Evidence map›Paper›PMID 40590968›Full record

ArticleAbdominal radiology (New York)2026

Expanding aorto-iliac calcification quantification in kidney transplant recipients: prognostic implications for survival and renal function.

Amirmasoud Negarestani, Gerges Abdelsayed, Ashima Kundu, Caleb Bhatnagar, Andrew Pasion, Joseph Zywiciel, Jian-Feng Chen, Emad Allam

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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Amirmasoud NegarestaniDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA. negaarestani@gmail.com.
Gerges AbdelsayedDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Ashima KunduDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Caleb BhatnagarDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Andrew PasionDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Joseph ZywicielDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Jian-Feng ChenDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.
Emad AllamDepartment of Radiology, Loyola University Medical Center, Maywood, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAorto-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.

methodsWe 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.

resultsHigher 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.

conclusionAIC 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.

Indexed as

Aortic DiseasesIliac ArteryKidney TransplantationPostoperative ComplicationsTomography, X-Ray ComputedVascular CalcificationAdultAgedFemaleGlomerular Filtration RateHumansMaleMiddle AgedPrognosisRetrospective StudiesAgatston scoreeGFR trajectoryKidney transplantationMortality risk stratificationSurvival predictionVascular calcification

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.