Normothermic ex-situ heart perfusion (ESHP) enables assessment of hearts donated after circulatory death (DCD) prior to transplantation. However, sensitive parameters of cardiac function of DCD hearts on ESHP are needed. This study proposes a novel approach using electrophysiological (EP) parameters derived from electrical mapping as biomarkers of post-ischemic cardiac performance. Porcine slaughterhouse hearts (PSH) were divided in two groups based on the type of warm ischemia (Group 1: 10 ± 1 min with animal depilation vs. Group 2: ≤5 min without depilation). Electrical mapping of the right (RV) and left ventricle (LV) was performed on ESHP. Potential voltages, slopes and conduction velocities were computed from unipolar electrograms and compared between groups. Voltages were lower in Group 1 compared to Group 2 (RV: 3.6 vs. 15.3 mV, p = 0.057; LV: 10.8 vs. 23.6 mV, p = 0.029). In addition, the percentage of low-voltage potentials was higher and potential slopes were flatter in Group 1. Voltages and slopes strongly correlated with the visual contractile performance of PSH, but showed weaker correlation with lactate profiles. In conclusion, unipolar potential voltages and potential slopes were decreased in hearts with severe warm ischemia. As such, EP parameters could aid transplantation teams in decision-making on transplantability of DCD hearts.

In order to prevent long-term immunity-related complications after lung transplantation, close monitoring of immunosuppressant levels using therapeutic drug monitoring (TDM) is paramount. Novel electronic nose (eNose) technology may be a non-invasive alternative to the current invasive procedures for TDM. We investigated the diagnostic and categorization capacity of eNose breathprints for Tacrolimus trough blood plasma levels (TAC _trough) in lung transplant recipients (LTRs). We performed eNose measurements in stable LTR attending the outpatient clinic. We evaluated (1) the correlation between eNose measurements and TAC _trough, (2) the diagnostic capacity of eNose technology for TAC _trough, and (3) the accuracy of eNose technology for categorization of TAC _trough into three clinically relevant categories (low: <7 µg ml ⁻¹, medium: 7-10 µg ml ⁻¹, and high: >10 µg ml ⁻¹ ). A total of 186 measurements from 86 LTR were included. There was a weak but statistically significant correlation (r = 0.21, p = 0.004) between the eNose measurements and TAC _trough. The root mean squared error of prediction for the diagnostic capacity was 3.186 in the training and 3.131 in the validation set. The accuracy of categorization ranged between 45%-63% for the training set and 52%-69% in the validation set. There is a weak correlation between eNose breathprints and TAC _trough in LTR. However, the diagnostic as well as categorization capacity for TAC _trough using eNose breathprints is too inaccurate to be applicable in TDM.