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Table 5 Variables selected by LASSO regression for predicting DGF

From: Development and validation of a novel nomogram model for predicting delayed graft function in deceased donor kidney transplantation based on pre-transplant biopsies

Variables

β

P value

OR (95%CI)

VIF

Donor variables

Died of CVA or HIE

0.242

0.556

1.27 (0.57–2.87)

1.777

Hypotensive procedure (SBP < 100 mmHg)

0.447

0.163

1.56 (0.83–2.94)

1.185

CPR procedure

0.906

0.041

2.47 (1.01–5.84)

1.051

Terminal BUN (mmol/L)

0.112

< 0.001

1.12 (1.06–1.18)

1.849

Hypertension history

0.425

0.283

1.53 (0.71–3.38)

1.136

HMP parameters

Initial perfusion resistance (mmHg·min·mL− 1)

2.019

0.087

7.54 (0.72–77.11)

1.068

WIT (min)

CIT (h)

0.078

0.369

0.217

0.07

1.08 (0.95–1.23)

1.05 (0.97–1.11)

1.051

1.124

Pre-transplant biopsies

Mesangial matrix hyperplasia

0.706

0.052

2.03 (0.99–4.15)

1.586

Moderate or severe ATI

2.131

< 0.001

8.42 (4.22–17.22)

1.059

Banff score

0.122

0.136

1.13 (0.96–1.33)

1.962

  1. β is the regression coefficient. Terminal BUN, initial perfusion resistance, WIT, and Banff score were entered into the logistic model as continuous variables, and the other variables were entered as dichotomous variables. Abbreviations: CVA, cerebrovascular accident; HIE, hypoxic encephalopathy; SBP, systolic pressure; CPR, cardiopulmonary resuscitation; BUN, blood urea nitrogen; HMP, hypothermia machine perfusion; WIT, warm ischemia time; CIT, Cold ischemia time; ATI, acute tubular injury; VIF, variance inflation factor