TY - JOUR
T1 - Random forest analysis identifies change in serum creatinine and listing status as the most predictive variables of an outcome for young children on liver transplant waitlist
AU - Kulkarni, Sakil
AU - Chi, Lisa
AU - Goss, Charles
AU - Lian, Qinghua
AU - Nadler, Michelle
AU - Stoll, Janis
AU - Doyle, Maria
AU - Turmelle, Yumirle
AU - Khan, Adeel
N1 - Publisher Copyright:
© 2020 Wiley Periodicals LLC
PY - 2021/5
Y1 - 2021/5
N2 - Young children listed for liver transplant have high waitlist mortality (WL), which is not fully predicted by the PELD score. SRTR database was queried for children < 2 years listed for initial LT during 2002-17 (n = 4973). Subjects were divided into three outcome groups: bad (death or removal for too sick to transplant), good (spontaneous improvement), and transplant. Demographic, clinical, listing history, and laboratory variables at the time of listing (baseline variables), and changes in variables between listing and prior to outcome (trajectory variables) were analyzed using random forest (RF) analysis. 81.5% candidates underwent LT, and 12.3% had bad outcome. RF model including both baseline and trajectory variables improved prediction compared to model using baseline variables alone. RF analyses identified change in serum creatinine and listing status as the most predictive variables. 80% of subjects listed with a PELD score at time of listing and outcome underwent LT, while ~70% of subjects in both bad and good outcome groups were listed with either Status 1 (A or B) prior to an outcome, regardless of initial listing status. Increase in creatinine on LT waitlist was predictive of bad outcome. Longer time spent on WL was predictive of good outcome. Subjects with biliary atresia, liver tumors, and metabolic disease had LT rate >85%, while >20% of subjects with acute liver failure had a bad outcome. Change in creatinine, listing status, need for RRT, time spent on LT waitlist, and diagnoses were the most predictive variables.
AB - Young children listed for liver transplant have high waitlist mortality (WL), which is not fully predicted by the PELD score. SRTR database was queried for children < 2 years listed for initial LT during 2002-17 (n = 4973). Subjects were divided into three outcome groups: bad (death or removal for too sick to transplant), good (spontaneous improvement), and transplant. Demographic, clinical, listing history, and laboratory variables at the time of listing (baseline variables), and changes in variables between listing and prior to outcome (trajectory variables) were analyzed using random forest (RF) analysis. 81.5% candidates underwent LT, and 12.3% had bad outcome. RF model including both baseline and trajectory variables improved prediction compared to model using baseline variables alone. RF analyses identified change in serum creatinine and listing status as the most predictive variables. 80% of subjects listed with a PELD score at time of listing and outcome underwent LT, while ~70% of subjects in both bad and good outcome groups were listed with either Status 1 (A or B) prior to an outcome, regardless of initial listing status. Increase in creatinine on LT waitlist was predictive of bad outcome. Longer time spent on WL was predictive of good outcome. Subjects with biliary atresia, liver tumors, and metabolic disease had LT rate >85%, while >20% of subjects with acute liver failure had a bad outcome. Change in creatinine, listing status, need for RRT, time spent on LT waitlist, and diagnoses were the most predictive variables.
KW - infant
KW - liver transplant
KW - machine learning
KW - outcome
KW - pediatric
KW - random forest analysis
KW - waitlist
UR - http://www.scopus.com/inward/record.url?scp=85096707862&partnerID=8YFLogxK
U2 - 10.1111/petr.13932
DO - 10.1111/petr.13932
M3 - Article
C2 - 33232568
AN - SCOPUS:85096707862
SN - 1397-3142
VL - 25
JO - Pediatric transplantation
JF - Pediatric transplantation
IS - 3
M1 - e13932
ER -