":""},{"id":633381454,"identity":"756d8ce6-94c7-45a1-a8f5-bb90b5418714","order_by":2,"name":"Zhang Hongmei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIie3RsQuCQBTH8SfCuRzOhnH2DwRPDgQX/xYlcDJobBRabT/I/yJwvghsqd01giYH2xqCcqzJawu67/6B9+MB6HQ/GPEuh3uHhHneXqoRG9J4JBY29wWJ1QiDbOLSjiV5Q1HxMDiCLzDgxqa4NS1EbJoPEWMt4w5TZo1P27CEGQ/kEDHteCew5kY+r1wKMqkGCaH+iuIzyWV2VSSUcpMi6ednRJE4JDUEEu4XNQ9LVNjiCbOG7tG/0lqdm3YZsUHykaP6mnfyrdDpdLq/6AVAhj8BzflQbQAAAABJRU5ErkJggg==","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zhang","middleName":"","lastName":"Hongmei","suffix":""},{"id":633381455,"identity":"81ccb55e-0e0d-424f-b882-cfa838bc5594","order_by":3,"name":"Yan Qi","email":"","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Qi","suffix":""},{"id":633381456,"identity":"52454def-538d-444c-8ea3-529e5b6410f5","order_by":4,"name":"Li Yuanyuan","email":"","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Yuanyuan","suffix":""},{"id":633381457,"identity":"4e1436fe-dc07-4c14-b9a7-630b3d479bb8","order_by":5,"name":"Liu Siye","email":"","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Liu","middleName":"","lastName":"Siye","suffix":""},{"id":633381458,"identity":"0b35dccf-1d05-4596-b035-88678d84a0b7","order_by":6,"name":"Yu Ximing","email":"","orcid":"","institution":"Wangjing Hospital of China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ximing","suffix":""}],"badges":[],"createdAt":"2026-04-12 08:54:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9392901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9392901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108804479,"identity":"c91e88fc-f11f-4748-83ce-0e8e93d5e858","added_by":"auto","created_at":"2026-05-08 15:20:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":315854,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9392901/v1/cae30a86-8b99-4534-bae4-5be5c33457ae.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Deviation from Native Posterior Tibial Slope and Dose‒Response Relationships with Forgotten Joint Score-12 in Robot-Assisted Total Knee Arthroplasty: A Retrospective Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn modern artificial joint surgery, the ultimate clinical goal of total knee arthroplasty (TKA) has evolved from simply pursuing prosthesis survival to achieving excellent functional recovery and patient satisfaction. Although prosthesis design and surgical techniques have matured, approximately 15\u0026ndash;20% of patients remain dissatisfied with their prognosis. This \u0026ldquo;subjective dissatisfaction\u0026rdquo; is typically attributed to loss of proprioception, limited flexion, or heightened self-awareness during joint motion (i.e., \u0026ldquo;foreign body sensation\u0026rdquo;) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among the parameters regulating postoperative kinematics, the posterior tibial slope (PTS) has emerged as a core research focus because of its decisive role in flexion-gap capacity, the femoral rollback trajectory, and extension-flexion balance.\u003c/p\u003e \u003cp\u003ePTS is defined as the posterior tilt angle of the tibial plateau relative to the tibial mechanical axis in the sagittal plane. Previous biomechanical studies have shown that a moderate PTS increase effectively enlarges the flexion gap and improves the knee range of motion (ROM); however, excessive posterior tilt may reduce mid-flexion stability and increase the risk of prosthesis wear and loosening, whereas insufficient PTS reconstruction often leads to a tight flexion gap and restricted motion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, precise intraoperative PTS reconstruction is critical for optimizing postoperative function.\u003c/p\u003e \u003cp\u003eIn conventional TKA, the PTS relies heavily on mechanical guidance and surgeon experience and is markedly affected by anatomical variation, frequently resulting in significant osteotomy deviation. Robot-assisted total knee arthroplasty (RATKA) substantially improves osteotomy accuracy through digital modeling and haptic limiting technology; this advantage has been widely confirmed [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, even when the technical precision reaches submillimeter levels, the optimal PTS target remains controversial: should a biomechanically derived population-optimal angle be pursued, or should native anatomy be individually reconstructed? Moreover, whether PTS reconstruction deviation independently influences patients\u0026rsquo; subjective functional experience has not been systematically investigated.\u003c/p\u003e \u003cp\u003eWith the increasing importance of patient-reported outcome measures (PROMs) in joint surgery evaluation, the Forgotten Joint Score-12 (FJS-12) has become a key indicator of TKA postoperative function. By quantifying how often patients \u0026ldquo;forget\u0026rdquo; the artificial joint in daily life, the FJS-12 is considered more sensitive than traditional scores for detecting proprioceptive recovery and psychological integration. Therefore, on the basis of a retrospective cohort, this study aims to elucidate the dose‒response relationship between PTS reconstruction accuracy and FJS-12 scores and to explore whether the precision boundary provided by robotic technology can substantially improve patients\u0026rsquo; postoperative subjective \u0026ldquo;forgotten\u0026rdquo; experience by precisely restoring the individualized native PTS and crossing the minimal clinically important difference (MCID) threshold.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Design\u003c/p\u003e\n\u003cp\u003eThis investigation adhered to a single-center retrospective cohort design and was approved by the hospital\u0026rsquo;s ethics committee.\u003c/p\u003e\n\u003cp\u003ePatient data from patients who underwent primary unilateral TKA from August 2021 to June 2024 were retrospectively analyzed.\u003c/p\u003e\n\u003cp\u003eInclusion criteria\u003c/p\u003e\n\u003cp\u003e(1) Primary knee osteoarthritis with Kellgren\u0026ndash;Lawrence grade III\u0026ndash;IV [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]; (2) primary unilateral TKA; (3) age 50\u0026ndash;80 years; (4) preoperative flexion contracture\u0026thinsp;\u0026lt;\u0026thinsp;15\u0026deg;; (5) complete preoperative and postoperative imaging follow-up data.\u003c/p\u003e\n\u003cp\u003eExclusion criteria\u003c/p\u003e\n\u003cp\u003e(1) History of ipsilateral knee surgery; (2) inflammatory arthropathy (e.g., rheumatoid arthritis); (3) severe osteoporosis or neuromuscular disease; (4) posterior cruciate ligament (PCL) insufficiency; (5) missing follow-up data.\u003c/p\u003e\n\u003cp\u003eA total of 240 patients met the inclusion criteria and were included.\u003c/p\u003e\n\u003cp\u003eSurgical \u003cstrong\u003etechnique\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe enrolled patients were divided into a conventional group (n\u0026thinsp;=\u0026thinsp;120) and a robot-assisted group (n\u0026thinsp;=\u0026thinsp;120). Grouping decisions were based on patients\u0026rsquo; personal preferences and the availability of intraoperative resources; patients in the robot-assisted group actively chose to undergo the robot-assisted surgery system (RATKA), while the remaining patients entered the conventional surgery control group. This study was a nonrandomized retrospective study. All surgeries were performed by the same senior joint surgery team. A midline knee incision and the medial parapatellar approach were used uniformly [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Femoral osteotomy was completed with intramedullary guidance and a preset external rotation angle of 3\u0026deg; [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. For tibial osteotomy, standard extramedullary positioning instruments were used for osteotomy in the conventional group. The robot-assisted group utilized the robotic navigation system to complete preoperative three-dimensional digital modeling and personalized planning, and under real-time optical navigation feedback during surgery, the haptic limiting technology of the robotic arm was used to precisely execute the osteotomy plan [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Both groups of patients received the same brand of posterior-stabilized (Posterior-Stabilized, PS) prosthesis, which was fixed with bone cement for biological fixation.\u003c/p\u003e\n\u003cp\u003ePostoperative Rehabilitation\u003c/p\u003e\n\u003cp\u003eBoth groups followed a standardized perioperative pathway, including multimodal analgesia and routine thromboprophylaxis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Quadriceps isometric exercises began on postoperative day 1; partial weight-bearing with a walker started on day 2. Progressive ROM training was supervised by rehabilitation therapists thereafter.\u003c/p\u003e\n\u003cp\u003eOutcome Measures\u003c/p\u003e\n\u003cp\u003ePrimary outcome measures\u003c/p\u003e\n\u003cp\u003eMaximum active knee flexion angle and FJS-12 score at 1 year post-operatively.\u003c/p\u003e\n\u003cp\u003eFlexion angle measurement: The measurement was performed independently by two senior physicians who did not participate in the surgery via a standard goniometer (range 0\u0026ndash;180\u0026deg;, precision 1\u0026deg;). During measurement, the subject was placed in the supine position, and the affected knee was actively flexed to the limit angle, with the readings recorded. For each patient, each of the two physicians repeated the measurement 3 times; the mean of each physician\u0026rsquo;s measurements was taken, and then the average between the two physicians was calculated as the final outcome data.\u003c/p\u003e\n\u003cp\u003eReliability testing: To verify the consistency of the measurements, 30 cases were randomly selected (approximately 12.5% of the total number of follow-up cases). The above two physicians performed independent measurements after a 1-week interval. The intraclass correlation coefficient (ICC) was used to assess test‒retest reliability. According to the evaluation criteria, an ICC value\u0026thinsp;\u0026gt;\u0026thinsp;0.75 indicates good reliability, whereas 0.50\u0026ndash;0.75 indicates moderate reliability.\u003c/p\u003e\n\u003cp\u003eForgotten Joint Score: The Chinese version of the FJS-12 scale was used to evaluate postoperative proprioceptive recovery. The scale contains 12 items, with a total score ranging from 0 to 100 points. A higher score indicates lower postoperative joint awareness, that is, a better \u0026ldquo;forgotten\u0026rdquo; state. The FJS-12 has been validated in multiple cultural backgrounds, demonstrating excellent reliability and validity with a lower ceiling effect; its minimal clinically important difference (MCID) is defined as 13.7\u0026ndash;16.6 points.\u003c/p\u003e\n\u003cp\u003eSecondary outcome measures\u003c/p\u003e\n\u003cp\u003eKSS, OKS, WOMAC index, anterior knee pain VAS, tibial anterior translation (stability), and perioperative/follow-up complication rates.\u003c/p\u003e\n\u003cp\u003eAssessment of Osteotomy Accuracy\u003c/p\u003e\n\u003cp\u003eThe actual PTS was measured on postoperative CT. Osteotomy error (absolute error) = |actual PTS \u0026ndash; target PTS|, with the target PTS determined from preoperative digital planning.\u003c/p\u003e\n\u003cp\u003eStatistical Analyses\u003c/p\u003e\n\u003cp\u003eIBM SPSS 26.0 was used. Continuous variables are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SDs and were compared with independent-samples t tests; categorical variables are presented as frequencies (percentages) and were compared with \u0026chi;\u0026sup2; tests or Fisher\u0026rsquo;s exact tests. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003ePropensity score matching (PSM): To balance baseline covariates between groups and reduce selection bias, PSM was performed at a 1:1 ratio to match the conventional and robot-assisted groups [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The propensity score model included age, sex, BMI, preoperative KSS score, preoperative flexion angle, degree of preoperative deformity, and preoperative native posterior tibial slope. Nearest-neighbor matching was used, with the caliper value set at 0.02. Balance after matching was assessed via the standardized mean difference (SMD), with SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.10 considered indicative of good balance between groups.\u003c/p\u003e\n\u003cp\u003eMinimal clinically important difference (MCID): This study introduced the MCID as the threshold for clinical efficacy evaluation to distinguish statistical significance from clinical relevance. In accordance with previous studies, the MCID for FJS-12 was set at 12 points [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and the MCID for the maximum active knee flexion angle was set at 5\u0026deg;.\u003c/p\u003e\n\u003cp\u003eCore variable construction and regression analysis: To quantitatively evaluate the effect of deviation between actual osteotomy values and anatomical morphology on postoperative function, the core index deviation (Deviation) was calculated as Deviation = |Actual PTS\u0026thinsp;\u0026minus;\u0026thinsp;Native PTS|. Multivariate linear regression was used to analyze the influencing factors of functional outcomes, with the FJS-12 score as the dependent variable. The independent variables of the model included (1) actual postoperative PTS (containing both linear and quadratic terms to capture potential nonlinear effects); (2) deviation (continuous variable); and (3) covariates (age, sex, BMI, preoperative flexion angle, and surgical method). The partial regression coefficients (\u0026beta;) and their significance levels for each variable were used to explore the independent contributions of \u0026ldquo;population-wide target value\u0026rdquo; and \u0026ldquo;individualized native restoration\u0026rdquo; to patients\u0026rsquo; subjective \u0026ldquo;forgotten\u0026rdquo; joint experience [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eSensitivity analysis: To further assess the potential independent interference of coronal alignment on clinical function and to verify the robustness of the model conclusions, postoperative lower-limb alignment deviation (the absolute value of the HKA angle deviation from the neutral position) was added as an additional control variable into the regression equation for sensitivity analysis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eReliability testing: The intraclass correlation coefficient (ICC) was used to evaluate the test-retest reliability of knee flexion angle measurements, with an ICC\u0026thinsp;\u0026gt;\u0026thinsp;0.75 considered indicative of good reliability [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eResults Patient Demographics\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in age, sex, BMI, preoperative flexion, KSS score, OKS score, WOMAC score, deformity, or native PTS (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) among the 240 patients (120 per group) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePatient baseline characteristics (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eConventional(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRobot-assisted(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003et/\u0026chi;\u0026sup2;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e67.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSex(male/female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e48/72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e52/68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBMI(kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e27.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePreoperative flexion(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e108.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e109.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePreoperative KSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e49.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePreoperative OKS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePreoperative WOMAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e53.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePreoperative deformity(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNative PTS(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOsteotomy Accuracy\u003c/p\u003e\n\u003cp\u003eThe preoperative target PTS did not differ significantly (5.8\u0026deg; \u0026plusmn; 1.2\u0026deg; vs 6.1\u0026deg; \u0026plusmn; 1.3\u0026deg;, P\u0026thinsp;=\u0026thinsp;0.065). The actual postoperative PTS was 6.8\u0026deg; \u0026plusmn; 2.5\u0026deg; (conventional) vs 6.5\u0026deg; \u0026plusmn; 1.8\u0026deg; (robot-assisted) (P\u0026thinsp;=\u0026thinsp;0.290). The absolute error was 2.8\u0026deg; \u0026plusmn; 1.6\u0026deg; vs 1.2\u0026deg; \u0026plusmn; 0.9\u0026deg; (t\u0026thinsp;=\u0026thinsp;9.46, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOsteotomy accuracy comparison (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eConventional(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRobot-assisted(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTarget PTS(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eActual PTS(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOsteotomy error(\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e9.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eReliability of the Flexion Angle Measurement\u003c/p\u003e\n\u003cp\u003eFor 30 patients, the interrater ICC was 0.89 (95% CI: 0.82\u0026ndash;0.94); the intrarater ICCs were 0.92 (Physician A) and 0.91 (Physician B) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFlexion angle measurement reliability\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eReliability type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eICC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eRating\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInterrater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.82\u0026ndash;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntrarater (Physician A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.86\u0026ndash;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIntrarater (Physician B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.85\u0026ndash;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eClinical functional outcomes at 1 year post-surgery\u003c/p\u003e\n\u003cp\u003eThe robot-assisted group had greater maximum flexion (121.5\u0026deg; \u0026plusmn; 9.2\u0026deg; vs 118.3\u0026deg; \u0026plusmn; 10.1\u0026deg;, P\u0026thinsp;=\u0026thinsp;0.011) and FJS-12 (68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8 vs 64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3, P\u0026thinsp;=\u0026thinsp;0.030) values. No significant differences were found in the KSS, OKS, WOMAC, tibial translation score, or anterior knee pain VAS score (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e1-year clinical outcomes (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eConventional(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRobot-assisted(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMaximum flexion (\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e118.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e121.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFJS-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eKSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e85.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e86.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOKS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e40.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e41.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eWOMAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e19.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e18.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTibial anterior translation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAnterior knee pain VAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMultivariate linear regression\u003c/p\u003e\n\u003cp\u003eAfter adjusting for age, sex, BMI, and preoperative flexion, (1) PTS and flexion were positively linearly correlated (\u0026beta;\u0026thinsp;=\u0026thinsp;1.9, 95% CI: 1.2\u0026ndash;2.6, P\u0026thinsp;=\u0026thinsp;0.008). (2) PTS and FJS-12: quadratic relationship (quadratic term \u0026beta; = \u0026minus;\u0026thinsp;0.95, 95% CI: \u0026minus;\u0026thinsp;1.58 to \u0026minus;\u0026thinsp;0.32, P\u0026thinsp;=\u0026thinsp;0.012); peak at PTS\u0026thinsp;=\u0026thinsp;5.3\u0026deg;. (3) Deviation and FJS-12 score: negative correlation (\u0026beta; = \u0026minus;\u0026thinsp;2.4, 95% CI: \u0026minus;\u0026thinsp;3.8 to \u0026minus;\u0026thinsp;1.0, P\u0026thinsp;=\u0026thinsp;0.006). (4) Sensitivity analysis for lower-limb alignment deviation (HKA): Postoperative HKA deviation was included in the model as an additional covariate. The results revealed that a quadratic relationship between actual PTS and the FJS-12 score (\u0026beta; = -0.89, P\u0026thinsp;=\u0026thinsp;0.018) and a negative correlation between deviation and the FJS-12 score (\u0026beta; = -2.1, P\u0026thinsp;=\u0026thinsp;0.012) still existed. In addition, HKA deviation was negatively correlated with the FJS-12 score (\u0026beta; = -1.8, 95% CI: -3.1 to -0.5, P\u0026thinsp;=\u0026thinsp;0.009). Since the intraoperative soft-tissue pressure distribution was not quantified, this factor was not included in the model. (5) Group differences did not exceed MCID thresholds (flexion difference 3.2\u0026deg; \u0026lt; 5\u0026deg; MCID; FJS-12 difference 4.5 points\u0026thinsp;\u0026lt;\u0026thinsp;12 points MCID).\u003c/p\u003e\n\u003cp\u003eSubgroup analysis: stratified influence of PTS deviation (\u0026Delta;)\u003c/p\u003e\n\u003cp\u003eThe \u0026Delta;\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; group (n\u0026thinsp;=\u0026thinsp;102) had greater FJS-12 scores (71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6 vs 63.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than did the \u0026Delta;\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026deg; group (n\u0026thinsp;=\u0026thinsp;138); there were no differences in flexion, KSS, or tibial translation (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical outcomes stratified by \u003cstrong\u003ethe\u003c/strong\u003e \u0026Delta; (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026Delta;\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; (n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026Delta;\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026deg; (n\u0026thinsp;=\u0026thinsp;138)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMaximum flexion (\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e120.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e119.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFJS-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e63.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eKSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e86.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e85.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTibial anterior translation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\n \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn the \u0026Delta;\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; group, the proportion of robot-assisted procedures was 87.3% (89/102), whereas the proportion of conventional procedures was 12.7% (13/102); in the \u0026Delta;\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026deg; group, the proportion of robot-assisted procedures was 21.7% (30/138), whereas the proportion of conventional procedures was 78.3% (108/138). The difference in the distribution of surgical methods between the groups was statistically significant (\u0026chi;\u0026sup2; = 108.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociation between surgical method and \u0026Delta; stratification [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSurgical method\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026Delta;\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; (n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026Delta;\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026deg; (n\u0026thinsp;=\u0026thinsp;138)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConventional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e13 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e108 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e108.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRobot-assisted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e89 (87.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e30 (21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e102 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e138 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAdverse Events\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in infection, deep vein thrombosis, or stiffness rates (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAdverse events [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEvent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eConventional(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRobot-assisted(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDeep vein thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eStiffness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e6 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective cohort study compared conventional and robot-assisted TKA with respect to PTS reconstruction accuracy and examined the relationship between postoperative PTS and clinical function.\u003c/p\u003e \u003cp\u003eRobot-assisted surgery significantly reduced the osteotomy error (1.2\u0026deg; \u0026plusmn; 0.9\u0026deg; vs 2.8\u0026deg; \u0026plusmn; 1.6\u0026deg;, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which is consistent with prior reports [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The advantage extends beyond sagittal PTS to coronal alignment, femoral rotation, and soft-tissue balance. Conventional techniques rely on intramedullary or extramedullary references and are strongly affected by anatomical variation, whereas the robotic system achieves higher prosthesis implantation accuracy through preoperative three-dimensional digital modeling and intraoperative real-time optical navigation feedback [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile FJS-12 scores were superior in the robot-assisted group, traditional objective scores (KSS, OKS, and WOMAC) showed no difference, suggesting that robotic benefits are most evident in subjective joint awareness rather than all functional domains [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Regression confirmed an independent PTS contribution to FJS-12 even after HKA adjustment. Notably, owing to the limitations of the retrospective design, this study failed to include dynamic mechanical parameters such as intraoperative soft-tissue pressure distribution in the model, which may constitute a potential confounding factor.\u003c/p\u003e \u003cp\u003eThe linear relationship between the postoperative PTS and knee flexion range of motion regression analysis revealed that for every 1\u0026deg; increase in the postoperative PTS, the maximum flexion angle increased by approximately 1.9\u0026deg; (β\u0026thinsp;=\u0026thinsp;1.9). This conclusion validates the regulatory role of the PTS in the knee flexion dimension: increasing the posterior slope can effectively enlarge the flexion gap and reduce posterior bony impingement between the femur and tibia, thereby improving flexion activity. Biomechanical and finite element analyses also support this view, considering that a moderate increase in PTS is a key means to increase the postoperative flexion range (ROM) of PS-type prostheses [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA quadratic (inverted U) relationship was found between PTS and FJS-12 (peak at 5.3\u0026deg;), aligning closely with the cohort\u0026rsquo;s mean native PTS (\u0026asymp;\u0026thinsp;6\u0026deg;). This finding indicates an optimal subjective \u0026ldquo;forgotten\u0026rdquo; experience when PTS approaches native anatomy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although the robot-assisted group had a significantly greater FJS-12 score, the 4.5-point difference did not exceed the MCID (\u0026asymp;\u0026thinsp;10\u0026ndash;14 points), implying limited gain in clinical perception. Deviation analysis revealed that greater PTS deviation from native anatomy independently lowered FJS-12 scores (β = \u0026minus;\u0026thinsp;2.4), independent of the absolute PTS value. The subgroup results reinforced that Δ\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; yields markedly better subjective outcomes. Therefore, clinical decision-making should tend toward precise replication of individualized native PTSs rather than blindly pursuing a certain fixed angle [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHierarchical influence of the PTS deviation amplitude (Δ) on subjective perception\u003c/p\u003e \u003cp\u003eThe results of the subgroup stratified analysis revealed that when the postoperative PTS deviation was controlled within 2\u0026deg; (Δ\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg;), patients\u0026rsquo; FJS-12 scores exhibited a significant hierarchical advantage. This finding defines the \u0026ldquo;precision threshold window\u0026rdquo; for subjective functional benefit and confirms that the anatomical reduction accuracy of PTS is the key factor determining the postoperative \u0026ldquo;natural feel.\u0026rdquo; The extremely high achievement rate of the robot-assisted group within this window (87.3%) provided empirical support for its significant advantage in FJS-12 scores. Although the 2\u0026deg; threshold was set on the basis of clinical experience, its mutual corroboration with the continuous-variable regression results further reveals the value of \u0026ldquo;anatomical reconstruction\u0026rdquo; in subjective functional recovery [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnatomical and biomechanical value of restoring the native posterior tibial slope\u003c/p\u003e \u003cp\u003eThis study revealed that the FJS-12 score in the Δ\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; group was significantly superior, indicating that precise anatomical alignment can more effectively place subjects into the \u0026ldquo;subjective functional benefit window.\u0026rdquo; From a biomechanical perspective, restoring the PTS close to the physiological state helps preserve joint proprioception and enhances patients\u0026rsquo; bodily cognition of the artificial prosthesis. Given the significant anatomical heterogeneity of the native PTS in the population, compared with pursuing a population-wide target value, precise reconstruction based on individualized anatomical features has far-reaching clinical significance for maintaining the native kinematic characteristics of the knee joint and improving mid- to long-term postoperative function [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnalysis of inconsistency between primary and secondary outcome indicators\u003c/p\u003e \u003cp\u003eIn this study, secondary outcome indicators, such as the KSS score, Oxford Knee score (OKS), and WOMAC, showed no statistically significant intergroup differences, which is in sharp contrast with the positive findings in the primary outcomes (FJS-12 score and flexion angle). The potential mechanisms may include the following: (1) FJS-12 has greater detection sensitivity for subtle differences in joint perception, whereas traditional functional scales are limited by the \u0026ldquo;ceiling effect,\u0026rdquo; making it difficult to distinguish microdifferences among high-functioning patients [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]; (2) the clinical benefits of robot-assisted technology have certain functional specificity, mainly manifested in the patients\u0026rsquo; subjective perception dimension rather than comprehensive objective functional domain improvement. In addition, this finding also suggests that within the retrospective study framework, differences in FJS-12 scores may be influenced by potential confounders such as selection bias, and causal inference should be interpreted with caution.\u003c/p\u003e \u003cp\u003eStudy limitations\u003c/p\u003e \u003cp\u003eThis study has the following limitations: (1) Retrospective design and selection bias: nonrandomized grouping driven by patients\u0026rsquo; socioeconomic status and high functional expectations may introduce a \u0026ldquo;placebo effect,\u0026rdquo; weakening the causal inference power of the conclusions. (2) Follow-up period limitations: the 1-year follow-up reflects only short-term efficacy and cannot yet assess long-term prosthesis survival, periprosthetic bone density changes, or long-term polyethylene liner wear. (3) Single prosthesis design: This study included only posterior-stabilized (PS) prostheses; the generalizability of the conclusions to cruciate-retaining (CR) and other prostheses with different mechanical designs needs further verification. (4) Multidimensional confounding interference: Although this study adjusted for HKA deviation, it did not quantify dynamic mechanical indicators such as soft-tissue balance. Given that robot-assisted surgery has systemic technical advantages (such as femoral rotation positioning optimization), it is difficult to completely isolate the independent contribution of PTS to FJS-12 scores.\u003c/p\u003e \u003cp\u003eClinical Implications and Future Directions\u003c/p\u003e \u003cp\u003eSurgeons should measure native PTS preoperatively via 3D imaging and leverage robotic precision to achieve Δ\u0026thinsp;\u0026le;\u0026thinsp;2\u0026deg; reconstruction, aiming to cross MCID thresholds. Future prospective RCTs stratified by native PTS, incorporating coronal alignment, sagittal PTS, and multidimensional soft-tissue data, are warranted. Artificial intelligence-assisted planning systems may further optimize individualized strategies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, under precise robotic osteotomy, the postoperative PTS is significantly nonlinearly related to the FJS-12 score, with an optimal population-level value of approximately 5.3\u0026deg;. PTS deviation from native anatomy is an independent predictor of FJS-12 score, underscoring the value of individualized native PTS restoration\u0026mdash;particularly in patients with marked anatomical variation. However, the observed FJS-12 score improvement did not exceed the MCID, and most secondary outcomes were negative; therefore, the clinical significance of this finding requires cautious interpretation. Large-scale prospective RCTs are needed to confirm the long-term benefits of individualized PTS reconstruction.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI Body mass index\u003c/p\u003e\n\u003cp\u003eFJS-12 Forgotten Joint Score-12\u003c/p\u003e\n\u003cp\u003eHKA Hip-knee-ankle\u003c/p\u003e\n\u003cp\u003eICC Intraclass correlation coefficient\u003c/p\u003e\n\u003cp\u003eKSS Knee Society score\u003c/p\u003e\n\u003cp\u003eMCID Minimal clinically important difference\u003c/p\u003e\n\u003cp\u003eOKS Oxford Knee Score\u003c/p\u003e\n\u003cp\u003ePCL Posterior cruciate ligament\u003c/p\u003e\n\u003cp\u003ePS Posterior stabilized\u003c/p\u003e\n\u003cp\u003ePSM Propensity score matching\u003c/p\u003e\n\u003cp\u003ePTS Posterior tibial slope\u003c/p\u003e\n\u003cp\u003eRATKA Robot-assisted total knee arthroplasty\u003c/p\u003e\n\u003cp\u003eROM Range of motion\u003c/p\u003e\n\u003cp\u003eSMD Standardized mean difference\u003c/p\u003e\n\u003cp\u003eTKA Total knee arthroplasty\u003c/p\u003e\n\u003cp\u003eVAS Visual analog scale\u003c/p\u003e\n\u003cp\u003eWOMAC Western Ontario and McMaster Universities Osteoarthritis Index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Wangjing Hospital, China Academy of Chinese Medical Sciences (approval numbers: WJEC-KT-2021-035-P003, WJEC-KT-2021-035-P004, WJEC-KT-2021-035-P005; dates of approval: July 15, 2021; July 28, 2022; July 24, 2023). Informed consent was obtained from all participants involved in the study.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from each patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eChen Boyi: Conceptualization, methodology, formal analysis, data curation, writing—original draft, writing—review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eYan Qi, Li Yuanyuan, Liu Siye, Yu Ximing: Investigation, Data curation, Validation.\u003c/p\u003e\n\u003cp\u003eJing Lin, Zhang Hongmei: Supervision, Project administration, Writing—review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAll the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information\u003c/strong\u003e (Not applicable)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGunaratne R, et al. Patient dissatisfaction following total knee arthroplasty: A systematic review of the literature. J Arthroplasty. 2017;32(12):3854-3860.\u003c/li\u003e\n \u003cli\u003eGuo N, et al. Posterior tibial slope influences joint mechanics and soft tissue loading patterns in total knee arthroplasty: A subject-specific musculoskeletal modeling study. Front Bioeng Biotechnol. 2024;12:1352794.\u003c/li\u003e\n \u003cli\u003eKang KT, et al. Influence of increased posterior tibial slope in total knee arthroplasty on knee joint biomechanics: A computational simulation study. J Arthroplasty. 2018;33(2):572-579.\u003c/li\u003e\n \u003cli\u003eBaek JH, et al. Better accuracy of robotic-assisted total knee arthroplasty compared with conventional total knee arthroplasty in patients with failed high tibial osteotomy. PLoS One. 2024;19(12):e0313391.\u003c/li\u003e\n \u003cli\u003eOosthuizen CR, et al. The Knee Osteoarthritis Grading System for Arthroplasty. J Arthroplasty. 2019;34(3):450-455.\u003c/li\u003e\n \u003cli\u003eVaishya R, et al. Surgical approaches for total knee arthroplasty. J Clin Orthop Trauma. 2016;7(2):71-79.\u003c/li\u003e\n \u003cli\u003eChoi YJ, et al. Early Results of Total Knee Arthroplasty Using a Built-in 3-Degree External Rotation Prosthesis. Knee Surg Relat Res. 2013;25(3):112-116.\u003c/li\u003e\n \u003cli\u003eSiddiqi A, et al. A clinical review of robotic navigation in total knee arthroplasty: historical systems to modern design. EFORT Open Rev. 2021;6(4):252-269.\u003c/li\u003e\n \u003cli\u003eMaheshwari AV, et al. Multimodal Pain Management after Total Hip and Knee Arthroplasty at the Ranawat Orthopaedic Center. Clin Orthop Relat Res. 2009;467(6):1418-1423.\u003c/li\u003e\n \u003cli\u003eNorton J, et al. Robotic arm-assisted versus conventional total knee arthroplasty: comparing complications, costs, and postoperative opioid use in propensity-matched cohorts. Eur J Orthop Surg Traumatol. 2024.\u003c/li\u003e\n \u003cli\u003eClement ND, et al. Meaningful values in the Forgotten Joint Score after total knee arthroplasty: minimal clinically important difference, minimal important and detectable changes, and patient-acceptable symptom state. Bone Joint J. 2021;103-B(5):846-854.\u003c/li\u003e\n \u003cli\u003eCho YT, et al. Restoring native posterior tibial slope within 4\u0026deg; leads to better clinical outcomes after cruciate-retaining robot-assisted total knee arthroplasty with functional alignment. Knee Surg Sports Traumatol Arthrosc. 2025;33(7):2592-2604.\u003c/li\u003e\n \u003cli\u003eKonishi T, et al. Pre- and postoperative Coronal Plane Alignment of the Knee classification and its impact on clinical outcomes in total knee arthroplasty. Bone Joint J. 2024;106-B(10):1059-1066.\u003c/li\u003e\n \u003cli\u003eSummers HKC, et al. Inter- and intra-rater reliability of knee flexion angle measurements on X-ray and MRI. Ann Joint. 2022;7:34.\u003c/li\u003e\n \u003cli\u003eDeckey DG, et al. Robotic-assisted total knee arthroplasty improves accuracy and precision compared to conventional techniques. Bone Joint J. 2021;103-B(6 Supple A):74-80.\u003c/li\u003e\n \u003cli\u003eFu X, et al. Comparison of robotic-assisted total knee arthroplasty: an updated systematic review and meta-analysis. J Robot Surg. 2024;18(1):292.\u003c/li\u003e\n \u003cli\u003eThomsen MG, et al. Good validity and reliability of the forgotten joint score in evaluating the outcome of total knee arthroplasty. Acta Orthop. 2016;87(3):280-285.\u003c/li\u003e\n \u003cli\u003eShi X, et al. The effect of posterior tibial slope on knee flexion in total knee arthroplasty. Clin Orthop Relat Res. 2013;471(9):2958-2963.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Total knee arthroplasty, Posterior tibial slope, Robot-assisted surgery, Forgotten joint score, Individualized reconstruction, Regression analysis","lastPublishedDoi":"10.21203/rs.3.rs-9392901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9392901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnder the premise of high-precision osteotomy enabled by robot-assisted total knee arthroplasty (TKA), this study compared functional outcomes between a population-wide optimal posterior tibial slope (PTS) target and individualized restoration of the native anatomical PTS. It also quantified the dose‒response relationship between PTS deviation from the native angle and the Forgotten Joint Score-12 (FJS-12).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective analysis included 240 patients who underwent primary unilateral TKA in our hospital from August 2021 to June 2024. Patients were divided into conventional and robot-assisted groups (120 patients each) according to surgical method. All patients received the same brand of posterior-stabilized prosthesis. The PTS was measured on pre- and postoperative CT scans, and the osteotomy error (|actual PTS \u0026ndash; target PTS|) was calculated. At the 1-year follow-up, the primary outcomes were the maximum active flexion angle and FJS-12 score; the secondary outcomes included the Knee Society Score, Oxford Knee Score, WOMAC score, anterior knee pain VAS score, tibial anterior translation distance, and complication rate. Multivariate linear and quadratic regression models were used to assess associations between postoperative PTS and clinical function, adjusting for age, sex, BMI, and preoperative flexion.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBaseline characteristics were comparable between the groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The incidence of osteotomy error was significantly lower in the robot-assisted group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At 1 year, the robot-assisted group achieved greater maximum flexion (121.5\u0026deg; \u0026plusmn; 9.2\u0026deg; vs 118.3\u0026deg; \u0026plusmn; 10.1\u0026deg;) and FJS-12 (68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8 vs 64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3) than did the conventional group (both P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate regression revealed a positive linear correlation between postoperative PTS and maximum flexion (β\u0026thinsp;=\u0026thinsp;1.9, 95% CI 1.2\u0026ndash;2.6, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and a significant quadratic (inverted U-shaped) relationship between PTS and FJS-12, peaking at approximately 5.3\u0026deg;. Subgroup analysis indicated that patients with |actual PTS \u0026ndash; native PTS| \u0026le; 2\u0026deg; had markedly higher FJS-12 scores than those with \u0026gt;\u0026thinsp;2\u0026deg; deviation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eUnder precise osteotomy conditions, the postoperative PTS is nonlinearly associated with subjective functional outcomes, with a population-level optimum of approximately 5.3\u0026deg;. For patients whose native PTS approximates this value, population-based and individualized targets converge; however, greater PTS deviation from native anatomy independently impairs FJS-12 scores, suggesting that individualized native PTS restoration is prioritized to improve patient satisfaction. These findings warrant validation in prospective randomized controlled trials.\u003c/p\u003e","manuscriptTitle":"Deviation from Native Posterior Tibial Slope and Dose‒Response Relationships with Forgotten Joint Score-12 in Robot-Assisted Total Knee Arthroplasty: A Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 07:04:21","doi":"10.21203/rs.3.rs-9392901/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T02:22:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:28:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T18:24:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T12:52:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41946184249603387473962674845731105615","date":"2026-04-29T12:58:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13918474680079506805915941380573373599","date":"2026-04-29T11:08:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158801855735883089279144950475908566117","date":"2026-04-27T14:36:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-27T10:38:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T02:36:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-23T02:35:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2026-04-12T08:44:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dc16b3eb-3785-41b3-be74-97bf3e2af22e","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T02:22:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:28:06+00:00","index":22,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T18:24:43+00:00","index":21,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T12:52:24+00:00","index":20,"fulltext":""},{"type":"reviewerAgreed","content":"41946184249603387473962674845731105615","date":"2026-04-29T12:58:38+00:00","index":18,"fulltext":""},{"type":"reviewerAgreed","content":"13918474680079506805915941380573373599","date":"2026-04-29T11:08:25+00:00","index":17,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T02:39:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 07:04:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9392901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9392901","identity":"rs-9392901","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}