Background: Right ventricular failure (RVF) is a cause of major morbidity and mortality after left ventricular assist device (LVAD) implantation. It is, therefore, integral to identify patients who may benefit from biventricular support early post-LVAD implantation. Our objective was to explore the performance of risk prediction models for RVF in adult patients undergoing LVAD implantation. Methods: A systematic search was performed on Medline, Embase, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews from inception until August 2019 for all relevant studies. Performance was assessed by discrimination (via C statistic) and calibration if reported. Study quality was assessed using the Prediction Model Risk of Bias Assessment Tool criteria. Results: After reviewing 3878 citations, 25 studies were included, featuring 20 distinctly derived models. Five models were derived from large multicenter cohorts: the European Registry for Patients With Mechanical Circulatory Support, Interagency Registry for Mechanically Assisted Circulatory Support, Kormos, Pittsburgh Bayesian, and Mechanical Circulatory Support Research Network RVF models. Seventeen studies (68%) were conducted in cohorts implanted with continuous-flow LVADs exclusively. The definition of RVF as an outcome was heterogenous among models. Seven derived models (28%) were validated in at least 2 cohorts, reporting limited discrimination (C-statistic range, 0.53–0.65). Calibration was reported in only 3 studies and was variable. Conclusions: Existing RVF prediction models exhibit heterogeneous derivation and validation methodologies, varying definitions of RVF, and are mostly derived from single centers. Validation studies of these prediction models demonstrate poor-to-modest discrimination. Newer models are derived in cohorts implanted with continuous-flow LVADs exclusively and exhibit modest discrimination. Derivation of enhanced discriminatory models and their validations in multicenter cohorts is needed.

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BackgroundMediation analysis tests whether the relationship between two variables is explained by a third intermediate variable. We sought to describe the usage and reporting of mediation analysis with time-to-event outcomes in published healthcare research.MethodsA systematic search of Medline, Embase, and Web of Science was executed in December 2016 to identify applications of mediation analysis to healthcare research involving a clinically relevant time-to-event outcome. We summarized usage over time and reporting of important methodological characteristics.ResultsWe included 149 primary studies, published from 1997 to 2016. Most studies were published after 2011 (n = 110, 74%), and the annual number of studies nearly doubled in the last year (from n = 21 to n = 40). A traditional approach (causal steps or change in coefficient) was most commonly taken (n = 87, 58%), and the majority of studies (n = 114, 77%) used a Cox Proportional Hazards regression for the outcome. Few studies (n = 52, 35%) mentioned any of the assumptions or limitations fundamental to a causal interpretation of mediation analysis.ConclusionThere is increasing use of mediation analysis with time-to-event outcomes. Current usage is limited by reliance on traditional methods and the Cox Proportional Hazards model, as well as low rates of reporting of underlying assumptions. There is a need for formal criteria to aid authors, reviewers, and readers reporting or appraising such studies.Electronic supplementary materialThe online version of this article (10.1186/s12874-018-0578-7) contains supplementary material, which is available to authorized users.

Symptomatic cytomegalovirus (CMV) disease has been the standard endpoint for clinical trials in organ transplant recipients. Viral load may be a more relevant endpoint due to low frequency of disease. We performed a meta-analysis and systematic review of the literature. We found several lines of evidence to support the validity of viral load as an appropriate surrogate end-point, including the following: (1) viral loads in CMV disease are significantly greater than in asymptomatic viremia (odds ratio, 9.3 95% confidence interval, 4.6-19.3); (2) kinetics of viral replication are strongly associated with progression to disease; (3) pooled incidence of CMV viremia and disease is significantly lower during prophylaxis compared with the full patient follow-up period (viremia incidence: 3.2% vs 34.3%; P < .001) (disease incidence: 1.1% vs 13.0%; P < .001); (4) treatment of viremia prevented disease; and (5) viral load decline correlated with symptom resolution. Based on the analysis, we conclude that CMV load is an appropriate surrogate endpoint for CMV trials in organ transplant recipients.