1. THE PROFILE OF THE HEART FAILURE PATIENT WHO DOESN’T BENEFIT FROM AN ICD Giosuè Mascioli, MD, FESC Humanitas Gavazzeni - Bergamo

2. Death in Heart Failure ICD Possible role of ICD ICD ? Modified from: Henkel DM, Circ Heart Fail, Jul 2008

3. ICD benefit is not homogeneous Risk Factor HR 95% CI p value NYHA > 21.871.23 - 2.860.004 AF1.871.05 - 3.220.034 QRS > 120 msec1.651.08 - 2.510.020 Age > 70 yrs1.571.02 - 2.410.042 BUN>26 mg/dl (and < 50)1.561.00 - 2.420.048 VHR: BUN ≥ 50 mg/dl and serum creatinine ≥ 2.5 mg/dl Goldenberg I, JACC Jan 2008

4. Greater or lesser benefit Burden of cardiovascular illness Magnitude of benefit (lower number needed to treat) Cost-efficacy threshold Low risk of SD Low overall risk of death High risk of SD Intermediate overall risk of death Intermediate risk of SD High overall risk of death

5. The deadly duo Goldenberg I, Circulation Jun 2006

6. ICD therapy and Competing Death First appropriate ICD therapy Death before first appropriate ICD therapy Koller MT, Circulation Apr 2008

7. ICD and Comorbidities Bruch C, Europace Sep. 2007

8. THE SICKEST THE WORST ? - 1 Analysis of MADIT 2 patients: Mutivariate analysis of predictor of mortality: Age > 65 yrs NYHA class III - IV AF Increased level of BUN Cygankiewicz I, Heart Rhythm Apr 2009

9. THE SICKEST THE WORST ? - 2 BMI < 26 Schernthaner C, Croat Med Journ 2007

10. Reverse epidemiology and acute HF Burger AJ, Int J Cardiol Mar 2008

11. BMI and unadjusted all-cause mortality Curtis JP, Arch Intern Med 2005

12. Importance of number of HF episodes Setoguchi S, CMAJ Mar 2009

13. Badly treated, worst prognosis- 1 In MADIT 2, use of ICD was associated with a significant 39% increase in risk of HF Risk can be reduced used the corrected therapy: With B-blockers + ACE-inhibitors HR 0.36 With B-blockers only HR 0.51 (metoprolol 0.49, carvedilol 0.48) With ACE-inhibitors only HR 0.64 (p NS) Pietrasik G, JCE Apr. 2009

14. Badly treated, worst prognosis- 2 Gardiwal A, Europace Oct 2008

15. Predictors of early mortality in ICD patients Parameter p value in univ. anal. p value in multiv. anal. History of AF < 0.0001p < 0.001 Diabetes= 0.0001= 0.004 Failure to use statins < 0.001NS Use of digitalis < 0.0001NS Use of diuretics < 0.0001NS Low BMI < 0.0001= 0.001 Increasing AGE < 0.0001NS Low EF < 0.0001NS Low activity hours < 0.0001NS Elevated resting HR = 0.014NS Low MAP = 0.007= 0.04 Poor NYHA class < 0.0001= 0.006 Stein KM, Europace Mar 2009

16. Predictors of late mortality in ICD patients Factor Hazard Ratio (95% CI) p value Digoxin 1.86 (1.12 - 2.86) = 0.0046 Loops diuretics 1.59 (1.06 - 2.38) = 0.024 ACE-inhibitors or Aldosterone receptor blockers 0.50 (0.31 - 0.80) = 0.0038 Thibodeau JB, Am J Cardiol Mar 2008

17. ICD and kidney disease Stage/ Age Stage 1Stage 2Stage 3Stage 4Stage 5 < 65 yrs < 75 yrs < 80 yrs Favored Unfavored * At standard procedural mortality. At procedural mortality rates increased, age thresholds for ICD implant decrease. Amin MS, JCE Dec. 2008

18. ICD and eGRF Goldenberg I, Am J Cardiol Aug 2006

19. Cause-specific mortality in ICD patients: evadef study - 1 Marijon E, Am Heart J Feb 2009

20. Cause-specific mortality in ICD patients: evadef study - 2 Among characteristics at implantation: EF < 30% and history of AF related to SCD Age, NYHA class, systemic HT, QRS duration, EF < 30% and lack of B-blockers related to HF death An EF < 30% at implant appears to be the most important predictor of ICD-unresponsive SCD Marijon E, Am Heart J Feb 2009

21. Age and ICDs- 1 Healey JS, Eur Heart J Feb 2007

22. Age and ICDs- 2 Cause - specific mortality rates Age < 75 yrs (1614 pts) Age ≥ 75 yrs (252 pts) p value Arrhythmic death 3,846,730,03 Heart Failure Death 3,968,740,001 Non-cardiac death 1,514,720,001 Non-arrhythmic death 5,4713,460,001 All-cause death 9,3120,190,001 Arrhythmic/All-cause death ratio 0,410,33 Healey JS, Eur Heart J Feb 2007

23. Conclusions - 1 We MUST keep in mind that we do not use ICD to reduce sudden death, but to reduce TOTAL mortality If we cannot reach this goal, to implant an ICD is absolutely USELESS (if not negative for the patient) The problem is: how I identify patients whose greater risk is to die of non cardiac cause of of HF ?

24. Conclusions - 2 Predictors od adverse prognosis in HF can be used to identify patients whose prognosis do not deserve an ICD Among this factor we can recognize: non optimal drug therapy, too low EF, comorbidities, AF, low BMI and - particularly - kidney function Score tables can be of some help in taking the right decision, together with good clinical sense

25. Extending Life, Defibrillators Can Prolong Misery By Gina Kolata March 25, 2002 Out of the Blue, a Lightning Bolt to the Heart By Sandeep Jahuar Febrary 10, 2004

26. The final answer...

27. ... and the final comment I’ve stopped smoking. My life will be one week longer. And that week will rain all the time! Woody Allen