Here we establish that the creation of a universal perinatal database and biospecimen collection is not only possible, but allows for the performance of state-of-the-science translational perinatal research and is a potentially valuable resource to academic perinatal researchers.

Cardio-oncology is a multidisciplinary field focusing on the management and prevention of cardiovascular complications in cancer patients and survivors. While the initial focus of this specialty was on heart failure associated with anthracycline use, novel anticancer agents are increasingly utilized and are associated with many other cardiotoxicities including hypertension, arrhythmias and vascular disease. Since its inception, the field has developed at a rapid pace with the establishment of programs at many major academic institutions and community practices. Given the complexities of this patient population, it is important for providers to possess knowledge of not only cardiovascular disease but also cancer subtypes and their specific therapeutics. Developing a cardio-oncology program at a stand-alone cancer center can present unique opportunities and challenges when compared to those affiliated with other institutions including resource allocation, cardiovascular testing availability and provider education. In this review, we present our experiences establishing the cardio-oncology program at Moffitt Cancer Center and provide guidance to those individuals interested in developing a program at a similar independent cancer institution.

BackgroundIn ST-elevation myocardial infarction (STEMI), acute kidney injury (AKI) may increase subsequent morbidity and mortality. Still, it remains difficult to predict AKI risk in these patients. We sought to 1) determine the frequency and clinical outcomes of AKI and, 2) develop, validate and compare a web-based tool for predicting AKI.Methods & findingsIn a racially diverse series of 1144 consecutive STEMI patients, Stage 1 or greater AKI occurred in 12.9% and was severe (Stage 2–3) in 2.9%. AKI was associated with increased mortality (5.7-fold, unadjusted) and hospital stay (2.5-fold). AKI was associated with systolic dysfunction, increased left ventricular end-diastolic pressures, hypotension and intra-aortic balloon counterpulsation. A computational algorithm (UT-AKI) was derived and internally validated. It showed higher sensitivity and improved overall prediction for AKI (area under the curve 0.76) vs. other published indices. Higher UT-AKI scores were associated with more severe AKI, longer hospital stay and greater hospital mortality.ConclusionsIn a large, racially diverse cohort of STEMI patients, Stage 1 or greater AKI was relatively common and was associated with significant morbidity and mortality. A web-accessible, internally validated tool was developed with improved overall value for predicting AKI. By identifying patients at increased risk, this tool may help physicians tailor post-procedural diagnostic and therapeutic strategies after STEMI to reduce AKI and its associated morbidity and mortality.

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