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31 MARZO 1 APRILE 2017 COMO

Aritmologia

MONITORAGGIO REMOTO

DEI DISPOSITIVI CARDIACI IMPIANTABILI

G. B. PeregoIstituto Auxologico Italiano

Ospedale S. Luca - Milano

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Parthiban et. Al.. JACC 2015; 65: 2591-2560

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Remote Patient Management

Results of Randomized Studies

Remote Control results in patient care that is non-inferior to classical FU with in-office visits

Remote Monitoring results:

➢earlier clinical decision-making

➢ less inappropriate shocks and improved device

longevity

➢“hard” endpoints

❖Reduction of health care utilization

❖Decrease of urgent hospital admissions

❖Reduction in the length of cardiovascular hospitalizations

❖Decrease of mortality in ICD patients with heart failure

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Parthiban et. Al.. JACC 2015; 65: 2591-2560

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(J Am Coll Cardiol 2011;57:1181–9)

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Circulation. 2012;125:2985-2992

Randomized, multicenter, prospective study

RM vs. Conventional Follow up

N = 100/100; F up 18 mos.

0.590.38

0.21

4.40

0.930.73

0.20

5.74

0

1

2

3

4

5

6

urgent cardiac or device-related in-hospital visits

(Primary endpoint)

urgent visits related toepisodes of worsening of HF

(Secondary endpoint 1)

urgent visits not related toepisodes of worsening of HF

(Secondary endpoint 2)

Planned and urgenthospital admissions for cardiac

or device-related events(Secondary endpoint 3)

An

nu

aliz

ed

Rat

e P

er

Pat

ien

t Y

ear

Remote Arm

Standard Arm

p=0.001 p<0.001p=0.398

p<0.001

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Parthiban et. Al.. JACC 2015; 65: 2591-2560

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European Heart Journal doi:10.1093/eurheartj/ehs425

«The proportion of patients whose battery was depleted at the end of the study

was .50% lower in the active than in the control group.»

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• chronic heart failure lasting for at least 3 months

• New York Heart Association (NYHA) functional class II or III

• left ventricular ejection fraction 35% or less

• indication for dual-chamber ICD or CRT-D treatment according to European guidelines

Lancet 2014; 384: 583–90

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Parthiban et. Al.. JACC 2015; 65: 2591-2560

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Parthiban et. Al.. JACC 2015; 65: 2591-2560

All cause mortality

All-cause mortality data were available for 7 RCTs, comprising 4,932 patients. The odds

ratio for mortality with RM was not statistically significant from IO follow-up.

Exclusion of the IN-TIME trial reduced the trend toward reduced mortality with RM and

eliminated between-study heterogeneity

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Limits & pitfalls of RCTs

Single vendor:Are results technology-specific?

Strictly defined protocols:Active groups: are protocols applicable in real life ?

Control groups: do we unterestimate the benefit ?

Relatively small numbers

Impact of nurse counselling

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(Circulation. 2010;122:2359-2367.)

“The decision to place a patient in the remote follow-up system is made by the implanting

physician at the time of device implantation or at the post implantation follow-up clinic visit”

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(Circulation. 2010;122:2359-2367.)

“To assess for possible physician referral bias that may influence the decision to refer a patient for

networked versus traditional device follow-up, patients followed on and off the network were further

compared by analysis of residential postal zip code. United States census data were then accessed to

determine and compare economic, racial, and educational status”

Networked vs. non networked

• White

• Rural

• Same age and sex

• Same educational level

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(Circulation. 2010;122:2359-2367.)

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(Circulation. 2010;122:2359-2367.)

Sensitivity analysis for ICDs cohort.

Scenarios of proportionate risk demonstrate that only if the risk factor burden in

the nonnetworked population were 5 times that of the networked patients would

imbalance in these baseline factors reproduce the mortality difference observed

(scenario 7; HR, 0.57).

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Circ Arrhythm Electrophysiol. 2015;8:1173-1180

A limited data set constructed from Boston Scientific ALTITUDE Registry and National

Cardiovascular Data Registry ICD Registry between January 2006 and March 2010

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Circ Arrhythm Electrophysiol. 2015;8:1173-1180

A limited data set constructed from Boston Scientific ALTITUDE Registry and National

Cardiovascular Data Registry ICD Registry between January 2006 and March 2010

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Circ Arrhythm Electrophysiol. 2015;8:1173-1180

Effect of RPM Use on Survival and Rehospitalization at 3-Year Follow-Up

(Patients Without RPM Use Are the Reference)

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Aim:

To better understand the influence of RM on outcomes,

Hypothesis:

Survival would be better in patients with greater RM use and should apply to all

types of CIEDs: patients with pacemakers (PMs) who have less cardiovascular

risk as well as those with implantable cardioverter-defibrillators (ICDs) and

cardiac resynchronization therapy (CRT) with pacing/defibrillation capability

(CRT-P/CRT-D).

Method:

We tested this in a cohort of CIED patients, all receiving automatic RM devices,

by leveraging “big data” from a nationwide RM system generated proprietary

database, which collects comprehensive longitudinal follow-up data

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JACC 2015; 65 (24): 2611-2613

More than one-half (53%) of patients implanted with RM-capable devices never

used the RM functionality.

There was a survival advantage for those patients who used RM, and increased

use of RM with weekly transmissions more than 75% of the time was associated

with a greater survival advantage compared with those who used RM less

frequently. >>> Threshold effect ?

These results were consistent across all device types including PMs, ICDs, and

CRT devices

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"Big Data" versus RCTs

Might be "multi vendor"

Real life population

Sustainable protocols

Affordable organization

Longer follow up

Confounding variables

Selection bias

Biased cross-over

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Istituto Auxologico Italiano

PA Pressure Sensor on Catheter Delivery System

CardioMEMS™ HF System

CardioMEMS™ Patient Electronics System

120cm4.5cm

Image from Merlin.net™ PCN

75

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CardioMEMS Wireless Heart Failure Sensor

Regression Plot of Sensor vs. SG Mean

Pressure Measurements for All Patients

R2 = 0.9788

0

10

20

30

40

50

60

70

0 20 40 60 80

SG reading (mm Hg)

Sen

sor

read

ing

(m

m H

g)

Clinical evaluation has demonstrated safety, stability and excellent correlation to swan-ganz catheter

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COMPASS –HF:

Acute decompensation prediction and ePAD

Zile ML et al.. J Cardiac Fail 2011;17:282e291

The product of small increases in pressure that occur over an extended period of time (PT) is the pressure-based hemodynamic factor most closely associated with the transition to acute decompensated heart failure.

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COMPASS –HF: average ePAD

Stevenson LW et al.. Circ Heart Fail 2010;3;580-587

(…)many patients with advanced HF live on a plateau of high filling pressuresfrom which later events occur. This risk is progressively higher with higherchronic ambulatory pressures. It is not known whether more targetedintervention could maintain lower chronic ambulatory pressures and betteroutcomes.

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CHAMPION Trial: By Targeting Pressure Ranges and Titrating Medications, Overall PAPs Can Be Reduced

Compared to the control group, patients managed with PAP had persistently lower mean PA pressures over the treatment period

CHAMPION Trial: PAP Mean Change from Baseline

Abraham WT, et al. Lancet, 2011.

PA

Me

an

Pre

as

ure

AU

C (

mm

Hg

-Da

ys

)

-220

-200

-180

-160

-140

-120

-100

-80

-60

-40

-20

0

20

40

60

80

100

Days from Implant

0 30 60 90 120 150 180

p = 0.0077

Treatment (-155.7 mmHg-Days)Control (33.1 mmHg-Days)

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28% reduction

37% reduction

CHAMPION Trial: PAP-Guided Therapy

Reduces HF-Related Hospitalizations

CHAMPION Trial

Reduction in HF-related Hospitalizations

p<0·0001

Abraham WT, et al. Lancet, 2011.

Patients managed with

PAP information had

significantly fewer

hospitalizations as

compared to the

control group

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PAP tele HF study

27.8±10.2

24.0±8.0

p<0.001

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Conclusioni