Predictive Model for Post-Transplant Renal Fibrosis Using Ultrasound Shear Wave Elastography

29 October 2024 : Original article

Juan Wang^1BE, Jianghong Chen^2CD, Yuewei Yin^3BF, Yuena Zhang^1C, Yulin Ma^1AG*

DOI: 10.12659/AOT.945699

Ann Transplant 2024; 29:e945699

Introduction Material and Methods Results Discussion Conclusions References

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Table 3 Predictive efficacy of each independent risk factor and nomogram for predicting renal allograft fibrosis.

Characteristics	Group	AUC	Youden index	P value	Cutoff	Sensitivity	Specificity	95% CI
Age (years)	Training group	0.637	0.532	0.000	43.00	0.688	0.605	0.231–0.67
Age (years)	Validation group	0.629	0.553	0.004	42.00	0.673	0.634	0.134–0.732
TST (months)	Training group	0.677	0.484	0.032	18.00	0.702	0.668	0.481–0.734
TST (months)	Validation group	0.679	0.477	0.020	18.00	0.699	0.654	0.346–0.702
Scr (μmol/L)	Training group	0.628	0.629	0.004	175.2	0.628	0.718	0.282–0.734
Scr (μmol/L)	Validation group	0.644	0.611	0.000	175.20	0.63	0.711	0.245–0.731
GFR (mL/min)	Training group	0.702	0.509	0.000	36.80	0.736	0.626	0.518–0.944
GFR (mL/min)	Validation group	0.711	0.503	0.000	36.80	0.721	0.611	0.483–0.883
Emean (kPa)	Training group	0.724	0.621	0.043	21.50	0.652	0.621	0.452–0.793
Emean (kPa)	Validation group	0.720	0.630	0.031	21.50	0.649	0.602	0.274–0.843
Nomogram	Training group	0.819	0.434	0.002	183.00	0.867	0.829	0.374–0.777
Nomogram	Validation group	0.808	0.472	0.002	183.00	0.854	0.83	0.325–0.802

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