Temkit, M'hamed H

AbstractBackgroundCardiac allograft vasculopathy (CAV) remains an important cause of graft failure after heart transplantation (HT). Although many risk factors for CAV have been identified, there are no clinical prediction models that enable clinicians to determine each recipient's risk of CAV.MethodsWe studied a cohort of 14 328 heart transplant recipients whose data were reported to the International Society for Heart and Lung Transplantation Registry between 2000 and 2010. The cohort was divided into training (75%) and test (25%) sets. Multivariable modeling was performed in the test set using variables available at the time of heart transplant using three methods: (i) stepwise Cox proportional hazard, (ii) regularized Cox proportional hazard, and (iii) Bayesian network.ResultsCardiac allograft vasculopathy developed in 4259 recipients (29.7%) at a median time of 3.0 years after HT. The regularized Cox proportional hazard model yielded the optimal performance and was also the most parsimonious. We deployed this model as an Internet‐based risk calculator application.ConclusionsWe have developed a clinical prediction model for assessing a recipient's risk of CAV using variables available at the time of HT. Application of this model may allow clinicians to determine which recipients will benefit from interventions to reduce the risk of development and progression of CAV.

Background Valvuloarterial impedance (Zva) was introduced as a prognostic measure in patients with aortic stenosis (AS). However, it is unclear whether Zva has a prognostic impact on survival after surgical aortic valve replacement (AVR) in patients with severe AS with preserved ejection fraction (EF). Methods We retrospectively reviewed 929 consecutive patients who had AVR. We investigated 170 elderly patients (age >65 years, mean 76 years) who had AVR secondary to severe AS (mean gradient ≥40 mm Hg; aortic valve area ≤1 cm2; peak velocity ≥4 m/s). Patients with EF <50%, greater than moderate aortic regurgitation, prior heart surgery and concomitant mitral or tricuspid valve surgery were excluded. Zva was calculated and the patients were divided into two groups; low Zva, Zva <4.3 (n=82) and high Zva, Zva ≥4.3 (n=88). The end point was all-cause of death. Survival curves were calculated according to Kaplan-Meier method. Results Age, prevalence of hypertension, diabetes, chronic kidney disease (CKD), atrial fibrillation, symptoms, EF, E/e′ and concomitant coronary artery bypass graft were not different between the groups. Survival was not different between the groups at 5 years (70% in low Zva and 81% in high Zva; p=0.21) and for the entire follow-up period (p=0.23). Only age was a significant factor in predicting survival by multivariate analyses in Cox proportional hazards model after adjusting for Zva, CKD, atrial fibrillation and hypertension. Conclusions Our results suggest that preoperative Zva does not have a prognostic impact on postoperative survival in elderly patients with severe AS with preserved EF. Further investigation is needed to elucidate the controversial results.