Prediction of early graft function after living donor kidney transplantation by quantifying the “nephron mass” using CT-volumetric software
Early renal function after living-donor kidney transplantation (LDKT) depends on the “nephron mass” in the renal graft. In this study, as a possible donor-recipient size mismatch parameter that directly reflects the “nephron mass,” the cortex to recipient weight ratio (CRWR) was calculated by CT-vol...
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Published in | Frontiers in medicine Vol. 9; p. 1007175 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
28.10.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Early renal function after living-donor kidney transplantation (LDKT) depends on the “nephron mass” in the renal graft. In this study, as a possible donor-recipient size mismatch parameter that directly reflects the “nephron mass,” the cortex to recipient weight ratio (CRWR) was calculated by CT-volumetric software, and its ability to predict early graft function was examined. One hundred patients who underwent LDKT were enrolled. Patients were classified into a developmental cohort (
n
= 79) and a validation cohort (
n
= 21). Using the developmental cohort, the correlation coefficients between size mismatch parameters, including CRWR, and the posttransplantation estimated glomerular filtration rate (eGFR) were calculated. Multiple regression analysis was conducted to define a formula to predict eGFR 1-month posttransplantation. Using the validation cohort, the validity of the formula was examined. The correlation coefficient was the highest for CRWR (1-month
r
= 0.66,
p
< 0.001). By multiple regression analysis, eGFR at 1-month was predicted using the linear model: 0.23 × donor preoperative eGFR + 17.03 × CRWR + 8.96 × preemptive transplantation + 5.10 (adjusted coefficient of determination = 0.54). In most patients in the validation cohort, the observed eGFR was within a 10 ml/min/1.73 m
2
margin of the predicted eGFR. CRWR was the strongest parameter to predict early graft function. Predicting renal function using this formula could be useful in clinical application to select proper donors and to avoid unnecessary postoperative medical interventions. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Rahul Grover, Max Super Speciality Hospital, India; Andrea Ranghino, Azienda Ospedaliero Universitaria Ospedali Riuniti, Italy; Sonu Manuel, St Mary’s Hospital, India These authors have contributed equally to this work This article was submitted to Nephrology, a section of the journal Frontiers in Medicine Edited by: Sree Bhushan Raju, Nizam’s Institute of Medical Sciences, India |
ISSN: | 2296-858X 2296-858X |
DOI: | 10.3389/fmed.2022.1007175 |