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Serum Serotonin Level Can Predict Outcomes in Heart Failure
S86 Journal of Cardiac Failure Vol. 18 No. 8S August 2012 26 (26%) had depression. Depressed patients were similar demographically to nondepressed patients (see table1). Depressed and non-depressed patients were similar clinically, as well: bridge to transplant with a left ventricular assist device (46% vs. 45% p50.92. There was no statistical difference in survival between groups at 4 years after HT (p5.94) (see figure 1). All cause hospitalizations were higher in depressed versus non-depressed patients (4.3 vs. 2.6 p50.05). There were no significant differences in hospitalizations between the two groups for the following complications: cardiac (volume overload, arrhythmias, MI/ACS, acute rejection) and infections. There was no significant difference in episodes of 2R and 3R rejection in depressed vs. non-depressed patients. Conclusion: Depression was not associated with increased mortality or cardiac rejection, however depression was associated with increased all cause hospitalizations. 92% of the depressed patients were treated with an antidepressant. The role treatment played in our cohort is unclear, but additional study is warranted.
high plasma serotonin (O 2.4 ng/ml) and the other had 65 patients with low plasma serotonin (# 2.4 ng/ml). Patients receiving medications affecting serotonin receptors and those with pulmonary hypertension were excluded. All patients were followed by the CHF outpatient clinic and were on stable doses of HF medications. The two groups were compared for their 18 months mortality and admission tates. Results: Mean serotonin level in the low group was 1.0 ng/ml vs 9.52 ng/ml in the high group. The group with high serotonin levels showed higher mortality rate at 18 months (19.5% VS 3.1%, P50.005) as well as higher hospital admission rate (41.5% VS 20%, P50.012) compared to the low serotonin group. There was no significant difference in the mean EF between the two groups (34.2 % 6 12.1% in the low VS 32.0% 6 12.7% in high serotonin group, P50.37).These findings were also independent of age, race, renal function, diabetes mellitus and hypertension. Conclusions: Serotonin levels can be used to predict both mortality and hospitalization in patients with stable heart failure. These correlations need to be further investigated in randomized trials with larger population.
281 Fig. 1. Kaplan-Meier Overall Survival Curves by Depression Status (log-rank pvalue50.989)
279 Patterns of Change in Cognitive Function Over Six Months in Adults With Chronic Heart Failure Barbara Riegel1, Christopher S. Lee2; 1School of Nursing, University of Pennsylvania, Philadelphia, PA; 2School of Nursing, Oregon Health & Science University, Portland, OR Few investigators have studied cognition over time in adults with heart failure (HF). Data were obtained from 279 adults with chronic HF in whom cognition was assessed using the digit symbol substitution task (DSST) at baseline, 3 and 6 months after enrollment from out-patient settings. Growth mixture modeling (GMM) was used to model cognitive patterns and describe how those patterns changed over time. Multivariate logistic regression modeling was used to identify factors associated with the identified patterns. The sample was predominantly male (63.2%), Caucasian (62.7%) with a mean age of 62 years. The best fit GMM revealed two trajectories of DSST scores. Average processing speed was identified in 40.5% of the sample and Below Average processing speed in 59.9%, although premorbid intelligence was average and not clinically different between the two groups. Neither group changed significantly over the six month study period. Factors significantly associated with increased odds of being classified in the Below Average processing speed group included older age, male gender, Non-Caucasian race, less education, high comorbid burden, higher ejection fraction, excessive daytime sleepiness, and higher BMI. These results suggest that HF patients who are more ill are more likely to have problems with cognition. Research testing interventions to address the modifiable factors of ejection fraction, sleepiness, and BMI is needed to identify ways to improve cognitive function in adults with HF.
Use of Bioelectrical Impedance Analysis To Assess Body Composition in Heart Failure Patients Elizabeth Thomas, Adrienne L. Clark, Gregg C. Fonarow, Tamara B. Horwich; Medicine/Cardiology, David Geffen School of Medicine, Los Angeles, CA Background: Obesity is common in heart failure (HF) and associated with improved prognosis (the “obesity paradox”). However, whether lean and/or fat mass are contributing to improved prognosis in obese HF patients is unknown. Hypothesis: Using bioelectrical impedance analysis (BIA) to assess body composition will help determine if fat and/or lean mass are contributing to the obesity paradox in HF. Methods: BIA was used to assess body composition in 274 HF patients using InBody 520 (Biospace Inc, CA), an 8-point tactile electrode system employing 5, 50, and 500 kHz frequencies. Body fat mass (BFM) and lean body mass (LBM) were indexed by body surface area (BSA). The cohort was stratified by median BFM and LBM indexed to BSA (BFMi, 12.0 kg/m2 and LBMi, 28.9 kg/m2). Results: Mean age was 55614, mean LVEF 36616. BFMi was highly correlated with both waist circumference (WC) and body mass index (BMI) (r50.815 and r50.710, p!0.001), but LBMi was not. Patients with high BFMi were more likely diabetic, had higher BP and HbA1c; there was no difference in high vs. low BFMi in age, LVEF, or NYHA. Patients with high LBMi were more likely to be male, have lower NYHA class, and higher BP and LDL levels. There was a trend towards lower BNP with high LBMi (Table). 6-month event-free survival was better in both the high vs. low BFMi and LBMi groups (98% vs 87% and 92 vs 84%, p5NS) Conclusions: BIA data suggests that both higher lean and fat mass may be protective in HF, as they are associated with variables that predict better prognosis such as high BP and LDL and lower NYHA. For a more complete understanding of the obesity paradox in HF, further investigation body composition and outcomes in HF is warranted.
Baseline Characteristics of the Cohort Stratified by Fat and Lean Mass
280 Serum Serotonin Level Can Predict Outcomes in Heart Failure Ahmed M. Selim2, Nitasha Sarswat1, Ramesh Chandra1, Norma Christian1, Catherine Galvin1, Ronald Zolty1; 1Cardiology, Albert Einstein College of Medicine, Bronx, NY; 2Internal Medicine, Bronx Lebanon Hospital Center, Bronx, NY Introduction: The relationship between Heart Failure (HF) and the serotonergic system has been established in the past. The utility of this relationship to predict outcomes, including mortality and Hospital admission was not investigated before. Methods: Serotonin levels were measured in 106 stable HF clinic patients (39 females and 67 males). The median value of the serum serotonin of all patients was used to divide the samples into two groups. One group included 41 patients with
Age (yrs) Male (%) Ischemic HF (%) NYHA 1/2/3/4 (%) Diabetes (%) SBP (mmHg) DBP (mmHg) BNP (pg/mL) LDL (mg/dL) Triglycerides Albumin (g/dL) Hb A1c (%)
Low BFMi (#12 kg/m2) n5137
High BFMi (O12 kg/m2) n5135
56 6 16 75 66 23/41/34/2 35 112 6 19 69 6 14 201 (52 - 593) 92 6 34 108 (78 - 149) 4.2 6 0.4 5.9 6 1.1
55 6 13 73 67 11/48/35/6 65 118 6 20 74 6 14 177 (21 - 398) 90 6 41 108 (89 - 159) 4.2 6 0.4 6.6 6 2
P
Low LBMi (#28.9 kg/m2) n5134
High LBMi (O28.9 kg/m2) n5137
P
0.5 0.4 0.5 0.2 0.01 0.007 0.007 0.1 0.7 0.2 0.7 0.03
56 6 15 52 71 11/41/45/4 27 114 6 19 69 6 12 225 (65 - 682) 85 6 38 96 (79 - 134) 4.2 6 0.4 6.3 6 1.8
53 6 13 94 65 24/45/26/5 26 117 6 20 74 6 15 155 (29 - 396) 98 6 37 121 (86 - 164) 4.3 6 0.4 6.3 6 1.5
0.08 !0.001 0.2 0.04 0.5 0.3 0.01 0.08 0.05 0.05 0.5 0.9
high plasma serotonin (O 2.4 ng/ml) and the other had 65 patients with low plasma serotonin (# 2.4 ng/ml). Patients receiving medications affecting serotonin receptors and those with pulmonary hypertension were excluded. All patients were followed by the CHF outpatient clinic and were on stable doses of HF medications. The two groups were compared for their 18 months mortality and admission tates. Results: Mean serotonin level in the low group was 1.0 ng/ml vs 9.52 ng/ml in the high group. The group with high serotonin levels showed higher mortality rate at 18 months (19.5% VS 3.1%, P50.005) as well as higher hospital admission rate (41.5% VS 20%, P50.012) compared to the low serotonin group. There was no significant difference in the mean EF between the two groups (34.2 % 6 12.1% in the low VS 32.0% 6 12.7% in high serotonin group, P50.37).These findings were also independent of age, race, renal function, diabetes mellitus and hypertension. Conclusions: Serotonin levels can be used to predict both mortality and hospitalization in patients with stable heart failure. These correlations need to be further investigated in randomized trials with larger population.
281 Fig. 1. Kaplan-Meier Overall Survival Curves by Depression Status (log-rank pvalue50.989)
279 Patterns of Change in Cognitive Function Over Six Months in Adults With Chronic Heart Failure Barbara Riegel1, Christopher S. Lee2; 1School of Nursing, University of Pennsylvania, Philadelphia, PA; 2School of Nursing, Oregon Health & Science University, Portland, OR Few investigators have studied cognition over time in adults with heart failure (HF). Data were obtained from 279 adults with chronic HF in whom cognition was assessed using the digit symbol substitution task (DSST) at baseline, 3 and 6 months after enrollment from out-patient settings. Growth mixture modeling (GMM) was used to model cognitive patterns and describe how those patterns changed over time. Multivariate logistic regression modeling was used to identify factors associated with the identified patterns. The sample was predominantly male (63.2%), Caucasian (62.7%) with a mean age of 62 years. The best fit GMM revealed two trajectories of DSST scores. Average processing speed was identified in 40.5% of the sample and Below Average processing speed in 59.9%, although premorbid intelligence was average and not clinically different between the two groups. Neither group changed significantly over the six month study period. Factors significantly associated with increased odds of being classified in the Below Average processing speed group included older age, male gender, Non-Caucasian race, less education, high comorbid burden, higher ejection fraction, excessive daytime sleepiness, and higher BMI. These results suggest that HF patients who are more ill are more likely to have problems with cognition. Research testing interventions to address the modifiable factors of ejection fraction, sleepiness, and BMI is needed to identify ways to improve cognitive function in adults with HF.
Use of Bioelectrical Impedance Analysis To Assess Body Composition in Heart Failure Patients Elizabeth Thomas, Adrienne L. Clark, Gregg C. Fonarow, Tamara B. Horwich; Medicine/Cardiology, David Geffen School of Medicine, Los Angeles, CA Background: Obesity is common in heart failure (HF) and associated with improved prognosis (the “obesity paradox”). However, whether lean and/or fat mass are contributing to improved prognosis in obese HF patients is unknown. Hypothesis: Using bioelectrical impedance analysis (BIA) to assess body composition will help determine if fat and/or lean mass are contributing to the obesity paradox in HF. Methods: BIA was used to assess body composition in 274 HF patients using InBody 520 (Biospace Inc, CA), an 8-point tactile electrode system employing 5, 50, and 500 kHz frequencies. Body fat mass (BFM) and lean body mass (LBM) were indexed by body surface area (BSA). The cohort was stratified by median BFM and LBM indexed to BSA (BFMi, 12.0 kg/m2 and LBMi, 28.9 kg/m2). Results: Mean age was 55614, mean LVEF 36616. BFMi was highly correlated with both waist circumference (WC) and body mass index (BMI) (r50.815 and r50.710, p!0.001), but LBMi was not. Patients with high BFMi were more likely diabetic, had higher BP and HbA1c; there was no difference in high vs. low BFMi in age, LVEF, or NYHA. Patients with high LBMi were more likely to be male, have lower NYHA class, and higher BP and LDL levels. There was a trend towards lower BNP with high LBMi (Table). 6-month event-free survival was better in both the high vs. low BFMi and LBMi groups (98% vs 87% and 92 vs 84%, p5NS) Conclusions: BIA data suggests that both higher lean and fat mass may be protective in HF, as they are associated with variables that predict better prognosis such as high BP and LDL and lower NYHA. For a more complete understanding of the obesity paradox in HF, further investigation body composition and outcomes in HF is warranted.
Baseline Characteristics of the Cohort Stratified by Fat and Lean Mass
280 Serum Serotonin Level Can Predict Outcomes in Heart Failure Ahmed M. Selim2, Nitasha Sarswat1, Ramesh Chandra1, Norma Christian1, Catherine Galvin1, Ronald Zolty1; 1Cardiology, Albert Einstein College of Medicine, Bronx, NY; 2Internal Medicine, Bronx Lebanon Hospital Center, Bronx, NY Introduction: The relationship between Heart Failure (HF) and the serotonergic system has been established in the past. The utility of this relationship to predict outcomes, including mortality and Hospital admission was not investigated before. Methods: Serotonin levels were measured in 106 stable HF clinic patients (39 females and 67 males). The median value of the serum serotonin of all patients was used to divide the samples into two groups. One group included 41 patients with
Age (yrs) Male (%) Ischemic HF (%) NYHA 1/2/3/4 (%) Diabetes (%) SBP (mmHg) DBP (mmHg) BNP (pg/mL) LDL (mg/dL) Triglycerides Albumin (g/dL) Hb A1c (%)
Low BFMi (#12 kg/m2) n5137
High BFMi (O12 kg/m2) n5135
56 6 16 75 66 23/41/34/2 35 112 6 19 69 6 14 201 (52 - 593) 92 6 34 108 (78 - 149) 4.2 6 0.4 5.9 6 1.1
55 6 13 73 67 11/48/35/6 65 118 6 20 74 6 14 177 (21 - 398) 90 6 41 108 (89 - 159) 4.2 6 0.4 6.6 6 2
P
Low LBMi (#28.9 kg/m2) n5134
High LBMi (O28.9 kg/m2) n5137
P
0.5 0.4 0.5 0.2 0.01 0.007 0.007 0.1 0.7 0.2 0.7 0.03
56 6 15 52 71 11/41/45/4 27 114 6 19 69 6 12 225 (65 - 682) 85 6 38 96 (79 - 134) 4.2 6 0.4 6.3 6 1.8
53 6 13 94 65 24/45/26/5 26 117 6 20 74 6 15 155 (29 - 396) 98 6 37 121 (86 - 164) 4.3 6 0.4 6.3 6 1.5
0.08 !0.001 0.2 0.04 0.5 0.3 0.01 0.08 0.05 0.05 0.5 0.9