The Breaking Point in Robotic Pancreaticoduodenectomy: Predictors of Conversion and Early Postoperative Impact in a Tertiary Referral Center

The Breaking Point in Robotic Pancreaticoduodenectomy: Predictors of Conversion and Early Postoperative Impact in a Tertiary Referral Center | 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 The Breaking Point in Robotic Pancreaticoduodenectomy: Predictors of Conversion and Early Postoperative Impact in a Tertiary Referral Center Alessia Fassari, Edouard Wasielewski, Antoine Castel, Hector Prudhomme, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8412822/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Robotic pancreaticoduodenectomy (RPD) is increasingly performed in high-volume centers, yet conversion to open surgery remains a critical intraoperative event. Often perceived as a technical failure, conversion may instead represent a safety-driven strategy in complex cases. Data on its determinants and peri- and postoperative impact in mature robotic programs remain limited. Methods. This retrospective single-center cohort study included adult patients undergoing elective RPD between April 2018 and October 2025 at a tertiary referral center for pancreatic surgery. Variables associated with conversion at univariable analysis (p < 0.10) were entered into a multivariable logistic regression model, with statistical significance set at p < 0.05. Peri- and postoperative outcomes were compared between converted and non-converted cases. Results. During the study period, 130 patients underwent RPD, of whom 16 (12.3%) required conversion. On multivariable analysis, vascular contact requiring resection was the strongest factor independently associated with conversion (p < 0.001). Periampullary tumor location (p = 0.023) and previous pancreatitis (p = 0.008) were also independently associated with conversion. Converted cases were characterized by a significantly higher rate of intraoperative bleeding requiring transfusion. Overall and major postoperative complication rates, including clinically relevant postoperative pancreatic fistula and R0 resection rates, did not differ significantly between groups. Conversion was associated with longer hospital stay and prolonged high-dependency unit stay. Conclusions. In this tertiary-center experience, conversion during RPD was mainly driven by preoperatively identifiable anatomical and disease-related factors. When anticipated and performed in a controlled manner, conversion did not adversely affect major postoperative outcomes. Robotic Pancreatic Surgery Pancreaticoduodenectomy Surgical Conversion Predictive Factors Postoperative Outcomes. Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Robotic pancreaticoduodenectomy (RPD) has emerged as a major evolution in minimally invasive pancreatic surgery, offering enhanced three-dimensional visualization, wristed instrumentation, and improved surgeon ergonomics. While these technical advantages over conventional laparoscopy are increasingly recognized, the extent to which RPD translates into a meaningful clinical benefit compared with open pancreaticoduodenectomy remains incompletely defined. Recent high-quality comparative studies, including the DIPLOMA-2 trial, have primarily focused on highly selected patient populations, restricting enrollment to upfront-resectable tumors without major vascular involvement and limiting participation to expert centers operating under strict credentialing requirements [ 1 ]. Although such trial designs ensure strong internal validity, they inevitably constrain external generalizability. Consequently, the real-world safety, effectiveness, and intraoperative behavior of RPD in less selected, clinically heterogeneous populations remain to be fully characterized. Within this context, conversion to open surgery represents a pivotal intraoperative event during RPD. Traditionally regarded as a marker of technical failure, conversion may instead reflect sound surgical judgment in response to intraoperative challenges such as bleeding, unfavorable anatomy, limited exposure, or oncologic concerns. Several patient-, disease-, and procedure-related factors have been proposed as drivers of conversion in minimally invasive pancreatic surgery [ 2 – 4 ]; however, data specifically addressing RPD remain limited. Against this background, the aims of the present single-center retrospective study were threefold: (1) to identify patient-, disease-, and procedure-related factors associated with conversion during RPD; (2) to determine which of these factors remained independently associated with conversion after multivariable analysis; and (3) to characterize the perioperative and early postoperative impact of conversion, with particular emphasis on postoperative morbidity and length of hospital stay. By addressing these objectives, this study seeks to clarify both the determinants and the clinical implications of conversion during RPD within a high-volume, mature robotic pancreatic surgery program. 2. PATIENTS AND METHODS Study design and setting This retrospective single-center cohort study was designed, conducted, and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 5 ]. It included all consecutive adult patients who underwent RPD at a tertiary referral center of pancreatic surgery between April 2018 and October 2025. The institution is a dedicated center for complex oncologic surgery, with a strong focus on hepatopancreatobiliary (HPB) procedures and is also active in liver transplantation. The center is equipped with three da Vinci robotic systems, a dedicated pancreatic surgery unit, and comprehensive perioperative facilities, including an intensive care unit (ICU) and a high-dependency unit (HDU), allowing structured postoperative management of high-risk patients. The robotic pancreatic program was established and conducted as a single-surgeon series by a dedicated pancreatic surgeon with extensive prior experience in open pancreaticoduodenectomy and formal training in minimally invasive and robotic surgery. At the start of the study period, the surgeon had already performed more than 500 pancreatic resections using open and laparoscopic approaches, providing a solid background in pancreatic surgery at the initiation of the robotic program. The present series also encompasses the early phase of the robotic learning curve. All RPDs were performed using a standardized four-arm robotic platform (da Vinci system; Intuitive Surgical, Sunnyvale, CA, USA), with a uniform port-placement strategy and consistent operative setup. The study was conducted in accordance with the Declaration of Helsinki [ 6 ]. Institutional review board approval was obtained, and the requirement for individual informed consent was waived due to the retrospective nature of the study and full anonymization of patient data. Patient selection Variables and data collection Data were extracted from a prospectively maintained institutional database and completed through targeted review of electronic medical records and operative reports. Patient-related variables included demographic characteristics (age and sex), body mass index (BMI, analyzed both as a continuous variable and by categories), comorbidity burden as assessed by the Charlson Comorbidity Index (CCI), history of previous abdominal surgery, and documented anatomical variations when available [ 7 ]. Disease-related variables included the underlying diagnosis, tumor location and size on preoperative imaging, with tumors categorized as periampullary (including bile duct, duodenal, and ampullary tumors) or pancreatic head tumors (including pancreatic ductal adenocarcinoma and intraductal papillary mucinous neoplasms). Histology was classified as benign or malignant. Tumor stage at diagnosis was defined as upfront resectable, borderline resectable, or locally advanced based on radiologic vascular involvement (venous or arterial abutment or encasement) and biological criteria, including a serum carbohydrate antigen (CA) 19 − 9 level more than 500 units/ml [ 8 ]. The administration of neoadjuvant therapy was also recorded. Surgeon- and procedure-related variables included learning-curve phase, the need for venous vascular resection, main pancreatic duct diameter (≤ 3 mm), and pancreatic texture (soft vs firm). Conversion served as the dependent variable in the primary analyses and was defined as any unplanned laparotomy occurring after initiation of the robotic approach, irrespective of timing or indication, and not performed solely for specimen extraction. Based on a prior internal assessment of operative time and perioperative outcomes, the learning curve for RPD at our institution was defined as the first 40 consecutive procedures. Accordingly, procedures were classified into two experience-based phases: an early learning phase (cases 1–40) and a proficiency phase (cases > 40) [ 9 ]. This dichotomization was used as an independent variable in multivariable models to account for the potential impact of surgical experience on the risk of conversion. Primary and Secondary Outcomes The primary aim of this study was to identify patient-, disease-, and surgeon- or procedure-related factors independently associated with intraoperative transition to an open approach during RPD. The primary reason for conversion was systematically recorded to distinguish between emergency and strategic conversions. Secondary outcomes were evaluated to assess the perioperative and early postoperative clinical impact of conversion and included intraoperative bleeding needing transfusions, operative time, overall postoperative morbidity, complication severity, length of hospital stay, HDU and ICU length of stay, hospital readmission within 30 days, resection margins and 30-day mortality. Postoperative complications and grading were defined according to internationally accepted criteria [ 10 ]. Clinically relevant postoperative pancreatic fistula (POPF grade B or C) was defined according to the International Study Group on Pancreatic Surgery (ISGPS) classification [ 11 ]. Delayed gastric emptying and postpancreatectomy hemorrhage were also defined and graded according to ISGPS criteria [ 12 , 13 ]. Biliary fistula was defined according to the International Study Group of Liver Surgery (ISGLS) metrics [ 14 ]. Statistical analysis All statistical analyses were performed using IBM SPSS Statistics (IBM Corp., Armonk, NY, USA). All tests were two-sided, and a p value < 0.05 was considered statistically significant. Continuous variables are reported as median (interquartile range), and categorical variables as counts and percentages. To identify factors associated with conversion, patient-, disease-, and procedure-related variables were first assessed individually using univariable analyses. Continuous variables were compared using the Mann-Whitney U test, while categorical variables were compared using Fisher’s exact test, given the limited number of conversion events. Variables showing a potential association with conversion at univariable analysis (p < 0.10), were entered into a multivariable logistic regression model to identify independent predictors of conversion. Results are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Peri- and postoperative outcomes were compared between converted and non-converted cases using univariable analyses only, applying Fisher’s exact test for categorical variables and the Mann-Whitney U test for continuous variables. The extent and pattern of missing data were assessed for all collected data. When missingness was limited, complete-case analyses were performed. Factors with substantial missingness were excluded from multivariable analyses. 3. RESULTS Temporal trends and study population Figure 1 illustrates the temporal trends in RPD volume and corresponding conversions over the study period. A progressive increase in annual case volume was observed, reflecting the consolidation of the robotic pancreatic program over time. Despite this volume expansion and the inclusion of increasingly complex cases, the number of conversions remained low and relatively stable, suggesting a controlled adoption of the robotic approach. Overall, 130 patients underwent RPD during the study period, of whom 16 (12.3%) required conversion to an open approach. Baseline patient-, disease-, and procedure-related characteristics stratified by conversion status are summarized in Table 1 . Table 1 Patient, disease, and procedural characteristics stratified by conversion during RPD. Baseline patient-, disease-, and procedure-related characteristics of patients undergoing RPD, stratified by conversion status. Continuous variables are expressed as median (IQR) and categorical variables as number (%). P -values are based on univariable comparisons between converted and non-converted cases, with a screening threshold set at p < 0.10. Patient-Related Factors Variables Total (n = 130) Unconverted RPD (n = 114) Converted RPD (n = 16 ) p-value Age [median, (IQR)] (y) 67.7 (59.8–74.2) 67.2 (59.4–74.1) 72.3 (66.1–76.3) 0.10 Sex - male [n (%)] - female [n (%)] 55 (42.3%) 75 (57.7%) 46 (40.4%) 68 (59.6%) 9 (56.3%) 7 (43.7%) 0.28 CCI score - < 4 [n, (%)] - ≥ 4 [n, (%)] 69 (53.1%) 61 (46.9%) 64 (56.1%) 50 (43.9%) 5 (31.2%) 11(68.8%) 0.10 BMI category (kg/m²) - < 25 [n, (%)] - ≥ 25 [n, (%)] 71 (54.6%) 59 (45.4%) 66 (57.9%) 48 (42.1%) 5 (31.3%) 11 (68.8%) 0.06 Previous abdominal surgery [n (%)] 82 (63.1%) 73 (64%) 9 (56.3%) 0.59 Previous Pancreatitis [n (%)] 15 (11.5%) 11 (9.6%) 4 (25%) 0.09 Anatomical variations - RHA from SMA [n, %] - Median Arcuate Ligament [n, %] - CHA from SMA [n, %] 11 (8.5%) 2 (1.5%) 3 (2.3%) 9 (7.9%) 2 (1.8%) 3 (2.6%) 2 (12.5%) 0 (0%) 0 (0%) 0.59 Disease-Related Factors Variables Total (n = 130) Unconverted RPD (n = 114) Converted RPD (n = 16) p-value Histology - Malignant - Benign 102 (78.5%) 28 (21.5%) 89 (78%) 25 (22%) 13 (81.3%) 3 (18.7%) 1.00 Tumor Location - Periampullary [n, (%)] - Pancreatic (Head/Isthmus/Uncus) [n, (%)] 57 (43.8%) 73 (56.2%) 46 (40.4%) 68 (59.6%) 11 (68.7%) 5 (31.3%) 0.004 Tumor size, [median (IQR)] (mm) 22 (15–30) 20 (15–28) 27.5 (13–38) 0.10 Stage at Diagnosis - Upfront Resectable [n, (%)] - Borderline Resectable [n, (%)] - Locally Advanced [n, (%)] 111 (85.4%) 18 (13.8%) 1 (0.8%) 97 (85.1%) 16 (14%) 1 (0.9%) 14 (87.5%) 2 (12.5%) 0 (0%) 0.92 Neoadjuvant Chemotherapy [n, (%)] 25 (19.2%) 23 (20.2) 2 (12.5%) 0.74 Procedure- and Surgeon-Related Factors Variables Total (n = 130) Unconverted RPD (n = 114) Converted RPD (n = 16) p-value Surgeon Experience* - Early Learning Phase: 1–40 procedures - Proficiency Phase: >40 procedures 40 (30.7%) 90 (69.3%) 34 (29.8%) 80 (70.2%) 6 (37.5%) 10 (62.5%) 0.57 Vascular contact requiring resection [n, %] 8 (6.2%) 1 (0.9%) 7 (43.8%) < 0.001 Main pancreatic duct ≤ 3 mm [n, %] 60 (46.2%) 49 (43%) 11(68.8%) 0.09 Soft pancreatic texture [n, %] 93 (71.5%) 79 (69.2%) 14 (87.5%) 0.153 RPD, Robotic Pancreaticoduodenectomy; CCI, Charlson-Comordbidity Index; BMI, Body Mass Index; RHA, Right Hepatic Artery; SMA, Superior Mesenteric Artery; CHA, Common Hepatic Artery; MPD, Main Pancreatic Duct. *In this study we used an institution-specific cut-off of 40 based on prior internal analysis [ 9 ]. Factors associated with conversion On univariable analysis, using a liberal screening threshold (p < 0.10), higher body mass index (BMI ≥ 25 kg/m²), a history of pancreatitis, and a main pancreatic duct diameter ≤ 3 mm showed a potential association with conversion and were retained as candidate variables for multivariable analysis. Age and comorbidity burden (CCI ≥ 4), although numerically higher in converted cases, did not meet the predefined inclusion threshold (p = 0.10) and were therefore not retained. Tumor location differed significantly between groups (p = 0.004), with a higher proportion of periampullary tumors among converted cases. Among procedure-related variables, vascular contact requiring resection showed the strongest association with intraoperative transition to an open approach (p < 0.001) (Table 1 ). In multivariable analysis, it remained the most powerful independent predictor of conversion (p = 0.001) (Table 2 ). Periampullary tumor location (p = 0.023) and previous pancreatitis (p = 0.008) were also independently associated with conversion. In contrast, BMI ≥ 25 kg/m² and a main pancreatic duct diameter ≤ 3 mm did not retain statistical significance after adjustment. Table 2 Multivariable logistic regression analysis of factors associated with conversion. Variables included in the multivariable model were selected based on clinical relevance and univariable analysis, with candidate predictors defined as those showing a potential association with conversion (p < 0.10) on univariable testing. In the multivariable analysis, a p value < 0.05 was considered statistically significant. Predictors of Conversion Odds Ratio (OR) 95% Confidence Interval p-value Vascular contact requiring resection 96.1 8.1–869.3 0.001 MPD ≤ 3 mm 0.54 0.11–2.12 0.33 BMI ≥ 25 kg/m² 2.17 0.51–9.26 0.30 Periampullary tumors 7.0 1.3–37.0 0.023 Previous pancreatitis 11.2 1.9–65.7 0.008 BMI, Body Mass Index; MPD, Main Pancreatic Duct. The ROC analysis was conducted to illustrate in-sample discrimination and should not be interpreted as evidence of predictive performance. The multivariable model showed good apparent discriminative ability, as illustrated by the ROC curve (Fig. 2), with an area under the curve (AUC) of 0.85. Reason for conversion To further characterize the mechanisms underlying conversion, operative reports were systematically reviewed and reasons for conversion were grouped into four predefined categories (Fig. 3). Vascular complications represented one of the most frequent causes (6 of 16 conversions), including portal or mesenteric venous injury, portal vein stenosis requiring resection, and bleeding at the gastroduodenal artery stump or portal anastomosis requiring open vascular control. Inflammatory or adhesive conditions accounted for six additional conversions, mainly due to dense peripancreatic inflammation, post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis, or extensive peritumoral adhesions. Technical or reconstructive limitations, such as inability to clearly identify the pancreatic duct or to safely perform the biliary anastomosis, led to three conversions. Finally, oncologic invasion precluding safe dissection was identified in one case. Importantly, only two of the sixteen conversions were performed as true emergency conversions due to uncontrolled intraoperative bleeding. In contrast, the remaining conversions were undertaken in a planned and timely manner, following early recognition of technical difficulty or unfavorable anatomy, and before the occurrence of hemodynamic instability or major intraoperative complications. Peri- and postoperative outcomes Perioperative and postoperative outcomes according to conversion status are detailed in Table 3 . Table 3 Surgical outcomes according to conversion status. Peri- and postoperative outcomes of patients undergoing robotic pancreaticoduodenectomy, stratified by conversion status. Categorical variables are reported as number (%), and continuous variables as median (interquartile range, IQR). Comparisons between converted and non-converted cases were performed using Fisher’s exact test for categorical variables and the Mann-Whitney U test for continuous variables. A p value < 0.05 was considered statistically significant. Peri- and Postoperative Outcomes Unconverted RPD (n = 114) Converted RPD (n = 16) p-value Intraoperative bleeding requiring transfusion [n (%)] 2 (1.8%) 5 (31.3%) 0.001 Operative Time [median, (IQR)] (min) 574 (546–605) 562 (550–628) 0.99 Postoperative Minor Complications (CD I-II) [n (%)] 70 (61.4%) 9 (56.3%) 0.79 Postoperative Major Complications (CD ≥ IIIa) [n (%)] 28 (24.6%) 6 (37.5%) 0.36 Clinically relevant DGE (B/C) [n (%)] 26 (22.8%) 5 (31.2%) 0.56 Clinically relevant PPH (B/C) [n (%)] 19 (16.7%) 5 (31.2%) 0.17 Clinically relevant POPF (B/C) [n (%)] 15 (13.2%) 2 (12.5%) 1.00 Biliary Fistula [n (%)] 18 (15.8%) 4 (25%) 0.46 Postoperative Transfusion [n (%)] 24 (21.1%) 5 (31.2%) 0.36 Reoperation [n (%)] 10 (8.7%) 3 (18.7%) 0.19 LOS [median (IQR)] (days) 13 (9–21) 22 (14–35) 0.033 HDU stay [median (IQR)] (days) 7.5 (5–12) 13 (7.5–14.5) 0.046 ICU stay [median (IQR)] (days) 0 (0-0.1) 0 (0-0.75) 0.12 Readmission [n (%)] 18 (15.8%) 4 (25%) 0.47 30 Days-Mortality [n (%)] 5 (4.4%) 1 (6.2%) 0.55 Negative Resection Margin, R0 [n (%)] 105 (92.1%) 13 (81.3%) 0.17 RPD, Robotic Pancreaticoduodenectomy; CD, Clavien-Dindo Classification System; DGE, Delayed Gastric Emptying; PPH, Postoperative Hemorrhage; POPF, Postoperative Pancreatic Fistula; LOS, Length of Stay; HDU, High Dependency Unit; ICU, Intensive Care Unit. Converted procedures were associated with a significantly higher rate of intraoperative bleeding requiring transfusion (31.3% vs 1.8%; p = 0.001). Operative time was comparable between converted and non-converted cases. No statistically significant differences were observed between converted and unconverted RPD in terms of minor complications, major complications (Clavien-Dindo ≥ IIIa), clinically relevant delayed gastric emptying (grade B/C), postpancreatectomy hemorrhage, clinically relevant POPF (grade B/C), biliary fistula, postoperative transfusion, reoperation rate, readmission, ICU stay, or 30-day mortality. Despite the absence of statistical significance, converted cases showed numerically higher rates of postoperative bleeding-related events and subsequent interventions, including need for transfusion, and reoperation. R0 resection rates were numerically lower in converted cases compared with fully robotic procedures (81.3% vs 92.1%), although this difference did not reach statistical significance (p = 0.17). Despite comparable complication rates, conversion was associated with significantly increased postoperative resource utilization, reflected by a longer median length of hospital stay (22 [IQR 14–35] vs 13 [IQR 9–21] days; p = 0.033) and prolonged high-dependency unit stay (13 [IQR 7.5–14.5] vs 7.5 [IQR 5–12] days; p = 0.046). 4. DISCUSSION The present findings highlight important elements influencing when and why conversion occurs during RPD and how these events translate into perioperative outcomes. A key strength of this study is the identification of predictors that are recognizable preoperatively or very early during the operation. This aspect is particularly relevant in robotic pancreatic surgery, as early recognition of conversion-predisposing factors allows optimization of patient selection, operative planning, and team readiness. Importantly, the predictors identified in our analysis predominantly reflect anatomical and inflammatory complexity rather than surgeon inexperience, supporting the applicability of these findings across centers with varying robotic volumes. In our experience, the conversion rate of 12.3% during RPD is consistent with contemporary robotic series, which generally report conversion rates between 5% and 13%, and remains substantially lower than those historically described for laparoscopic pancreaticoduodenectomy [ 2 , 3 , 15 ]. Beyond its occurrence, conversion should also be interpreted in terms of timing and intent. Large multicenter analyses, such as the European E-MIPS study by Löf et al., have highlighted the distinction between emergency conversions, often triggered by acute intraoperative events such as bleeding, and elective or strategic conversions undertaken in a controlled setting when operative conditions are unfavorable but stable [ 2 ]. In line with these observations, anticipating the risk of abandonment of the robotic approach in favor of laparotomy based on preoperative imaging and clinical history allows for a deliberate and timely change in operative strategy, rather than a late, reactive decision following prolonged dissection, cumulative inflammation, or significant blood loss. Within this framework, conversion should be viewed as an expression of appropriate surgical judgment rather than a failure of the minimally invasive approach, a concept further supported by the low proportion of emergency conversions observed in the present robotic series (2 of 16). Key Drivers of Conversion: What Can We Anticipate? In our multivariable model, three variables remained independently associated with conversion: vascular involvement requiring venous resection, periampullary tumor location, and a history of pancreatitis. The good in-sample discriminative performance of the multivariable model, as shown by the ROC analysis (Fig. 2), supports the clinical relevance of these factors, while emphasizing that conversion remains a context-dependent intraoperative decision rather than a fully predictable event. Vascular involvement emerged as the strongest predictor, reflecting the intrinsic limitations of minimally invasive surgery when safe proximal and distal vascular control cannot be reliably secured. This finding is consistent with reports from high-volume robotic series and multicenter experiences, including the study by Löf et al., in which vascular complexity and bleeding represented leading causes of conversion [ 2 ]. Similarly, robotic difficulty-scoring systems such as the PD-ROBOSCORE and the Tampa Difficulty Score have identified vascular involvement, venous resection, and bleeding-related parameters as markers of increased surgical complexity [ 16 , 17 ]. These observations underscore the critical role of meticulous preoperative staging, particularly triphasic computed tomography (CT) with dedicated vascular reconstructions, in identifying venous abutment, caliber changes, or collateralization that may compromise the safety of robotic dissection. Periampullary tumors, particularly distal bile duct and duodenal lesions, were also independently associated with conversion. These lesions are classically associated with a soft pancreatic gland and a small main pancreatic duct, a well-established anatomical setting linked to a challenging reconstructive scenario [ 18 , 19 ]. This combination increases technical complexity during both the resection and anastomotic phases and may lower the threshold for conversion when intraoperative conditions become unfavorable. Finally, a history of pancreatitis completed the triad of independent predictors. Pancreatitis is well known to induce peripancreatic fibrosis, obliteration of tissue planes, and increased perivascular fragility, thereby complicating dissection and increasing the likelihood of conversion [ 20 ]. Moreover, recent radiologic studies have highlighted the role of pancreatic parenchymal biology and inflammation in shaping perioperative risk, further supporting the association between pancreatic inflammatory status and operative complexity [ 21 ]. Learning Curve: How Much Does it Matter? The impact of surgical experience on outcomes in robotic pancreatic surgery has progressively shifted from a focus on technical feasibility to a broader understanding of how expertise influences case selection, intraoperative decision-making, and procedural safety. Nationwide data from the Dutch Pancreatic Cancer Group have demonstrated a steady increase in annual RPD volume with a relatively stable conversion rate, despite growing procedural complexity over time [ 22 ]. This pattern closely mirrors our findings, in which conversion numbers remained stable even as overall caseload increased (Fig. 1). The learning curve of RPD is widely recognized as a stepwise process, progressing from feasibility to proficiency, followed by an advanced phase and eventual mastery (> 84 procedures) [ 23 ]. As reported by Napoli et al., surgeons operating in the advanced and mastery phases increasingly undertake complex cases, including patients with high fistula risk, prior neoadjuvant therapy, or vascular involvement, without a proportional increase in conversion or adverse outcomes [ 24 ]. This evolution reflects a transition from technical refinement to a deliberate and controlled expansion of robotic indications as experience accrues. In our cohort, learning-curve status was not independently associated with conversion, suggesting that conversion was driven primarily by anatomical complexity and intraoperative findings rather than by lack of experience. This observation is consistent with a prior institutional analysis of the operating surgeon in this series, in which proficiency was achieved after the first 40 robotic procedures [ 9 ]. Within this framework, our data support the concept of a second-phase learning curve in RPD, whereby increasing experience enhances the surgeon’s ability to anticipate challenges, maintain stable conversion rates, and safely incorporate more complex patients into the robotic program. This provides essential context for interpreting the postoperative impact of conversion in a mature robotic practice. Does Conversion Really Worsen Outcomes? In our cohort, conversion to an open approach was not associated with higher overall or major postoperative complication rates, nor with increased rates of clinically relevant POPF. Although converted patients showed numerically higher incidences of postpancreatectomy hemorrhage, biliary leak, delayed gastric emptying, and short-term mortality compared with fully robotic procedures, these differences did not reach statistical significance. Notably, converted cases were characterized by a significantly higher rate of intraoperative bleeding requiring transfusion, reflecting increased perioperative complexity rather than a direct worsening of postoperative morbidity. By contrast, length of hospital stay and HDU stay were significantly longer in the converted group, indicating that conversion primarily impacts postoperative resource utilization rather than the severity of postoperative morbidity. Importantly, the absence of significant differences in overall or major postoperative complications suggests that conversion did not result in an apparent clinical penalty, rather than reflecting reduced surgical complexity. In high-volume settings, accumulated experience often translates less into lower complication rates and more into improved anticipation, early recognition, and structured management of adverse events. This concept is well illustrated by the nationwide implementation of the PORSCH algorithm, which promotes standardized postoperative surveillance and a step-up, minimally invasive management strategy for POPF [ 25 ]. The so-called PORSCH effect describes how earlier detection and structured management lead to increased identification of grade B fistulas and greater use of interventional treatments, while reducing grade C fistulas, failure to rescue, and postoperative mortality [ 26 ]. The PORSCH experience therefore provides a useful framework for interpreting our findings. Within this framework, it is plausible that structured perioperative pathways, early decision-making, and timely intervention mitigated the clinical impact of conversion in our series, preserving short-term outcomes despite the greater anatomical and procedural complexity of converted cases. Our results differ from larger series, such as that reported by Slavin et al., in which unplanned conversions during RPD were associated with higher major complication rates, longer ICU stays, and increased mortality, largely driven by intraoperative hemorrhage and physiological instability [ 3 ]. This difference likely reflects variation in the timing and intent of conversion. In our experience, most conversions reflected a strategic change in operative approach informed by preoperative imaging or early intraoperative findings, with emergency cases accounting for only 2 of 16 conversions. Taken together, these findings suggest that timing and intent are more relevant than conversion itself. When anticipated and performed early within structured perioperative pathways, conversion can preserve postoperative outcomes, although associated with increased hospital resource utilization. Limitations and Future Directions This study has some limitations that should be acknowledged. First, the sample size (130 patients with only 16 conversions) limits statistical power, resulting in wide confidence intervals for some associations. These reflect the limited number of conversion events and the exploratory nature of the analysis, and warrant cautious interpretation of the effect estimates. Second, the retrospective, single-center design is subject to selection biases and unmeasured confounding. Third, all procedures were performed by a single high-volume surgeon, enhancing internal consistency but reducing generalizability, as conversion thresholds and operative strategies may vary across surgeons and institutions. While predictive tools exist for minimally invasive distal pancreatectomy, no comparable framework is currently available for RPD, despite its higher technical complexity. Our findings therefore represent an important step toward identifying meaningful predictors, but a prospective multicenter study will be essential to refine and validate a robust risk model integrating patient-, disease-, and procedure-related factors. Future research should evaluate whether advanced imaging, intraoperative data, or video review can enhance prediction models beyond standard clinical factors. Clarifying how surgeon thresholds and team dynamics influence conversion decisions, and comparing early planned versus late reactive conversion, may further guide strategies to improve safety and outcomes. 5. CONCLUSION In this tertiary-center series, conversion during RPD was mainly driven by preoperatively identifiable factors such as vascular involvement, periampullary tumor location and previous pancreatitis rather than by surgeon inexperience. When anticipated and performed in a controlled manner, conversion did not significantly increase major postoperative morbidity, although it was associated with longer hospital and HDU stay. These findings support the view that, within a mature robotic program, conversion represents a strategic safety decision rather than a failure of minimally invasive surgery. Future multicenter studies are needed to validate a dedicated conversion risk score and to further optimize case selection and operative planning. Declarations Statement of Ethics This study was conducted in accordance with the ethical standards of our institutional research committee and the principles of the Declaration of Helsinki. Patient anonymity has been preserved throughout. No identifiable personal information is disclosed. Declaration of Figures’ Authenticity All figures submitted have been created by the authors who confirm that the images are original with no duplication and have not been previously published in whole or in part. Conflict of Interest Statement The authors have no conflicts of interest to declare. Funding Sources This study was not supported by any sponsor or funder. Author Contributions Study concept and design and drafting of the manuscript: A.F., L.S.; Acquisition of data: A.C., S.A., H.P.; Analysis and interpretation of data: E.W., M.L., A.M.; Critical revision of the manuscript for important intellectual content: A.F., F.R., E.W., L.S. Final approval of the manuscript: all authors. References de Graaf N, Emmen AMLH, Ramera M, van Hilst J, Björnsson B, Boggi U et al (2025) Minimally invasive versus open pancreatoduodenectomy for resectable neoplasms. NEJM Evid 4:EVIDoa2500045. https://doi.org/10.1056/EVIDoa2500045 Löf S, Vissers FL, Klompmaker S, Berti S, Boggi U, Coratti A et al (2021) Risk of conversion to open surgery during robotic and laparoscopic pancreatoduodenectomy and effect on outcomes: international propensity score-matched comparison study. Br J Surg 108:80–87. https://doi.org/10.1093/bjs/znaa026 Slavin M, Ross SB, Sucandy I, Saravanan S, Crespo KL, Syblis CC et al (2024) Unplanned conversions of robotic pancreaticoduodenectomy: short-term outcomes and a suggested stepwise approach for safe conversion. Surg Endosc 38:964–974. https://doi.org/10.1007/s00464-023-10527-7 Müller PC, Sedlaczek P, Billeter AT, Shen B, Jin J, Nickel F et al (2025) Conversion of robotic distal pancreatectomy: predictors and outcomes in an international multicenter study. Ann Surg. https://doi.org/10.1097/SLA.0000000000006821 von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 61:344–349. https://doi.org/10.1016/j.jclinepi.2007.11.008 World Medical Association (2013) Ethical principles for medical research involving human subjects. JAMA310:2191–2194. https://doi.org/10.1001/jama.2013.281053 Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383. https://doi.org/10.1016/0021-9681(87)90171-8 Isaji S, Mizuno S, Windsor JA et al (2018) International consensus on definition and criteria of borderline resectable pancreatic ductal adenocarcinoma 2017. Pancreatology 18:2–11. https://doi.org/10.1016/j.pan.2017.11.011 Castel A, De Rosa RV, Esvan M, Merdrignac A, Livin M, Wasielewski E, Robin F, Sulpice L (2025) Safety and learning curve of robotic pancreatoduodenectomy with limited robotic platform access: a propensity score-matched comparison with open surgery in a high-volume center. Hepatobiliary Surg Nutr 14:937–948. https://doi.org/10.21037/hbsn-2024-723 Dindo D, Demartines N, Clavien PA (2004) Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 240:205–213 Bassi C, Marchegiani G, Dervenis C et al (2017) The 2016 update of the International Study Group (ISGPS) definition and grading of postoperative pancreatic fistula: 11 years after. Surgery 161:584–591. https://doi.org/10.1016/j.surg.2016.11.014 Wente MN, Bassi C, Dervenis C et al (2007) Delayed gastric emptying after pancreatic surgery: a suggested definition by the International Study Group of Pancreatic Surgery (ISGPS). Surgery 142:761–768. https://doi.org/10.1016/j.surg.2007.05.005 Wente MN, Veit JA, Bassi C et al (2007) Postpancreatectomy hemorrhage: an International Study Group of Pancreatic Surgery (ISGPS) definition. Surgery 142:20–25. https://doi.org/10.1016/j.surg.2007.02.001 Koch M, Garden OJ, Padbury R et al (2011) Bile leakage after hepatobiliary and pancreatic surgery: a definition and grading of severity by the International Study Group of Liver Surgery. Surgery 149:680–688. https://doi.org/10.1016/j.surg.2010.12.002 Palacio J, Sanchez D, Samuels S et al (2023) Impact of conversion at time of minimally invasive pancreaticoduodenectomy on perioperative and long-term outcomes: review of the National Cancer Database. Ann Hepatobiliary Pancreat Surg 27:292–300. https://doi.org/10.14701/ahbps.22-101 Napoli N, Cacace C, Kauffmann EF et al (2023) The PD-ROBOSCORE: a difficulty score for robotic pancreatoduodenectomy. Surgery 173:1438–1446. https://doi.org/10.1016/j.surg.2023.02.020 Ross SB, Dugan MM, Sucandy I et al (2024) Tampa difficulty score: a scoring system for difficulty of robotic pancreaticoduodenectomy. J Robot Surg 19:27. https://doi.org/10.1007/s11701-024-02189-x Callery MP, Pratt WB, Kent TS, Chaikof EL, Vollmer CM Jr (2013) A prospectively validated clinical risk score accurately predicts pancreatic fistula after pancreatoduodenectomy. J Am Coll Surg 216:1–14. https://doi.org/10.1016/j.jamcollsurg.2012.09.002 Mungroop TH, Klompmaker S, Wellner UF et al (2021) Updated alternative fistula risk score to include minimally invasive pancreatoduodenectomy: pan-European validation. Ann Surg 273:334–340. https://doi.org/10.1097/SLA.0000000000003234 De Ponthaud C, Nassar A, Dokmak S et al (2025) Conversion during minimally invasive left pancreatectomy: a nationwide study of causes and consequences. Ann Surg. https://doi.org/10.1097/SLA.0000000000006685 Addeo P, de Marini P, Averous G, Trog A, de Mathelin P, Gussago S, Fiore L, Geyer L, Noblet V, Bachellier P (2024) Preoperative pancreatic radiologic characteristics predict pancreatic-specific complications before pancreaticoduodenectomy: the pancreatic acinar radiologic score. HPB (Oxford) 26:717–725. https://doi.org/10.1016/j.hpb.2024.02.004 Emmen AMLH, van den Broek BLJ, Hendriks TE et al (2025) Nationwide outcomes of 1000 robotic pancreatoduodenectomies across the four phases of the learning curve. Br J Surg 112:znaf210. https://doi.org/10.1093/bjs/znaf210 Zwart MJW, van den Broek B, de Graaf N et al (2023) The feasibility, proficiency, and mastery learning curves in 635 robotic pancreatoduodenectomies following a multicenter training program. Ann Surg 278:e1232–e1241. https://doi.org/10.1097/SLA.0000000000005928 Napoli N, Ginesini M, Kauffmann EF et al (2025) Navigating the learning curve of robotic pancreatoduodenectomy: competency, proficiency, and mastery in a first-generation robotic surgeon with established open pancreatic expertise. Surgery 184:109347. https://doi.org/10.1016/j.surg.2025.109347 Smits FJ, Henry AC, Besselink MG et al (2022) Algorithm-based care versus usual care for early recognition and management of complications after pancreatic resection: a nationwide stepped-wedge cluster-randomised trial. Lancet 399:1867–1875. https://doi.org/10.1016/S0140-6736(22)00182-9 Smits FJ, Henry AC, van Eijck CH et al (2020) Care after pancreatic resection according to an algorithm for early detection and minimally invasive management of pancreatic fistula (PORSCH-trial): design and rationale. Trials 21:389. https://doi.org/10.1186/s13063-020-4167-9 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8412822","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":567452402,"identity":"2885d65e-cfdc-4e56-ba13-2186210dd64c","order_by":0,"name":"Alessia Fassari","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Alessia","middleName":"","lastName":"Fassari","suffix":""},{"id":567452409,"identity":"a397e441-bd5a-4547-a19c-beef937e980d","order_by":1,"name":"Edouard Wasielewski","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Edouard","middleName":"","lastName":"Wasielewski","suffix":""},{"id":567452410,"identity":"102f43c9-2ae3-45f4-98d3-7b5293d3ca05","order_by":2,"name":"Antoine Castel","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Antoine","middleName":"","lastName":"Castel","suffix":""},{"id":567452411,"identity":"dae86621-06a0-4be1-9978-ac1c9ecfeee4","order_by":3,"name":"Hector Prudhomme","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Hector","middleName":"","lastName":"Prudhomme","suffix":""},{"id":567452412,"identity":"1d9831ae-0a5c-4a51-8f7c-f9810da0822f","order_by":4,"name":"Salah Abdennebi","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Salah","middleName":"","lastName":"Abdennebi","suffix":""},{"id":567452413,"identity":"6794b58d-79ec-4ddd-9586-4b14145308ba","order_by":5,"name":"Marie Livin","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Livin","suffix":""},{"id":567452414,"identity":"479219c7-95d9-4f8a-88f8-35fb08fa5901","order_by":6,"name":"Aude Merdrignac","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Aude","middleName":"","lastName":"Merdrignac","suffix":""},{"id":567452415,"identity":"61b64ce2-a000-4f59-bd07-99605dd9cead","order_by":7,"name":"Fabien Robin","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Fabien","middleName":"","lastName":"Robin","suffix":""},{"id":567452416,"identity":"6d657cf4-a34f-4788-ad0a-a440a71e7bdf","order_by":8,"name":"Laurent Sulpice","email":"data:image/png;base64,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","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":true,"prefix":"","firstName":"Laurent","middleName":"","lastName":"Sulpice","suffix":""}],"badges":[],"createdAt":"2025-12-20 14:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8412822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8412822/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99287390,"identity":"35fe2e31-02ee-4ebb-beef-bf58a1e18ece","added_by":"auto","created_at":"2025-12-31 09:37:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3670074,"visible":true,"origin":"","legend":"","description":"","filename":"MANUSCRIPTRPDJRSdef.docx","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/0c0727118e4a971852512125.docx"},{"id":99287386,"identity":"11523756-440d-45b9-afe0-e09437b9beff","added_by":"auto","created_at":"2025-12-31 09:37:18","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":230820,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/f3d9777597bf8b8fff1d5338.png"},{"id":99320778,"identity":"6f7d9447-7b6c-4686-b27b-de31d1eb1b66","added_by":"auto","created_at":"2025-12-31 16:38:54","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":292854,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/24d4d868bc8c58e38d96c8d1.png"},{"id":99287393,"identity":"6927ab0f-84d5-4902-989b-3d3bc4b60c07","added_by":"auto","created_at":"2025-12-31 09:37:18","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3677796,"visible":true,"origin":"","legend":"","description":"","filename":"Table1JRSRPDdef.docx","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/1b67de912239b5c9105986e6.docx"},{"id":99321270,"identity":"2c66256e-8265-4a2c-8412-b2843a586dda","added_by":"auto","created_at":"2025-12-31 16:39:17","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70685,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2RPD.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/0367db9934f2dca679645550.png"},{"id":99320935,"identity":"7b641d9c-fc4a-4092-8331-97f5e096c0e9","added_by":"auto","created_at":"2025-12-31 16:38:58","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2925662,"visible":true,"origin":"","legend":"","description":"","filename":"Table2JRSRPDdef.docx","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/09946e1c8394036547d25eb5.docx"},{"id":99287402,"identity":"c438d9cf-9ee9-4e65-914a-ed5f7ff8abd2","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2927217,"visible":true,"origin":"","legend":"","description":"","filename":"Table3JRSRPDdef.docx","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/8ad58e3b32b4fbc865ee8b5b.docx"},{"id":99287392,"identity":"99d0d55d-015c-4ce1-bf66-071ab8765224","added_by":"auto","created_at":"2025-12-31 09:37:18","extension":"json","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10196,"visible":true,"origin":"","legend":"","description":"","filename":"5433052fbbb64da48924cf27b6e3e3a9.json","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/934ba0c263949b992b159428.json"},{"id":99319976,"identity":"1b16e11d-ae54-4f5c-9570-4fde4537cc07","added_by":"auto","created_at":"2025-12-31 16:38:04","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":113867,"visible":true,"origin":"","legend":"","description":"","filename":"5433052fbbb64da48924cf27b6e3e3a91enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/d3dbc96ca1cb713c38ee8bfa.xml"},{"id":99320393,"identity":"55e1366d-a0c0-471d-9859-ce80be43d2c1","added_by":"auto","created_at":"2025-12-31 16:38:33","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":230820,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/2ec5f7bf0a340f9001b38eef.png"},{"id":99320011,"identity":"23089a3a-3b61-40d8-9526-e8b8e87d35e3","added_by":"auto","created_at":"2025-12-31 16:38:05","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":292854,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/d5ec7ed8fefbbf2a66251f82.png"},{"id":99287395,"identity":"b7677b20-c19b-444b-b499-a640f4170a95","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70685,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2RPD.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/8bf33aad803348c5123663eb.png"},{"id":99287397,"identity":"0bc6862d-a5cc-4dd4-8216-129e0fc0dfb8","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":69222,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/f59aa18bbd84263dc8a193b7.png"},{"id":99287400,"identity":"a8076aa5-a879-417a-bfa5-853637c23f59","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":58085,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/a401fb63807163a8d42aba3d.png"},{"id":99320876,"identity":"860da3e7-1502-49e4-afce-53d4c85aef54","added_by":"auto","created_at":"2025-12-31 16:38:56","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":30004,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2RPD.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/5fbd0c4c8e197bf0b8f76be6.png"},{"id":99287405,"identity":"a673671e-3e4d-4d9f-8e8a-e1555bde8e13","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111496,"visible":true,"origin":"","legend":"","description":"","filename":"5433052fbbb64da48924cf27b6e3e3a91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/f238cddf601186d6b2a5fc64.xml"},{"id":99287403,"identity":"a81ebb88-04ae-4374-a0bd-5c6594561ce2","added_by":"auto","created_at":"2025-12-31 09:37:19","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122738,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/cad88c200c9301580f20fd83.html"},{"id":99319795,"identity":"6e75a052-8f64-4e51-94de-1a67bced9ad1","added_by":"auto","created_at":"2025-12-31 16:37:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":230820,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnnual volume of robotic pancreaticoduodenectomy and conversions. \u003c/strong\u003eAnnual number of robotic pancreaticoduodenectomies performed during the study period, with the corresponding number of conversions displayed by year.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/1389cdb29800f1f6d70f5845.png"},{"id":99287385,"identity":"99c5cb5f-b507-438e-bd00-7aa26b49f917","added_by":"auto","created_at":"2025-12-31 09:37:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70685,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic (ROC) curve of the multivariable logistic regression model evaluating factors associated with conversion. \u003c/strong\u003eThe ROC curve illustrates the trade-off between true positive rate and false positive rate across different probability thresholds and demonstrates good in-sample discriminative ability (AUC = 0.85). Given the exploratory nature of the analysis and the limited number of conversion events, the ROC curve is presented to illustrate in-sample discrimination rather than predictive performance.\u003c/p\u003e","description":"","filename":"Figure2RPD.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/9347f48e0ae70b703ba76790.png"},{"id":99320036,"identity":"7c453a41-114a-4b8b-bb00-b7cf3ffccc54","added_by":"auto","created_at":"2025-12-31 16:38:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":292854,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Intraoperative Reasons for Conversion During Robotic Pancreaticoduodenectomy. \u003c/strong\u003eDonut chart illustrating the distribution of intraoperative reasons for conversion among the 16 converted cases. Causes were grouped into four major categories: vascular complications (n=6), inflammatory or adhesive conditions (n=6), technical or reconstructive difficulties (n=3), and oncologic invasion precluding safe dissection (n=1). Vascular and inflammatory factors together accounted for the majority of conversions.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/3a6f4d788b6cdf690aacc21f.png"},{"id":100548159,"identity":"0971274d-302d-4cd9-a065-08764b441c4c","added_by":"auto","created_at":"2026-01-19 08:17:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1934149,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8412822/v1/da32e044-1190-4a1b-b267-44aa833b4370.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Breaking Point in Robotic Pancreaticoduodenectomy: Predictors of Conversion and Early Postoperative Impact in a Tertiary Referral Center","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eRobotic pancreaticoduodenectomy (RPD) has emerged as a major evolution in minimally invasive pancreatic surgery, offering enhanced three-dimensional visualization, wristed instrumentation, and improved surgeon ergonomics. While these technical advantages over conventional laparoscopy are increasingly recognized, the extent to which RPD translates into a meaningful clinical benefit compared with open pancreaticoduodenectomy remains incompletely defined.\u003c/p\u003e \u003cp\u003eRecent high-quality comparative studies, including the DIPLOMA-2 trial, have primarily focused on highly selected patient populations, restricting enrollment to upfront-resectable tumors without major vascular involvement and limiting participation to expert centers operating under strict credentialing requirements [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although such trial designs ensure strong internal validity, they inevitably constrain external generalizability. Consequently, the real-world safety, effectiveness, and intraoperative behavior of RPD in less selected, clinically heterogeneous populations remain to be fully characterized.\u003c/p\u003e \u003cp\u003eWithin this context, conversion to open surgery represents a pivotal intraoperative event during RPD. Traditionally regarded as a marker of technical failure, conversion may instead reflect sound surgical judgment in response to intraoperative challenges such as bleeding, unfavorable anatomy, limited exposure, or oncologic concerns. Several patient-, disease-, and procedure-related factors have been proposed as drivers of conversion in minimally invasive pancreatic surgery [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; however, data specifically addressing RPD remain limited.\u003c/p\u003e \u003cp\u003eAgainst this background, the aims of the present single-center retrospective study were threefold: (1) to identify patient-, disease-, and procedure-related factors associated with conversion during RPD; (2) to determine which of these factors remained independently associated with conversion after multivariable analysis; and (3) to characterize the perioperative and early postoperative impact of conversion, with particular emphasis on postoperative morbidity and length of hospital stay. By addressing these objectives, this study seeks to clarify both the determinants and the clinical implications of conversion during RPD within a high-volume, mature robotic pancreatic surgery program.\u003c/p\u003e"},{"header":"2. PATIENTS AND METHODS","content":"\u003cp\u003e \u003cb\u003eStudy design and setting\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis retrospective single-center cohort study was designed, conducted, and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It included all consecutive adult patients who underwent RPD at a tertiary referral center of\u003c/p\u003e \u003cp\u003epancreatic surgery between April 2018 and October 2025.\u003c/p\u003e \u003cp\u003eThe institution is a dedicated center for complex oncologic surgery, with a strong focus on hepatopancreatobiliary (HPB) procedures and is also active in liver transplantation. The center is equipped with three da Vinci robotic systems, a dedicated pancreatic surgery unit, and comprehensive perioperative facilities, including an intensive care unit (ICU) and a high-dependency unit (HDU), allowing structured postoperative management of high-risk patients.\u003c/p\u003e \u003cp\u003eThe robotic pancreatic program was established and conducted as a single-surgeon series by a dedicated pancreatic surgeon with extensive prior experience in open pancreaticoduodenectomy and formal training in minimally invasive and robotic surgery. At the start of the study period, the surgeon had already performed more than 500 pancreatic resections using open and laparoscopic approaches, providing a solid background in pancreatic surgery at the initiation of the robotic program. The present series also encompasses the early phase of the robotic learning curve. All RPDs were performed using a standardized four-arm robotic platform (da Vinci system; Intuitive Surgical, Sunnyvale, CA, USA), with a uniform port-placement strategy and consistent operative setup.\u003c/p\u003e \u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Institutional review board approval was obtained, and the requirement for individual informed consent was waived due to the retrospective nature of the study and full anonymization of patient data.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePatient selection\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eVariables and data collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData were extracted from a prospectively maintained institutional database and completed through targeted review of electronic medical records and operative reports.\u003c/p\u003e \u003cp\u003ePatient-related variables included demographic characteristics (age and sex), body mass index (BMI, analyzed both as a continuous variable and by categories), comorbidity burden as assessed by the Charlson Comorbidity Index (CCI), history of previous abdominal surgery, and documented anatomical variations when available [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDisease-related variables included the underlying diagnosis, tumor location and size on preoperative imaging, with tumors categorized as periampullary (including bile duct, duodenal, and ampullary tumors) or pancreatic head tumors (including pancreatic ductal adenocarcinoma and intraductal papillary mucinous neoplasms). Histology was classified as benign or malignant. Tumor stage at diagnosis was defined as upfront resectable, borderline resectable, or locally advanced based on radiologic vascular involvement (venous or arterial abutment or encasement) and biological criteria, including a serum carbohydrate antigen (CA) 19\u0026thinsp;\u0026minus;\u0026thinsp;9 level more than 500 units/ml [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The administration of neoadjuvant therapy was also recorded.\u003c/p\u003e \u003cp\u003eSurgeon- and procedure-related variables included learning-curve phase, the need for venous vascular resection, main pancreatic duct diameter (\u0026le;\u0026thinsp;3 mm), and pancreatic texture (soft vs firm).\u003c/p\u003e \u003cp\u003eConversion served as the dependent variable in the primary analyses and was defined as any unplanned laparotomy occurring after initiation of the robotic approach, irrespective of timing or indication, and not performed solely for specimen extraction.\u003c/p\u003e \u003cp\u003eBased on a prior internal assessment of operative time and perioperative outcomes, the learning curve for RPD at our institution was defined as the first 40 consecutive procedures. Accordingly, procedures were classified into two experience-based phases: an early learning phase (cases 1\u0026ndash;40) and a proficiency phase (cases\u0026thinsp;\u0026gt;\u0026thinsp;40) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This dichotomization was used as an independent variable in multivariable models to account for the potential impact of surgical experience on the risk of conversion.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrimary and Secondary Outcomes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe primary aim of this study was to identify patient-, disease-, and surgeon- or procedure-related factors independently associated with intraoperative transition to an open approach during RPD. The primary reason for conversion was systematically recorded to distinguish between emergency and strategic conversions.\u003c/p\u003e \u003cp\u003eSecondary outcomes were evaluated to assess the perioperative and early postoperative clinical impact of conversion and included intraoperative bleeding needing transfusions, operative time, overall postoperative morbidity, complication severity, length of hospital stay, HDU and ICU length of stay, hospital readmission within 30 days, resection margins and 30-day mortality.\u003c/p\u003e \u003cp\u003ePostoperative complications and grading were defined according to internationally accepted criteria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Clinically relevant postoperative pancreatic fistula (POPF grade B or C) was defined according to the International Study Group on Pancreatic Surgery (ISGPS) classification [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Delayed gastric emptying and postpancreatectomy hemorrhage were also defined and graded according to ISGPS criteria [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Biliary fistula was defined according to the International Study Group of Liver Surgery (ISGLS) metrics [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics (IBM Corp., Armonk, NY, USA). All tests were two-sided, and a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Continuous variables are reported as median (interquartile range), and categorical variables as counts and percentages. To identify factors associated with conversion, patient-, disease-, and procedure-related variables were first assessed individually using univariable analyses.\u003c/p\u003e \u003cp\u003eContinuous variables were compared using the Mann-Whitney U test, while categorical variables were compared using Fisher\u0026rsquo;s exact test, given the limited number of conversion events. Variables showing a potential association with conversion at univariable analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10), were entered into a multivariable logistic regression model to identify independent predictors of conversion. Results are reported as odds ratios (ORs) with 95% confidence intervals (CIs).\u003c/p\u003e \u003cp\u003ePeri- and postoperative outcomes were compared between converted and non-converted cases using univariable analyses only, applying Fisher\u0026rsquo;s exact test for categorical variables and the Mann-Whitney U test for continuous variables.\u003c/p\u003e \u003cp\u003eThe extent and pattern of missing data were assessed for all collected data. When missingness was limited, complete-case analyses were performed. Factors with substantial missingness were excluded from multivariable analyses.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003eTemporal trends and study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 illustrates the temporal trends in RPD volume and corresponding conversions over the study period. A progressive increase in annual case volume was observed, reflecting the consolidation of the robotic pancreatic program over time. Despite this volume expansion and the inclusion of increasingly complex cases, the number of conversions remained low and relatively stable, suggesting a controlled adoption of the robotic approach.\u003c/p\u003e\n\u003cp\u003eOverall, 130 patients underwent RPD during the study period, of whom 16 (12.3%) required conversion to an open approach. Baseline patient-, disease-, and procedure-related characteristics stratified by conversion status are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient, disease, and procedural characteristics stratified by conversion during RPD.\u003c/strong\u003e Baseline patient-, disease-, and procedure-related characteristics of patients undergoing RPD, stratified by conversion status. Continuous variables are expressed as median (IQR) and categorical variables as number (%). \u003cem\u003eP\u003c/em\u003e-values are based on univariable comparisons between converted and non-converted cases, with a screening threshold set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003ePatient-Related Factors\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;130)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnconverted RPD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;114)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConverted RPD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16 )\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\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\"\u003e\n \u003cp\u003eAge [median, (IQR)] (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.7 (59.8\u0026ndash;74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.2 (59.4\u0026ndash;74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.3 (66.1\u0026ndash;76.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003e- male [n (%)]\u003c/p\u003e\n \u003cp\u003e- female [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55 (42.3%)\u003c/p\u003e\n \u003cp\u003e75 (57.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46 (40.4%)\u003c/p\u003e\n \u003cp\u003e68 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9 (56.3%)\u003c/p\u003e\n \u003cp\u003e7 (43.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCI score\u003c/p\u003e\n \u003cp\u003e- \u0026lt;\u0026thinsp;4 [n, (%)]\u003c/p\u003e\n \u003cp\u003e- \u0026ge;\u0026thinsp;4 [n, (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e69 (53.1%)\u003c/p\u003e\n \u003cp\u003e61 (46.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64 (56.1%)\u003c/p\u003e\n \u003cp\u003e50 (43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (31.2%)\u003c/p\u003e\n \u003cp\u003e11(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI category (kg/m\u0026sup2;)\u003c/p\u003e\n \u003cp\u003e- \u0026lt;\u0026thinsp;25 [n, (%)]\u003c/p\u003e\n \u003cp\u003e- \u0026ge;\u0026thinsp;25 [n, (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71 (54.6%)\u003c/p\u003e\n \u003cp\u003e59 (45.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66 (57.9%)\u003c/p\u003e\n \u003cp\u003e48 (42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003cp\u003e11 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevious abdominal surgery [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (63.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (56.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevious Pancreatitis [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnatomical variations\u003c/p\u003e\n \u003cp\u003e- RHA from SMA [n, %]\u003c/p\u003e\n \u003cp\u003e- Median Arcuate Ligament [n, %]\u003c/p\u003e\n \u003cp\u003e- CHA from SMA [n, %]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (8.5%)\u003c/p\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003cp\u003e3 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9 (7.9%)\u003c/p\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003cp\u003e3 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease-Related Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;130)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnconverted RPD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eConverted RPD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistology\u003c/p\u003e\n \u003cp\u003e- Malignant\u003c/p\u003e\n \u003cp\u003e- Benign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e102 (78.5%)\u003c/p\u003e\n \u003cp\u003e28 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e89 (78%)\u003c/p\u003e\n \u003cp\u003e25 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (81.3%)\u003c/p\u003e\n \u003cp\u003e3 (18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor Location\u003c/p\u003e\n \u003cp\u003e- Periampullary [n, (%)]\u003c/p\u003e\n \u003cp\u003e- Pancreatic (Head/Isthmus/Uncus) [n, (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (43.8%)\u003c/p\u003e\n \u003cp\u003e73 (56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46 (40.4%)\u003c/p\u003e\n \u003cp\u003e68 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (68.7%)\u003c/p\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size, [median (IQR)] (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (15\u0026ndash;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (15\u0026ndash;28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.5 (13\u0026ndash;38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage at Diagnosis\u003c/p\u003e\n \u003cp\u003e- Upfront Resectable [n, (%)]\u003c/p\u003e\n \u003cp\u003e- Borderline Resectable [n, (%)]\u003c/p\u003e\n \u003cp\u003e- Locally Advanced [n, (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e111 (85.4%)\u003c/p\u003e\n \u003cp\u003e18 (13.8%)\u003c/p\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e97 (85.1%)\u003c/p\u003e\n \u003cp\u003e16 (14%)\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14 (87.5%)\u003c/p\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeoadjuvant Chemotherapy [n, (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eProcedure- and Surgeon-Related Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;130)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnconverted RPD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eConverted RPD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgeon Experience*\u003c/p\u003e\n \u003cp\u003e- Early Learning Phase: 1\u0026ndash;40 procedures\u003c/p\u003e\n \u003cp\u003e- Proficiency Phase: \u0026gt;40 procedures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40 (30.7%)\u003c/p\u003e\n \u003cp\u003e90 (69.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34 (29.8%)\u003c/p\u003e\n \u003cp\u003e80 (70.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (37.5%)\u003c/p\u003e\n \u003cp\u003e10 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular contact requiring resection [n, %]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMain pancreatic duct\u0026thinsp;\u0026le;\u0026thinsp;3 mm [n, %]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (46.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoft pancreatic texture [n, %]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93 (71.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eRPD, Robotic Pancreaticoduodenectomy; CCI, Charlson-Comordbidity Index; BMI, Body Mass Index; RHA, Right Hepatic Artery; SMA, Superior Mesenteric Artery; CHA, Common Hepatic Artery; MPD, Main Pancreatic Duct.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e*In this study we used an institution-specific cut-off of 40 based on prior internal analysis [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with conversion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn univariable analysis, using a liberal screening threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10), higher body mass index (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u0026sup2;), a history of pancreatitis, and a main pancreatic duct diameter\u0026thinsp;\u0026le;\u0026thinsp;3 mm showed a potential association with conversion and were retained as candidate variables for multivariable analysis. Age and comorbidity burden (CCI\u0026thinsp;\u0026ge;\u0026thinsp;4), although numerically higher in converted cases, did not meet the predefined inclusion threshold (p\u0026thinsp;=\u0026thinsp;0.10) and were therefore not retained. Tumor location differed significantly between groups (p\u0026thinsp;=\u0026thinsp;0.004), with a higher proportion of periampullary tumors among converted cases. Among procedure-related variables, vascular contact requiring resection showed the strongest association with intraoperative transition to an open approach (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In multivariable analysis, it remained the most powerful independent predictor of conversion (p\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Periampullary tumor location (p\u0026thinsp;=\u0026thinsp;0.023) and previous pancreatitis (p\u0026thinsp;=\u0026thinsp;0.008) were also independently associated with conversion. In contrast, BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u0026sup2; and a main pancreatic duct diameter\u0026thinsp;\u0026le;\u0026thinsp;3 mm did not retain statistical significance after adjustment.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable logistic regression analysis of factors associated with conversion.\u003c/strong\u003e Variables included in the multivariable model were selected based on clinical relevance and univariable analysis, with candidate predictors defined as those showing a potential association with conversion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10) on univariable testing. In the multivariable analysis, a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePredictors of Conversion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio (OR)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eVascular contact requiring resection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.1\u0026ndash;869.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMPD\u0026thinsp;\u0026le;\u0026thinsp;3 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.11\u0026ndash;2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.51\u0026ndash;9.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeriampullary tumors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u0026ndash;37.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious pancreatitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.9\u0026ndash;65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eBMI, Body Mass Index; MPD, Main Pancreatic Duct.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe ROC analysis was conducted to illustrate in-sample discrimination and should not be interpreted as evidence of predictive performance. The multivariable model showed good apparent discriminative ability, as illustrated by the ROC curve (Fig.\u0026nbsp;2), with an area under the curve (AUC) of 0.85.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReason for conversion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further characterize the mechanisms underlying conversion, operative reports were systematically reviewed and reasons for conversion were grouped into four predefined categories (Fig.\u0026nbsp;3). Vascular complications represented one of the most frequent causes (6 of 16 conversions), including portal or mesenteric venous injury, portal vein stenosis requiring resection, and bleeding at the gastroduodenal artery stump or portal anastomosis requiring open vascular control. Inflammatory or adhesive conditions accounted for six additional conversions, mainly due to dense peripancreatic inflammation, post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis, or extensive peritumoral adhesions. Technical or reconstructive limitations, such as inability to clearly identify the pancreatic duct or to safely perform the biliary anastomosis, led to three conversions. Finally, oncologic invasion precluding safe dissection was identified in one case.\u003c/p\u003e\n\u003cp\u003eImportantly, only two of the sixteen conversions were performed as true emergency conversions due to uncontrolled intraoperative bleeding. In contrast, the remaining conversions were undertaken in a planned and timely manner, following early recognition of technical difficulty or unfavorable anatomy, and before the occurrence of hemodynamic instability or major intraoperative complications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeri- and postoperative outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerioperative and postoperative outcomes according to conversion status are detailed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgical outcomes according to conversion status.\u003c/strong\u003e Peri- and postoperative outcomes of patients undergoing robotic pancreaticoduodenectomy, stratified by conversion status. Categorical variables are reported as number (%), and continuous variables as median (interquartile range, IQR). Comparisons between converted and non-converted cases were performed using Fisher\u0026rsquo;s exact test for categorical variables and the Mann-Whitney U test for continuous variables. A p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeri- and Postoperative Outcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnconverted RPD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;114)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConverted RPD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\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\"\u003e\n \u003cp\u003eIntraoperative bleeding requiring transfusion [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOperative Time [median, (IQR)] (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e574 (546\u0026ndash;605)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e562 (550\u0026ndash;628)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Minor Complications (CD I-II) [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (61.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (56.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Major Complications (CD\u0026thinsp;\u0026ge;\u0026thinsp;IIIa) [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinically relevant DGE (B/C) [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (22.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinically relevant PPH (B/C) [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinically relevant POPF (B/C) [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiliary Fistula [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Transfusion [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReoperation [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLOS [median (IQR)] (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (9\u0026ndash;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (14\u0026ndash;35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHDU stay [median (IQR)] (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5 (5\u0026ndash;12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (7.5\u0026ndash;14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eICU stay [median (IQR)] (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0-0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0-0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReadmission [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 Days-Mortality [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative Resection Margin, R0 [n (%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105 (92.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (81.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eRPD, Robotic Pancreaticoduodenectomy; CD, Clavien-Dindo Classification System; DGE, Delayed Gastric Emptying; PPH, Postoperative Hemorrhage; POPF, Postoperative Pancreatic Fistula; LOS, Length of Stay; HDU, High Dependency Unit; ICU, Intensive Care Unit.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eConverted procedures were associated with a significantly higher rate of intraoperative bleeding requiring transfusion (31.3% vs 1.8%; p\u0026thinsp;=\u0026thinsp;0.001). Operative time was comparable between converted and non-converted cases. No statistically significant differences were observed between converted and unconverted RPD in terms of minor complications, major complications (Clavien-Dindo\u0026thinsp;\u0026ge;\u0026thinsp;IIIa), clinically relevant delayed gastric emptying (grade B/C), postpancreatectomy hemorrhage, clinically relevant POPF (grade B/C), biliary fistula, postoperative transfusion, reoperation rate, readmission, ICU stay, or 30-day mortality.\u003c/p\u003e\n\u003cp\u003eDespite the absence of statistical significance, converted cases showed numerically higher rates of postoperative bleeding-related events and subsequent interventions, including need for transfusion, and reoperation. R0 resection rates were numerically lower in converted cases compared with fully robotic procedures (81.3% vs 92.1%), although this difference did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.17). Despite comparable complication rates, conversion was associated with significantly increased postoperative resource utilization, reflected by a longer median length of hospital stay (22 [IQR 14\u0026ndash;35] vs 13 [IQR 9\u0026ndash;21] days; p\u0026thinsp;=\u0026thinsp;0.033) and prolonged high-dependency unit stay (13 [IQR 7.5\u0026ndash;14.5] vs 7.5 [IQR 5\u0026ndash;12] days; p\u0026thinsp;=\u0026thinsp;0.046).\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe present findings highlight important elements influencing when and why conversion occurs during RPD and how these events translate into perioperative outcomes. A key strength of this study is the identification of predictors that are recognizable preoperatively or very early during the operation. This aspect is particularly relevant in robotic pancreatic surgery, as early recognition of conversion-predisposing factors allows optimization of patient selection, operative planning, and team readiness. Importantly, the predictors identified in our analysis predominantly reflect anatomical and inflammatory complexity rather than surgeon inexperience, supporting the applicability of these findings across centers with varying robotic volumes.\u003c/p\u003e \u003cp\u003eIn our experience, the conversion rate of 12.3% during RPD is consistent with contemporary robotic series, which generally report conversion rates between 5% and 13%, and remains substantially lower than those historically described for laparoscopic pancreaticoduodenectomy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond its occurrence, conversion should also be interpreted in terms of timing and intent. Large multicenter analyses, such as the European E-MIPS study by L\u0026ouml;f et al., have highlighted the distinction between emergency conversions, often triggered by acute intraoperative events such as bleeding, and elective or strategic conversions undertaken in a controlled setting when operative conditions are unfavorable but stable [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In line with these observations, anticipating the risk of abandonment of the robotic approach in favor of laparotomy based on preoperative imaging and clinical history allows for a deliberate and timely change in operative strategy, rather than a late, reactive decision following prolonged dissection, cumulative inflammation, or significant blood loss. Within this framework, conversion should be viewed as an expression of appropriate surgical judgment rather than a failure of the minimally invasive approach, a concept further supported by the low proportion of emergency conversions observed in the present robotic series (2 of 16).\u003c/p\u003e \u003cp\u003e \u003cb\u003eKey Drivers of Conversion: What Can We Anticipate?\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn our multivariable model, three variables remained independently associated with conversion: vascular involvement requiring venous resection, periampullary tumor location, and a history of pancreatitis. The good in-sample discriminative performance of the multivariable model, as shown by the ROC analysis (Fig.\u0026nbsp;2), supports the clinical relevance of these factors, while emphasizing that conversion remains a context-dependent intraoperative decision rather than a fully predictable event.\u003c/p\u003e \u003cp\u003eVascular involvement emerged as the strongest predictor, reflecting the intrinsic limitations of minimally invasive surgery when safe proximal and distal vascular control cannot be reliably secured. This finding is consistent with reports from high-volume robotic series and multicenter experiences, including the study by L\u0026ouml;f et al., in which vascular complexity and bleeding represented leading causes of conversion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Similarly, robotic difficulty-scoring systems such as the PD-ROBOSCORE and the Tampa Difficulty Score have identified vascular involvement, venous resection, and bleeding-related parameters as markers of increased surgical complexity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These observations underscore the critical role of meticulous preoperative staging, particularly triphasic computed tomography (CT) with dedicated vascular reconstructions, in identifying venous abutment, caliber changes, or collateralization that may compromise the safety of robotic dissection.\u003c/p\u003e \u003cp\u003ePeriampullary tumors, particularly distal bile duct and duodenal lesions, were also independently associated with conversion. These lesions are classically associated with a soft pancreatic gland and a small main pancreatic duct, a well-established anatomical setting linked to a challenging reconstructive scenario [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This combination increases technical complexity during both the resection and anastomotic phases and may lower the threshold for conversion when intraoperative conditions become unfavorable.\u003c/p\u003e \u003cp\u003eFinally, a history of pancreatitis completed the triad of independent predictors. Pancreatitis is well known to induce peripancreatic fibrosis, obliteration of tissue planes, and increased perivascular fragility, thereby complicating dissection and increasing the likelihood of conversion [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, recent radiologic studies have highlighted the role of pancreatic parenchymal biology and inflammation in shaping perioperative risk, further supporting the association between pancreatic inflammatory status and operative complexity [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eLearning Curve: How Much Does it Matter?\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe impact of surgical experience on outcomes in robotic pancreatic surgery has progressively shifted from a focus on technical feasibility to a broader understanding of how expertise influences case selection, intraoperative decision-making, and procedural safety. Nationwide data from the Dutch Pancreatic Cancer Group have demonstrated a steady increase in annual RPD volume with a relatively stable conversion rate, despite growing procedural complexity over time [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This pattern closely mirrors our findings, in which conversion numbers remained stable even as overall caseload increased (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe learning curve of RPD is widely recognized as a stepwise process, progressing from feasibility to proficiency, followed by an advanced phase and eventual mastery (\u0026gt;\u0026thinsp;84 procedures) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As reported by Napoli et al., surgeons operating in the advanced and mastery phases increasingly undertake complex cases, including patients with high fistula risk, prior neoadjuvant therapy, or vascular involvement, without a proportional increase in conversion or adverse outcomes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This evolution reflects a transition from technical refinement to a deliberate and controlled expansion of robotic indications as experience accrues.\u003c/p\u003e \u003cp\u003eIn our cohort, learning-curve status was not independently associated with conversion, suggesting that conversion was driven primarily by anatomical complexity and intraoperative findings rather than by lack of experience. This observation is consistent with a prior institutional analysis of the operating surgeon in this series, in which proficiency was achieved after the first 40 robotic procedures [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Within this framework, our data support the concept of a \u003cem\u003esecond-phase learning curve\u003c/em\u003e in RPD, whereby increasing experience enhances the surgeon\u0026rsquo;s ability to anticipate challenges, maintain stable conversion rates, and safely incorporate more complex patients into the robotic program. This provides essential context for interpreting the postoperative impact of conversion in a mature robotic practice.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDoes Conversion Really Worsen Outcomes?\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn our cohort, conversion to an open approach was not associated with higher overall or major postoperative complication rates, nor with increased rates of clinically relevant POPF. Although converted patients showed numerically higher incidences of postpancreatectomy hemorrhage, biliary leak, delayed gastric emptying, and short-term mortality compared with fully robotic procedures, these differences did not reach statistical significance. Notably, converted cases were characterized by a significantly higher rate of intraoperative bleeding requiring transfusion, reflecting increased perioperative complexity rather than a direct worsening of postoperative morbidity.\u003c/p\u003e \u003cp\u003eBy contrast, length of hospital stay and HDU stay were significantly longer in the converted group, indicating that conversion primarily impacts postoperative resource utilization rather than the severity of postoperative morbidity.\u003c/p\u003e \u003cp\u003eImportantly, the absence of significant differences in overall or major postoperative complications suggests that conversion did not result in an apparent clinical penalty, rather than reflecting reduced surgical complexity. In high-volume settings, accumulated experience often translates less into lower complication rates and more into improved anticipation, early recognition, and structured management of adverse events. This concept is well illustrated by the nationwide implementation of the PORSCH algorithm, which promotes standardized postoperative surveillance and a step-up, minimally invasive management strategy for POPF [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The so-called \u003cem\u003ePORSCH effect\u003c/em\u003e describes how earlier detection and structured management lead to increased identification of grade B fistulas and greater use of interventional treatments, while reducing grade C fistulas, failure to rescue, and postoperative mortality [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The PORSCH experience therefore provides a useful framework for interpreting our findings.\u003c/p\u003e \u003cp\u003eWithin this framework, it is plausible that structured perioperative pathways, early decision-making, and timely intervention mitigated the clinical impact of conversion in our series, preserving short-term outcomes despite the greater anatomical and procedural complexity of converted cases.\u003c/p\u003e \u003cp\u003eOur results differ from larger series, such as that reported by Slavin et al., in which unplanned conversions during RPD were associated with higher major complication rates, longer ICU stays, and increased mortality, largely driven by intraoperative hemorrhage and physiological instability [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This difference likely reflects variation in the timing and intent of conversion. In our experience, most conversions reflected a strategic change in operative approach informed by preoperative imaging or early intraoperative findings, with emergency cases accounting for only 2 of 16 conversions.\u003c/p\u003e \u003cp\u003eTaken together, these findings suggest that timing and intent are more relevant than conversion itself. When anticipated and performed early within structured perioperative pathways, conversion can preserve postoperative outcomes, although associated with increased hospital resource utilization.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and Future Directions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study has some limitations that should be acknowledged. First, the sample size\u003c/p\u003e \u003cp\u003e(130 patients with only 16 conversions) limits statistical power, resulting in wide confidence\u003c/p\u003e \u003cp\u003eintervals for some associations. These reflect the limited number of conversion events and the\u003c/p\u003e \u003cp\u003eexploratory nature of the analysis, and warrant cautious interpretation of the effect estimates.\u003c/p\u003e \u003cp\u003eSecond, the retrospective, single-center design is subject to selection biases and unmeasured confounding. Third, all procedures were performed by a single high-volume surgeon, enhancing internal consistency but reducing generalizability, as conversion thresholds and operative strategies may vary across surgeons and institutions.\u003c/p\u003e \u003cp\u003eWhile predictive tools exist for minimally invasive distal pancreatectomy, no comparable framework is currently available for RPD, despite its higher technical complexity. Our findings therefore represent an important step toward identifying meaningful predictors, but a prospective multicenter study will be essential to refine and validate a robust risk model integrating patient-, disease-, and procedure-related factors.\u003c/p\u003e \u003cp\u003eFuture research should evaluate whether advanced imaging, intraoperative data, or video review can enhance prediction models beyond standard clinical factors.\u003c/p\u003e \u003cp\u003eClarifying how surgeon thresholds and team dynamics influence conversion decisions, and comparing early planned versus late reactive conversion, may further guide strategies to improve safety and outcomes.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eIn this tertiary-center series, conversion during RPD was mainly driven by preoperatively identifiable factors such as vascular involvement, periampullary tumor location and previous pancreatitis rather than by surgeon inexperience. When anticipated and performed in a controlled manner, conversion did not significantly increase major postoperative morbidity, although it was associated with longer hospital and HDU stay. These findings support the view that, within a mature robotic program, conversion represents a strategic safety decision rather than a failure of minimally invasive surgery. Future multicenter studies are needed to validate a dedicated conversion risk score and to further optimize case selection and operative planning.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatement of Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of our institutional research committee and the principles of the Declaration of Helsinki. Patient anonymity has been preserved throughout. No identifiable personal information is disclosed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Figures’ Authenticity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll figures submitted have been created by the authors who confirm that the images are\u003c/p\u003e\n\u003cp\u003eoriginal with no duplication and have not been previously published in whole or in part.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was not supported by any sponsor or funder.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design and drafting of the manuscript: A.F., L.S.; Acquisition of data: A.C., S.A., H.P.; \u0026nbsp;Analysis and interpretation of data: E.W., M.L., A.M.; Critical revision of the manuscript for important intellectual content: A.F., F.R., E.W., L.S. Final approval of the manuscript: all authors.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ede Graaf N, Emmen AMLH, Ramera M, van Hilst J, Bj\u0026ouml;rnsson B, Boggi U et al (2025) Minimally invasive versus open pancreatoduodenectomy for resectable neoplasms. NEJM Evid 4:EVIDoa2500045. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/EVIDoa2500045\u003c/span\u003e\u003cspan address=\"10.1056/EVIDoa2500045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026ouml;f S, Vissers FL, Klompmaker S, Berti S, Boggi U, Coratti A et al (2021) Risk of conversion to open surgery during robotic and laparoscopic pancreatoduodenectomy and effect on outcomes: international propensity score-matched comparison study. Br J Surg 108:80\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bjs/znaa026\u003c/span\u003e\u003cspan address=\"10.1093/bjs/znaa026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlavin M, Ross SB, Sucandy I, Saravanan S, Crespo KL, Syblis CC et al (2024) Unplanned conversions of robotic pancreaticoduodenectomy: short-term outcomes and a suggested stepwise approach for safe conversion. Surg Endosc 38:964\u0026ndash;974. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00464-023-10527-7\u003c/span\u003e\u003cspan address=\"10.1007/s00464-023-10527-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller PC, Sedlaczek P, Billeter AT, Shen B, Jin J, Nickel F et al (2025) Conversion of robotic distal pancreatectomy: predictors and outcomes in an international multicenter study. Ann Surg. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/SLA.0000000000006821\u003c/span\u003e\u003cspan address=\"10.1097/SLA.0000000000006821\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 61:344\u0026ndash;349. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jclinepi.2007.11.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jclinepi.2007.11.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Medical Association (2013) Ethical principles for medical research involving human subjects. JAMA310:2191\u0026ndash;2194. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jama.2013.281053\u003c/span\u003e\u003cspan address=\"10.1001/jama.2013.281053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373\u0026ndash;383. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0021-9681(87)90171-8\u003c/span\u003e\u003cspan address=\"10.1016/0021-9681(87)90171-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsaji S, Mizuno S, Windsor JA et al (2018) International consensus on definition and criteria of borderline resectable pancreatic ductal adenocarcinoma 2017. Pancreatology 18:2\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pan.2017.11.011\u003c/span\u003e\u003cspan address=\"10.1016/j.pan.2017.11.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastel A, De Rosa RV, Esvan M, Merdrignac A, Livin M, Wasielewski E, Robin F, Sulpice L (2025) Safety and learning curve of robotic pancreatoduodenectomy with limited robotic platform access: a propensity score-matched comparison with open surgery in a high-volume center. Hepatobiliary Surg Nutr 14:937\u0026ndash;948. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21037/hbsn-2024-723\u003c/span\u003e\u003cspan address=\"10.21037/hbsn-2024-723\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDindo D, Demartines N, Clavien PA (2004) Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 240:205\u0026ndash;213\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassi C, Marchegiani G, Dervenis C et al (2017) The 2016 update of the International Study Group (ISGPS) definition and grading of postoperative pancreatic fistula: 11 years after. Surgery 161:584\u0026ndash;591. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2016.11.014\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2016.11.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWente MN, Bassi C, Dervenis C et al (2007) Delayed gastric emptying after pancreatic surgery: a suggested definition by the International Study Group of Pancreatic Surgery (ISGPS). Surgery 142:761\u0026ndash;768. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2007.05.005\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2007.05.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWente MN, Veit JA, Bassi C et al (2007) Postpancreatectomy hemorrhage: an International Study Group of Pancreatic Surgery (ISGPS) definition. Surgery 142:20\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2007.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2007.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoch M, Garden OJ, Padbury R et al (2011) Bile leakage after hepatobiliary and pancreatic surgery: a definition and grading of severity by the International Study Group of Liver Surgery. Surgery 149:680\u0026ndash;688. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2010.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2010.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalacio J, Sanchez D, Samuels S et al (2023) Impact of conversion at time of minimally invasive pancreaticoduodenectomy on perioperative and long-term outcomes: review of the National Cancer Database. Ann Hepatobiliary Pancreat Surg 27:292\u0026ndash;300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14701/ahbps.22-101\u003c/span\u003e\u003cspan address=\"10.14701/ahbps.22-101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNapoli N, Cacace C, Kauffmann EF et al (2023) The PD-ROBOSCORE: a difficulty score for robotic pancreatoduodenectomy. Surgery 173:1438\u0026ndash;1446. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2023.02.020\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2023.02.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss SB, Dugan MM, Sucandy I et al (2024) Tampa difficulty score: a scoring system for difficulty of robotic pancreaticoduodenectomy. J Robot Surg 19:27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11701-024-02189-x\u003c/span\u003e\u003cspan address=\"10.1007/s11701-024-02189-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallery MP, Pratt WB, Kent TS, Chaikof EL, Vollmer CM Jr (2013) A prospectively validated clinical risk score accurately predicts pancreatic fistula after pancreatoduodenectomy. J Am Coll Surg 216:1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jamcollsurg.2012.09.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jamcollsurg.2012.09.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMungroop TH, Klompmaker S, Wellner UF et al (2021) Updated alternative fistula risk score to include minimally invasive pancreatoduodenectomy: pan-European validation. Ann Surg 273:334\u0026ndash;340. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/SLA.0000000000003234\u003c/span\u003e\u003cspan address=\"10.1097/SLA.0000000000003234\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Ponthaud C, Nassar A, Dokmak S et al (2025) Conversion during minimally invasive left pancreatectomy: a nationwide study of causes and consequences. Ann Surg. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/SLA.0000000000006685\u003c/span\u003e\u003cspan address=\"10.1097/SLA.0000000000006685\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAddeo P, de Marini P, Averous G, Trog A, de Mathelin P, Gussago S, Fiore L, Geyer L, Noblet V, Bachellier P (2024) Preoperative pancreatic radiologic characteristics predict pancreatic-specific complications before pancreaticoduodenectomy: the pancreatic acinar radiologic score. HPB (Oxford) 26:717\u0026ndash;725. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.hpb.2024.02.004\u003c/span\u003e\u003cspan address=\"10.1016/j.hpb.2024.02.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmmen AMLH, van den Broek BLJ, Hendriks TE et al (2025) Nationwide outcomes of 1000 robotic pancreatoduodenectomies across the four phases of the learning curve. Br J Surg 112:znaf210. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bjs/znaf210\u003c/span\u003e\u003cspan address=\"10.1093/bjs/znaf210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZwart MJW, van den Broek B, de Graaf N et al (2023) The feasibility, proficiency, and mastery learning curves in 635 robotic pancreatoduodenectomies following a multicenter training program. Ann Surg 278:e1232\u0026ndash;e1241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/SLA.0000000000005928\u003c/span\u003e\u003cspan address=\"10.1097/SLA.0000000000005928\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNapoli N, Ginesini M, Kauffmann EF et al (2025) Navigating the learning curve of robotic pancreatoduodenectomy: competency, proficiency, and mastery in a first-generation robotic surgeon with established open pancreatic expertise. Surgery 184:109347. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surg.2025.109347\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2025.109347\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmits FJ, Henry AC, Besselink MG et al (2022) Algorithm-based care versus usual care for early recognition and management of complications after pancreatic resection: a nationwide stepped-wedge cluster-randomised trial. Lancet 399:1867\u0026ndash;1875. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(22)00182-9\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(22)00182-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmits FJ, Henry AC, van Eijck CH et al (2020) Care after pancreatic resection according to an algorithm for early detection and minimally invasive management of pancreatic fistula (PORSCH-trial): design and rationale. Trials 21:389. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13063-020-4167-9\u003c/span\u003e\u003cspan address=\"10.1186/s13063-020-4167-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Robotic Pancreatic Surgery, Pancreaticoduodenectomy, Surgical Conversion, Predictive Factors, Postoperative Outcomes.","lastPublishedDoi":"10.21203/rs.3.rs-8412822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8412822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eRobotic pancreaticoduodenectomy (RPD) is increasingly performed in high-volume centers, yet conversion to open surgery remains a critical intraoperative event. Often perceived as a technical failure, conversion may instead represent a safety-driven strategy in complex cases. Data on its determinants and peri- and postoperative impact in mature robotic programs remain limited.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eThis retrospective single-center cohort study included adult patients undergoing elective RPD between April 2018 and October 2025 at a tertiary referral center for pancreatic surgery. Variables associated with conversion at univariable analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10) were entered into a multivariable logistic regression model, with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Peri- and postoperative outcomes were compared between converted and non-converted cases.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eDuring the study period, 130 patients underwent RPD, of whom 16 (12.3%) required conversion. On multivariable analysis, vascular contact requiring resection was the strongest factor independently associated with conversion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Periampullary tumor location (p\u0026thinsp;=\u0026thinsp;0.023) and previous pancreatitis (p\u0026thinsp;=\u0026thinsp;0.008) were also independently associated with conversion. Converted cases were characterized by a significantly higher rate of intraoperative bleeding requiring transfusion. Overall and major postoperative complication rates, including clinically relevant postoperative pancreatic fistula and R0 resection rates, did not differ significantly between groups. Conversion was associated with longer hospital stay and prolonged high-dependency unit stay.\u003c/p\u003e\u003ch2\u003eConclusions.\u003c/h2\u003e \u003cp\u003eIn this tertiary-center experience, conversion during RPD was mainly driven by preoperatively identifiable anatomical and disease-related factors. When anticipated and performed in a controlled manner, conversion did not adversely affect major postoperative outcomes.\u003c/p\u003e","manuscriptTitle":"The Breaking Point in Robotic Pancreaticoduodenectomy: Predictors of Conversion and Early Postoperative Impact in a Tertiary Referral Center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-31 09:37:09","doi":"10.21203/rs.3.rs-8412822/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a52d706-ac13-4d6a-8a67-b9d01967af02","owner":[],"postedDate":"December 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-18T13:38:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-31 09:37:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8412822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8412822","identity":"rs-8412822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}