KangDuo vs. da Vinci robot-assisted pyeloplasty: a propensity score-matched analysis of surgical outcomes

Introduction

Ureteropelvic junction obstruction (UPJO) impairs urinary drainage from the renal pelvis to the proximal ureter and may lead to progressive hydronephrosis, recurrent infection, and renal function deterioration. Open Anderson-Hynes dismembered pyeloplasty remains the standard surgical treatment, providing durable relief of obstruction through complete excision of the stenotic segment and tension-free anastomosis (1). With the evolution of minimally invasive surgery, laparoscopic pyeloplasty has demonstrated success rates comparable to open repair while offering reduced complications and faster recovery (2,3). However, its technical complexity and demanding intracorporeal suturing have limited widespread adoption.

Robot-assisted pyeloplasty (RAP) has been introduced to overcome these limitations. The da Vinci (DV) robotic system, with its three-dimensional visualization and articulated instruments, has become the most widely used platform and has shown excellent and reproducible outcomes in pyeloplasty (4-6). In recent years, alternative robotic systems have emerged, including the KangDuo (KD) surgical robot, which has been increasingly applied in urological reconstruction (7,8). Our group previously reported a preliminary comparison of 16 KD-RAP and 16 DV-RAP cases, demonstrating the technical feasibility and safety of the KD system in pyeloplasty (9). Nevertheless, the study was constrained by a small sample size and the absence of adjustment for baseline differences between groups. Moreover, only Anderson-Hynes dismembered primary pyeloplasty was included, whereas non-dismembered techniques and secondary pyeloplasty were not evaluated.

In the context of an expanding robotic landscape, robust comparative evidence is required to determine whether newer platforms can achieve outcomes comparable to established systems. Given the practical challenges of randomized trials in surgical robotics, propensity score matching (PSM) offers a methodologically sound approach to reduce selection bias in observational studies. Therefore, this study aims to compare perioperative and surgical outcomes between KD-RAP and DV-RAP using a PSM design, with a larger cohort and more comprehensive assessment. This analysis seeks to provide clinically meaningful evidence to guide the future development and adoption of emerging robotic platforms in pyeloplasty. We present this article in accordance with the STROBE reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0448/rc).

Methods

Patient selection

This study included consecutive UPJO patients who underwent KD-RAP between January 2024 and September 2025 and DV-RAP between May 2020 and September 2025 at Peking University First Hospital. Patient data were prospectively collected in our Reconstruction of the Urinary Tract: Technology, Epidemiology, and Result (RECUTTER) database. Patients with concomitant uncontrolled urinary tract infection, coagulation dysfunction, pregnancy or lactation, inability to tolerate surgery, inability or reluctance to cooperate during follow-up, or unclear clinical information were excluded. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Peking University First Hospital (No. 2024yan083). Informed consent was waived due to the retrospective design of the study.

Robot system introduction

In this study, DV-RAP was performed using the DV-Si or DV-Xi system. KD-RAP was performed using the KD-SR-1000 (KD 1.0) or KD-SR-2000 (KD 2.0) system. The KD system operates on a master-slave model, comprising a surgeon console, a patient-side cart, and a vision cart. The vision cart provides real-time three-dimensional imaging, enabling the surgeon to make informed decisions. The surgeon console controls the robotic instruments on the patient-side cart, which replicate and execute the planned surgical actions. Unlike the KD 1.0, which has three arms, the KD 2.0 is a four-arm surgical robot (Figure 1).

Figure 1 KangDuo-SR-2000 system. (A) Patient side cart. (B) Surgeon console. (C) Vision cart.

Surgical procedures

All patients underwent either dismembered pyeloplasty (1,8,10,11) or non-dismembered pyeloplasty (12,13). The basic procedural steps for pyeloplasty were similar between the KD-RAP and DV-RAP groups. The choice of surgical technique was determined by experienced urologists based on the individual patient’s condition. Figure 2 illustrated the surgical process of KD robot-assisted Anderson-Hynes dismembered pyeloplasty. All pyeloplasty procedures in both the KD-RAP and DV-RAP cohorts were performed by a single surgeon, who had accumulated extensive experience with robotic urological surgery prior to this study.

Figure 2 KangDuo robot-assisted pyeloplasty procedure. (A) Identification of the UPJO and surrounding anatomical landmarks. (B) Creation of an oblique ureterotomy above the UPJO. (C) Suturing of the posterior wall anastomosis between the ureter and renal pelvis. (D) Placement of a Double-J ureteral stent in an antegrade fashion prior to anterior wall closure. (E) Completion of the anterior wall anastomosis. (F) Final appearance of the reconstructed UPJO demonstrating a tension-free repair. UPJO, ureteropelvic junction obstruction.

Data collection and Follow-up

The demographics, lesion characteristics, perioperative results, intraoperative details, surgical outcomes and follow-up data were collected prospectively. The operative time was calculated from the time of the skin incision for the first port to suturing of the last port. Complete surgical success was defined as resolution of both clinical symptoms and obstruction on radiographic evaluation, with no recurrence of UPJO by the time of the last follow-up. The follow-up schedule for patients included visits at 1, 3, 6, and 12 months postoperatively, followed by annual visits thereafter. Follow-up assessments included medical history collection, laboratory tests, and imaging evaluation.

Statistical analyses

SPSS version 26.0 and R version 4.4.1 were used for statistical analysis. PSM analysis was performed to address baseline imbalances between the KD-RAP and DV-RAP groups. The 1:1 nearest-neighbor matching method was employed, with a caliper width of 0.2. The PSM model included all baseline covariates (except for robotic system version) presented in Table 1. Balance between the two groups was assessed using standardized mean differences (SMDs). Absolute SMDs <0.1 were considered indicative of good balance, while values between 0.1 and 0.2 were considered acceptable. To assess the robustness of our findings and address potential concerns regarding sample exclusion in PSM, inverse probability of treatment weighting (IPTW) analysis using average treatment effect on the treated weighting (ATT) was performed as a sensitivity analysis.

To address the potential learning curve effect, we performed a chronological analysis of operative times within each KD subgroup. Cases were arranged in chronological order according to the date of surgery, and operative time was plotted against case sequence number. Moving average curves were fitted with a 5-case window for the KD 1.0 cohort and a 3-case window for the KD 2.0 cohort due to differences in sample size. Linear regression and Spearman’s rank correlation were used to assess the correlation between case number and operative time.

Categorical variables were expressed as frequencies and percentages. Continuous variables were presented as mean ± standard deviation for normally distributed data or as median (interquartile range, IQR) for non-normally distributed data. Categorical variables were analyzed using the chi-square test, Fisher’s exact test, or McNemar test, and continuous variables were analyzed using the Mann-Whitney U test or Wilcoxon signed-rank test. After PSM, the ordinal three-category variable ASA grade was analyzed using the marginal homogeneity test, and operative laterality was analyzed using Bowker’s test. Effect sizes were reported as median or mean differences for continuous variables, and as odds ratios for categorical variables. A two-tailed P value of less than 0.05 was considered statistically significant.

Results

Baseline characteristics

The baseline characteristics of the two groups were shown in Table 1. Before PSM, 263 patients with DV-RAP and 74 patients with KD-RAP were included (Figure 3). There were significant differences between the two groups in terms of surgical side (P=0.01) and preoperative ureteral stent placement (P=0.03). After 1:1 PSM, the differences in baseline characteristics between the two groups were no longer significant (all P>0.05 and all absolute SMDs <0.1, Table 1, Figure 4A). In the matched cohort, 66 patients underwent DV-RAP (median age 28 years, IQR: 23–36 years; 39 males and 27 females), and 66 patients underwent KD-RAP (median age 30 years, IQR: 21–40 years; 35 males and 31 females). In the DV-RAP group, 10 patients (15.2%) had congenital renal malformations, including 6 cases of horseshoe kidney, 2 cases of duplicated kidney, 1 case of nephroptosis, and 1 case of megacalicosis. Additionally, 20 patients (30.3%) had crossing vessels, 15 patients (22.7%) had renal calculus, and 15 patients (22.7%) underwent secondary pyeloplasty. In the KD-RAP group, 10 patients (15.2%) had congenital renal malformations, including 5 cases of horseshoe kidney, 2 cases of nephroptosis, 1 case of duplicated kidney, 1 case of ectopic kidney, and 1 case of solitary kidney. Additionally, 15 patients (22.7%) had crossing vessels, 13 patients (19.7%) had renal calculus, and 16 patients (24.2%) underwent secondary pyeloplasty.

Figure 3 Study flowchart of patient selection and propensity score matching analysis. DV, da Vinci; IPTW, inverse probability of treatment weighting; KD, KangDuo; KD 1.0, KangDuo-SR-1000; KD 2.0, KangDuo-SR-2000; PSM, propensity score matching; RAP, robotic-assisted pyeloplasty; UPJO, ureteropelvic junction obstruction.

Figure 4 Covariate balance before and after PSM and IPTW. (A) Absolute standardized mean differences of baseline covariates between the DV-RAP and KD-RAP groups before and after PSM. (B) Absolute standardized mean differences of baseline covariates between the two groups before and after IPTW. ASA, American Society of Anesthesiologists physical status classification system; BMI, body mass index; DV-RAP, da Vinci robot-assisted pyeloplasty; eGFR, estimated glomerular filtration rate; IPTW, inverse probability of treatment weighting; KD-RAP, KangDuo robot-assisted pyeloplasty; PSM, propensity score matching.

Surgical and follow-up outcomes

All procedures were performed successfully without conversion to open or laparoscopic surgery. The median operative time {DV-RAP: 132 [IQR: 107–153] vs. KD-RAP: 149 [IQR: 132–181] minutes, effect size [95% confidence interval (CI)]: 19.5 [2.5–36.5], P=0.02, Table 2} and postoperative length of stay (PLOS) {DV-RAP: 4 [IQR: 4–5] vs. KD-RAP: 5 [IQR: 4–7] days, effect size [95% CI]: 1 [0.5–1.5], P<0.001, Table 2} were significantly longer in the KD-RAP group than the DV-RAP group. There was no significant difference in estimated blood loss (P=0.82). At a median follow-up of 8 (IQR: 4–13) months for the DV-RAP group and 7 (IQR: 3–14) months for the KD-RAP group, no difference was found in the success rates between the two groups (93.9% vs. 90.9%, P=0.75, Table 2).

Regarding postoperative complications, no significant difference in complication rates was observed between the two groups (P=0.63). In the KD-RAP group, three patients experienced postoperative complications, all of which were urinary tract infections that resolved after oral or intravenous antibiotics. In the DV-RAP group, one complication was recorded, which was also urinary tract infection. According to the Clavien-Dindo classification of surgical complications (14), all four complications were classified as grade II. In addition, there were no significant differences between the two groups in estimated glomerular filtration rate (eGFR) (P=0.09) at the final follow-up (Table 2).

Stratified by robotic system version

Given the heterogeneity of robotic system versions, we performed an exploratory analysis stratifying the whole and matched cohorts by version, respectively. In the whole cohort, no significant differences were observed between KD 1.0 and KD 2.0 in any surgical outcomes, whereas DV-Si and DV-Xi differed significantly in estimated blood loss {DV-Si: 20 [10–30] vs. DV-Xi: 20 [10–20] mL; effect size [95% CI]: 0 [0–10]; P=0.008) and PLOS (DV-Si: 4 [4–5] vs. DV-Xi: 5 [4–6] days; effect size [95% CI]: 0 [−1 to 0]; P=0.015} (Table S1).

Given the potential differences between DV-Si and DV-Xi, we further compared each with KD separately. In the whole cohort, DV-Si was associated with significantly shorter operative time {DV-Si: 135 [110–163] vs. KD-RAP: 149 [133–183] minutes; effect size [95% CI]: 19 [9–29]; P<0.001} and PLOS {DV-Si: 4 [4–5] vs. KD-RAP: 5 [4–7] days; effect size [95% CI]: 1 [0–1]; P<0.001} compared with KD, and after matching, only the difference in PLOS remained significant {DV-Si: 4 [4–4] vs. KD-RAP: 5 [4–7] days; effect size [95% CI]: 1 [0.5–2]; P=0.003} (Table S2). Similarly, DV-Xi demonstrated significantly shorter operative time than KD in the whole cohort {DV-Xi: 129 [107–171] vs. KD-RAP: 149 [133–182] minutes; effect size [95% CI]: 27 [15–38]; P<0.001}, and in the matched cohort, DV-Xi remained superior to KD in both operative time {DV-Xi: 122 [105–138] vs. KD-RAP: 149 [134–182] minutes; effect size [95% CI]: 36 [12–59]; P=0.006} and PLOS {DV-Xi: 4 [4–6] vs. KD-RAP: 6 [5–7], effect size [95% CI]: 1.5 [0–2], P=0.006} (Table S3).

Sensitivity analysis

To address the 8/74 (10.8%) sample loss in the KD-RAP group following PSM, we performed IPTW as a sensitivity analysis to validate the robustness of our findings (Figure 4B, Table S4). The IPTW results were consistent with the PSM analysis: DV-RAP remained associated with significantly shorter operative time compared with KD-RAP {effect size [95% CI]: 25.1 [10.8–39.3]; P<0.001}. PLOS was also shorter in the DV-RAP group {effect size [95% CI]: 0.7 [0.2–1.3]; P=0.008}. No significant between-group differences were observed in estimated blood loss, transfusion requirement, complete success rate, complication rate, or follow-up eGFR (Table 2). These findings confirm the robustness of our primary PSM results.

To address the potential temporal bias arising from the non-overlapping study periods (DV-RAP: May 2020–September 2025; KD-RAP: January 2024–September 2025), we performed a sensitivity analysis restricted to the overlapping period (January 2024–September 2025). Notably, all DV procedures performed during this overlapping period were conducted using the Xi system, rendering the DV-Xi vs. KD comparison inherently a concurrent cohort analysis, which has been presented above.

Learning curve analysis

Given the surgeon’s prior experience with the KD platform since 2021, we assessed whether operative efficiency changed over time during the study period. In the KD 1.0 cohort (n=51), chronological analysis revealed stable operative times throughout the case series, with no significant correlation between case number and operative time (Spearman’s ρ=0.134, P=0.35; Figure 5A). In the KD 2.0 cohort (n=23), a modest negative correlation was observed between case number and operative time (Spearman’s ρ=−0.374, P=0.08; Figure 5B), but this trend did not reach statistical significance, and the overall magnitude of improvement was small.

Figure 5 Learning curve for operative time in KangDuo robot-assisted pyeloplasty. (A) KD 1.0 robot-assisted pyeloplasty (n=51). (B) KD 2.0 robot-assisted pyeloplasty (n=23). Each gray dot represents the operative time of an individual case plotted against its chronological case sequence number. The solid red line represents the moving average of operative time calculated over a sliding window. The dashed blue line indicates the linear regression trend, and the shaded blue area represents the 95% confidence interval. KD 1.0, KangDuo-SR-1000; KD 2.0, KangDuo-SR-2000.

Discussion

This study aimed to compare the clinical outcomes and safety of KD-RAP and DV-RAP. Through 1:1 PSM, baseline differences between the two groups were successfully controlled, ensuring the reliability of the results. In the matched cohort, we found no significant differences between the two robotic systems in terms of surgical success rate, complication incidence, and renal function recovery, with both achieving high efficacy and safety. However, the KD-RAP group demonstrated significantly longer operative time and PLOS compared to the DV-RAP group. These differences were further corroborated by IPTW sensitivity analysis, confirming the robustness of our findings. Although the surgical success rate in the KD-RAP group was comparable to that of the DV-RAP group, indicating the safety and efficacy of KD in pyeloplasty, the observed discrepancies in operative efficiency warrant careful consideration.

In terms of perioperative indicators, there was a significant difference in operative time between the groups after PSM. The median operative time for the DV-RAP group was 132 minutes, while the KD-RAP group had a median of 149 minutes. This result is consistent with a previous small-sample report (9). Several studies comparing the KD and DV systems have also reported that the KD system generally takes longer in terms of operative time across various procedures (15-18). However, no significant differences were observed in cystectomy (19) and colorectal cancer surgery (20,21). The extended operative time may be attributed to several factors: the KD system was introduced into clinical practice later, so surgeons were still becoming familiar with its operation; differences in the kinematics of the robotic arms and control interfaces between the two systems; and the KD system may require more time during suturing or instrument exchanges.

Notably, our learning curve analysis revealed that in the KD 1.0 cohort, the surgeon had already surpassed the learning curve before the study period, with stable operative times throughout the case series. In the KD 2.0 cohort, a modest negative correlation was observed between case number and operative time, suggesting a slight improvement in operative efficiency with increasing experience, with stabilization observed after approximately the 8^th to 10^th case. However, this trend did not reach statistical significance, and the early KD 2.0 cases already achieved operative times comparable to the mature KD 1.0 phase, supporting rapid skill transferability between the two system generations. Importantly, our stratified analysis by robotic system version revealed that both DV-Si and DV-Xi demonstrated significantly shorter operative times than KD in the whole cohort, and in the matched cohort, DV-Xi remained superior to KD in both operative time and PLOS. These findings suggest that the observed time discrepancy may not be entirely attributable to the learning curve, but rather may reflect inherent differences in system design and workflow optimization between the platforms. With increased experience and system upgrades, this time discrepancy may gradually diminish, but further investigation is warranted.

The KD-RAP group also had a significantly longer PLOS compared to the DV-RAP group, a finding that was consistently observed in both PSM and IPTW analyses, and further substantiated by the stratified comparison. While the absolute difference was small and may have limited clinical significance, this disparity could be related to institutional protocols, surgeon preference, or subtle differences in postoperative recovery trajectories. There were no significant differences between the two groups in estimated blood loss, transfusion rate, or other perioperative indicators. This result suggests that, despite the differences in operative time and PLOS, the KD system did not increase the surgical risk for patients. Existing studies also indicate that, although the KD system has a longer operative time and PLOS, its intraoperative performance and postoperative recovery outcomes are not significantly different from those of the DV system (15-19). This suggests that both systems are comparable in terms of minimally invasive efficiency.

The KD and DV groups had high and comparable success rates. At the final follow-up, the success rate in the KD-RAP group was 90.9%, while that in the DV-RAP group was 93.9%, with no significant difference between the groups. This is consistent with a previous small-sample report, in which the success rates for the KD and DV groups were 93.75% and 100%, respectively (9). Additionally, randomized controlled trials in cystectomy, partial nephrectomy, and radical prostatectomy demonstrated no significant difference between the KD and DV systems in surgical success rate with both showing comparable clinical outcomes (17,19). Current evidence supports that KD system can achieve comparable efficacy to the DV system in urological surgeries.

Additionally, both KD-RAP and DV-RAP groups had low complication rates with no significant differences. All complications of the two groups were Clavien-Dindo grade II and patients recovered with conservative treatment. There were no major complications (grade ≥ III) or equipment-related adverse events. Overall, both robotic systems demonstrated comparable safety profiles. Previous studies also indicate that the complication rates for urological surgeries using KD are similar to those of DV (15-19), suggesting that the KD system demonstrates good safety in urological procedures.

From a technical perspective, both KD and DV systems operate as master-slave robotic platforms. However, the KD system introduces distinctive ergonomic innovations. Specifically, the KD platform features an open surgeon console that allows the surgeon to maintain an upright neck position, thereby significantly relieving neck fatigue during prolonged procedures. Additionally, the suspended surgical arm design facilitates flexible instrument positioning and adjustments. The open console architecture also fosters enhanced active communication and interaction between the primary surgeon and the bedside assistant, as the surgeon remains positioned away from the operating table while maintaining direct visual and verbal contact with the team.

Regarding economic considerations, the KD platform offers potential cost-saving advantages. The KD robot has inherently lower manufacturing costs and demonstrates compatibility with conventional laparoscopic equipment. These characteristics suggest a relatively lower price point compared to the DV system, potentially reducing the financial burden on healthcare institutions and expanding accessibility to robot-assisted surgery (22). However, no formal cost analysis was performed in this study, and the final commercial pricing remains to be established. Prospective studies incorporating structured cost-effectiveness analyses are needed to substantiate these speculations.

This study has several limitations. First, although PSM was used to balance the baseline imbalance between the two groups, selection bias and the influence of unmeasured confounding factors could not be fully eliminated. Second, the sample size in the matched cohort was relatively small, which may have reduced the statistical power to detect differences in certain outcomes. Third, as a retrospective study, detailed technical parameters such as docking time were not routinely documented in medical records and thus could not be compared. While both systems share similar master-slave teleoperation architectures, subtle technical differences may theoretically influence outcomes, and their clinical significance warrants prospective evaluation. Furthermore, the median follow-up period was relatively short, and long-term surgical success rates and renal function outcomes still require validation with longer follow-up. Finally, all surgeries in this study were performed by an experienced urological team. The reproducibility of these results in centers with less experienced teams or varying levels of expertise remains to be further investigated. Future multicenter, prospective, randomized controlled trials are necessary to further validate the conclusions of this study and clarify the long-term value of the KD system in the treatment of UPJO.

Conclusions

KD-RAP was comparable to DV-RAP in terms of surgical safety, perioperative outcomes, and clinical efficacy. Although the operative time and PLOS of KD were slightly longer, they did not increase the risk of complications or affect postoperative recovery. The KD system can serve as a safe and effective alternative platform for pyeloplasty.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0448/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0448/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0448/prf

Funding: This work was supported by the National Key R&D Program of China (No. 2023YFC2413400) and Capital’s Funds for Health Improvement and Research (No. 2024-1-4072).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-0448/coif). Xuesong Li serves as an Editor-in-Chief of Translational Andrology and Urology from March 2026 to March 2029. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Peking University First Hospital (No. 2024yan083). Informed consent was waived due to the retrospective design of the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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