Effect of implanted device-based impedance monitoring with telemedicine alerts on mortality and morbidity in heart failure (OptiLink HF)

Transcription

1 Effect of implanted device-based impedance monitoring with telemedicine alerts on mortality and morbidity in heart failure (OptiLink HF) Michael Böhm, Helmut Drexler, Hanno Oswald, Karin Rybak, Ralph Bosch, Christian Butter, Gunnar Klein, Bart Gerritse, Johannes Brachmann for the OptiLink HF Study Investigators In memoriam

2 Declaration of interest -Authors received scientific support from Medtronic

3 Executive Committee Board Members Prof. Dr. med. Michael Böhm (Co-Chair) Prof. Dr. med. Johannes Brachmann (Co-Chair) Prof. Dr. med. Gunnar Klein Dr. med. Hanno Oswald Dr. med. Karin Rybak PD Dr. med. Ralph Bosch PD Dr. med. Christian Butter Event Adjudication Committee Prof. Dr. med. Markus Haass Prof. Dr. med. Wilhelm Haverkamp PD Dr. med. Stefan Stoerk Data Safety Monitoring Board Prof. Dr. med. Stefan Anker (Chairman) Prof. Karl Swedberg Prof. Hein Wellens Prof. Luigi Tavazzi Prof. Stuart Pocock Homburg / Saar Coburg Hannover Hannover Dessau Ludwigsburg Bernau Mannheim Berlin Wuerzburg Berlin Gothenburg, Sweden Maastricht, Netherlands Cotignola(RA), Italy London, United Kingdom 3

4 Disclosures Authors received grant support from the study sponsor. Authors are responsible for the design and conduct of this study, the drafting and editing of the presentation and its final contents. Statistical support for the presentation and for the study design was provided by Bart Gerritse, Medtronic Bakken Research Center(BRC) Maastricht, Netherlands, and Joao Monteiro, Medtronic plc., United States. Sponsored and funded by Medtronic (Minneapolis, MN, USA).

5 Optimization of Heart Failure Management using OptiVol TM Fluid Status Monitoring and CareLink TM (OptiLink HF Study) Primary objective Does Intrathoracic Impedance Monitoring with an Automatic Wireless Telemedicine Notification Compared to Standard Clinical Assessment Reduces All-cause Death or Cardiovascular Hospitalizations? Rationale and design of OPTILINK HF: Eur J. Heart Fail 2011;13: Trial Registration ClinicalTrials.gov ID: NCT

6 Inclusion criteria ICD Indication according to SCD-HeFT ChronicHeartFailure(HF),NYHAII III,LVEF<=35%, Optimized Medical Therapy(OMT) CRT-ICD Indication according to the ESC Guidelines(2008) Chronic Heart Failure(HF), only NYHA III, LVEF <= 35%, QRS>=120msec,LVEDD>=55mm Optimized Medical Therapy(OMT)

7 Additional Inclusion criteria Patients with potentially higher risk of cardiac decompensation/ detoriation Atleast1outof4criteria HF-related Hospitalization or IV-/Oral Diuretic Treatment or Increased BNP or Increased NT-pro-BNP within the last 12 months within last 30 days within last 30 days >400pg/ml within last 30 days >400pg/ml(<50years) > 900 pg/ml(50-75 years) >1.800pg/ml(>75years)

8 Exclusion criteria Chronic renal failure needing renal dialysis Increased serum creatinine value(> 2,5 mg/dl) within 14 days prior to enrollment Chronic Obstructive Pulmonary Disease(COPD) GOLD standard class III(severe) and IV(very severe)

9 OptiLink HF Study Design Implant Enrollment Randomization 1:1 day 3 21 after implant Access arm: telemedicine guided, no audible alert for fluid retention Control arm: standard clinical assessment, no alert for fluid retention Access arm Follow up 6 Months every 6 Months Control arm Follow up 6 Months every 6 Months Risk stratified: NYHA II vs. III, Ischemic vs. Non-Ischemic, Atrial Fibrillation, Primary vs. Secondary Prevention (VT/VF before Implant)

10 OptiLink HF Study Design Follow-Up - 18 months/patient - Extended Follow-Up, if re-consent achievable Primary endpoint - composite of all-cause mortality and CV hospitalizations Analysis -time to first event

11 Secondary endpoints - all-cause mortality - CV hospitalizations - composite of all-cause death and HF hospitalizations - HF hospitalizations - CV mortality - all-cause hospitalizations during follow-up

12 Statistical methods - Study was designed to include 1000 patients - 80% power to detect 8.4% event free rate difference at 18 months (72% control vs. 80.4% intervention, 30% relative risk reduction) - Two interims analyses at 33% and 67% of 238 expected primary endpoints (using p< and p<0.001 respectively) - Stratified log-rank test to compare between randomized arms (Stratification variables: NYHA, Ischemic status, VT/VF history, AF history, device type) - Hazard ratios(hr) and 95% confidence intervals(ci) reported from Stratified Cox proportional hazards regression models

13 Telemedicine guided Intervention Brachmann J, et al. Eur J HF. 2011;13(7):

14 Patient flow Patients enrolled (n = 1002) Randomised Patients 1:1 (n = 1002) Excluded (n = 0) Allocated to transmit fluid index alerts (n = 505) Received alert enabled system (n = 505) Did not receive alert enabled system (n = 0) Follow-up (mean 23.6 ± 14.0 months) Died (n = 59) Withdraw consent / Not completed (n = 61) Allocated to no alert transmission (n = 497) Received alert disabled system (n = 497) Did not receive alert disabled system (n = 0) Follow-up (mean 22.3 ± 13.7 months) Died (n = 63) Withdraw consent / Not cpmpleted (n = 65) Device replaced with incompatible system (n = 2) Analysed intention-to-treat (n = 505) Analysed intention-to-treat (n = 497) Mean follow-up was 22.9 ± 18.2 months 14

15 Baseline characteristics Intervention (N = 505) Control (N = 497) Age years 66.1 ± ±10.7 Male sex * 77% 82% Ischemic cardiomyopathy 54% 55% LV ejection fraction % 26.7 ± ±6.1 Ventricular tachyarrhythmia 15% 14% NYHA class II, III 20%, 80% 19%, 81% HF hospitalisation within last 12 months * 68% 60% VR-ICD, DR-ICD, CRT-D 22%, 14%, 64% 25%, 14%, 61% Hypertension 72% 71% Beta-blocker 95% 92% ACE Inhibitor or ARB 91% 94% Diuretic 95% 95% Nitrate or vasodilator 8% 8% Aldosterone antagonist 69% 70% Plus-minus values are means ± SD. *Significantly different between groups (P<0.05) 15

16 Intervention effectiveness All Intrathoracic Fluid Threshold Crossings(FTC) 1748 In N(%) of 505 intervention patients 406(80.4%) FTC transmitted via telemedicine 1324 %ofallftc* (75.7%) *FTCnottransmittedduetopatientinhospitalattimeof FTC:71(4.1%),ornotlinked to system FTC followed with Intervention acc. Protocol(CIP) 1128 % of 1324 transmitted FTC (85.2%) Patient reported worsening of HF symptoms 425 % of 1128 followed FTC (37.7%) Medical actions taken, including medication changes 529 % of 1128 followed FTC (46.9%)

17 Primary endpoint: All-Cause Death or CV Hospitalisation Intervention Control

18 All-Cause Death or CV Hospitalisation by Subgroups 18

19 All-Cause Death Control Intervention 19

20 CV Hospitalisation Intervention Control 20

21 Primary and Secondary endpoints Intervention (N = 505) Control (N = 497) Hazard Ratio (95% CI) P Value Primary composite endpoint no. (%) Death from any cause or first CV hospitalisation 227 (45.0) 239 (48.1) 0.87 ( ) 0.13 Death from any cause 59 (6.2) 63 (8.5) 0.89 ( ) 0.52 First CV hospitalisation 214 (42.4) 221 (44.5) 0.89 ( ) 0.22 Secondary endpoints Death from any cause or first HF hospitalisation no. (%) 139 (27.5) 155 (31.2) 0.81 ( ) 0.09 after adjustment on HF hospitalisation, IV diuretics prior to baseline 0.77 ( ) 0.03* First HF hospitalisation no. (%) 119 (23.6) 128 (25.8) 0.87 ( ) 0.28 Hospitalisations for HF no. (events per patient per year) 220 (0.24) 218 (0.30) ** Death from cardiovascular causes no. (%) 46 (9.1) 48 (9.7) 0.90 ( ) 0.60 * Stratified Cox Regression Model with historyof HF hospitalization (12 months) and IV diuretics (30 days) prior to baseline as covariates. For all the other endpoints the treatment arms did not differ significantly after same adjustment ** P-value based on a negative binomial model with treatment as covariate and log(follow up time) as an offset 21

22 Conclusions OptiLink HF did not show superiority of a specific intrathoracic impedance and telemedicine-based heart failure disease management strategy over standard clinical assessment. Telemonitoringdepends upon multiple factors, successful transmission, subsequent intervention/medical action, and patient adherence. These latter obstacles need to be overcome.

23 Thank you! M. Böhm Klinik für Innere Medizin III (Kardiologie / Angiologie / Internistische Intensivmedizin) Universitätskliniken des Saarlandes Homburg/Saar michael.boehm@uks.eu

24 Back up M. Böhm Klinik für Innere Medizin III (Kardiologie / Angiologie / Internistische Intensivmedizin) Universitätskliniken des Saarlandes Homburg/Saar michael.boehm@uks.eu

25 Alert-Guided Remote Management 1748 Fluid Threshold Crossings (FTC) 1324 (76%) Successful transmissions 979 (56%) Patients contacted 529 (30%) Medical action taken 455 (26%) Medication altered 25

26 Primary and Secondary endpoints Primary composite endpoint no. (%) Intervention (N = 505) Control (N = 497) Death from any cause or first CV hospitalisation 227 (45.0) 239 (48.1) Death from any cause 59 (6.2) 63 (8.5) First CV hospitalisation 214 (42.4) 221 (44.5) Secondary endpoints Death from any cause or first HF hospitalisation no. (%) 139 (27.5) 155 (31.2) First HF hospitalisation no. (%) 119 (23.6) 128 (25.8) Hazard Ratio (95% CI) P Value 0.87 ( ) 0.89 ( ) 0.89 ( ) Adjusted Hazard Ratio * (95% CI) 0.84 ( ) 0.86 ( ) 0.86 ( ) ( ) ( ) 0.87 ( ) ( ) Adjusted P Value * Hospitalisations for HF no. (events per patient per year) 220 (0.24) 218 (0.30) ** - - Death from cardiovascular causes no. (%) 46 (9.1) 48 (9.7) 0.90 ( ) ( ) 0.57 * Results from a Cox proportional-hazards regression model with history of HF hospitalisation(12 months), IV-Diuretics (30 days) and treatment arm as covariates. Moreover, this model is stratified by NYHA, ischemic status, VT/VF history. AF history and device type ** P-value based on a negative binomial model with treatment as covariate and log(follow up time) as an offset 26

27 Primary and Secondary endpoints up to 18-M-Follow-up Intervention (N = 505) Control (N = 497) Hazard Ratio (95% CI) P Value Primary composite endpoint no. (%) Death from any cause or first CV hospitalisation 194 (38.4) 205 (41.2) 0.88 ( ) 0.23 Death from any cause 30 (5.9) 41 (8.2) 0.71 ( ) 0.15 First CV hospitalisation 184 (36.4) 193 (38.8) 0.89 ( ) 0.25 Secondary endpoints Death from any cause or first HF hospitalisation no. (%) 109 (21.6) 128 (25.8) 0.81 ( ) 0.11 First HF hospitalisation no. (%) 97 (19.2) 108 (21.7) 0.85 ( ) 0.26 Hospitalisations for HF no. (events per patient per year) 142 (0.24) 172 (0.30) * Death from cardiovascular causes no. (%) 21 (4.2) 30 (6.0) 0.69 ( ) 0.19 * P-value based on a negative binomial model with treatment as covariate and log(follow up time) as an offset 27