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An n2 algorithm for determining the bridges of a graph
S34 Journal of Cardiac Failure Vol. 23 No. 8S August 2017
Table 1. Biomarker levels at rest and exercise
Baseline hs troponin T (pg/mL) Copeptin (pmol/L) NT-proBNP (pg/mL) MR-proANP (pmol/L) CT-proET-1 (pmol/L) MR-proADM (nmol/L) Peak Exercise hs troponin T (pg/mL) Copeptin (pmol/L) NT-proBNP (pg/mL) MR-proANP (pmol/L) CT-proET-1 (pmol/L) MR-proADM (nmol/L)
Control (n = 20)
HFpEF (n = 38)
P
5.2 (4.2, 8.6) 5.3 (3.4, 12.8) 100 (54, 236) 128 (90, 147) 69 (56, 74) 0.6 (0.5, 0.7)
12.4 (7.8, 22.3) 11.0 (6.0, 20.8) 436 (147, 978) 239 (139, 300) 105 (83, 130) 1.0 (0.8, 1.4)
<0.0001 0.04 0.0002 0.001 <0.0001 <0.0001
6.3 (4.8, 9.7) 5.8 (3.4, 9.3) 122 (47, 279) 174 (128, 226) 73 (62, 85) 0.6 (0.5, 0.7)
13.8 (8.9, 26.2) 14.5 (8.4, 35.1) 484 (155, 1133) 267 (184, 359) 118 (87, 138) 1.0 (0.8, 1.3)
0.0002 0.001 0.0009 0.007 <0.0001 <0.0001
NT-proBNP > 70,000 pg/ml and mortality. In addition, predicting variables of mortality among this patient population have not been identified. Purpose To determine the mortality rate among patients with NT-proBNP > 70,000 pg/ml and identify mortality predicting variables in this population. Methods We collected retrospective data from 141 patients from January 1, 2012 through January 30, 2016. Predicting mortality variables including ejection fraction, E/e’, age, gender, race and BMI were collected to determine their influence in mortality. Living status was determined via chart review or through the social security death index. Our primary endpoint was death from any cause, with secondary endpoints including the association between mortality and predicting variables as above. We defined systolic left ventricular failure as EF < 40%, while diastolic left ventricular failure >40% and E/e’ > 12. Further statistical analysis was performed among patients with EF <35% and <25%. The vast majority of our patients had end-stage renal disease. Results All-cause mortality was 45.39%, with a mean survival time of 204.1 days. There was a statistically significant difference in mortality (P = .0089) and survival (P = .0043) among patients with an ejection fraction <25% (Fig. 1). The best-fit logistic regression model predicting mortality contained only age (P = .0203; OR: 1.0301, 95% CI = 1.005, 1.057) and ejection fraction <25% (P.0306). The odds of death were 2.5 times higher for patients with an ejection fraction <25%. Conclusion Our study demonstrates that among patients with symptomatic heart failure and NT-proBNP > 70,000 pg/ml, mortality rate is nearly 50% over four years. Furthermore, it re-emphasizes the important role of left ventricular systolic function in predicting mortality in this patient population.
082 Sepsis and Congestive Heart Failure as Strong Independent Factors in Elevated Troponin I Chien-Wen Yang1, Huijun Li1, Lisa Thomas2, Manuel Ramos1, Po-Hong Liu3, Thomas Roe4, Ravinder Valadri1, Qi Shi1; 1The Wright Center for Graduate Medical Education, Scranton, Pennsylvania; 2Hematology & Oncology Associates of Northeast Pennsylvania, Pennsylvania; 3Harvard T.H. Chan School of Public Health, Boston, Massachusetts; 4 Commonwealth Health Physician Network Great Valley Cardiology, Scranton, Pennsylvania Background: Troponin I (TnI) is one of the most commonly tested biochemical markers to access cardiomyocyte damage. Coronary artery disease (CAD) has been well recognized to cause TnI elevation. Other than CAD, demand ischemia with underlying tachycardia, anemia, hypertensive emergency, congestive heart failure (CHF), kidney disease, sepsis, and pulmonary embolism (PE) have also been reported to cause TnI elevation. However, there is only a few reports excluding the patients with CAD, and no study has summarized up the proportion of these risks. Purpose: The aim of this retrospective study was designed to investigate the level of contribution of the causes of TnI elevation. Method: Records of patients tested for troponin during ER visit or hospitalization were collected. Patients with known CAD, positive stress test or cardiac cathriztiona, or being discharged without adequate cardiac evaluation were excluded. Age, sex, Hb, HR, systolic BP, calculated GFR by Cockcroft Gault equation and underlying conditions including CHF, sepsis, PE and Afib were collected from the medical records. Elevation of TnI was defined according to the parameter of the hospital and is equal or greater than 0.03 ng/ml. Logistic regression was used to identify predictors of elevated troponin. Result: A total of 586 patients were investigated in this study. Age, Hb, HR, GFR, Afib, CHF, and sepsis were significant predictors of elevated TnI according to analysis of invariable logistic regression (all P < .001). In multivariable logistic regression, sepsis (P < .001, OR 21.96) and CHF (P < .001, OR 6.055) were shown to be the two strongest underlying conditions causing elevation of TnI. Age, Hb, HR were also independent predictors of troponin (all P < .01). A simple clinical scoring system was generated with one score on patients with age ≥ 60, Hb < 10 g/ dL, and HR ≥ 100 per minute. The prevalence of elevated troponin was 4%, 16%, 38%, and 50% for patients with scores of 0, 1, 2, and 3, respectively. In the patients without sepsis and CHF, the chances of elevated troponin are 2%, 11%, 28%, 43%. Conclusion: Sepsis and CHF were found to be the strongest independent causes of elevated troponin I in non-CAD patients. The scoring system composed of age, Hb, HR can assist clinical evaluation of elevated troponin tests in non-CAD patients.
083 Predicting Variables of Mortality among Patients with NT-proBNP > 70,000 Pg/Ml Julio Perez-Downes, Carlos Palacio, Alan Miller, Pramod Reddy; University of Florida College of Medicine-Jacksonville, Jacksonville, Florida Introduction: Elevated NT-pro-BNP levels have been identified as independent predictors of mortality in patients with heart failure, end stage renal disease, as well as the general population. No study to date has evaluated the significance of
Fig. 1. Survival estimates between patients with an EF <25 versus those with an EF > or equal to 25. Y-axis represents the probability of survival. The X-axis represents survival in number of days. The blue line represents those patients with an ejection fraction <25, while the red line represents patients with an EF > or equal to 25. The shaded areas represent the 95% confidence intervals for the curves. Note the significant divergence between survival curves in the two populations. P = .0043. EF: ejection fraction.
Table 1. Biomarker levels at rest and exercise
Baseline hs troponin T (pg/mL) Copeptin (pmol/L) NT-proBNP (pg/mL) MR-proANP (pmol/L) CT-proET-1 (pmol/L) MR-proADM (nmol/L) Peak Exercise hs troponin T (pg/mL) Copeptin (pmol/L) NT-proBNP (pg/mL) MR-proANP (pmol/L) CT-proET-1 (pmol/L) MR-proADM (nmol/L)
Control (n = 20)
HFpEF (n = 38)
P
5.2 (4.2, 8.6) 5.3 (3.4, 12.8) 100 (54, 236) 128 (90, 147) 69 (56, 74) 0.6 (0.5, 0.7)
12.4 (7.8, 22.3) 11.0 (6.0, 20.8) 436 (147, 978) 239 (139, 300) 105 (83, 130) 1.0 (0.8, 1.4)
<0.0001 0.04 0.0002 0.001 <0.0001 <0.0001
6.3 (4.8, 9.7) 5.8 (3.4, 9.3) 122 (47, 279) 174 (128, 226) 73 (62, 85) 0.6 (0.5, 0.7)
13.8 (8.9, 26.2) 14.5 (8.4, 35.1) 484 (155, 1133) 267 (184, 359) 118 (87, 138) 1.0 (0.8, 1.3)
0.0002 0.001 0.0009 0.007 <0.0001 <0.0001
NT-proBNP > 70,000 pg/ml and mortality. In addition, predicting variables of mortality among this patient population have not been identified. Purpose To determine the mortality rate among patients with NT-proBNP > 70,000 pg/ml and identify mortality predicting variables in this population. Methods We collected retrospective data from 141 patients from January 1, 2012 through January 30, 2016. Predicting mortality variables including ejection fraction, E/e’, age, gender, race and BMI were collected to determine their influence in mortality. Living status was determined via chart review or through the social security death index. Our primary endpoint was death from any cause, with secondary endpoints including the association between mortality and predicting variables as above. We defined systolic left ventricular failure as EF < 40%, while diastolic left ventricular failure >40% and E/e’ > 12. Further statistical analysis was performed among patients with EF <35% and <25%. The vast majority of our patients had end-stage renal disease. Results All-cause mortality was 45.39%, with a mean survival time of 204.1 days. There was a statistically significant difference in mortality (P = .0089) and survival (P = .0043) among patients with an ejection fraction <25% (Fig. 1). The best-fit logistic regression model predicting mortality contained only age (P = .0203; OR: 1.0301, 95% CI = 1.005, 1.057) and ejection fraction <25% (P.0306). The odds of death were 2.5 times higher for patients with an ejection fraction <25%. Conclusion Our study demonstrates that among patients with symptomatic heart failure and NT-proBNP > 70,000 pg/ml, mortality rate is nearly 50% over four years. Furthermore, it re-emphasizes the important role of left ventricular systolic function in predicting mortality in this patient population.
082 Sepsis and Congestive Heart Failure as Strong Independent Factors in Elevated Troponin I Chien-Wen Yang1, Huijun Li1, Lisa Thomas2, Manuel Ramos1, Po-Hong Liu3, Thomas Roe4, Ravinder Valadri1, Qi Shi1; 1The Wright Center for Graduate Medical Education, Scranton, Pennsylvania; 2Hematology & Oncology Associates of Northeast Pennsylvania, Pennsylvania; 3Harvard T.H. Chan School of Public Health, Boston, Massachusetts; 4 Commonwealth Health Physician Network Great Valley Cardiology, Scranton, Pennsylvania Background: Troponin I (TnI) is one of the most commonly tested biochemical markers to access cardiomyocyte damage. Coronary artery disease (CAD) has been well recognized to cause TnI elevation. Other than CAD, demand ischemia with underlying tachycardia, anemia, hypertensive emergency, congestive heart failure (CHF), kidney disease, sepsis, and pulmonary embolism (PE) have also been reported to cause TnI elevation. However, there is only a few reports excluding the patients with CAD, and no study has summarized up the proportion of these risks. Purpose: The aim of this retrospective study was designed to investigate the level of contribution of the causes of TnI elevation. Method: Records of patients tested for troponin during ER visit or hospitalization were collected. Patients with known CAD, positive stress test or cardiac cathriztiona, or being discharged without adequate cardiac evaluation were excluded. Age, sex, Hb, HR, systolic BP, calculated GFR by Cockcroft Gault equation and underlying conditions including CHF, sepsis, PE and Afib were collected from the medical records. Elevation of TnI was defined according to the parameter of the hospital and is equal or greater than 0.03 ng/ml. Logistic regression was used to identify predictors of elevated troponin. Result: A total of 586 patients were investigated in this study. Age, Hb, HR, GFR, Afib, CHF, and sepsis were significant predictors of elevated TnI according to analysis of invariable logistic regression (all P < .001). In multivariable logistic regression, sepsis (P < .001, OR 21.96) and CHF (P < .001, OR 6.055) were shown to be the two strongest underlying conditions causing elevation of TnI. Age, Hb, HR were also independent predictors of troponin (all P < .01). A simple clinical scoring system was generated with one score on patients with age ≥ 60, Hb < 10 g/ dL, and HR ≥ 100 per minute. The prevalence of elevated troponin was 4%, 16%, 38%, and 50% for patients with scores of 0, 1, 2, and 3, respectively. In the patients without sepsis and CHF, the chances of elevated troponin are 2%, 11%, 28%, 43%. Conclusion: Sepsis and CHF were found to be the strongest independent causes of elevated troponin I in non-CAD patients. The scoring system composed of age, Hb, HR can assist clinical evaluation of elevated troponin tests in non-CAD patients.
083 Predicting Variables of Mortality among Patients with NT-proBNP > 70,000 Pg/Ml Julio Perez-Downes, Carlos Palacio, Alan Miller, Pramod Reddy; University of Florida College of Medicine-Jacksonville, Jacksonville, Florida Introduction: Elevated NT-pro-BNP levels have been identified as independent predictors of mortality in patients with heart failure, end stage renal disease, as well as the general population. No study to date has evaluated the significance of
Fig. 1. Survival estimates between patients with an EF <25 versus those with an EF > or equal to 25. Y-axis represents the probability of survival. The X-axis represents survival in number of days. The blue line represents those patients with an ejection fraction <25, while the red line represents patients with an EF > or equal to 25. The shaded areas represent the 95% confidence intervals for the curves. Note the significant divergence between survival curves in the two populations. P = .0043. EF: ejection fraction.