Heart disease is the leading cause of death in the United States (US). Over 253,000 people undergo cardiac surgery to treat coronary artery and valve disease costing over $8 billion dollars annually. Twenty percent of these patients are readmitted within 30 days and have an 11-fold increased risk of death resulting in $8,000 of additional healthcare expenditures within the first month after surgery, and adding $200 million in health care costs each year. However, limited information exists on readmissions following cardiac or congenital heart surgery or on the factors leading to readmission or death. It has been shown that clinical variables alone do not predict 30-day readmissions accurately. Externally validated clinical risk tools for readmission or mortality could have large benefits to routine clinical practice, but to date these models have lacked predictive ability. To improve on these risk models, the researchers hypothesize that elevated levels of current and novel biomarkers of cardiac injury (ST2, B-type natriuretic peptide, cardiac troponin T), inflammation (galectin-3, cytokines), renal injury (cystatin C), and brain injury in children (glial fibrillary cidic protein [GFAP]) will predict 30- day readmission or death in adult and pediatric patients undergoing cardiac surgery. The research team will use five cohorts totaling 5,294 patients (4,400 adults and 894 children) including controls. First, the research team will use the Translational Research Investigating Biomarkers in Early Acute Kidney Injury (TRIBE) cohort of 2,500 adult and 500 pediatric cardiac surgical patients to develop clinical prediction rules for 30 day readmission or death. Second, the biomarkers will be added to current adult and pediatric clinical risk models for readmission and mortality to determine the incremental improvement of biomarkers over the clinical risk models. Third, adult and pediatric risk models will be externally validated using the Northern New England (NNE) multicenter cohort of 1,800 patients and the Johns Hopkins pediatric cohort of 294 patients. Fourth, we will measure biomarkers and 30-day readmission and mortality on 100 elective non-cardiac surgery adult controls and 100 non-cardiac surgery children. TRIBE is one of the largest adult and pediatric biomarker cohorts with excellent data collection, patient retention, longitudinal follow-up, and ability to carefully collct and secure bio-samples, which provides a unique opportunity to evaluate biomarkers for 30-day readmission or death with external validation. The proposed translational research is innovative through the evaluation of current and novel biomarkers on novel endpoints in both adult and pediatric cardiac surgery patients and through the development of multi-marker risk models for prediction of readmission or mortality. This innovative study will bring additional modeling and biomarker measurement to translate the use of biomarkers into routine clinical practice by developing web-based risk calculators for 30-day readmission or mortality to further equip clinical care teams in targeting interventions at the time of discharge, reduce avoidable readmissions and early death, and reduce healthcare costs.

Public Health Relevance

Many readmissions to a hospital and some deaths after major adult and pediatric heart surgery are avoidable through care coordination and discharge planning. The proposed research will develop a risk calculator that will help clinicians better predict patients that are at high risk of being readmitted or dying after discharge from heart surgery and determine if biological signals in the blood could help in predicting readmission and death risk. Reducing readmissions and death will improve patient care and reduce healthcare costs.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Cardiovascular and Sleep Epidemiology Study Section (CASE)
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Miller, Marissa A
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Dartmouth College
Public Health & Prev Medicine
Schools of Medicine
United States
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