New Devices to Monitor Heart Failure and Reduce Hospitalizations

Transcription

1 New Devices to Monitor Heart Failure and Reduce Hospitalizations Michael Shochat, BSc, MD, PhD Hillel Yaffe Medical Center, Hadera, affiliated to Technion Israel Institute of Technology, Haifa I, Michael Shochat, is The Directory of Board RSMM technology Company produced device for congestion monitoring

2 My objective today is to prove to you that we are close to achieve effective non-invasive monitoring of pulmonary congestion in chronic heart failure patients. What was the basis for more than 30 years of unsuccessful attempts to design a non-invasive device for monitoring of pulmonary congestion?

3 The Problem: Recurrent HF hospitalizations in CHF patients that occur due to lung fluid overload (pulmonary congestion). A period: Hours to 14 days B period: Some hours A period: Pulmonary congestion in progress but there are no additional specific patient s complains A B B period: Quick deterioration. Dyspnea complains. HF hospitalization. Goal: to diagnose deterioration at period A when lung fluid accumulation is small

4 Chest of patients The lungs which lies within the chest cavity are the target organ for monitoring. Direct measurements of pulmonary congestion is impossible.

5 Ohms First attempts to monitor pulmonary congestion Technologies mainly measured changes in Total Thoracic Fluid by measuring Total Thoracic Impedance (BioZ, ZOE, NICOM Cheetach Medical, Nimedical). Blood in aorta is a 10-fold better conductor than lung tissue. Therefore, such technologies mainly measure aortic impedance which makes possible calculation Cardiac Output but the signal from lung tissue is weak and is not enough sensitive to diagnose an A Period of pulmonary congestion. +1 SD -1 SD 33.5 Stable stage 18% decrease +1 SD SD At hospital admission Packer M, Abraham W.T, Mehra M et al. Utility of Impedance Cardiography for the Identification of Short-Term Risk of Clinical Decompensation in Stable Patients With Chronic Heart Failure. JACC 2006;47: White line: distribution electromagnetic wave though aorta Black line: distribution electromagnetic wave though thoracic cavity and lungs Conclusion: Individual monitoring for HF hospitalizations is impossible for significant value overlapping. Reason: Low sensitivity of the method for detection a degree of Pulmonary Congestion.

6 Pacemaker based technologies (by Medtronic and Biotronic Companies). A Ypenburg C et al. Intrathoracic Impedance Monitoring to Predict Decompensated Heart Failure. Am J Cardiol ;: Results for prediction of HF hospitalizations: sensitivity of 60% and specificity of 73% Veldhuisen D et al. DOT-HF Investigators. Intrathoracic impedance monitoring, audible patient alerts, and outcome in patients with heart failure. Circulation 2011;124: Conclusion: The use, in the present study, of an implantable diagnostic tool to measure intrathoracic impedance with patient alert did not improve outcome in the outpatient management of patients with heart failure. B Conclusion: Pacemaker based Impedance devices are not sensitive enough to detect changes in lung fluid content. Why? Two reasons. Charles C et al. Thoracic impedance measures tissue characteristics in the vicinity of the electrodes, not intervening lung water: implications for heart failure monitoring. J Clin Monit Comput 2015;29: Results of work support the hypothesis that intrathoracic impedance actually measures local tissue characteristics rather than intervening lung water (Figure A). 2. An additional problem is a parallel distribution of electromagnetic energy (Figure B).

7 New generation of surface devices Outside device has to measure a fluid content inside of the chest

8 KYMA. Innovative Body-Penetrating RF Technology (Radar Technology) How does it Work? µcor Antenna Emits RF Signals Signals Propagate through Lungs Signal Reflected from Heart Back to the Device RF electromagnetic wave (2-3 GHz) is sent into the chest wall from a generator which is putting on the chest wall. Reflecting signal is collected and analyzed. Changes in signal path delay and strength are measured to indicate changes in fluid. Harmless - Non-ionizing radiation with very low power - 1/100 of a cell phone

9 KYMA studies Comparison to Invasive Thermodilution 7 sheep Pilot study (Presented at ESC meeting 2014). Correlation between Kyma s RF Lung Water to Extra Vascular Lung Water (EVLW): R = 0.96 GLP study in 15 sheep (Presented at HFSA 2014). Correlation between Kyma s score to EVLW: R = Calculated Accuracy of RFLW: σ= 50-60ml Now: Trial Design (Israel: Kaplan MC) CHF patients (Ongoing, n>30) admitted with pulmonary edema secondary to Acute Decompensated HF. Thoracic fluid trends followed during dehydration process. Measurements were compared to an ADHF Index (Clinical assessment, Lung auscultation, Difficulty breathing)

10 Sensible Medical ReDS Technology CE Marked & FDA Cleared (510k) See-through-wall (Radar Technology. 3 GHz RF electromagnetic wave) Original Technology Adapted for Clinical Application Military see-through-wall technology SensiVest ReDS TM Technology

11 Sensible Medical Studies Number of Heart Failure Hospitalizations (N = 50) % Reduction 2 78% Increase 9 0 Pre-clinical: ReDS vs. CT Correlation Pre vs. ReDS: P = 0.01 Post vs. ReDS: P = ReDS Guided Management Reduced the Number of Heart Failure Hospitalization Over 90 Days 2

12 Motion Motion Non Invasive Monitoring of Patients with Heart Failure by Objective Indices of Dyspnea Shmuel Rispler, Yakov Tsibulsky, Amir Landesberg Cardiac decompensation leads to graduate increase in respiratory effort which is reflected in chest wall dynamics The respiratory dynamics were measured non-invasively by 3 miniature motion sensors that were attached to HF patient's thorax and epigastrium during their hospitalization The measured respiratory signals were quantified and a new parameter excessive effort index (EEI) was defined At Admission At Discharge Time [sec]

13 EEI at discharge VS respiratory rate at discharge as predictors for re-hospitalization within the first 30 days 17 patients NYHA=3-4 EF=25.3±7.8 [%] BNP=1566 ±1182 [pg/ml] All patients who had an EEI less than 0.4 were not re-hospitalized during 30 days post hospital discharge This non invasive, simple to use and simple to understand technology allows to quantify dyspnea and to provide physicians with a tool for a better decision making before discharge

14 Parametric Electrical Impedance (pei TM ): A Novel Method that Accurately Identifies Early Hemodynamic Changes, Prior to Development of Pulmonary Congestion Andre Keren 1,2, Shay Faitelzon 2, Shimon Abboud 3, Lisa Deutsch 2, Israel Gotsman 1, Gerasimos Filippatos 4, Philip B. Adamson 5 1 Heart Institute, Hadassah-Hebrew University, Israel 2 Research and Development Department, CardioLogic Innovations Ltd, Israel 3 Department of Biomedical Engineering, Tel Aviv University, Israel 4 Department of Cardiology, Athens University Hospital Attikon, Greece 5 Oklahoma Heart Hospital, Oklahoma Foundation for Cardiovascular Research, USA Correspondence: Prof. Andre Keren MD Affiliated with Division of Cardiology, Hadassah University Hospita,l Jerusalem Director Heart Failure Services, Clalit Medical Organization, Jerusalem Medical Director Assuta Heart Institute, Hashalom, Tel Aviv. Medical Director CadioLogic Innovations Ltd, Neveh Ilan, Israel [email protected]

15 MAJOR RESULTS IN A Resistivity Changed Concomitantly with LVEDP GR1 Sheep 1 N=24 Sheep 2 N=23 Sheep 3 N=20 Sheep 4 N=41 Sheep 5 N=9 Sheep 6 N=17 Mean LVEDP RESISTIVITY Resistivity vs LVEDP r= p<.0001 r= p<.0001 r= p<.0001 r= p<.0001 r= p<. 001 r= p<.0001 r= SD ±0.06 R=0.91 SD±0.06 GR2 Sheep 1 N=13 Sheep 2 N=17 Sheep 3 N=15 Sheep 4 N=16 Sheep 5 N=17 Mean Resistivity vs LVEDP r= <.0001 r= p<.0001 r= p<.0001 r= p<.0001 r= p=.0004 r= SD ±0.05 CardioLogic Innovations 2015, proprietary information 15

16 MAJOR RESULTS Time Relationship of % Changes in the 3 Main Parameters Intrathoracic Blood Volume (ITBV) Extravascular Lung Water (EVLW) CardioLogic Innovations 2015, proprietary information 16

17 RSMM Company technological solution 1. Transverse distribution of electromagnetic field A B. A B 2. Transthoracic Impedance A-B (TTIAB) = Chest Wall Impedance1 (CWI1) + Lung Impedance (LI) + Chest Wall Impedance2 (CWI2)

18 RSMM Start Up Company Technology Putting additional 2 electrodes on front and back side of the chest wall enables calculation of parasitic CWI1 and CWI2 and operate with net Lung Impedance. Sensitivity for detection small changes in Lung Fluid increases more than 25 times.

19 Lung Impedance (LI) from initial in % Gr.2 Treatment start according clinical assessment Randomization Gr.1 Treatment start according LI Usefulness of Lung Impedance (LI)-guided pre-emptive therapy to prevent pulmonary edema during STelevation myocardial infarction and to improve long-term outcomes (In ICCU)* Admission Discharge from hospital after 5.5 days. LI -3% 750 STEMI patients. No clinical or X-ray signs of congestion LI -14% In 285 (38%) patients. No complains LI -17% No congestion LI -18% First crepitation. No complains Discharge from hospital after 7.9 days. LI -15% 0 9 h 13 h LI -27% Start complains on dyspnea. Mild to moderate pulmonary congestion 18 h Days in hospital 5.5± ±5.4 p< Number deaths in hospital 0 7 p< 0.01 Mortality within 6 years Follow Up 7.0% 19.7% p< 0.01 New CHF development within 6 years FU 18.3% 37.3% p< 0.01 In hospital period Results: Group 1 Group 2 *Shochat M et al. Usefulness of lung impedance- LI -36% Moderate to severe pulmonary congestion 25 h 5.5 d 7.9 d guided pre-emptive therapy to prevent pulmonary edema during ST-elevation myocardial infarction and to improve long-term outcomes. Am J Cardiol 2012;110:190-6

20 Survival Hospitalizations Randomized Impedance HF trial. 256 CHF out hospital patients (1:1). Mean = 48 months Follow Up. Monitoring group was treated according Lung Impedance and Control group according clinical assessment A Control group B C C Monitoring group P < P < P < All cause hospitalizations Cardiovascular hospitalizations Heart Failure hospitalizations Monitoring group D E F Control group All cause mortality Cardiovascular mortality Heart Failure mortality Follow up period (months) Follow up period (months) Follow up period (months) A - All cause hospitalizations B Cardiovascular hospitalizations C Heart Failure hospitalizations D - All cause mortality E Cardiovascular mortality F Heart Failure mortality Monitored group Control group Cumulative rate of hospitalizations and survival analyses during follow up period

21 Thank you