Novel Biomarkers to Predict Readmission in Pediatric and Adult Heart Surgery

描述（由申请人提供）：心脏病是美国（US）的主要死亡原因。超过253，000人接受心脏手术治疗冠状动脉和瓣膜疾病，每年花费超过80亿美元。这些患者中有20%在30天内再次入院，死亡风险增加了11倍，导致手术后第一个月内的医疗保健支出增加了8,000美元，每年增加2亿美元的医疗保健费用。然而，关于心脏或先天性心脏手术后再入院或导致再入院或死亡的因素的信息有限。已经表明，单独的临床变量不能准确预测30天的再入院。外部验证的再入院或死亡率的临床风险工具可能对常规临床实践有很大的益处，但迄今为止，这些模型缺乏预测能力。为了改善这些风险模型，研究人员假设，心脏损伤（ST 2，B型利钠肽，心肌肌钙蛋白T），炎症（半乳糖凝集素-3，细胞因子），肾损伤（半胱氨酸蛋白酶抑制剂C）和儿童脑损伤（胶质细胞酸性蛋白[GFAP]）的当前和新型生物标志物水平升高将预测接受心脏手术的成人和儿科患者30天的再入院或死亡。研究小组将使用五个队列，共计5,294名患者（4,400名成人和894名儿童），包括对照组。首先，研究小组将使用2,500名成人和500名儿科心脏手术患者的早期急性肾损伤（TRIBE）转化研究生物标志物队列，为30名患者制定临床预测规则。 日再入院或死亡。第二，将生物标志物添加到当前成人和儿童再入院和死亡率的临床风险模型中，以确定生物标志物在临床风险模型中的增量改善。第三，成人和儿童风险模型将从外部 使用北方新英格兰（NNE）1，800例患者的多中心队列和294例患者的约翰霍普金斯儿科队列进行验证。第四，我们将测量100例选择性非心脏手术成人对照组和100例非心脏手术儿童的生物标志物和30天再入院率和死亡率。TRIBE是最大的成人和儿童生物标志物队列之一，具有出色的数据收集，患者保留，纵向随访以及仔细收集和保护生物样本的能力，这为评估30天再入院或死亡的生物标志物提供了独特的机会。拟议的转化研究是创新的，通过评估成人和儿科心脏手术患者的新终点的当前和新型生物标志物，并通过开发多标志物风险模型来预测再入院或死亡率。这项创新研究将带来额外的建模和生物标志物测量，通过开发基于网络的30天再入院或死亡率风险计算器，将生物标志物的使用转化为常规临床实践，以进一步装备临床护理团队在出院时进行针对性干预，减少可避免的再入院和过早死亡，并降低医疗成本。

DESCRIPTION (provided by applicant): 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.