Prediction of Renal Graft Function 1 Year After Adult Deceased-Donor Kidney Transplantation Using Variables Available Prior to Transplantation

01 October 2024 : Original article

Ulrich Zwirner

^1ABCDEF*, Dennis Kleine-Döpke

^1ABCD, Alexander Wagner^1CDE, Simon Störzer^1BE, Felix Gronau^1EF, Oliver Beetz^2BDE, Nicolas Richter

^1BD, Wilfried Gwinner

^3DE, Ulf Kulik

^1ABE, Moritz Schmelzle^1DE, Harald Schrem

^4ABCDEF

DOI: 10.12659/AOT.944603

Ann Transplant 2024; 29:e944603

Introduction Material and Methods Results Discussion Conclusions References

Related articles Order reprints Share article Share by email

View HTML version

Table 5 Univariable linear regression analysis of pre-transplant donor variables and their influence on eGFR 1 year after KTx.

Continuous data		R2	p-value
Clinical characteristics	Age in years	0.198	<0.001
	Weight in kg	0.001	0.225
	Height in cm	0.029	<0.001
	BMI in kg/m	0.005	0.011
	Ventilation time in hours	<0.001	0.602
	Last potassium value in mmol/l	0.001	0.421
	Last creatinine value in μmol/l	0.003	0.085
	Last urea value in mmol/l	0.001	0.415

Clinical characteristics	Sex (Female)	0.009	0.001
	Blood group A (yes)	<0.001	0.589
	Blood group B (yes)	0.002	0.181
	Blood group 0 (yes)	<0.001	0.747
	Blood group AB (yes)	<0.001	0.913
Most probable cause of death	Anoxic brain damage, not elsewhere classified (yes)	<0.001	0.720
	Cerebral oedema (yes)	0.011	<0.001
	Cerebro-vascular accident, not otherwise specified (yes)	<0.001	0.625
	Circulatory (yes)	0.001	0.308
	CNS infarction (yes)	0.002	0.111
	CNS trauma (yes)	0.031	<0.001
	CNS tumor (yes)	<0.001	0.578
	CVA bleeding (yes)	0.028	<0.001
	Meningitis/encephalitis (yes)	<0.001	0.956
	Not otherwise specified (yes)	0.002	0.091
	Respirational (yes)	0.010	0.001
	Subdural Hematoma (yes)	0.001	0.207
	Subarachnoid haemorrhage (yes)	0.005	0.012
	Trauma (yes)	0.010	0.001
Results of the univariable linear regression analysis to determine significance of the influence of donor-related variables on eGFR one year after KTx. All continuous variables were additionally subjected to a principal component analysis for exclusion of multi-collinearity. All remaining variables were included into the subsequent multivariable linear regression modelling. BMI – body mass index; CNS – central nervous system; CVA – cerebro-vascular accident.

Back to the Article