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Normalization of Hemodynamics Following LVAD Implantation May be Related to Improved Long Term Outcome
The 19th Annual Scientific Meeting
HFSA
S99
of patients were female and 35.1% (33/94) had ischemic cardiomyopathy. The median ejection fraction was 15% (IQR 15%-30%). Biventricular support accounted for 22.6% (24/106) of pumps, left VAD alone accounted for 16.0% (17/106), and right VAD alone accounted for 61.3% (65/106). Median duration of left and right VAD support were 10 days (IQR 3-23) and 9 days (5-16), respectively. Median overall and ICU length of stay were 38 (IQR 18-50) and 47 (IQR 26-67) days, respectively. Survival to discharge was 64.9% (61/94). While on support, 5.3% (5/94) developed bloodstream infections, 10.6% (10/94) had strokes, and 28.7% (28/94) required hemodialysis. Among survivors to discharge, 72.1% (44/61) experienced myocardial recovery, 3.3% (2/61) underwent durable left VAD implantation, and 24.6% (15/61) underwent heart transplantation. At discharge, 70.5% (44/61) of survivors were ambulatory without assistance. Conclusions: Our seven-year experience demonstrates acceptable mortality and morbidity with the ecfVAD. Its long term use as a right VAD is safe and effective. The majority of survivors are ambulatory at discharge.
improvements in hemodynamic measures and post CF-LVAD survival. Methods: A retrospective chart review was conducted for all CF-LVAD patients in a large center between 2009-2013. Patients who had undergone a right heart catheterization (RHC) before implantation and within 3-6 months post-implantation were included. Data was collected from the electronic medical record. Primary outcome was improvement in hemodynamics normalization. Normal Hemodynamics were defined as the following: right atrial pressure ! 12 mmHg, pulmonary capillary wedge pressure ! 18 mmHg, and cardiac index (by Fick method) O 2.1. Secondary outcome was Kaplan-Meier survival analysis. Patients were stratified into two groups based on the number of hemodynamics criteria that were normalized postimplantation: completely normalized or partially normalized. Results: 54 patients had hemodynamic data collected within the study period and were included. The number of abnormal hemodynamics parameters decreased in 45 patients after CF-LVAD implantation. Only 46% of the patients had complete normalization of hemodynamics while 28% of the patients improved most of their hemodynamics (only 1 parameter was not normalized) and 36% of the patients remained with multiple abnormal hemodynamics (2 or more) despite CF-LVAD support. The group with complete resolution trended to better 2 years survival (p50.17) (figure 1). Conclusion: CF-LVAD implantation led to a complete resolution of cardiogenic shock parameters in only 46% of patients. Patients with complete resolution of cardiogenic criteria trend to better outcome, however larger studies will be required to learn the role hemodynamic optimization plays in the outcomes of CF-LVAD patients.
Figure 1.
Figure 1. Kaplan-meier survival curves of patients with complete normalization of cardiogentic shock parameters compared to those complete normalization.
Table 1. Post-implantation outcomes
All patients(n594) Mortality and Length of Stay (LOS) Death prior to explantation In-hospital mortality In-hospital mortality Median ICU LOS (days) Median hospital LOS (days) Complications Re-exploration for bleeding Bloodstream infection on support Stroke while on support TIA on support Hemodialysis on support Functional Outcomes in Survivors to Discharge Ambulatory with no assistance at discharge Required rehabilitation at discharge Outcomes in Survivors to Discharge Myocardial recovery Durable left VAD implantation Heart transplantation
16.0% 35.1% 64.9% 37.5 47.0
(15/94) (33/94) (61/94) (18-50) (26-67)
40.4% 5.3% 10.6% 4.3% 28.7%
(38/94 (5/94) (10/94) (4/94) (28/94)
70.5% (43/61) 29.5% (18/61) 72.1% (44/61) 3.3% (2/61) 24.6% (15/61)
228 Normalization of Hemodynamics Following LVAD Implantation May be Related to Improved Long Term Outcome Emeka C. Anyanwu, Kershaw Patel, Cory Henderson, Savitri E. Fedson, Gene H. Kim, Nitasha Sarswat, Colleen Juricek, Takeyoshi Ota, Valluvan Jeevanandam, Gabriel Sayer, Nir Uriel; University of Chicago Medicine, Chicago, IL Purpose: Continuous flow left ventricular assist devices (CF-LVAD) improve hemodynamics in heart failure patients. However, data is lacking to demonstrate a significant correlation between post-implantation hemodynamic improvement and changes in outcomes. This study aims to assess the relationship between
230 Development of a Preoperative Risk Model that Predicts Gastrointestinal Bleeding after Implantation of Continuous-Flow LVADs Christopher T. Sparrow, Michael E. Nassif, David S. Raymer, Paul M. Lavigne, Eric Novak, Shane J. LaRue, Joel D. Schilling, Gregory A. Ewald, Justin M. Vader; Washington University in Saint Louis, St. Louis, MO Background: Gastrointestinal bleeding (GIB) is a frequent complication after implantation of continuous-flow LVADs (CF-LVADs). Identifying patients at increased risk of post-LVAD GIB in the preoperative setting has proven difficult. We sought to develop a preoperative risk model to stratify patients with regard to GIB risk. Methods: We retrospectively identified 446 patients who received a CF-LVAD at our institution from 6/2005 - 9/2014. From this cohort, univariate Cox proportional hazards models were built on 30 variables known or theorized to be associated with GIB. Death was considered a competing risk. Eleven variables correlated with GIB: age, INTERMACS profile, hemoglobin, smoking, ICM, DT strategy, diabetes, BUN, LVEDD, right atrial pressure (RAP) and TAPSE. These variables were used to develop a multivariable Cox model to predict GIB. A step-down variable selection technique with Akaike’s information criteria used to establish a stopping point was conducted to develop a parsimonious cause-specific model. The final model included age, INTERMACS profile, BUN, TAPSE, and RAP. Gender was added to the model as a documented predictor of GIB. Model-based probabilities of GIB at 6 months were determined for all patients, and a c-statistic was determined to identify the discriminatory ability of the model. A calibration plot was used to identify how accurately the model reflects actual event rates. Results: During mean follow up of 17.8 6 13.8 months, 150 (33.6%) patients had a GIB event. In the final multivariable risk model, male sex (HR 0.606, CI 0.404-0.909, P50.016) and higher TAPSE (HR 0.581, CI 0.3870.871, P50.009) were protective against GIB. Older age (HR 1.036, CI 1.0171.056, P!0.001) and higher INTERMACS profile (HR 1.383, CI 1.037-1.845, P50.028), BUN (HR 1.011, CI 1.002-1.020, P50.023) and RAP (HR 1.041, CI 1.009-1.074, P50.012) were identified as risk factors for GIB. The model accurately reflected actual 6-month event rates (Figure 1) and was a reliable discriminator of GIB events vs. non-events (C-statistic - 0.68, CI 0.62-0.74, P!0.001). Conclusion: In this study we have derived a risk model that accurately predicts the risk of post-LVAD GIB. The model incorporates data routinely obtained prior to LVAD, making it a practical tool to inform downstream decisions. While
HFSA
S99
of patients were female and 35.1% (33/94) had ischemic cardiomyopathy. The median ejection fraction was 15% (IQR 15%-30%). Biventricular support accounted for 22.6% (24/106) of pumps, left VAD alone accounted for 16.0% (17/106), and right VAD alone accounted for 61.3% (65/106). Median duration of left and right VAD support were 10 days (IQR 3-23) and 9 days (5-16), respectively. Median overall and ICU length of stay were 38 (IQR 18-50) and 47 (IQR 26-67) days, respectively. Survival to discharge was 64.9% (61/94). While on support, 5.3% (5/94) developed bloodstream infections, 10.6% (10/94) had strokes, and 28.7% (28/94) required hemodialysis. Among survivors to discharge, 72.1% (44/61) experienced myocardial recovery, 3.3% (2/61) underwent durable left VAD implantation, and 24.6% (15/61) underwent heart transplantation. At discharge, 70.5% (44/61) of survivors were ambulatory without assistance. Conclusions: Our seven-year experience demonstrates acceptable mortality and morbidity with the ecfVAD. Its long term use as a right VAD is safe and effective. The majority of survivors are ambulatory at discharge.
improvements in hemodynamic measures and post CF-LVAD survival. Methods: A retrospective chart review was conducted for all CF-LVAD patients in a large center between 2009-2013. Patients who had undergone a right heart catheterization (RHC) before implantation and within 3-6 months post-implantation were included. Data was collected from the electronic medical record. Primary outcome was improvement in hemodynamics normalization. Normal Hemodynamics were defined as the following: right atrial pressure ! 12 mmHg, pulmonary capillary wedge pressure ! 18 mmHg, and cardiac index (by Fick method) O 2.1. Secondary outcome was Kaplan-Meier survival analysis. Patients were stratified into two groups based on the number of hemodynamics criteria that were normalized postimplantation: completely normalized or partially normalized. Results: 54 patients had hemodynamic data collected within the study period and were included. The number of abnormal hemodynamics parameters decreased in 45 patients after CF-LVAD implantation. Only 46% of the patients had complete normalization of hemodynamics while 28% of the patients improved most of their hemodynamics (only 1 parameter was not normalized) and 36% of the patients remained with multiple abnormal hemodynamics (2 or more) despite CF-LVAD support. The group with complete resolution trended to better 2 years survival (p50.17) (figure 1). Conclusion: CF-LVAD implantation led to a complete resolution of cardiogenic shock parameters in only 46% of patients. Patients with complete resolution of cardiogenic criteria trend to better outcome, however larger studies will be required to learn the role hemodynamic optimization plays in the outcomes of CF-LVAD patients.
Figure 1.
Figure 1. Kaplan-meier survival curves of patients with complete normalization of cardiogentic shock parameters compared to those complete normalization.
Table 1. Post-implantation outcomes
All patients(n594) Mortality and Length of Stay (LOS) Death prior to explantation In-hospital mortality In-hospital mortality Median ICU LOS (days) Median hospital LOS (days) Complications Re-exploration for bleeding Bloodstream infection on support Stroke while on support TIA on support Hemodialysis on support Functional Outcomes in Survivors to Discharge Ambulatory with no assistance at discharge Required rehabilitation at discharge Outcomes in Survivors to Discharge Myocardial recovery Durable left VAD implantation Heart transplantation
16.0% 35.1% 64.9% 37.5 47.0
(15/94) (33/94) (61/94) (18-50) (26-67)
40.4% 5.3% 10.6% 4.3% 28.7%
(38/94 (5/94) (10/94) (4/94) (28/94)
70.5% (43/61) 29.5% (18/61) 72.1% (44/61) 3.3% (2/61) 24.6% (15/61)
228 Normalization of Hemodynamics Following LVAD Implantation May be Related to Improved Long Term Outcome Emeka C. Anyanwu, Kershaw Patel, Cory Henderson, Savitri E. Fedson, Gene H. Kim, Nitasha Sarswat, Colleen Juricek, Takeyoshi Ota, Valluvan Jeevanandam, Gabriel Sayer, Nir Uriel; University of Chicago Medicine, Chicago, IL Purpose: Continuous flow left ventricular assist devices (CF-LVAD) improve hemodynamics in heart failure patients. However, data is lacking to demonstrate a significant correlation between post-implantation hemodynamic improvement and changes in outcomes. This study aims to assess the relationship between
230 Development of a Preoperative Risk Model that Predicts Gastrointestinal Bleeding after Implantation of Continuous-Flow LVADs Christopher T. Sparrow, Michael E. Nassif, David S. Raymer, Paul M. Lavigne, Eric Novak, Shane J. LaRue, Joel D. Schilling, Gregory A. Ewald, Justin M. Vader; Washington University in Saint Louis, St. Louis, MO Background: Gastrointestinal bleeding (GIB) is a frequent complication after implantation of continuous-flow LVADs (CF-LVADs). Identifying patients at increased risk of post-LVAD GIB in the preoperative setting has proven difficult. We sought to develop a preoperative risk model to stratify patients with regard to GIB risk. Methods: We retrospectively identified 446 patients who received a CF-LVAD at our institution from 6/2005 - 9/2014. From this cohort, univariate Cox proportional hazards models were built on 30 variables known or theorized to be associated with GIB. Death was considered a competing risk. Eleven variables correlated with GIB: age, INTERMACS profile, hemoglobin, smoking, ICM, DT strategy, diabetes, BUN, LVEDD, right atrial pressure (RAP) and TAPSE. These variables were used to develop a multivariable Cox model to predict GIB. A step-down variable selection technique with Akaike’s information criteria used to establish a stopping point was conducted to develop a parsimonious cause-specific model. The final model included age, INTERMACS profile, BUN, TAPSE, and RAP. Gender was added to the model as a documented predictor of GIB. Model-based probabilities of GIB at 6 months were determined for all patients, and a c-statistic was determined to identify the discriminatory ability of the model. A calibration plot was used to identify how accurately the model reflects actual event rates. Results: During mean follow up of 17.8 6 13.8 months, 150 (33.6%) patients had a GIB event. In the final multivariable risk model, male sex (HR 0.606, CI 0.404-0.909, P50.016) and higher TAPSE (HR 0.581, CI 0.3870.871, P50.009) were protective against GIB. Older age (HR 1.036, CI 1.0171.056, P!0.001) and higher INTERMACS profile (HR 1.383, CI 1.037-1.845, P50.028), BUN (HR 1.011, CI 1.002-1.020, P50.023) and RAP (HR 1.041, CI 1.009-1.074, P50.012) were identified as risk factors for GIB. The model accurately reflected actual 6-month event rates (Figure 1) and was a reliable discriminator of GIB events vs. non-events (C-statistic - 0.68, CI 0.62-0.74, P!0.001). Conclusion: In this study we have derived a risk model that accurately predicts the risk of post-LVAD GIB. The model incorporates data routinely obtained prior to LVAD, making it a practical tool to inform downstream decisions. While