Associated Clinical and Laboratory Markers of Donor on Allograft Function After Heart Transplant

Cardiac Graft Assessment in the Era of Machine Perfusion: Current and Future Biomarkers

Heart transplantation remains the treatment of reference for patients experiencing end‐stage heart failure; unfortunately, graft availability through conventional donation after brain death is insufficient to meet the demand. Use of extended‐criteria donors or donation after circulatory death has emerged to increase organ availability; however, clinical protocols require optimization to limit or prevent damage in hearts possessing greater susceptibility to injury than conventional grafts. The emergence of cardiac ex situ machine perfusion not only facilitates the use of extended‐criteria donor and donation after circulatory death hearts through the avoidance of potentially damaging ischemia during graft storage and transport, it also opens the door to multiple opportunities for more sensitive monitoring of graft quality. With this review, we aim to bring together the current knowledge of biomarkers that hold particular promise for cardiac graft evaluation to improve precision and reliability in the identification of hearts for transplantation, thereby facilitating the safe increase in graft availability. Information about the utility of potential biomarkers was categorized into 5 themes: (1) functional, (2) metabolic, (3) hormone/prohormone, (4) cellular damage/death, and (5) inflammatory markers. Several promising biomarkers are identified, and recommendations for potential improvements to current clinical protocols are provided.

C-Reactive protein level and left ventricular mass are associated with acute cellular rejection after heart transplant

OBJECTIVES

Acute cellular rejection (ACR) remains a major complication of heart transplant (HT). The gold standard for its diagnosis is endomyocardial biopsy (EMB), whereas the role of non-invasive biomarkers for detecting ACR is unclear. This study aimed to identify non-invasive biomarkers for the diagnosis of ACR in patients undergoing HT and presenting with normal left ventricular function.

METHODS

We evaluated patients who underwent HT at a single center between January 2010 and June 2019. Patients were enrolled after HT, and those with left ventricular (LV) systolic dysfunction before EMB were excluded. We included only the results of the first EMB performed at least 30 days after HT (median, 90 days). Troponin, B-type natriuretic peptide (BNP), and C-reactive protein (CRP) levels were measured and echocardiography was performed up to 7 days before EMB. ACR was defined as International Society for Heart and Lung Transplantation grade 2R or 3R on EMB. We performed logistic regression analysis to identify the non-invasive predictors of ACR (2R or 3R) and evaluated the accuracy of each using area under the receiver operator characteristic curve analysis.

RESULTS

We analyzed 72 patients after HT (51.31±13.63 years; 25 [34.7%] women); of them, 9 (12.5%) developed ACR. Based on multivariate logistic regression analysis, we performed forward stepwise selection (entry criteria, p<0.05). The only independent predictors that remained in the model were CRP level and LV mass index. The optimal cut-off point for CRP level was ≥15.9 mg/L (odds ratio [OR], 11.7; p=0.007) and that for LV mass index was ≥111 g/m2 (OR, 13.6; p=0.003). The area under the receiver operating characteristic curve derived from this model was 0.87 (95% confidence interval [CI], 0.75-0.99), with sensitivity of 85.7% (95% CI, 42.1%-99.6%), specificity of 78.4% (95% CI, 64.7%-88.7%), positive predictive value of 35.3% (95% CI, 14.3%-61.7%), and negative predictive value of 97.6% (95% CI, 87.1%-99.9%).

CONCLUSIONS

Among patients undergoing HT, CRP level and LV mass were directly associated with ACR, but troponin and BNP levels were not.

Primary graft dysfunction after heart transplantation: a thorn amongst the roses

Primary graft dysfunction (PGD) remains the leading cause of early mortality post-heart transplantation. Despite improvements in mechanical circulatory support and critical care measures, the rate of PGD remains significant. A recent consensus statement by the International Society of Heart and Lung Transplantation (ISHLT) has formulated a definition for PGD. Five years on, we look at current concepts and future directions of PGD in the current era of transplantation.

Hurdles to Cardioprotection in the Critically Ill

Cardiovascular disease is the largest contributor to worldwide mortality, and the deleterious impact of heart failure (HF) is projected to grow exponentially in the future. As heart transplantation (HTx) is the only effective treatment for end-stage HF, development of mechanical circulatory support (MCS) technology has unveiled additional therapeutic options for refractory cardiac disease. Unfortunately, despite both MCS and HTx being quintessential treatments for significant cardiac impairment, associated morbidity and mortality remain high. MCS technology continues to evolve, but is associated with numerous disturbances to cardiac function (e.g., oxidative damage, arrhythmias). Following MCS intervention, HTx is frequently the destination option for survival of critically ill cardiac patients. While effective, donor hearts are scarce, thus limiting HTx to few qualifying patients, and HTx remains correlated with substantial post-HTx complications. While MCS and HTx are vital to survival of critically ill cardiac patients, cardioprotective strategies to improve outcomes from these treatments are highly desirable. Accordingly, this review summarizes the current status of MCS and HTx in the clinic, and the associated cardiac complications inherent to these treatments. Furthermore, we detail current research being undertaken to improve cardiac outcomes following MCS/HTx, and important considerations for reducing the significant morbidity and mortality associated with these necessary treatment strategies.

Donor biomarkers as predictors of organ use and recipient survival after neurologically deceased donor organ transplantation

PURPOSE

We sought to build prediction models for organ transplantation and recipient survival using both biomarkers and clinical information.

MATERIALS AND METHODS

We abstracted clinical variables from a previous randomized trial (n = 556) of donor management. In a subset of donors (n = 97), we measured two candidate biomarkers in plasma at enrollment and just prior to explantation.

RESULTS

Secretory leukocyte protease inhibitor (SLPI) was significant for predicting liver transplantation (C-statistic 0.65 (0.53, 0.78)). SLPI also significantly improved the predictive performance of a clinical model for liver transplantation (integrated discrimination improvement (IDI): 0.090 (0.009, 0.210)). For other organs, clinical variables alone had strong predictive ability (C-statistic >0.80). Recipient 3-years survival was 80.0% (71.9%, 87.0%). Donor IL-6 was significantly associated with recipient 3-years survival (adjusted Hazard Ratio (95%CI): 1.26(1.08, 1.48), P = .004). Neither clinical variables nor biomarkers showed strong predictive ability for 3-year recipient survival.

CONCLUSIONS

Plasma biomarkers in neurologically deceased donors were associated with organ use. SLPI enhanced prediction within a liver transplantation model, whereas IL-6 before transplantation was significantly associated with recipient 3-year survival. Clinicaltrials.gov: NCT00987714.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as predictors of survival after heart transplantation

Aims

The aim of this study was to evaluate whether neutrophil‐to‐lymphocyte ratio (NLR) and platelet‐to‐lymphocyte ratio (PLR) predict outcome in heart failure (HF) patients undergoing heart transplantation (HTX).

Methods and results

Data from 111 HF patients undergoing HTX 2010–2015 were retrospectively reviewed. NLR and PLR were calculated before HTX, immediately after HTX, and at 6 and 24 hours. Primary endpoint was in‐hospital mortality, and secondary endpoints were 1 year mortality and renal replacement therapy (RRT). Prognostic factors were assessed by multivariate analysis, and the predictive values of NLR and PLR for mortality were compared. The discriminatory performance for predicting in‐hospital mortality was better for NLR [area under the receiver operating characteristic curve (AUC) = 0.644, 95% confidence interval 0.492–0.797] than for PLR (AUC = 0.599, 95% confidence interval 0.423–0.776). Best cut‐off value was 2.41 for NLR (sensitivity 86%, specificity 67%) and 92.5 for PLR (sensitivity 86%, specificity 68%). When divided according to best cut‐off value, in‐hospital mortality was significantly higher in the high NLR group (17.5% vs. 3.2%, P < 0.05), but not in the high PLR group (16.5% vs. 6.3%, P = ns). One year mortality was not significantly higher for either group (37.5% vs. 6.5% for NLR; 36.7% vs. 9.4% for PLR, P = ns for both), while RRT was significantly higher in both the NLR and PLR high groups (33.8% vs. 0%; 32.9% vs. 3.1%, respectively, P < 0.001). Multivariate analysis indicated that only high NLR (hazard ratio = 3.403, P < 0.05) and pre‐transplant diabetes (hazard ratio = 3.364, P < 0.05) were independent prognostic factors for 1 year mortality.

Conclusions

High NLR was a predictor for in‐hospital mortality, and an independent prognostic factor for 1 year mortality. Both high NLR and high PLR were predictors for RRT.