Dataset Information

Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study.

ABSTRACT: Delayed graft function (DGF) after kidney transplantation is common and associated with worse graft outcomes. However, little is known about factors affecting graft survival post-DGF. We studied the association of cold ischemia time (CIT) and Kidney Donor Profile Index (KDPI) with the long-term outcomes of deceased brain-dead donor kidneys with and without DGF. Data from Finland (n = 2,637) and from the US Scientific Registry of Transplant Recipients (SRTR) registry (n = 61,405) was used. The association of KDPI and CIT with the graft survival of kidneys with or without DGF was studied using multivariable models. 849 (32%) kidneys had DGF in the Finnish cohort. DGF and KDPI were independent risk factors for graft loss, [HR 1.32 (95% CI 1.14-1.53), p < 0.001, and HR 1.01 per one point (95% CI 1.01-1.01), p < 0.001, respectively], but CIT was not, [HR 1.00 per CIT hour (95% CI 0.99-1.02), p = 0.84]. The association of DGF remained similar regardless of CIT and KDPI. The US cohort had similar results, but the association of DGF was stronger with higher KDPI. In conclusion, DGF and KDPI, but not CIT, are independently associated with graft survival. The association of DGF with worse graft survival is consistent across different CITs but stronger among marginal donors.

SUBMITTER: Ahlmark A

PROVIDER: S-EPMC10942003 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study.

Ahlmark Amanda A Sallinen Ville V Eerola Verner V Lempinen Marko M Helanterä Ilkka I

Transplant international : official journal of the European Society for Organ Transplantation 20240301

Delayed graft function (DGF) after kidney transplantation is common and associated with worse graft outcomes. However, little is known about factors affecting graft survival post-DGF. We studied the association of cold ischemia time (CIT) and Kidney Donor Profile Index (KDPI) with the long-term outcomes of deceased brain-dead donor kidneys with and without DGF. Data from Finland (<i>n</i> = 2,637) and from the US Scientific Registry of Transplant Recipients (SRTR) registry (<i>n</i> = 61,405) wa ...[more]

PMID: 38495816

Similar Datasets

Project description:BackgroundKidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making.MethodsThis single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods.ResultsThe study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model.ConclusionsIn this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

Project description:BACKGROUND:Critical shortages of organs for transplantation jeopardize many lives. Observational data suggest that better fluid management for deceased organ donors could increase organ recovery. We conducted the first large multicenter randomized trial in brain-dead donors to determine whether protocolized fluid therapy increases the number of organs transplanted. METHODS:We randomly assigned donors to either protocolized or usual care in eight organ procurement organizations. A "protocol-guided fluid therapy" algorithm targeting the cardiac index, mean arterial pressure and pulse pressure variation was used. Our primary outcome was the number of organs transplanted per donor, and our primary analysis was intention to treat. Secondary analyses included: (1) modified intention to treat where only subjects able to receive the intervention were included and (2) 12-month survival in transplant recipients. The study was stopped early. RESULTS:We enrolled 556 donors: 279 protocolized care and 277 usual care. Groups had similar characteristics at baseline. The study protocol could be implemented in 76 % of subjects randomized to the intervention. There was no significant difference in mean number of organs transplanted per donor: 3.39 organs per donor (95 % CI 3.14-3.63) with protocolized care compared to 3.29 usual care (95 % CI 3.04-3.54; mean difference, 0.1, 95 % CI -0.25 to 0.45; p = 0.56). In modified intention-to-treat analysis the mean number of organs increased (3.52 organs per donor, 95 % CI 3.23-3.8), but not statistically significantly (mean difference, 0.23, 95 % CI -0.15 to 0.61; p = 0.23). Among the 1,430 recipients of organs from study subjects with data available, 56 deaths (7.8 %) occurred in the protocolized care arm and 56 (7.9 %) in the usual care arm in the first year (hazard ratio: 0.97, p = 0.86). CONCLUSIONS:In brain-dead organ donors, protocol-guided fluid therapy compared to usual care may not increase the number of organs transplanted per donor.

Dataset Information

Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study.

Publications

Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets