Plasma biomarkers to predict or rule out early post-discharge events after hospitalization for acute heart failure.

Autor:	Demissei, Biniyam G, Postmus, Douwe, Cleland, John G, O'Connor, Christopher M, Metra, Marco, Ponikowski, Piotr, Teerlink, John R, Cotter, Gad, Davison, Beth A, Givertz, Michael M, Bloomfield, Daniel M, van Veldhuisen, Dirk J, Dittrich, Howard C, Hillege, Hans L, Voors, Adriaan A
Předmět:	NEUROTRANSMITTERS DRUG therapy CHRONIC kidney failure COMPARATIVE studies ENZYME-linked immunosorbent assay HEART failure RESEARCH methodology MEDICAL cooperation PEPTIDE hormones PEPTIDES PROGNOSIS RESEARCH RISK assessment SURVIVAL EVALUATION research DISCHARGE planning DISEASE incidence RECEIVER operating characteristic curves PATIENT readmissions PREVENTION THERAPEUTICS
Zdroj:	European Journal of Heart Failure; Mar2017, Vol. 19 Issue 3, pN.PAG-N.PAG, 1p
Abstrakt:	Aim: Improved prediction of early post-discharge death or rehospitalization after admission for acute heart failure is a major unmet need. We evaluated the value of biomarkers to predict either low or high risk for early post-discharge events.Methods and Results: A total of 1653 patients enrolled in the PROTECT trial who were discharged alive and with available blood samples were included. Forty-seven biomarkers were serially evaluated in these patients. Measurement closest to discharge was used to evaluate the predictive value of biomarkers for low and high post-discharge risk. Patients were classified as 'low risk' if post-discharge 30-day risk of death or heart failure rehospitalization was <5% while risk >20% was used to define 'high risk'. Cut-off values that yielded a 95% negative predictive value and a 20% positive predictive value were identified for each biomarker. Partial area under the receiver operating characteristic curve (pAUC) in the high-sensitivity and high-specificity regions was calculated to compare low-risk and high-risk predictive values. Of patients analysed, 193 (11.7%) patients reached the 30-day death or heart failure rehospitalization outcome. We found marked differences between low-risk and high-risk predictors. Cardiac-specific troponin I was the strongest biomarker for low-risk prediction (pAUC = 0.552, 95% confidence interval 0.52-0.58) while endothelin-1 showed better performance for high-risk prediction (pAUC = 0.560, 95% confidence interval 0.53-0.59). Several biomarkers (individually and in combination) provided added predictive value, on top of a clinical model, in both low-risk and high-risk regions.Conclusion: Different biomarkers predicted low risk vs. high risk of early post-discharge death or heart failure readmission in patients hospitalized for acute heart failure. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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