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Predicting Acute HF Events in CRT Patients: Results & Perspectives

This luncheon panel will discuss recent advances in predicting acute heart failure events in patients with cardiac resynchronization therapy (CRT), including results and perspectives on the topic.

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Predicting Acute HF Events in CRT Patients: Results & Perspectives

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  1. LUNCHEON PANEL II: PROGRESSI IN CRT (ADVANCES IN CRT) Come predire eventi acuti HFnei pz CRT: risultati e prospettiveHow to Predict Acute HF Eventsin CRT pts: Results & Perspectives Maurizio LUNATI, MD Cardiology Dptm – Electrophysiology Ospedale Ca’ Granda Niguarda, MILANO, Italy

  2. Devices for HF … “Preventive CRT” & CRT devices

  3. S Y M P T O M S Abnormal lung function Respiratory muscle dysfunction Other factors  RV + RA pressure •  Hydrostatic pressure •  Oncotic pressure •  Permeability • Lymphatic drainage capacity • Alveolar-capillary membrane integrity Increase PA pressure Increased PCWP (congestion ) MitralRegurgitation Abnormal LV function (Syst. &/or Dias.) WHY to “monitor HF” in CRT pts ? Symptoms = Tip of Congestion Iceberg in HF Systemic congestion(JVD, edema) Dyspnea Alveolar edema Redistribution in pulmonary vascular bed+ Interstitial edema  LA and LV diastolic pressure LVDP + Impaired volume regulation

  4. WHY predict acute HF events is important … With each event, myocardial injury (as shown by Tn release) might occur, contributing to the progressive ventricular dysfunction and dilatation Acute event Functional Capacity Time Jain P, Massie BM & al. Am Heart J 2003; 145: S3-S17

  5. Gavazzi A. Lo scompenso cardiaco (p. 139). Editors “Scripta Manent” (2002) To-date tools to “Monitor HF” • Signs & symptoms • Body weight • Natriuretic peptides (BNP, NT-proBNP) • Hemodynamic sensors • Data from implantable devices • (ICD, CRT, CCM, …)

  6. Several NON-INVASIVE variables have been commonly used to assess the clinical & functional status in HF pts, but generally they are NOT a lot usefulto predict the clinical evolution, because: influenced by psychological or subjective factors (NYHA class, dyspnea, QoL) useful to describe the status @ FU time only (echocardio, 6’ WT, ergometric test) predict worsening with a very short predictive delay(body weight, edema) Are clinical & instrumental variables USEFUL to accurately track HF ?

  7. The way towards an acute HF event … 100% Edema Weight increase Dyspnea under effort Dyspnea at rest Ortopnea 80% 60% % cumulative of pts who experienced 40% 20% 0% 35 30 25 20 15 10 5 0 Days (before HFH) Schiff & al. Am J Med 2003; 114: 625

  8. Data today monitored (implemented in therapeutic implantable devices) • Heart Rate Variability • Physical activity • Fluid accumulation (impedance measurement) • Minute ventilation • … ?

  9. HRV: SDAAM, nocturnal HR & physical activity [ 3 months before HFH ] SDAAM standard deviation of 5 min median atrial-atrial intervals sensed by the device n = 34 pts Adamson P. & al. Circulation 2004; 110: 2389-94

  10. Better Worse Fluid accumulation monitoring with OptiVol “Dry” lungs  High impedance “Wet” lungs  Low impedance

  11. OptiVol: MAIN findings Yu CM & al. Circulation 2005;112: 841-8 33 pts, NYHA class III / IV, FU: 20 ± 8.4 M Predictive delay:15.3 ± 10.6 days Sensitivity = 76.9 % False Positives = 1.5 unnecessary visits / year / pt Vollmann D & al. Eur Heart J 2007 • 373 CRT-D pts, median FU 4.2 M, Alert = ON in all pts • Reported all clinical data (HF) vs telemetry of CRT-Ds • Sensitivity & PPV: 60%(33/53, adjusted by multiple events/pt) • 20 alerts not given upon “true HF events” Ypenburg C & al. Am J Cardiol 2007 • 115 CRT-D pts; FU time 9±5 M; Alert = ON (empiric threshold 60 omega) • HF clinical data retrieved in case of ALERT heard by pt • ROC curve  optimal alert threshold = 120 omega - sensitivity 60% - specificity 73%

  12. (N=430) (N=102) Usefulness of the alert in clinical practice 67 % of True Detection of Relevant Clinical Events Monitoring Intrathoracic Impedance with an Implantable Defibrillator Reduces Hospitalizations in Patients with Heart Failure Catanzariti D, Lunati M, Landolina M, Zanotto G, Lonardi G, Iacopino S, Oliva F, Perego GB, Varbaro A, Denaro A, Valsecchi S, Vergara G; Italian Clinical Service Optivol-CRT Group Pacing Clin Electrophysiol. 2009 Mar;32(3):363-70 Time to cardiac death, heart transplantation and heart failure hospitalization Events of reduced Impedance and associated clinical events. unexplained or untreated Alerts: 0.25 per patient-year The ICD reliably detected Clinical Events and yielded low rates of unexplained and undetected events. The alert reduces the number of HF hospitalizations by allowing timely detection and therapeutic intervention

  13. Risk stratification by device diagnostic trends Implantable CRT device diagnostics identify patients with increased risk for heart failure hospitalization Perego GB, Landolina M, Vergara G, Lunati M, Zanotto G, Pappone A, Lonardi G, Speca G, Iacopino S, Varbaro A, Sarkar S, Hettrick DA, Denaro A; Optivol-CRT Clinical Service Observational Group. J Interv Card Electrophysiol. 2008 Dec;23(3):235-42 558 HF patients Decreased intra-thoracic impedance is associated to a 36% increased risk for HF hospitalization in a population of HF patients treated with CRT. Other device parameters including patient activity, VT episodes, NHR and HRV are prognostic predictors of Acute HF events and can be associated to intra-thoracic impedance to better evaluate the risk of Acute HF events.

  14. Efficacy of the remote follow-ups "Remote Monitoring of Patients with Biventricular Defibrillators Through the CareLink System Improves Clinical Management of Arrhythmias and Heart Failure Episodes”, M. Santini, R.P. Ricci, M. Lunati, M. Landolina, G.B. Perego, M. Marzegalli, M. Schirru, C. Belvito, R. Brambilla, G. Guenzati, S. Gilardi, S. Valsecchi J Interv Card Electrophysiol 2009 Jan;24(1):53-61 The remote monitoring systems (CareLink network) may increase the efficacy of the OptiVol algorithm by allowing the early detection and remote review of clinical events

  15. An expert system with the aim to: Continuously monitor the pt’s functional status with multi-sensor capability Predict acute HF events to prevent the (probable) related hospitalizations

  16. Daily & weekly analysis of variables PhD = software (Rules & Meta-rules) to interpretate the trend of variables (daily & weekly basis) MV under EFFORT phases PhD alert ( rule of MV rest  ) MV in RESTING phases Physical Activity (Workload) Stable Workload, MV rest progressive  At the end of this FU, the pt was hospitalized for HF

  17. System Tuning & “reaction” times SUB-CLINICAL phase of ACUTE episode CLINICAL phase AUTOMATIC “TUNING” of PhD function (about 1M) MV exer MV rest Workload Page E, Cazeau S & al. Europace 2007; 9: 687-93

  18. X: rule W O: rule MVA +: rule MVR 20 days --------: ALERT on meta-rule MVR --------: ALERT on meta-rule W MV exer W MVrest Clinical case #1 (impl ►M3): step-by-step worsening 8 9 5 • Post-implant: pt OK • Pt starts moderate W • MV-exer increases (physiolog.) • Pt increases level of W • MV-exer increases • MV-rest increases (compensation) • Pt worsens, reduces W • MV-exer decreases, not a lot … • MV-rest not back to prev. values; • slow drifting increase … • 10. HFH … 3 7 4 9 2 6 9 1 10 Last 90 days

  19. INCLUSION / IMPLANT FU M4 FU M7 Every 3M … FU M1 • fu ICD • BNP • QoL • fu ICD • BNP • QoL • fu ICD • BNP • QoL • fu ICD • BNP • QoL PhD = ON (ALL pts) M2 M3 M5 M6 M8 M9 Next step: prospective evaluation • Trial under submission (2H-2009 / 2010) • Size: 430 CRT-D pts in 50 Centers among Europe, US & Canada • 1-ary endpoint: % sensitivity of PhD(MV & workload) • Monthly Phone Call: to appropriately track ALLclinical events

  20. Tools for HEMODYNAMIC monitoring RVDP RVSP HR Adamson P & al. Clin Cardiol. 2007; 30: 567-75 Wadas TM. Critical Care Nurse 2005; Vol. 25 n. 5: Cover Article CHRONICLE (Medtronic)investig. device; (IHM = implantable hemodynamic monitor)

  21. Mechanical vibrations & sonR • The mechanical vibrations generated by the system “myocardium + blood” might be detected by a sensor (sonR), a micro- accelerometer realized in the tip of a standard permanent pacing lead

  22. sonR & FU: trend of contractility • Pt included in the CLEAR trial M, 78 y old; idiopathic dilated CMP, NYHA III implant of CRT-P (NewLiving CHF) in Nov. 2005 sonR values: 24h post-implant (green), vs last 24h before M1 FU visit (red) M1 FU visit: • Peripheral edema • Reduction 0,8►0,4 sonR ampl. • Hospitalization (8 days) 0.4g @ M1 0.8g @ Implant

  23. 3 sonR & FU: trend of contractility sonR (g) Last month 0,7g 1 0,65g 0,63g Last week 0,5g 2 Last 24h 0,4g HFH (8 d) Diuretics Time Follow-up M3 Stable situation sonR (0,65g) Peripheral edema sonR (0,7g►0,4g) Discharge sonR (0,4g►0,65g) Trend amplitude sonR signal • Post-implant sonR value restored … • … and maintained at 3M FU visit 0.65 g M1+1wk 0.63 g M3

  24. HRV: ANS activity (pNN-50; SDAAM; etc.) The key for future: multi-sensor systems Minute Ventilation (MV): respiratory dynamics Physical activity (G): workload sonR sensor: contractility ( LVdP/dt)

  25. & Info on functional status MV exercise MV rest Workload (G) Tomorrow: automatic ALERTS Tomorrow: (contractility  endocardial acceleration) The evolution of PhD function ( « Advanced PhD » )

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