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Updated: Sep 17, 2025

A Semi-Automated and Reproducible Biological-Based Method to Quantify Calcium Deposition In Vitro
Published on: June 2, 2022
Expanding aorto-iliac calcification quantification in kidney transplant recipients: prognostic implications for
Amirmasoud Negarestani1, Gerges Abdelsayed2, Ashima Kundu2
1Department of Radiology, Loyola University Medical Center, Maywood, IL, USA. negaarestani@gmail.com.
Background:
Aorto-iliac calcification (AIC) is increasingly recognized as a prognostic marker in kidney transplantation, yet its relationship with long-term outcomes remains unclear.
Purpose:
To evaluate whether pre-transplant AIC scores independently predict post-transplant mortality and renal function (eGFR trajectory) in kidney transplant recipients.
Methods:
We retrospectively analyzed 150 renal transplant recipients ≥ 40 years old who underwent pre-transplant abdominopelvic CT within 3 years of surgery (2005-2018). AIC scores were calculated using a modified Agatston method. Primary outcome was all-cause mortality; secondary outcome was longitudinal eGFR. Cox proportional hazards models assessed the association between AIC and mortality. Linear mixed-effects models and nonparametric tests evaluated the relationship between AIC and eGFR trajectory. Time-dependent ROC curves evaluated model discrimination over time.
Results:
Higher AIC scores were independently associated with increased mortality (adjusted HR per 100 units: 1.009, 95% CI: 1.004-1.013, p < 0.001). When modeled by quartiles, patients in the highest AIC quartile had a 10.87-fold higher adjusted mortality risk than those in the lowest (p < 0.001). AIC was not significantly associated with eGFR decline in either multivariable models or sensitivity analyses. Time-dependent AUCs ranged from 0.70 to 0.79 across 2-11 years, demonstrating stable model discrimination.
Conclusion:
AIC is a robust predictor of post-transplant mortality but not of eGFR trajectory. Incorporating AIC quantification into pre-transplant evaluations may improve long-term risk stratification and guide clinical decision-making.
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