Fractional Creatinine Clearance of the Donated Kidney Using Cockcroft-Gault Formula as a Predictor of Graft Function After Living Donor Transplantation

Lee, B.M.; Yoon, Seokyoung; Oh, Chang‐Keun; Kim, J.H.; Kim, S.J.; Kim, H.; Shin, Gyu‐Tae

doi:10.1016/j.transproceed.2006.06.024

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…The correlation between postoperative renal function and parameters such as BMIR, BSAR, WR, and GRWR-act have previously been discussed as indicators of donor-recipient size mismatch ( 12 – 16 ). Several reports have demonstrated some degree of correlation, but none of these indices sufficiently reflect the quantity of the “nephron mass.” Although GRWR-act might be a closer indicator than other parameters, it does not always reflect the “nephron mass” because it includes the weight of perirenal fatty tissue, renal portal vessels, and the ureter.…”

Section: Discussionmentioning

confidence: 99%

“…The donor-recipient size mismatch is manifested by the clearance capacity of the “nephron mass” in the donor graft, which is less than the recipient’s metabolite production. Because the “nephron mass” cannot be directly measured, alternative parameters that can be used as indicators of donor-recipient size mismatch include the donor to recipient weight ratio (WR), body mass index (BMI) ratio (BMIR), body surface area (BSA) index ratio (BSAR), actual graft weight (Graft-act) to recipient weight ratio (GRWR-act), and Graft-act to recipient BSA ratio, and the relationship between these parameters and posttransplantation renal function has been discussed in the previous literature ( 12 – 16 ). On the other hand, with the recent developments in medical technology, the “nephron mass” can be measured directly by quantifying the renal cortex using 3-dimensional (3D) CT-volumetry based on contrast-enhanced images obtained by multidetector raw CT (MDCT) ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

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Prediction of early graft function after living donor kidney transplantation by quantifying the “nephron mass” using CT-volumetric software

Takahashi

Furuya²,

Gosho³

et al. 2022

Front. Med.

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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 m2 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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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of early graft function after living donor kidney transplantation by quantifying the “nephron mass” using CT-volumetric software

Takahashi

Furuya²,

Gosho³

et al. 2022

Front. Med.

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“…Unfortunately, creatinine generation is also determined by the age, sex, weight and nutritional/ catabolic state of the patient. Creatinine clearance was used to estimate kidney function as a metric for glomerular filtration rate (GFR) as early as the 1930's [23,24] and is still widely used now to estimate GFR using a number of formulae such as Cockroft-Gault, Nankivell and MDRD (Modification of Diet in Renal Disease study) [25][26][27] designed to account for the factors noted above that affect creatinine generation and elimination. The obvious irony for kidney transplantation is that creatinine is still another surrogate biomarker for kidney function yet we are using it as the primary biomarker with which to manage complex immunosuppression regimes.…”

Section: Brief History Of Biomarkers-discovery and Current Statusmentioning

confidence: 99%

Applying genomics to organ transplantation medicine in both discovery and validation of biomarkers

Kurian

Grigoryev

Head

et al. 2007

International Immunopharmacology

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The field of biomarker discovery made a significant leap over the past few decades. As we enter the Era of the Human Genome, thousands of biomarkers can be identified in a relatively high-throughput fashion. While such magnitude and diversity of biomarkers can be seen as a challenge by itself, the field is being moved forward by new advances in bioinformatics and Systems Biology. Because of the life and death nature of end stage organ failure that transplantation treats, the severe donor organ shortage, and the powerful and toxic drug therapies required for the lifetimes of transplant patients, we envision a future for biomarkers as tools to diagnose disease in its early stages, predict prognosis, suggest treatment options and then assist in the implementation of therapies. By harnessing the power of multiple technologies in parallel makes it possible to discover and then validate the next generation of biomarkers for transplantation. We see the road ahead diverge into two paths: one from biomarkers to diagnosis and therapy and the other to a new level of insight into the complex molecular networks that determine when a healthy state becomes diseased and dysfunctional.

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Recovery of Graft Function Early Posttransplant Determines Long-Term Graft Survival in Deceased Donor Renal Transplants

Hassanain

Cantarovich

Metrakos

et al. 2009

Transplantation Proceedings

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Fractional Creatinine Clearance of the Donated Kidney Using Cockcroft-Gault Formula as a Predictor of Graft Function After Living Donor Transplantation

Cited by 7 publications

References 8 publications

Prediction of early graft function after living donor kidney transplantation by quantifying the “nephron mass” using CT-volumetric software

Prediction of early graft function after living donor kidney transplantation by quantifying the “nephron mass” using CT-volumetric software

Applying genomics to organ transplantation medicine in both discovery and validation of biomarkers

Recovery of Graft Function Early Posttransplant Determines Long-Term Graft Survival in Deceased Donor Renal Transplants

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