Validation of the IWATE Criteria in Robotic-Assisted Liver Resections.
Sophia A LambertyJens Peter HölzenShadi KatouFelix BeckerMazen A JuratliAndreas AndreouM Haluk MorgulAndreas PascherBenjamin StrückerPublished in: Journal of clinical medicine (2024)
Background/Objectives : The IWATE criteria are well-established as a helpful tool to preoperatively estimate the difficulty and perioperative outcome of laparoscopic liver resections. We evaluated the relationship between the IWATE criteria and the perioperative outcomes in robotic-assisted liver resections (RARLs). Methods : We retrospectively analyzed the data of 58 patients who underwent robotic-assisted liver surgery at our center between July 2019 and April 2023. The operative difficulty of every patient was graded according to the IWATE criteria and compared to the perioperative outcome. Results : The median operation time was 236.5 min (range 37-671 min), and the median length of stay was 6 days (range 3-37 min). The majority had no complications (65.5%; n = 38), 18 (31.0%) patients suffered from mild complications (CD ≤ 3A) and 2 patients (3.4%) suffered from relevant complications (CD ≥ 3B). We observed no deaths within 30 postoperative days. The surgery time, postoperative ICU stay and perioperative blood transfusions increased significantly with a higher difficulty level ( p = < 0.001; p < 0.001; p = 0.016). The length of stay, conversion to open surgery ( n = 2) and complication rate were not significantly linked to the resulting IWATE group. Conclusions : The IWATE criteria can be implemented in robotic-assisted liver surgery and can be helpful in preoperatively estimating the difficulty of robotic liver resections. Whether there is a "robotic effect" in minimally invasive liver resections has to be further clarified. The IWATE criteria can help to develop curricula for robotic training.
Keyphrases
- minimally invasive
- end stage renal disease
- patients undergoing
- ejection fraction
- chronic kidney disease
- robot assisted
- newly diagnosed
- coronary artery bypass
- cardiac surgery
- peritoneal dialysis
- type diabetes
- risk factors
- intensive care unit
- acute coronary syndrome
- machine learning
- patient reported
- surgical site infection
- atrial fibrillation
- deep learning