Perioperative Outcomes and Learning Curve for Robotic Liver Resection: An Exploratory Single-Surgeon CUSUM Analysis Stratified by IWATE Difficulty Score

Background: Robotic liver resections (RLRs) are rapidly expanding, yet the association between the learning curve, procedural complexity, and outcomes at intermediate-volume centers remains poorly defined. We evaluated the learning-curve trajectory and perioperative outcomes of a single surgeon’s initial RLR experience according to procedural complexity (IWATE difficulty score). Methods: We retrospectively analyzed 58 consecutive RLRs at an intermediate-volume center. We stratified outcomes by IWATE difficulty category and chronological tertile (early/middle/late). Textbook outcomes (TOs) and a composite failure endpoint (conversion, major complications [Clavien–Dindo ≥ IIIa] and 90-day mortality) were also assessed. Learning-curve behavior was examined with CUSUM and risk-adjusted CUSUM (RA-CUSUM) analyses. Results: Fifty-four procedures (93.1%) were minor resections and four were major hepatectomies; two were classified as IWATE Expert difficulty. Median estimated blood loss was 100 mL; conversion occurred in 10.3%, overall morbidity in 10.3% and severe complications (Clavien–Dindo ≥ IIIa) in 3.4%, with no mortalities within 90 days. TOs were achieved in 69.0% using the Delphi (TOLS) definition and in 46.6% using a length-of-stay-extended definition. Operative time and length of stay increased significantly with IWATE difficulty (p < 0.001 and p = 0.030), as did the composite failure endpoint (p = 0.039), whereas blood loss and complications did not. TOs decreased with difficulty under the extended definition (p = 0.016). No outcome except estimated blood loss differed across chronological tertiles (p = 0.032). Operative time was associated with the IWATE score (26.3 min per point; R2 = 0.32) but not with case order (p = 0.93). CUSUM and RA-CUSUM curves showed a non-linear, multiphase pattern without an identifiable inflection point, with extremes attributable to individual high-complexity procedures. Conclusions: In this exploratory single-surgeon series, consisting predominantly of minor resections, no case-number threshold could be identified, and perioperative outcomes were more closely associated with procedural complexity than with chronological experience, supporting a complexity-adjusted interpretation of RLR outcomes rather than a fixed case-number learning threshold.