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Heart Failure Diagnostics Waqas Ghumman MD FACC Community Health Network Heart Failure Director HEART FAILURE – A GROWING GLOBAL CONCERN Prevalence and Incidence Mortality Overall 2.1% prevalence: 5.1M heart failure patients in 2010 1 For AHA/ACC stage C/D patients diagnosed with HF: 825,000 people ≥ 45 years of age are newly diagnosed each year with HF1 15M heart failure patients in the ESC 51-member countries 2 30% will die in the first year.3-5 60% will die within 5 years.5 Overall 2-3% prevalence2 HF prevalence in the US is projected to increase 46% from 2012 to 2030, resulting in > 8M people ≥ 18 years of age with HF.6 1. 2. 3. 4. 5. 6. AHA 2014 Statistics at a Glance, 2014 The European Society of Cardiology, ESC HF Guideline, 2008 Curtis et al, Arch Intern Med, 2008. Roger et al. JAMA, 2004. Cowie et al, EHJ, 2002. Heidenreich PA et al. Circ Heart Failure 2013. HEART FAILURE IS ASSOCIATED WITH HIGH HOSPITALIZATION AND READMISSION RATES In 2010, there were 1 million hospitalizations in the US with HF as the principal diagnosis 1 Hospitalization rate did not change significantly from 2000 1 Average length of hospital stay Approximately 5 days (US) 2 11 days (Europe) 3 HF is also associated with high readmission rates: ~25% all-cause readmission within 30 days and ~50% within 6 months 4,5 Graph from www.health.org.uk. Bridging the gap: Heart Failure, 2010. Data from Organization for Economic Cooperation and Development, 2009. 1. 2. 3. 4. 5. CDC NCHS National Hospital Discharge Survey, 2000-2010 Yancy et al. JACC, 2006. Cleland et al. EuroHeart, 2003. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009. Wexler DJ, et al. Am Heart J 2001. ECONOMIC BURDEN OF HF WILL CONTINUE TO RISE THROUGH 2030* The AHA estimates that the total medical costs for HF are projected to increase to $70B by 2030 a 2-fold increase from 2013. 1 50% of the costs are attributed to hospitalization. 2 Graph: Heidenreich PA, et al. Circulation Heart Failure 2013. *Study projections assumes HF prevalence remains constant and continuation of current hospitalization practices 1. Heidenreich PA, et al. Circulation Heart Failure 2013. 2. Yancy CW, et al. Circulation 2013. ECONOMIC RISKS OF HF READMISSIONS IN THE US Medicare’s Hospital Readmissions Reduction program penalizes hospitals that have above average all-cause readmissions within 30 days following HF discharge. 22.7% national average 30-day readmissions rate1,2 Percent withholding of all inpatient Medicare payments will increase to up to 3% by 2015 and beyond.3 Fiscal Year 2013 2014 2015+ % payment withholding up to 1% up to 2% up to 3% 1. Dharmarajan K, et al. JAMA. 2013;309(4):355-363. 2. Linden A, Adler-Milstein J. Health Care Finance Rev. 2008;29(3):1-11. 3. CMS Hospitals Readmissions Reductions Program of the Patient Protection and Affordable Care Act (PPACA), 2010. WORSENING HEART FAILURE LEADING TO HF HOSPITALIZATIONS CONTRIBUTES TO DISEASE PROGRESSION With each subsequent HF-related admission, the patient leaves the hospital with a further decrease in cardiac function. Graph adapted from: Gheorghiade MD, et al. Am J. Cardiol. 2005 HF HOSPITALIZATIONS ARE A STRONG PREDICTOR OF MORTALITY1,2 Data from the EFFECT study, n = 9138 patients 1 Data from Setoguchi et al., n = 14,374 patients 2 Among 1 year survivors after index EFFECT-HF discharge, the number of heart failure hospitalizations in the preceding year stratified the risk of death in crude analysis. 1 KP cumulative mortality curve for all-cause mortality after each subsequent hospitalization for HF. 2 Studies show each admission decreases a patient’s chance of survival. 1. Lee DS, et al. Am J of Med, 2009. 2. Setoguchi S, et al. Am Heart J, 2007. CURRENT HF MANAGEMENT IS INADEQUATE FOR IDENTIFYING AND MANAGING CONGESTION LEADING TO DECOMPENSATION Identifying congestion early will lead to early treatment, prevent hospitalizations and slow the progression of HF. 90% of HF hospitalizations present with symptoms of pulmonary congestion. 1,2 Post-hoc analysis of 463 acute decompensated HF patients from DOSE-HF and CARRESS-HF trials showed: 40% of patients are discharged with moderate to severe congestion. 3 Of patients decongested at discharge, 41% had severe or partial re-congestion by 60 days. 3 Congestion state of patients discharged without congestion at 60-day follow-up3 Congestion state at discharge Maintained decongestion 17% Absent or mild congestion Moderate to severe congestion 1. Adams KF, et al. Am Heart J. 2005 2. Krum H and Abraham WT. Lancet 2009 3. Lala A, et al. JCF 2013 40% 60% 24% 59% Partial recongestion Relapse to severe congestion INCREASES IN FILLING PRESSURE START THE CYCLE OF WORSENING HEART FAILURE SYNDROMES Pulmonary Artery Pressure Left Heart Failure Left Atrial Pressure Right Heart Failure Cardiac Output Right Atrial Pressure Dyspnea Fatigue Heptic Insufficiency Orthopnea Confusion Renal Insufficiency Pulmonary Edema Renal Insufficiency Peripheral Edema Peripheral Edema Adapted from Jaski BE, “Basics of Heart Failure A Problem Solving Approach” TIME COURSE OF DECOMPENSATION Physiologic Markers of Acute Decompensation Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009. PHYSIOLOGIC MARKERS OF ACUTE DECOMPENSATION Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009. CLINICAL EXAMINATION HAS LIMITED RELIABILITY IN ASSESSING FILLING PRESSURES Data from clinical evaluations has poor sensitivity and predictive value in determining hemodynamic profile Capomolla, 2005. N = 366 Variable JVP Edema Pulse Press S3 Dyspnea Rales Estimate of Sensitivity (%) Specificity (%) PPV (%) NPV (%) RAP 48 10 78 94 60 55 69 60 Cardiac Index 27 69 52 44 PCWP 36 50 13 81 73 90 69 67 60 54 57 48 Table adapted from Capomolla S, et al. Eur J Heart Failure, 2005. TIM-HF TRIAL: TELEMONITORING OF WEIGHT AND BLOOD PRESSURE DO NOT REDUCE READMISSION OR MORTALITY Randomized study of 710 patients Primary Endpoint: Total Mortality Control Group: Standard-of-care (no telemonitoring) Treatment Group: Telemonitoring of weight and BP information Results: No difference in all-cause death or HF hospitalizations Telemonitoring n = 354 (%) Usual care n = 356 (%) HR (95% CI) p All-cause mortality 15.3 15.4 0.97 (0.67-1.41) 0.87 Cardiovascular-related mortality 11.3 12.9 0.86 (0.56-1.31) 0.49 All-cause readmission 54.2 50.3 1.12 (0.91-1.37) 0.29 End Point Koehler F et al, Circulation 2011 IS THERE VALUE IN FREQUENT MONITORING OF WEIGHT, SYMPTOM AND BP TO MONITOR DECOMPENSATION? Frequent monitoring of weight, symptoms, BP has mixed results in reducing mortality and hospitalization. Author n Mean age Type of interventions Goldberg 2002 (WHARF)1 280/280 59 Wt. and symptoms Bondmass 20011 164/164 61 Wt., BP, HR and oxygen saturation Gattis 1999 (PHARM study)2 181 67 symptoms Significant reduction in mortality Rainville 19992 34 70 symptoms Significant reduction in hospitalization Massie 20011 147/147 69 Wt., vital signs and symptoms Cleland 2005 (TEN-HMS)2 426 67 Wt, BP, symptoms, ECG Barth 20012 34 75 symptoms No difference in hospitalization Riegel 20022 358 74 symptoms No difference in hospitalization Laramee 20032 287 71 symptoms No difference in hospitalization De Busk 20042 462 72 symptoms No difference in hospitalization Tsuyuke 20042 276 72 symptoms No difference in hospitalization Riegel 20062 134 72 symptoms No difference in hospitalization 1. Louis AA, et al. EJHF, 2003. 2. Clark RA, et al. BMJ, 2007. Outcome Significant reduction in mortality with no difference in readmission rates Fewer HF readmissions with reduced length of stay compared to nurse visit group No significant difference in outcome No difference in hospitalization, significant difference in mortality DOT-HF TRIAL: MONITORING IMPEDANCE WITH AUDIBLE ALERT INCREASED HF HOSPITALIZATIONS Monitoring intrathoracic impedance (OptiVol™ algorithm, Medtronic) with an audible alert did not improve mortality and increased HF hospitalizations van Veldhuisen DJ, et al. Circulation, 2011. IMPEDANCE MONITORING COMBINED WITH MULTIPLE DEVICE-DERIVED DIAGNOSTICS MAY BE USED IN RISK STRATIFICATION Study Description Implication PARTNERS-HF1 Impedance monitoring combined with device diagnostics High (> 100) fluid index threshold identified patients at a 3.9-fold risk of HF hospitalization with pulmonary congestion (p < 0.0001) HF Risk Score2 Development and validation of combining multiple device-derived diagnostic parameters into a single-dynamic HF risk score HF risk score may be used to triage patients at a higher risk for HF events in the next 30 days 1. Whellan DJ, et al. JACC, 2010. 2. Cowie MR, et al. EHJ 2013. COMBINED DIAGNOSTIC ALGORITHM • Based on 8 Diagnostic trends which are recorded daily • Individual algorithms for each trend have been used to flag significant observations from the trends in Medtronic ICDs/CRTs OptiVol VT/VF therapy AF burden Rate during AF %CRT HR Activity HRV COMBINED ALGORITHM Positive Combined Algorithm = any 2 criteria + Parameter Criterion Fluid Index AT/AF Duration V. rate during AT/AF Patient Activity Night Heart Rate HRV CRT % Pacing Shock(s) ≥60 ohm/days ≥6 hours & not persistent AT/AF AT/AF ≥24 hrs & V. ≥ 90 bpm Avg. <1 hr over 1 week ≥85 bpm for 7 consecutive days <60 ms for 7 consecutive days < 90% for 5 of 7 days 1 or more shocks OR Fluid Index ≥100 COMBINED DIAGNOSTICS TRIGGERED 1324 monthly evaluations with combined algorithm triggered ≥ 2 Diagnostic Criteria Met 43% % of evaluations when ≥2 Diagnostic Criteria Met (N = 960) 75% OptiVol Fluid Index ≥100 ohm days Met 29% 67% 28% % of triggered evaluations 62% 60% 43% 45% 30% 21% 18% 14% 15% 7% 5% 0% AF AF+RVR OptiVol Low Night Index ≥60 Activity HR Low HRV Low ICD Shock(s) Pacing% Evaluations with Heart Failure Hospitalization (Pulmonary) KAPLAN-MEIER HF HOSPITALIZATION CURVES P < 0.0001 Hazard Ratio = 5.5 (95% CI: 3.4 – 8.8) 6% 5% + Diagnostic 4% 3% 2% - Diagnostic 1% 0 0 10 20 30 Days After Diagnostic Evaluation Risk of a HF hosp. for pts with + Diagnostic was 5.5 x risk of pts w/ - Diagnostic CASE STUDY 1 HF Hospitalization with Pulmonary Congestion 30 Day Evaluation window AF+ Fluid + MECHANISMS OF WORSENING HEART FAILURE Increased pressure is the proximate cause of congestion Precipitating cause Sympathetic activation Renal and dietary Venous redistribution (fast) Fluid retention (slow) Increased L Heart Filling LAP/PAP Pulmonary capillary transudation Decompensation / hospitalization Pressures rise early and have few confounders CARDIOMEMS™ HF SYSTEM Pulmonary Artery Pressure Sensor Patient Electronics System CardioMEMS™ HF System Website CARDIOMEMS™ HF SYSTEM The pulmonary artery pressure sensor is implanted via a right heart catheterization procedure via femoral vein approach . Target location for pulmonary artery pressure sensor CHAMPION CLINICAL TRIAL: THE EFFECT OF PULMONARY ARTERY PRESSURE-GUIDED THERAPY ON HF HOSPITALIZATIONS VS. STANDARD OF CARE Patients with moderate NYHA class III HF for at least 3 months, irrespective of LVEF and a HF hospitalization within the past 12 months were included in the study. 550 Pts with CardioMEMS™ HF System Implants All Pts Take Daily readings Treatment 270 Pts Management Based on PA Pressure +Traditional Info 26 (9.6%) Exited < 6 Months 15 (5.6%) Death 11 (4.0%) Other Control 280 Pts Management Based on Traditional Info Primary Endpoint: Rate of HF Hospitalization Secondary Endpoints: Change in PA Pressure at 6 months No. of patients admitted to hospital for HF Days alive outside of hospital QOL Abraham WT, et al. Lancet, 2011. 26 (9.6%) Exited < 6 Months 20 (7.1%) Death 6 (2.2%) Other CHAMPION CLINICAL TRIAL: MANAGING TO TARGET PA PRESSURES 550 Pts with CardioMEMS™ HF System Implants All Pts Take Daily readings Treatment 270 Pts Management Based on PA Pressure +Traditional Info 26 (9.6%) Exited < 6 Months 15 (5.6%) Death 11 (4.0%) Other Control 280 Pts Management Based on Traditional Info PA pressures were managed to target goal Primary rate of with HF Hospitalization pressures byEndpoint: physicians appropriate titration of HF medications. Target Goal PA Pressures: Secondary Endpoints included: PA Pressure 15 –at35 mmHg Change Systolic in PA Pressure 6 months No. of patients admitted to hospital for HF PA Pressure diastolic 8 – 20 mmHg Days alive outside of hospital QOL mean 10 – 25 mmHg PA Pressure Abraham WT, et al. Lancet, 2011. 26 (9.6%) Exited < 6 Months 20 (7.1%) Death 6 (2.2%) Other PULMONARY ARTERY PRESSURE DATABASE Trend Data Reading Discrete data seconds Systolic: 24 Mean: 19 Diastolic: 16 Heart Rate: 81 CHAMPION CLINICAL TRIAL: PA PRESSURE-GUIDED THERAPY REDUCES HF HOSPITALIZATIONS Patients managed with PA pressure data had significantly fewer HF hospitalizations as compared to the control group. Abraham WT, et al. Lancet, 2011. CHAMPION CLINICAL TRIAL: BOTH PRIMARY SAFETY ENDPOINTS AND ALL SECONDARY ENDPOINTS WERE MET AT 6 MONTHS Primary Safety Endpoints Device-related or system-related complications Pressure-sensor failures Control (n = 280) 3 (1%) 3 (1%) Total 8 (1%)* P-value < 0.0001 0 0 < 0.0001 -156 33 0.008 Number and proportion of patients hospitalized for HF (%) 55 (20%) 80 (29%) 0.03 Days alive and out of hospital for HF (mean ± SD) 174.4 ± 31.1 172.1 ± 37.8 0.02 Quality of life (Minnesota Living with Heart Failure Questionnaire, mean ± SD) 45 ± 26 51±25 0.02 Change from baseline in PA mean pressure (mean AUC [mm Hg x days]) Secondary Endpoints Treatment (n = 270) * Total of 8 DSRCs including 2 events in Consented not implanted patients (n = 25) Abraham WT, et al. Lancet, 2011. CHAMPION CLINICAL TRIAL: THE NUMBER NEEDED TO TREAT (NNT) TO PREVENT ONE HF-RELATED HOSPITALIZATION IS LOWER VS. OTHER THERAPIES Intervention Trial Mean Duration of Randomized Follow-Up Beta-blocker COPERNICUS 10 months 33% 7 RALES 24 months 36% 7 CRT CARE-HF 29 months 52% 7 Beta-blocker MERIT-HF 12 months 29% 15 ACE inhibitor SOLVD 41 months 30% 15 EMPHASIS-HF 21 months 38% 16 DIG 37 months 24% 17 Angiotensin receptor blocker Val-HeFT 23 months 23% 18 Angiotensin receptor blocker CHARM 40 months 27% 19 CHAMPION 17 months 33% 4 Aldosterone antagonist Aldosterone antagonist Digoxin PA pressure monitoring Annualized Reduction in HF Hospitalization Rates NNT per year to Prevent 1 HF Hospitalization CHAMPION CLINICAL TRIAL: PA PRESSURE-GUIDED THERAPY IMPROVES OUTCOMES IN PATIENTS WITH PRESERVED EJECTION FRACTION HF Hospitalization Reduction (18 mo follow-up) Preserved Ejection Fraction Heart Failure (HFpEF) or diastolic HF patients represent ~50% of all HF patients Pulmonary artery pressure-guided therapy significantly reduced HF hospitalizations in HFpEF patients in the treatment group by 46% at 6 months (p<0.0001) and by 50% at 18 months (p<0.0001) The effect in HFpEF patients is even more dramatic than HFrEF or systolic patients with an estimated NNT = 2 60% Relative Risk Reduction p<0.0001 vs. control 50% 40% 30% P<0.0001 vs. control 20% 10% 0% HFrEF reduced EF (< 40%) Adamson PB,, et al.. Circ Heart Fail. 2014. HFpEF preserved EF (≥ 40%) SUMMARY: MANAGING PRESSURES TO MAINTAIN HEALTH AND MANAGE ACUTE EVENTS Unreliable, late, and indirect markers8,9 May be used in risk stratification, but not actionable4-7 Enables proactive and personalized HF management 1-3 * Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009. 1. Steimle AE, et al. Circulation, 1997. 2. Abraham WT, et al. Lancet, 2011 3. Ritzema J, et al. Circulation, 2010. 4. Abraham WT, HFSA, 2009. 5. Conraads VM, et al. EHJ, 2011. 6. Whellan DJ, et al. JACC, 2010. 7. van Veldhuisen DJ, et al. Circulation, 2011. 8. Chaudry SI, et al. NEJM 2010 9. Anker SD, et al. AHA 2010 CARDIOMEMS AT COMMUNITY HEALTH NETWORK http://www.theindychannel.com/lifestyle/health/new-implant-helping-heart-failure-patients