LIVE WEBINAR Boston Scientific External Use. Show and Distribute CRM AA-June 2017

Transcription

1 LIVE WEBINAR 1

2 LIVE WEBINAR AGENDA 2

3 The use of diagnostics in the management of HF Patients Prof. Martin Cowie 3

4 The patient journey is complex 4

5 Remote monitoring Initially, telephone monitoring of patients Then, patient-initiated monitoring using stand alone equipment More recently, data can be transmitted often without patient needing to do anything usually from implanted device Some devices implanted for therapeutic indications Monitoring-only devices now also available 5

6 What can be monitored? Remotely In Person Symptoms Yes Yes Body weight Yes Yes Pulse rate Yes Yes Blood pressure Yes Yes Oxygen saturation Yes Yes ECG Yes Yes Patient activity Yes Yes Heart rate variability Yes Yes Arrhythmic episodes Yes Yes Transthoracic impedance Yes Yes Right ventricular or pulmonary artery pressure Yes Yes Left atrial pressure Yes Yes 6

7 What is the rationale? Frequent monitoring by a health professional may enable earlier intervention to treat deterioration in e.g. heart failure The intervention can be: Reminders about lifestyle and diet Advice about medication (e.g. adjustment of diuretic dose) Recall for early clinic review (primary or secondary care) Home visit Urgent hospitalisation Remote monitoring usually (but not always) builds on self-monitoring, and helps reinforce educational messages BUT Who, how and what to monitor?? 7

8 What has been shown to date? 8 8

9 Which components are effective? All cause mortality HR 0.88 [ ] P=0.08 No heterogeneity HF hospitalisation HR 0.77 [ ] P< No heterogeneity Inglis SC et al. Eur J Heart Failure 2011; 13: (Abridged Cochrane Review) 9

10 Which components are effective? All cause mortality HR 0.66 [ ] P< No heterogeneity HF hospitalisation HR 0.79 [ ] P=0.008 No heterogeneity Inglis SC et al. Eur J Heart Failure 2011; 13: (Abridged Cochrane Review) 10

11 TELE-HF Trial: Weight Changes and HF Symptoms Randomized study of 1653 patients Primary endpoint: Readmission for any reason or death from any cause within 180 days after enrollment Control group: Usual care (no telemonitoring) Treatment group: telemonitoring of symptoms and weight by telephone-based interactive voice-response system (NB 15% never called; 55% of those who did had stopped by 180 days) Result: No difference in number of deaths, readmissions, or days in hospital Chaudhry SI et al. N Engl J Med 2010; 363:

12 TIM-HF Trial: Weight changes and BP Information Randomized study of 710 patients Primary Endpoint: Total Mortality Control Group: Standard-of-care (no telemonitoring) Treatment Group: Telemonitoring of weight and BP information No difference in all cause death No difference in CV death or HF hospitalisations NB 50% NYHA II; Average duration of HF: 6.7 years; 95% ACEI or ARB; 92% BB Koehler F et al. Circulation 2011; 123:

13 BEAT-HF 1437 patients aged 50, hospitalized for HF in 6 academic centres in California Randomized 1:1 to usual care or remote patient monitoring 180 days follow-up Health coaching telephone calls + telemonitoring of BP, HR, symptoms and weight Nurse telemonitoring centre No adverse events No difference in 30 or 180 day readmission rate or 180 day mortality Small difference in QOL at 180 days (4 points on MLHFQ: p=0.02) Ong MK. JAMA Intern Med 2016; 176:

14 Implanted systems (The concept is simple) 14

15 Indicators of possible HF decompensation 15 Heart Rate Variability (ms) Night Heart Rate (BPM) Patient Activity (minutes/day) Days Relative to Hospital Admission Adamson PB. Circulation 2004; 110: Circulation. 2004;110:

16 Don t rely on just one parameter certainly not OptiVol TM Alert HF hospitalisation 79% P=0.02 OptiVol TM is a trademark of Medtronic 16 DOT-HF: Van Veldhuisen D et al. Circulation 2011; 124:

17 Better validated risk prediction A multi-parameter algorithm 17 Cowie MR et al. EHJ 2013; 34:

18 REM-HF Southampton Royal Brompton Guy s and St Thomas Liverpool Newcastle Blackpool Manchester Leeds Leicester Morgan JM et al. Eur Heart J 2017 (e-pub ahead of print) DOI: 18

19 Primary endpoint neutral All-cause mortality or CV hospitalisation HR 1.01 [ ] P=0.87 (adjusted for site and device type) Morgan JM et al. Eur Heart J 2017 (e-pub ahead of print) DOI: 19

20 REM-HF ALL secondary enpoints: NEUTRAL 20

21 Implanted monitoring-only devices 21

22 Cumulative HFR Hospitalisations Over entire randomized follow-up period 6 months: 83 hospitalisation in 54 patients versus 120 hospitalisations in 80 patients RRR 30% (P<0.001) 22 Abraham WT et al. Lancet 2011; 377:

23 What does the future look like? 23

24 HeartLogic TM concept Yi Zhang, PhD 24

25 HeartLogic Sensors The HeartLogic TM sensors target the different aspects of heart failure pathophysiology and are associated with common signs and symptoms of heart failure Heart Sounds S1 Ventricular contraction status S3 Early diastolic filing Thoracic Impedance Fluid accumulation and pulmonary edema Unique to BSC Respiration Rapid breathing and reduced tidal volume (shortness of breath) Heart Rate Indicator of cardiac status Unique to BSC Activity Global patient status and fatigue 25

26 HeartLogic Algorithm Sensor Measurements Heart Sounds S1 & S3 Impedance Thoracic Respiration Rate & Volume Activity Time Spent Active Heart Rate Night time Assess patient risk for worsening HF Evaluate changes from patient baseline Combined into a single, simple index with alert Daily Index Values Physician programmable threshold Alert issued when index crosses threshold 26

27 Benefit of Multi-Sensor Approach: Two observed cases Patient A Patient B HeartLogic Alert before a HF Event Impedance-only alert with NO event HeartLogic S3 Which patient had a Heart Failure Event? S1 Respiration Rate Thoracic Impedance Each tick mark is a month 27

28 Benefit of Multi-Sensor Approach: Two observed cases Patient A Patient B HeartLogic TM Alert before a HF Event Impedance-only alert with NO event HeartLogic TM S3 S1 Respiration Rate Thoracic Impedance Each tick mark is a month 28

29 LATITUDE TM : Heart Failure Management Report 29

30 DISCUSSION: The potential of Advanced Diagnostics to improve on the disappointing outcomes of earlier HF management studies Prof. John Morgan 30

31 MultiSENSE Study Prof. Martin Cowie 31

32 The potential of HeartLogic GOAL: Develop an alert algorithm for the early notification of worsening heart failure by combining information from a diverse set-of implanted sensors chosen to target the different aspects of heart failure pathophysiology associated with common signs and symptoms of worsening heart failure 32

33 MultiSENSE Trial Design International, multi-center, non-randomised,clinical study designed to develop and prospectively evaluate a multi-sensor index and alert for the early detection of worsening heart failure 33 Boehmer J et a. JACC HF 2017; 5:

34 MultiSENSE Study Design Investigational software was downloaded into cardiac resynchronisation defibrillator devices (CRT-D) to enable high resolution data collection Treating clinicians, investigators and clinical events committee members were blinded to the investigational sensor data The study data were chronologically allocated into: Development Set Test Set Used to develop the composite index and alert algorithm Sequestered and used for independent validation of algorithm performance Boehmer J et a. JACC HF 2017; 5:

35 Alert development Development data set: 500 patients with SRD-1 conversion Median follow-up time 324 days 64 patients (12.8%) with HF events (HFE) 127 total HFEs Sensor feature trends assessed for meaningful associated with HFE Boehmer J et a. JACC HF 2017; 5:

36 Primary endpoints 36 Boehmer J et a. JACC HF 2017; 5:

37 Next steps: further evidence MANAGE-HF Multiple cardiac sensors for management of HF FDA approved protocol Poised to start PHASE 1: Optimisation of HeartLogic clinical integration & alert management (N=200) PHASE 2: Assess impact on patient outcomes (death and HF hospitalisations) (N= ) 37

38 Discussion: What is the potential of HeartLogic TM in preventive therapy? 38

39 Interactive Q&A with the audience 39

40 Conclusions The value of Remote Monitoring to manage HFs patients in a way that improves outcomes remains unclear The results of multiple studies have been generally disappointing either because of sensitivity and specificity issues or definition of optimal clinical practices HeartLogic TM utilizes multiple physiologic measurements and an algorithm that promises to offer high sensitivity and specificity. HeartLogic TM has shown in MultiSENSE study to be able to predict HFEs with 70% sensitivity, unexplained alert rate of 1,47 per patient-year at a Median Time of 34 days prior to a HFE Now we need to learn how best to use it and show that it can deliver the goal of better HF management 40

41 Disclaimer Caution: The law restricts this device to sale by or on the order of a physician. Indications, contraindications, warnings and instructions for use can be found in the product labeling supplied with each device. Information for the use only in countries with applicable health authority product registrations. Information not intended for use or distribution in France." 41