Gender mismatch and outcomes following heart transplantation in the United States

Background

Available literature indicates the possible detrimental effect of gender mismatching on mortality in patients undergoing heart transplantion. Our objective was to examine the role of gender mismatching on mortality and graft rejection in patients undergoing heart transplantation in the US.

Methods

Data on adult patients January who underwent heart transplantation between January 2015 and October 2021, was queried from the United Network of Organ Sharing (UNOS) registry. The main outcomes were all-cause mortality, 1-year all-cause mortality and treated acute rejection.

Results

A total of 19,805 adult patients underwent heart transplant during the study period. Approximately, one out of ten patients in the M-F group had a PHM mismatch<25%, while only four out of ten patients had such a mismatch in the F-M group. In both M-M and F-F groups, seven out of ten patients had a PHM mismatch<25% (p=0.122). Proportion of PHM mismatch was similar throughout the study period. Unadjusted analysis showed that M-F was associated with increased risk for all-cause mortality (HR: 1.13; 95% CI: 1.02, 1.27; p=0.026) and 1-year mortality (HR: 1.26; 95% CI: 1.09, 1.45; p=0.002) compared to M-M. Graft failure incidence was higher in the M-F group compared to M-M (HR: 1.12; 95% CI: 1.01, 1.25; p=0.041).

Conclusions

Gender mismatching is associated with post-transplant mortality with transplantation of female donor grafts to male recipients demonstrating worse outcomes. Further research is required to elucidate pathways involved and possible changes in clinical practice.

Funding Acknowledgement

Type of funding sources: None.

Characteristics, predictors and outcomes of early mTOR inhibitor use after heart transplantation: insights from the UNOS database

Background

The clinical characteristics of mammalian target of rapamycin (mTOR) inhibitors use in heart transplant (HT) recipients and their outcomes have not been well described.

Methods

We compared patients that received mTOR inhibitors within the first 2 years after HT to patients that did not by inquiring the United Network for Organ Sharing database between 2010 and 2018. The primary endpoint was all-cause mortality with re-transplantation as a competing event. Rejection, malignancy, hospitalization for infection and renal transplantation were secondary endpoints.

Results

There were 1,619 (9%) and 15,686 (81%) mTORi+ and mTORi− patients respectively. Body mass index, induction, cardiac allograft vasculopathy, calculated panel reactive antibody and less days in 1A status were independently associated with mTORi+ status. Over a follow up of 10.4 years there was no difference in all cause mortality after adjusting for donor and recipient characteristics (adjusted subdistribution hazard ratio 1.03 [0.90–1.19], p=0.66) (Figure 2). mTORi+ was independently associated with increased risk for rejection (odds ratio 1.43 [1.11–1.83], p=0.005) but not for infection, malignancy or renal transplantation.

Conclusion

mTOR inhibitors are used in <10% patients in the first 2 years after HT and are non-inferior to contemporary immunosuppression regimens in terms of all-cause mortality, infection, malignancy or renal transplantation. They are associated with risk for rejection.

Funding Acknowledgement

Type of funding sources: None.

Outcomes of patients after repeat heart transplantation – insights from the UNOS database

Background

Cardiac graft failure may require repeat heart transplantation (HTx). Outcomes of patients that undergo repeat HTx have not been well described.

Methods

We compared patients that received repeat HTx with patients that received initial HTx by inquiring the United Network for Organ Sharing database between 2015–2021. The primary endpoint was all-cause mortality.

Results

A total of 19,805 HTx patients were included in the study. Patients that underwent repeat HTx (n=578, 3%) were younger (43.8±15.3 vs. 53.7±12.7 years, p<0.001) with lower body mass index (26.8±5.3 vs. 27.6±4.9 kg/m2, p<0.001) and worse renal function (Cr 1.8±1.4 vs. 1.4±0.9 mg/dl). Patients with repeat HTx had increased risk for 1-year mortality (hazard ratio 1.49 [1.16–1.90], p=0.002) compared to patients with initial HTx after adjusting for age, ethnicity, use of left ventricular assist device, UNOS recipient status, diabetes, ischemic time, donor age and predicted heart mass mismatch (Figure 1). Results did not change with the new allocation system (10/2018).

Conclusion

Repeat HTx occurred in 3% of a contemporary UNOS cohort and carried an increased and independent risk for mortality.

Funding Acknowledgement

Type of funding sources: None.

Prediction of outcomes after heart transplantation by machine learning models

Background

Models based on traditional statistics for the prediction of outcomes after heart transplantation (HT) have moderate accuracy. We sought to develop and validate state-of-the-art machine learning (ML) models to predict mortality and acute rejection after contemporary HT.

Methods

We included adult HT recipients from the UNOS database between 2010–2018 using solely pre-transplant clinical and laboratory variables. The study cohort was randomly split in a derivation and a validation cohort with a 3:1 ratio. An effective feature selection algorithm was used to identify strong predictors of 1-year mortality and rejection in the training cohort. Results were used to train the ML models, which were then internally tested using the validation cohort. LIME explainability analysis was used for the best performing ML model. A similar subgroup analysis was performed for 3- and 5-year survival.

Results

The study cohort comprised of 18,625 patients (53±13 years, 73% males). At 1-year after cardiac transplant, there were 2,334 (12.5%) deaths. Out of a total of 134 pre-transplant variables, 39 and 27 were selected as highly predictive of 1-year mortality and acute rejection respectively, and were used in the ML models. Areas under the curve for the prediction of 1-year survival were 0.689, 0.642, 0.649, 0.637, 0.526 for the Adaboost, Logistic Regression, Decision Tree, Support Vector Machine and K-nearest neighbor models respectively, whereas the IMPACT score had an AUC of 0.569. For the prediction of 1-year acute rejection, Adaboost achieved the highest predictive performance (AUC 0.629). LIME explainability analysis identified the relative impact of the 10 strongest predictors of 1-year mortality and acute rejection. Subgroup analysis using a similar methodology for 3- and 5-year survival yielded AUC of 0.609 and 0.610 using 31 and 91 selected variables respectively.

Conclusion

ML models created and validated using a contemporary cohort of the UNOS database showed improved accuracy in predicting survival and acute rejection after HT.

Funding Acknowledgement

Type of funding sources: None.

Impact of induction therapy on outcomes after heart transplantation

Introduction

Approximately 50% of heart transplant (HT) programs currently employ a strategy of induction therapy (IT) with either interleukin-2 receptor antagonists (IL2RA) or polyclonal anti-thymocyte antibodies (ATG) during the early postoperative period. However, the overall utility of such therapy is uncertain and data comparing induction protocols are limited.

Methods

Adult HT recipients were identified in the United Network for Organ Sharing (UNOS) registry between 1990 and 2020. Patients were grouped according to administration of induction in the post-operative period after HT. Accounting for re-transplantation, Fine and Gray's test compared cumulative incidences of all-cause mortality between groups. Univariate and multivariate analysis were performed using the competing risk model. The risk of treated rejection and hospitalization for infection or rejection was analyzed with multivariable logistic regression.

Results

A total of 63,849 HT recipients were included in the study and among those 59% did not receive induction, 16.6% received ATG, 19.1% IL2RA, 0.7% alemtuzumab, and 4.6% OKT3. Since 2000 IL2RA is the most frequently used form of induction therapy whereas OK3 is not used in the past decade. In multivariable logistic regression models, use of ATG is associated with lower risk of treated rejection at one year after HT (relative risk ratio 0.55, 95% CI 0.47–0.63, p<0.001) compared with no induction whereas IL2RA had similar risk of treated rejection. Similarly, the risk of rejection requiring hospitalization was significantly lower with ATG than no induction. No significant differences in rates of infection requiring hospitalization were noted between groups. Moreover, no differences in rates of post-transplant lymphoproliferative disease and any malignancy were noted between those receiving induction versus no induction. Adjusted all-cause mortality was significantly lower among those treated with ATG than patients that did not receive induction therapy (sub-hazard ratio 0.72, 95% CI 0.63–0.82, p<0.001) (Figure).

Conclusion

Induction therapy with IL2RA is the most used approach. ATG is associated with lower risk of treated rejection and all-cause mortality than no induction and IL2RA.

Funding Acknowledgement

Type of funding sources: None.

Trends, risk factors and prognostic implications of postoperative stroke after heart transplantation: an analysis of the UNOS database

Background

Post-operative stroke increases morbidity and mortality after cardiac surgery. Data on characteristics and outcomes of stroke after heart transplantation (HT) are limited.

Methods

We conducted a retrospective analysis of the UNOS database from 2009 to 2020 to identify adults who developed stroke after orthotropic HT. HT recipients were divided according to the presence or absence of postoperative stroke. The primary endpoint was all-cause mortality after HT.

Results

A total of 25,015 HT recipients were analyzed, including 719 (2.9%) patients who suffered perioperative stroke. The rates of stroke increased from 2.1% in 2009 to 3.7% in 2019 and the risk of stroke was higher after the implantation of the new allocation system (odds ratio 1.29, 1.29, 95% Confidence Intervals [CI] 1.06–1.56, p=0.01). HT recipients with postoperative stroke were older (p=0.008), with higher rates of prior cerebrovascular accident (CVA) (p=0.004), prior cardiac surgery (p<0.001), longer waitlist time (p=0.04), higher rates of extracorporeal membrane oxygenation support (ECMO) (p<0.001), left ventricular assist devices (LVAD) (p<0.001), mechanical ventilation (p=0.003) and longer ischemic time (p<0.001). After multivariable adjustment for recipient and donor characteristics, age, prior cardiac surgery, CVA, support with LVAD, ECMO, ischemic time and mechanical ventilation at the time of HT were independent predictors of postoperative stroke. Stroke was associated with increased risk of 30-day and all-cause mortality after HT (hazard ratio [HR] 1.49, CI 1.12–1.99, p=0.007).

Conclusion

Perioperative stroke after HT is infrequent but associated with higher mortality. Redo sternotomy, LVAD and ECMO support at HT are among the risk factors identified.

Funding Acknowledgement

Type of funding sources: None. Risk factors for stroke