Journal of Heart and Lung Transplantation最新文献

Background: Multicomponent improvement (MCI) is a novel endpoint for predicting survival in patients with pulmonary arterial hypertension (PAH), included in the sotatercept clinical program. For the first time, we investigated the prognostic value of MCI, ESC/ERS 4-strata risk (4SR) assessment, and the non-invasive French risk stratification score (FRS), for predicting survival in PAH patients in Sweden. All risk prediction models are based on three parameters: WHO-FC (World Health Organization Functional Class), NT-proBNP, and 6MWD (6-minute walk distance).

Methods: Data from the Swedish PAH & CTEPH Registry (SPAHR) collected 2008-2021 were used for the analyses. The association of MCI achievement, 4SR, and FRS calculated at 6 months (6M), with transplant-free (TF) survival was investigated in the whole cohort, as well as categorized by age (<65 and ≥65 years). All risk prediction models are based on three parameters: WHO-FC (World Health Organization Function Class), NT-proBNP, and 6MWD (6-minute walk distance). Kaplan-Meier estimate/Log-Rank test and Cox proportional model were used for survival analyses.

Results: The study included 411 patients (70% women) with a median [IQR] age of 66y.²¹ At 6M, the mean (SD) NT-proBNP decrease was 808 (603) and the mean 6MWD increase was 44 (11) meters. Median survival/follow-up time was 3.5y [1.7, 5.4]. After adjustment for sex and comorbidities, achievement of MCI independently predicted TF-survival; one MCI-criterion met (HR 0.65; CI 0.46-0.92, p=0.015); two MCI-criteria met (HR 0.45; CI 0.31-0.66, p<0.001); all three MCI-criteria met (HR 0.32; CI 0.21-0.52, p<0.001). Likewise, 4SR and FRS demonstrated a strong association with TF-survival with patients achieving lower risk scores exhibiting longer survival compared to those with higher risk scores. Patients ≥65Y more often had connective tissue disease-associated PAH, lower DLCO, more pronounced comorbidity burden, higher risk at baseline, less improvement during follow-up, and worse TF-survival then patients <65Y.

Conclusion: All models were found to have prognostic relevance for TF-survival. Risk prediction was incremental with the number of low-risk criteria met, while improvements in only one of 6MWD, NT-proBNP, or FC showed a modest association with survival. The risk assessment tools predicted outcome in patients across both age categories.

Ischemia-reperfusion injury (IRI) plays a crucial role in the development of primary graft dysfunction (PGD) following lung transplantation. A promising novel approach to optimize donor organs before transplantation and reduce the incidence of PGD is mitochondrial transplantation. In this study, we explored the delivery of isolated mitochondria in 4 hour ex vivo lung perfusion (EVLP) before transplantation as a means to mitigate IRI. To provide a fresh and viable source of mitochondria, as well as to streamline the workflow without the need for donor muscle biopsies, we investigated the impact of autologous, allogeneic and xenogeneic mitochondrial transplantation. In the xenogeneic settings, isolated mitochondria from mouse liver were utilized while autologous and allogeneic sources came from pig skeletal muscle biopsies. Treatment with mitochondrial transplantation increased the P/F ratio and reduced pulmonary peak pressure of the lungs during EVLP, compared to lungs without any mitochondrial transplantation, indicating IRI mitigation. Extensive investigations using advanced light and scanning electron microscopy did not reveal evidence of acute rejection in any of the groups, indicating safe xenotransplantation of mitochondria. Future work is needed to further explore this novel therapy for combating IRI in lung transplantation, where xenotransplantation of mitochondria may serve as a fresh, viable source to reduce IRI.

Background: Lung continuous distribution (CD), implemented on March 9, 2023, changed the calculation and relative importance of medical urgency and posttransplant survival in prioritizing candidates for transplant. We aimed to identify factors associated with waitlist clinical deterioration and change in expected posttransplant survival from listing to transplant in the current system.

Methods: We used Organ Procurement and Transplantation Network (OPTN) data to conduct a retrospective study of 2,395 adult, lung-only transplant recipients added to the waiting list and transplanted between March 09, 2023, and March 08, 2024. We used multivariable linear regression to identify factors associated with change in waitlist area under the curve (WLAUC) and posttransplant area under the curve (PTAUC), representing expected survival (in days) without and with transplant, respectively.

Results: In multivariable analysis, longer waiting time (β=-1.3 per 7 days; p<0.001), male birth sex (β=-11; p=0.006), diagnosis group D (β=-27; p<0.001), and blood type O (β=-13; p<0.001) were associated with greater clinical deterioration from listing to transplant. Older (β=3.2 per 10-year increase in age; p=0.023) and taller (β=3.0 per 5 cm increase in height; p=0.003) recipients were less likely to clinically deteriorate from listing to transplant. Diagnosis group D (β=-4.7, p=0.032) and blood type O (β=-4.2, p=0.025) recipients had lower expected posttransplant survival at transplant compared to listing.

Conclusion: Our findings suggest the need to further investigate and address factors associated with waitlist clinical deterioration under CD. Future analysis of the effect of waitlist clinical deterioration on posttransplant outcomes under CD is needed.

Background: Although the demand for allografts continuously surpasses the supply, the majority of lungs offered for transplant are declined based on various factors, including donor age. This in turn sustains the wait-list mortality of patients with end-stage pulmonary disease.

Methods: In this single center, observational cohort study we investigated the impact of donor age on graft survival. We additionally, compared our center's data to data reported to the International Society for Heart and Lung Transplantation (ISHLT) Thoracic Organ Transplant Registry. Kaplan-Meier method was used to describe overall graft survival. Multivariate Cox proportional hazards regression was used to assess clinical features associated with graft loss.

Results: Between January 2010 and December 2023, the Alfred performed 1101 single and double lung transplant and the combined ISHLT cohort totaled 32,200 transplants. At the Alfred, grafts originating from donors ≥65 years were used in 13.3% of lung transplant cases and univariate analysis showed no impact of donor age ≥65 on graft survival (HR 0.86, p=0.34). In the combined cohort, North America had a lower proportion of donors aged ≥65 years compared to Europe and the Alfred (2.4% vs 9.8% vs 13.3%, p<0.001). The univariate analysis showed a negative impact of donor age ≥65 on graft survival (HR 1.16, p<0.001). However, this did not hold in a multivariate model (HR 1.06, p=0.298) when adjusted for center experience and recipient characteristics.

Conclusion: Donor age might impact outcomes to a lesser degree than previously suggested. Therefore, appropriately assessed age-extended lungs should be routinely considered for lung transplantation.

Background: Approximately 2700 lung transplants are performed annually in the United States. These patients are at increased risk of developing low bone mineral density (osteopenia/osteoporosis) and subsequent osteoporosis-related fractures. Dual energy x-ray absorptiometry (DXA) is the most common method used for screening for low BMD, however, the optimal surveillance frequency for low BMD using DXA is unknown.

Methods: We evaluated the change in femoral neck, total femur, L1, L2, L3 and L4 BMD after lung transplant in a retrospective cohort of 259 patients (69.9% male) who were followed with serial DXA scans for a median of 725 (interquartile range (IQR) (361-1116)) days after transplant. Generalized linear mixed effects models allowing for random intercepts and random slopes adjusting for sex, time, time-squared, baseline osteopenia/osteoporosis, active rejection, and their interaction terms were used to model the rate of change of BMD at each site. The final multivariable models for the femoral neck, L1, and L4 BMD measurements had random slopes and intercepts, and the models for the total hip, L2, and L3 measurements had random slopes.

Results: 65% of the patients undergoing lung transplants had osteopenia or osteoporosis before transplant. Men exhibited higher baseline BMD levels compared to women at all sites (P<0.001 for all). After transplant, the greatest rate of BMD decrease was at the femoral neck. Although patients with low BMD (osteopenia/osteoporosis) had significantly lower baseline BMDs (P<0.001 for all), they experienced a slower rate of BMD decrease at all sites compared to patients with normal BMD at baseline (P<0.001 for all). All patients received corticosteroids. 25% of patients had a history of active rejection. Patients with low BMD at baseline had significantly higher odds of receiving bisphosphonate therapy (odds ratio (OR) = 3.95, 95% CI (1.44, 13.51), P=0.003). We estimated that a significant change in the femoral neck BMD would be expected to occur within 409 days (95% CI (131, 708)) and again at 867 days (95% CI (551, 1216)) after lung transplant.

Conclusions: On average, patients undergoing lung transplant should be screened annually with DXA for the first two years after transplant, consistent with the current International Society for Heart and Lung Transplantation (ISHLT) guidelines.

Background: Missing data can undermine a registry's ability to draw valid inferences by decreasing study power and introducing bias. We evaluated how missing data are reported and addressed in observational studies of adult heart transplantation (HT) recipients using the United Network for Organ Sharing (UNOS) database.

Methods: We conducted a systematic literature search of Medline from January 1^st, 2018 through August 22nd, 2023 and included studies that used the UNOS database to evaluate adult (≥18 years) de novo HT recipients. We collected details on the study population, timeframe, primary endpoint, use of missing data, and whether and what methods were used to handle missing data. Approaches were classified as variable selection, complete case analysis (CCA), missing indicator method, single imputation, or multiple imputation.

Results: 229 studies were included from 2018-2023. 67 (29.3%) studies limited their cohorts to those without missing data for the outcome or key variables and 93 (40.6%) reported missing data in their final cohort. 78 (34.1%) studies reported how they handled missing data in their statistical modeling. Of these, CCA was most used (n=41, 52.6%) followed by multiple imputation (n=22, 28.2%), and other methods (n=15, 19.2%) including a combination of missing indicator method (for binary variables) and single imputation. Thirty-one (13.5%) studies reported removing covariates from their analysis because of missing data. Only four (5.1%) studies reported sensitivity analysis to evaluate different missing data approaches.

Conclusions: Merely a third of the identified UNOS database studies reported how they handled missing data in their analysis, with strategies varying. Although no singular approach to handling missing data exists, methods are available that can improve upon the most used approaches by, for example, reducing bias and increasing statistical power. Though these improvements are contingent on the missing data mechanism and the goals of the analysis. Future best practices should include explicit reporting of missingness, detailed methods, and sensitivity checks to maximize the credibility of UNOS database analyses.

Background: Management of tacrolimus trough levels influences morbidity and mortality after lung transplantation. Several studies have explored pharmacokinetic and artificial intelligence models to monitor tacrolimus levels. However, many models depend on a wide range of variables, some of which, like genetic polymorphisms, are not commonly tested for in regular clinical practice. This study aimed to verify the efficacy of a novel approach simply utilizing time series data of tacrolimus dosing, with the objective of accurately predicting trough levels in the variety of clinical settings.

Methods: Data encompassing 36 clinical variables for each patient were gathered, and a multivariate long short-term memory algorithm was applied to forecast subsequent tacrolimus trough levels based on the selected clinical variables. The tool was developed using a dataset of 87,112 data points from　117 patients and its efficacy was confirmed using six additional cases.

Results: Shapley Additive exPlanations revealed a significant correlation between trough levels and prior dose-concentration data. By using simple trend learning of dose, administration route, and previous trough levels of tacrolimus, we could predict values within 30% of the actual values for 88.5% of time points, which facilitated the creation of a tool for simulating tacrolimus trough levels in response to dosage adjustments. The tool exhibited the potential for rectifying clinical misjudgments in a simulation cohort.

Conclusions: Utilizing our time series forecasting tool, precise prediction of trough levels is attainable independently of other clinical variables, through the analysis of historical tacrolimus dose-concentration trends alone.