Dataset Information

A CT-based pelvic calcification score in kidney transplant patients is a possible predictor of graft and overall survival.

ABSTRACT:

Objectives

Computerized tomography (CT) is the most accurate method for evaluating pelvic calcifications, which are of utmost importance for planning kidney transplantation (KT). The aim of our study was to evaluate the incidence and distribution of iliac artery calcifications and correlate the novel pelvic calcification score (PCS) with cardiovascular risk factors and graft and overall survival in KT patients.

Methods

We retrospectively included 118 KT patients operated at our institution with pretransplant pelvic CT. Calcification morphology, circumference and length of both common and external iliac arteries were independently scored by two uroradiologists. PCS was calculated as the total score sum of all three calcification features in all vessels. PCS correlation with graft and patient survival was performed.

Results

Calcification in at least one vascular segment was found in 79% of patients. PCS was significantly higher in male patients (p = 0.006), patients over 55 years (p < 0.001), and patients on haemodialysis (p = 0.016). Patients with a PCS >3 had significantly shorter graft and overall survival rates (p = 0.041 and p = 0.039, respectively).

Conclusions

The extent of iliac artery calcification in KT recipients quantified by PCS on pretransplant CT correlates with graft and overall patient survival. A PCS over three was associated with worse clinical outcomes and could become a possible prognostic factor.

Advances in knowledge

Our novel PCS is a robust method for quantifying iliac artery calcification burden. Since higher a PCS correlates with worse patient and graft survival, PCS has the potential to become a prognostic factor in kidney transplant patients.

SUBMITTER: Zuza I

PROVIDER: S-EPMC9793470 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A CT-based pelvic calcification score in kidney transplant patients is a possible predictor of graft and overall survival.

Žuža Iva I Dodig Doris D Brumini Ivan I Tokmadžić Dorian D Orlić Lidija L Zgrablić David D Vukelić Ivan I Gršković Antun A Katalinić Nataša N Jakšić Ante A Miletić Damir D Rački Sanjin S Markić Dean D

The British journal of radiology 20221006 1139

<h4>Objectives</h4>Computerized tomography (CT) is the most accurate method for evaluating pelvic calcifications, which are of utmost importance for planning kidney transplantation (KT). The aim of our study was to evaluate the incidence and distribution of iliac artery calcifications and correlate the novel pelvic calcification score (PCS) with cardiovascular risk factors and graft and overall survival in KT patients.<h4>Methods</h4>We retrospectively included 118 KT patients operated at our in ...[more]

PMID: 36116132

Similar Datasets

Project description:BackgroundGraft loss is a major health concern for kidney transplant (KTx) recipients. It is of clinical interest to develop a prognostic model for both graft function, quantified by estimated glomerular filtration rate (eGFR), and the risk of graft failure. Additionally, the model should be dynamic in the sense that it adapts to accumulating longitudinal information, including time-varying at-risk population, predictor-outcome association, and clinical history. Finally, the model should also properly account for the competing risk by death with a functioning graft. A model with the features above is not yet available in the literature and is the focus of this research.MethodsWe built and internally validated a prediction model on 3,893 patients from the Wisconsin Allograft Recipient Database (WisARD) who had a functioning graft 6 months after kidney transplantation. The landmark analysis approach was used to build a proof-of-concept dynamic prediction model to address the aforementioned methodological issues: the prediction of graft failure, accounted for competing risk of death, as well as the future eGFR value, are updated at each post-transplant time. We used 21 predictors including recipient characteristics, donor characteristics, transplant-related and post-transplant factors, longitudinal eGFR, hospitalization, and rejection history. A sensitivity analysis explored a less conservative variable selection rule that resulted in a more parsimonious model with reduced predictors.ResultsFor prediction up to the next 1 to 5 years, the model achieved high accuracy in predicting graft failure, with the AUC between 0.80 and 0.95, and moderately high accuracy in predicting eGFR, with the root mean squared error between 10 and 18 mL/min/1.73m2 and 70%-90% of predicted eGFR falling within 30% of the observed eGFR. The model demonstrated substantial accuracy improvement compared to a conventional prediction model that used only baseline predictors.ConclusionThe model outperformed conventional prediction model that used only baseline predictors. It is a useful tool for patient counseling and clinical management of KTx and is currently available as a web app.

Dataset Information

A CT-based pelvic calcification score in kidney transplant patients is a possible predictor of graft and overall survival.

Objectives

Methods

Results

Conclusions

Advances in knowledge

Publications

A CT-based pelvic calcification score in kidney transplant patients is a possible predictor of graft and overall survival.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets