Determination of tacrolimus dosage using machine learning in kidney transplantation
Sangkyun Mok3, Sun Cheol Park1, Young Jun Park2, Sang Seob Yun1.
1Department of Surgery, Seoul St. Mary's Hospital, Seoul, Korea; 2Department of Surgery, Yeouido St. Mary's Hospital, Seoul, Korea; 3Department of Surgery, Uijeongbu St. Mary's Hospital, Uijeongbu, Korea
Introduction: Maintaining tacrolimus trough levels in kidney transplantation is very important. The purpose of this study is to analyze the determination of tacrolimus dosage to maintain tacrolimus trough levels using machine learning.
Methods: This retrospective study included 801 consecutive patients from a prospectively registered database who underwent kidney transplantation at Seoul St. Mary’s Hospital, South Korea, between January 1, 2015 and December 30, 2019. After kidney transplantation, supervised learning was performed based on individual tacrolimus trough levels and tacrolimus dosage during hospitalization.
Results: A total of 771 patients were enrolled in the study with a mean age 48.7± 11.5 years (range 16 –75). 445 (57.7%) patients was male. 326 (42.3%) patients was female. 157 (20.4%) was ABO incompatible kidney transplantation. and 196 (25.4%) patinets was deceased donor kidney transplnatation. Significant results of tacrolimus trough levels and tacrolimus dosage during hospitalization were confirmed through machine learning, It was analyzed that weight had a significant effect.
Conclusion: Determination of tacrolimus dosage to maintain appropriate tacrolimus trough levels through machine learning during hospitalization after kidney transplantation should be considered as a useful tool.
Keywords: Kidney transplantation, Machine learning, Tacrolimus.
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