1. Predicting Patients at Risk for Poor Global Outcomes after DT- MCS Therapy Suzanne V. Arnold, MD, MHA Saint Luke’s Mid America Heart Institute/UMKC May 16, 2015

2. Background LVADs improve survival and quality of life for most patients with end-stage heart failure who are not candidates for heart transplant There are a group of patients who, despite LVAD, do not improve functionally or live longer following intervention

3. Background Previous risk models have focused on mortality Improved quality of life may be an equally or even more important treatment goal –Patients with severe heart failure symptoms were willing to trade over half of their remaining life years to achieve a better quality of life We sought to define the incidence and predictors of poor global outcome Lewis et al-J Heart Lung Transplant. 2001 Sep;20(9):1016-24

4. Prior Work in TAVR - Similarities Highly symptomatic patients with expected short survival without intervention Both interventions have large effects on both of these factors High residual mortality despite intervention –1 year mortality 20-25% Kirklin et al-Heart Lung Transplant. 2014;33(6):555-564

5. Prior Work in TAVR - Differences LVAD patients generally younger –Median age 60’s vs. 80’s LVADs often placed in emergent settings LVADs have many subsequent complications that impact outcomes

6. Definition of Combined Outcome Assessed at 1 year after LVAD Death Very poor quality of life –KCCQ <45 over the year following LVAD Arnold et al., Circ Cardiovasc Qual Outcomes. 2013 Sep 1;6(5):591-7. Arnold et al., Circulation. 2014 Jun 24;129(25):2682-90.

7. Preliminary Study – Single Center LVAD Patients N=168 LVAD Patients N=168 Analytic Cohort N=164 Analytic Cohort N=164 Acceptable Outcome N=106 (65%) Acceptable Outcome N=106 (65%) Poor Outcome N=58 (35%) Poor Outcome N=58 (35%) Dead N=37 (23%) Dead N=37 (23%) Very Poor QoL N=17 (10%) Very Poor QoL N=17 (10%) Recurrent HF N=3 (2%) Recurrent HF N=3 (2%) –4 patients (under 18, intra-op death, transferred care) –4 patients (under 18, intra-op death, transferred care) Severe CVA N=1 (1%) Severe CVA N=1 (1%) Fendler et al., Circ Cardiovasc Qual Outcomes. 2015;8(Suppl 2):A225

8. Characteristics of patients with vs. without poor global outcome Poor Global Outcome (n = 58) Favorable Outcome (n = 106) P-value Age-years 55.9± 13.556.0± 12.4 0.956 White race 72%79.0% 0.569 Male 72%82.9%0.116 Device strategy0.010 Bridge to transplant52%72% Destination therapy46%24% Bridge to decision2%5% Days in hospital per months alive Mean 17.0 ± 11.66.8 ± 8.3 <0.001 Median (IQR) 18.6 (5.0-31.0)3.7 (1.8-8.3) <0.001 Major gastrointestinal bleeding 44%28%0.056 Non-disabling stroke 10%6%0.348 Hemorrhagic 12%2%0.031 Ischemic 9%4%0.259

9. INTERMACS VAD Patients v3.0 May 2012-Sept 2013 N=3922 VAD Patients v3.0 May 2012-Sept 2013 N=3922 Analytic Cohort N=1487 Analytic Cohort N=1487 Died <1 year N=336 (23%) Died <1 year N=336 (23%) Survived N=1151 Survived N=1151 Very Poor QoL N=94 (7%) Very Poor QoL N=94 (7%) Acceptable QoL N=880 (67%) Acceptable QoL N=880 (67%) –2208 BTT/possible BTT –45 BTR, rescue, other –31 BiVAD –151 missing all comorbidity data –2208 BTT/possible BTT –45 BTR, rescue, other –31 BiVAD –151 missing all comorbidity data Follow-up KCCQ data N=974 Follow-up KCCQ data N=974 –177 No KCCQ follow-up

10. Methods Multivariable logistic model was built to predict a poor outcome at 1 year after DT-LVAD –18 baseline demographic and clinical variables –Parameter estimates penalized to minimize the effect of over-fitting –Inverse propensity weighting was used to adjust for loss to follow-up

11. OR (95% CI)P-value Age (per +10 years)1.23 (1.08-1.40)0.002 KCCQ-12 Summary Score (per -10 pts)1.10 (1.02-1.18)0.010 BMI (per +5 kg/m 2 )1.12 (1.02-1.24)0.017 INTERMACS Patient Profile 1-21.27 (0.97-1.65)0.078 History of solid organ cancer1.39 (0.96-2.01)0.079 Previous cardiac operation1.23 (0.95-1.59)0.119 Hemoglobin (per +1 g/dL)0.95 (0.89-1.02)0.170 History of illicit drug use/alcohol abuse1.29 (0.88-1.89)0.189 Model 0 1 2 3 Non-significant factors: sex, diabetes, stroke, PAD, creatinine, lung disease, albumin, arrhythmias, tricuspid regurgitation, KCCQ missing

12. Discrimination: C-index=0.64, Validated=0.62 Calibration: Slope=1.01, Intercept=0.01 Discrimination: C-index=0.64, Validated=0.62 Calibration: Slope=1.01, Intercept=0.01 Model Performance

13. Outcomes by Predicted Risk

14. Characteristics by Risk Group Low Risk n=133 Intermediate Risk n=1040 High Risk n=137 Age Group <5053%11%2% 50-5921%17%9% 60-6917%37%34% 70+9%36%55% BMI (kg/m2)26.7±6.528.2±6.332.0±11.5 Pulmonary disease11%13%21% Atrial arrhythmia12%24%32% Severe diabetes3%12%32% Peripheral vascular disease3%8%22% Cancer2%10%27% Creatinine (mg/dL)1.2±0.41.5±0.61.7±0.7 Previous cardiac surgery14%41%74% INTERMACS 1-226%41%77% KCCQ Pre-Implant54.7±22.132.7±19.219.1±13.4

15. Uncertainty Poor outcomes after LVAD are difficult to predict –Coarse characterization at baseline –KCCQ may not fully encompass post-LVAD QoL –Post-LVAD complications play more of a role

16. Impact of Post-LVAD Events Poor Global Outcome Acceptable Outcome P-value Major bleeding47%40%0.010 Stroke21%5.5%<0.001 OR (95% CI)P-value Major bleeding1.19 (0.92-1.54)0.187 Stroke3.87 (2.61-5.73)<0.001 When added to the pre-LVAD model: C-index=0.70; validated=0.68

17. Summary Nearly one-third of patients have poor global outcomes over the year after DT-LVAD Identifying patients at such a high-risk of this poor outcome to deem the LVAD futile is unlikely This model could be used to enable more realistic expectations of outcomes for individual patients

18. Thank you