Rationale: Heart Failure (HF) elevated prevalence in Brasil and the world; 20-30% AHF patients develop CardioRenal Syndrome (CRS) type 1; Worsening Renal Failure (WRF) is a prognostic marker of mortality in Acute HF; available biomarker shows irreversible damage, late in CRS evolution.(creatinine);NGAL is a novel biomarker of Acute Kidney Injury released in 2 hours, and addressed in several different clinical scenarios(contrast injury, cardiopulmonary bypass, critical illness...); Acute HF patient's risk stratification will allow appropriate resource allocation and establishment of criteria for hospital admission and discharge.~Hypothesis: Admission NGAL predicts CRS in AHF patients admitted to the Emergency Room (ER).~Primary goal: To evaluate the diagnostic accuracy and the best cutoff value of urinary NGAL to predict the development of CRS type 1 in patients admitted to the Emergency Room.~Secondary goals: 1- To evaluate the prognostic impact of NGAL on in-hospital adverse outcomes (length of hospitalization, death, institution of renal replacement therapy, use of vasoactive drugs, mechanical ventilation).2- Evaluate the prognostic impact of NGAL in adverse outcomes in 30 days, 60 days and 6 months (death, rehospitalization, institution of renal replacement therapy).3- Identify clinical and hemodynamic characteristics of Acute HF that can influence the evolutionary behavior of NGAL levels in 48 hours.4- Identify the association of drugs commonly used for HF management, which might influence the evolutionary behavior of NGAL levels in 48 hours.5-Assess the impact of NGAL results in clinical decision making.~Methods: Observational, prospective, blinded study. Population: Acute HF patients admitted to the ER of Hospital Pró Cardiaco and Hospital Antonio Pedro - Universidade Federal Fluminense.~Statistics: Convenience Sample size (n=180); determination of best cut-off: ROC analysis; Predictive performance of the cut-off: sensibility, specificity, likelihood ratio, predictive value, accuracy; Identification of variables to predict CRS: logistic regression and square-Qui test; Correlations analysis of normally distributed variables: Pearson's linear correlation test; Mean values for normally distributed variables: Mann-Wittney test; Significance on p<0,05; Intra-assay variation analysis.~Study chronogram: Recruitment: 12 months; Results analysis and conclusions: 60 days; Manuscript preparation for paper submission: 30 days.
Rationale: Heart Failure (HF) elevated prevalence in Brasil and the world; 20-30% AHF patients develop CardioRenal Syndrome (CRS) type 1; Worsening Renal Failure (WRF) is a prognostic marker of mortality in Acute HF;NGAL is a novel biomarker of Acute Kidney Injury released in 2 hours, and addressed in several different clinical scenarios(contrast injury, cardiopulmonary bypass, critical illness.~Hypothesis: Admission NGAL predicts CRS in AHF patients admitted to the Emergency Room (ER).~Primary goal: To evaluate the diagnostic accuracy and the best cutoff value of urinary NGAL to predict the development of CRS type 1 in patients admitted to the Emergency Room.~Secondary goals: 1- To evaluate the prognostic impact of NGAL on in-hospital adverse outcomes (length of hospitalization, death, institution of renal replacement therapy, use of vasoactive drugs, mechanical ventilation).2- Evaluate the prognostic impact of NGAL in adverse outcomes in 30 days, 60 days and 6 months (death, rehospitalization, institution of renal replacement therapy).3- Identify clinical and hemodynamic characteristics of Acute HF that can influence the evolutionary behavior of NGAL levels in 48 hours.4- Identify the association of drugs commonly used for HF management, which might influence the evolutionary behavior of NGAL levels in 48 hours.5-Assess the impact of NGAL results in clinical decision making.~Methods: Observational, prospective, blinded study. Population: Acute HF patients admitted to the ER of Hospital Pró Cardiaco and Hospital Antonio Pedro - Universidade Federal Fluminense.~Statistics: Convenience Sample size (n=180); determination of best cut-off: ROC analysis; Predictive performance of the cut-off: sensibility, specificity, likelihood ratio, predictive value, accuracy; Identification of variables to predict CRS: logistic regression and square-Qui test; Correlations analysis of normally distributed variables: Pearson's linear correlation test; Mean values for normally distributed variables: Mann-Wittney test; Significance on p<0,05; Intra-assay variation analysis.~Study chronogram: Recruitment: 12 months; Results analysis and conclusions: 60 days; Manuscript preparation for paper submission: 30 days.