Evaluation of the learning curve of pediatric kidney transplantation anesthesia

Abstract

Background/aim Pediatric kidney transplantation (PKT) anesthesia brings some different challenges than adult kidney transplantation (KT) anesthesia and there are still no studies analyzing the role of experience on PKT outcomes. In this study, we aimed to evaluate the anesthesia learning curve in pediatric kidney transplants performed in our institution and the effect of increasing experience on renal transplantation-related data. Materials and methods Patients age ≤ 18 years who underwent KT were included in the study, while patients age >18 years were excluded. Patients were divided into 3 groups according to the date of transplant, as the first 10 patients in Group 1, the second 10 patients in Group 2, and the final 11 in Group 3. Groups were compared according to recorded data. Results Thirty-one patients were included in the study. Age, sex, and body mass index were matched between the 3 groups. The mean durations of dialysis were 75.0 ± 63.0, 22.4 ± 27.9, and 5.7 ± 4.5 months for Group 1, Group 2, and Group 3, respectively (p = 0.009). Blood loss, duration of postoperative mechanical ventilation, and length of stay in the intensive care unit (ICU) were comparable between the groups. The duration of anesthesia gradually shortened from Group 1 to Group 3 but there was no significant difference between the groups. The mean number of red blood cell (RBC) transfusion was 0.9 ± 0.7 unit in group 1. It decreased to a mean of 0.6 ± 0.7 unit for group 2, and afterward significant decrease occurred down to 0 for group 3 (p = 0.004). Conclusion Our results demonstrate that considering the decrease in preoperative dialysis duration and operative RBC transfusion, 20 patients may be enough for anesthesia competency. Transplantation anesthesia experience before PKT, anesthesia technique, and patient characteristics may differ between institutions. Therefore, further prospective studies with established learning curve goals, larger patient volumes, and more variables are needed to validate our results.