Journal of Transplantation最新文献

Introduction: The integration of artificial intelligence (AI) in liver and kidney transplantation (LKT) research has surged in recent years, promising novel approaches to address traditional statistical challenges and enhance result robustness and generalizability. This study aims to explore the extent of international collaboration and the evolution of research trends in AI applications for LKT.

Methods: On August 12, 2025, a systematic search was conducted using the Web of Science database to identify relevant literature. Bibliometric tools, including the "bibliometrix" package in R, VOSviewer, and Microsoft Excel were used. Key indicators such as country contributions, multiple-country publications, single-country publications, co-authorship, and keyword co-occurrence were examined to assess collaboration patterns and research hotspots. Inclusion criteria involved all published peer-reviewed articles related to AI in LKT. Editorials, corrections, and irrelevant documents were excluded.

Results: A total of 633 articles published between 1994 and 2025 were included in the analysis. These collectively received 8959 citations. The United States of America emerged as the leading contributor, accounting for 37.12% of the publications, followed by China and South Korea. Notably, international co-authorship was evident in 30.02% of the publications. Keyword analysis revealed that "survival," "outcomes," "risk," "mortality," and "prediction" were the most frequent terms, highlighting them as hotspots in transplantation research.

Conclusion: The field of AI in LKT research is characterized by a growing international collaboration, despite the fact that participation is still uneven and concentrated in high-income countries. In order to advance the field and enhance outcomes across diverse patient populations, it will be crucial to strengthen global data-sharing and cultivate equity-focused, culturally adaptable AI models.

Background: Liver transplantation (LT) is offered as a life-saving treatment to those with end-stage liver disease. There has recently been much interest in considering the survival benefit of transplant when prioritizing patients for transplant. In this study, we aimed to measure the survival benefit of LT across various patient demographics by measuring the number of life-years gained after LT.

Method: In this study, 101,770 patients were included from the Scientific Registry of Transplant Recipients (SRTR) transplanted between 2003 and 2021. The survival benefit of LT was calculated using restricted mean survival time (RMST) in the next 16 years post-transplant. Cox proportional hazard models and Weibull models were employed to quantify the impact of various predictors on survival benefit.

Results: LT was found to provide survival gains of 4.93, 6.43, 6.30, and 3.67 years for the 18-29, 30-49, 50-69, and 70+ age groups, respectively. Survival benefit was highest at 6.62 years for patients with model for end-stage liver disease (MELD) scores of 15-19, with survival benefits of 5.7, 5.4, and 5.85 years for the 6-14, 20-29, and 30-40 MELD score cohorts, respectively. Older age (HR: 1.13), male sex (HR: 1.32), diabetes (HR: 1.32), and higher MELD scores were predictors of lesser survival benefit. Protective factors included higher education levels (HR: 0.70) as well as diagnoses of fulminant liver failure and autoimmune biliary disease (HR: 0.65).

Conclusion: This study underscores how survival benefit varies across patients with different demographic and clinical characteristics, highlighting the nuanced interplay of these characteristics with survival and emphasizing the need for tailored post-transplant management strategies to optimize outcomes.

Background: Predicting whether an organ offer will be accepted for transplantation remains challenging for several reasons, including large offer volumes, highly imbalanced observations (more declines than acceptances), and lack of information about the human decision-making process. Offer acceptance models are used for risk-adjusted program evaluations and policy development, but there is a lack of literature on baselines and best practices for predictive applications. We compared a suite of machine learning models, feature sets, and sampling procedures to identify performance impacts when training offer acceptance prediction models.

Methods: We evaluated several kidney offer acceptance models from logistic regression to gradient boosted trees that were trained on donor and candidate characteristics. We then selected the best-performing model and augmented training data with additional features (e.g., distance from the closest airport to the transplant hospital) or additional sampling procedures (e.g., undersampling).

Results: Compared to the baseline logistic regression model (average precision: 0.0645), the XGBoost model offered the best performance improvement over the baseline (average precision: 0.0907). Including transportation-related features in the model further improved model performance (average precision: 0.0940); however, we did not observe substantial model performance differences based on the sampling procedure used.

Conclusions: Leveraging advanced machine learning models and incorporating nonclinical datapoints (like transportation distances) can improve transplant organ offer acceptance prediction models. However, we observed steep tradeoffs between precision and recall as captured in the low average precision scores despite deceptively high AUROCs (baseline AUROC 0.832). Our findings suggest that even the best-performing models would not provide clear, equitable benefits over existing allocation policies. More research is needed before these models are practical for clinical implementation.

Objectives: To retrospectively review all cases of posttransplant lymphoproliferative disorder (PTLD) in a large Brazilian transplant center, describing patients' clinical, virological, and histopathological profiles and treatment strategies and prognostic factors.

Methods: This retrospective cohort study was conducted between January 2000 and June 2024. Adult patients with confirmed PTLD following solid-organ or bone marrow transplant were included. Patients with other systemic cancers or on concurrent chemotherapy/radiotherapy were excluded. Clinical characteristics, PTLD prevalence, histopathology, and survival were assessed.

Results: Thirty-eight cases of PTLD were identified in the 5928 transplant patients (0.6%). Incidence was highest in lung recipients (31%). Median time to PTLD onset was 42 months. EBV DNA was detectable in 54.8% of cases. Monomorphic PTLD was the most common (89.5%), primarily in non-Hodgkin lymphomas (91.2%). Immunotherapy (anti-CD20) and immunosuppression reduction were standard initial treatments. R-CHOP and rituximab monotherapy were the main first-line regimens. Age and treatment response significantly influenced overall survival. Mortality was 42%, mainly due to infections and disease progression.

Conclusions: Despite the higher prevalence of EBV in Brazil, PTLD patterns and incidence were consistent with those found in developed countries. The strong association with lung transplants mirrors global data. Local EBV subtype characteristics and host immunogenetic factors warrant further investigation.

Introduction: Thymoglobulin, a lymphocyte-depleting agent, is widely used for induction immunosuppression in kidney transplantation. Despite guideline support, there is no standardized dosing recommendation, resulting in variability across centers. In April 2022, our institution reduced its institutional practice thymoglobulin dose from 4.5 to 3 mg/kg for low-risk kidney transplant recipients. This study aimed to evaluate the noninferiority of the reduced dose compared to the prior regimen in terms of effectiveness and safety.

Methods: This single-center retrospective noninferiority cohort study of low-risk kidney transplant recipients was conducted from April 2020 to April 2024. Patients received either 3 or 4.5 mg/kg of thymoglobulin. The primary outcome was a composite of biopsy-proven or suspected acute rejection, graft loss, or death within 6 months posttransplant. Secondary outcomes included leukopenia, thrombocytopenia, infections, delayed graft function, eGFR, malignancies, and hospital length of stay.

Results: A total of 196 patients were included (116 in 4.5 mg/kg; 80 in 3 mg/kg). The primary outcome occurred in 11% and 3% of patients, respectively (risk difference -8.7%, 95% CI -15.4 to -2.0; p = 0.024). The reduced-dose group experienced significantly lower rates of leukopenia, thrombocytopenia, and viral infections.

Conclusion: A 3 mg/kg thymoglobulin dose is noninferior to 4.5 mg/kg and is associated with improved safety in low-risk kidney transplant recipients.

Autoimmune cytopenia (AIC) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT) is relatively rare but it is a challenging complication, and standardized treatment guidelines are lacking. We retrospectively analyzed 436 pediatric patients undergoing allo-HSCT; 37 (8.5%) developed AIC, characterized by autoimmune hemolytic anemia (n = 13), immune thrombocytopenia (n = 11), and Evans syndrome (n = 13). Risk factor analysis revealed that younger age at HSCT, nonmalignant diseases, unrelated donor transplantation, and chronic graft-versus-host disease (cGVHD) were significantly associated with the development of AIC. Through multivariate analysis, cGVHD was identified as an independent risk factor for AIC. In our study, the first-line treatment for AIC involved steroids and/or intravenous immunoglobulin, with a complete remission rate of 48.6%. Additional therapeutic strategies included rituximab, which led to complete remission in 5 of 12 patients we treated, and sirolimus, with 3 of 7 patients achieving complete remission. Three patients achieved partial remission, while 9 patients died due to complications, such as severe infections, extensive GVHD, and multiorgan bleeding. Our findings suggest that cGVHD is an independent risk factor for post-transplant AIC and is typically associated with adverse outcomes, highlighting the critical importance of timely and effective interventions.

Background: Urinary tract infections (UTIs) remain the leading infectious complication after kidney transplantation. We evaluated intraoperative gentamicin bladder irrigation as a novel preventive strategy.

Methods: In this randomized, double-blind controlled trial at a tertiary transplant center (January-December 2021), 147 kidney transplant recipients were randomized to receive intraoperative bladder irrigation with gentamicin (160 mg/250 mL) or saline during ureteroneocystostomy. Due to baseline imbalances, propensity score matching yielded 49 matched pairs. The primary endpoint was UTI incidence within 30 days post-transplant, defined by both microbiological (≥ 10⁵ CFU/mL) and clinical criteria.

Results: UTI incidence was 26.5% (13/49) in controls versus 16.3% (8/49) with gentamicin (absolute risk reduction 10.2%, p=0.325). The number needed to treat was 10 overall. Striking sex-specific differences emerged: females demonstrated 40.7% baseline UTI risk versus 14.1% in males (p=0.004). Gentamicin efficacy varied markedly by sex, with the NNT of 5 for females (50.0%-30.8%) versus 17 for males (17.1%-11.1%). Living donor recipients showed greater benefit (NNT = 7) than deceased donor recipients (NNT = 23). No adverse events were attributable to gentamicin, with similar rates of bacteremia and surgical site infections between groups.

Conclusions: Intraoperative gentamicin bladder irrigation safely reduced early post-transplant UTIs by 38.5%, with efficacy in female recipients. While underpowered for statistical significance, the clinically meaningful effect size and excellent safety profile support considering this intervention for high-risk recipients, especially females, pending larger confirmatory trials.

Introduction: Liver transplantation (LT) offers a lifesaving treatment for patients with end-stage liver disease (ESLD). There have been conflicting reports of outcomes in younger and elderly patients undergoing LT. This study assesses the outcomes of younger and elderly LT recipients by complications and graft survival at early and late time-points, up to 10 years.

Patients and methods: This retrospective study was conducted on a prospectively collected database of patients who underwent LT between January 2011 and December 2021 at the University of Alberta Hospital in Edmonton, Canada.

Results: A total of 696 patients who were 18 years and older were included and then classified into two groups: the younger adult group (YG; n = 631, < 65 years old) and the older adult group (OG; n = 65, > 65 years old). The YG was sicker, with a high model for ESLD (MELD) score, while the OG had a high incidence of coronary artery disease (CAD), hypertension, smoking, and hepatocellular carcinoma. The YG had a higher incidence of postoperative pleural effusion requiring drainage (108/631 [17%] versus 4/65 [6%]; p value < 0.02) and more rejection episodes (202/631 [32%] versus 10/65 [15%]; p value < 0.04). However, the OG had more hepatic artery thrombosis (HAT) (4/65 [6.1%] versus 10/631 [1.6%]; p value 0.03). CAD and smoking history were associated with lower patient and graft survivals; acute rejection episodes were also associated with significantly lower graft survival.

Conclusion: The patient and graft survival between the YG and OG are comparable at 30 days, 90 days, 1, 5 and 10 years. A history of CAD, smoking and rejection episodes decreased graft survival and age alone should not be a contraindication for LT.

Background: Despite the National Kidney Registry's (NKR) widespread adoption, limited data exist to explain center-specific trends in live kidney donation (LKD) in rural areas.

Methods: A retrospective review of 1776 referrals (894 before and 882 after NKR integration on February 1, 2018) for LKD at our center between June 1, 2012, and May 31, 2022, was performed. LKD referrals were comparatively analyzed between pre- and post-NKR phases and followed through subsequent evaluation, donation, or termination of donor candidacy.

Results: Both pre- and post-NKR, donors were most likely to be White (93.2% vs. 89.4%, p=0.33), women (73.0% vs. 66.0%, p=0.51), from South Dakota or neighboring states (97.3% vs. 89.4%, p=0.11), and employed (95.9% vs. 95.7%, p=0.99). Following NKR affiliation, our center experienced a significant increase in LKDs (74 vs. 47, p=0.008), most notably from nondirected (9 vs. 1, p=0.04) and rural (37 vs. 18, p=0.099) donors and those from socioeconomically disadvantaged (Area Deprivation Index: 3 vs. 4 state decile, p=0.055, and 47 vs. 54 national percentile, p=0.056) communities. Post-NKR donor pool showed greater diversity in educational backgrounds and lower rates of tobacco and illicit drug use. Also, post-NKR referrals were evaluated, on average, 10 days sooner (66 vs. 76 days and p=0.01) and were less likely to retract or be lost to follow-up after evaluation (25.1% vs. 32.7% and p=0.04).

Conclusion: NKR potentiates expanded LKD at rural transplant centers. Efforts to increase LKD among men and People of Color remain areas of opportunity.

Background: Weight gain is common after kidney transplantation. This study assessed the incidence of overweight and obesity, identified the risk factors, and evaluated their impact on graft function and metabolic outcomes at 1 year.

Methods: This retrospective observational study included 179 kidney transplant recipients at King Fahad Armed Forces Hospital, Jeddah, Saudi Arabia, between January 2020 and December 2023. The baseline and 12-month BMI were recorded. Associations with demographic, clinical, and metabolic variables, as well as graft function and complications, were analyzed. Logistic regression identified independent predictors of being overweight (BMI ≥ 25 kg/m²) and obese (BMI ≥ 30 kg/m²).

Results: At baseline, 83 (46.4%) recipients had BMI < 25 kg/m², 55 (30.7%) were overweight, and 41 (22.9%) were obese. At 12 months, the prevalence of obesity increased to 67 (37.4%), while the normal BMI category decreased to 55 (30.7%), with the overweight category remaining relatively stable at 57 (31.8%). The baseline BMI was the strongest predictor of overweight (OR 1.72, 95% CI 1.45-2.04) and obesity (OR 1.74, 95% CI 1.47-2.05) at 12 months. In sensitivity analysis excluding the baseline BMI, a family history of diabetes predicted obesity (OR 4.41, 95% CI 1.78-10.96). Obese patients had numerically higher creatinine and lower eGFR, but differences were not statistically significant. No differences were observed in CMV infection, prediabetes, new-onset diabetes after transplantation, acute coronary syndrome, or mortality. Overall, patient survival was 100% at 12 months.

Conclusion: Posttransplant overweight and obesity are common. The baseline BMI and family history of diabetes are key predictors. The higher BMI is associated with early metabolic changes and trends toward lower graft function, highlighting the need for early monitoring and targeted interventions.