The Potential of Telemedical Devices to Monitor and Enhance Patient Health:

-----------------------------------------Focus on Cardiovascular Disease

Robert C. Bourge, MDProfessor of Medicine, Radiology, and Surgery

Director, Division of Cardiovascular DiseaseThe University of Alabama at Birmingham

<bbourge@uab.edu>

TeleMedicine Patient Access

Physically remote from a nurse or doctor Actively engaged in monitoring health

‘Long-distance’ communication link Telephone / Wired or Wireless Broadband Internet (GPS)

Monitoring methodology Questionnaires, Verbal / Video Non-invasive – patient/carer/technician operated Implanted - +/- patient operated

Patient Interaction / Feedback Patient Directed – Per Patient Specific Rx Verbal / Video – Health Professional Directed Automated – Per Patient Specific Rx

Adapted for J.G.Cleland, 2009, with permission

ImplantedDevice Diagnostics

Patient activity h/day

AT/AF total h/day

V. rate during AT/AF, bmp

Average V. rate, bpm

Heart Failure Management Report

OptiVol fluid index

Thoracic impedance

Heart Failure Management Report

Acute Exacerbations Contribute to the Progression of the Heart Failure

TimeTime

Cli

nic

al S

tatu

sC

lin

ical

Sta

tus

Acute eventAcute event

With each event, hemodynamic With each event, hemodynamic alterations/myocardial injury alterations/myocardial injury contribute to progressive contribute to progressive ventricular dysfunctionventricular dysfunction

Heart failure progression may be accelerated by the aggressive therapiesinitiated during hospitalization

Jain P et al. Jain P et al. Am Heart JAm Heart J. 2003;145:S3-S17. . 2003;145:S3-S17.

Congestive Heart Failure

Congestion (as measured by increased intracardiac

end diastolic pressures)

Symptoms and Survival

Physiological Premise of Monitor Guided Care (1)

-21-21 -14-14 - 7 - 7 DaysDays

ReactiveReactiveProactiveProactive

0 0

SymptomsSymptoms

Pressure ChangesPressure Changes

Heart Failure EventHeart Failure Event

Physiological Premise of Monitor Guided Care

-21 -14 - 7 Days

ProactiveProactive

0

Pressure ChangesPressure Changes

Medical InterventionMedical Intervention AvertedAvertedHeart Failure EventHeart Failure Event

7

TEN-HMS: Patients Baseline Characteristics

0,05777580Mean Weight (kg)

ns3,873 [1,607 to

7,518]

2,909 [1,116 to

6,140

2,309 [1,057 to

6,935]

Median NT-proBNP(pg/ml)

ns252524Mean LVEF (%)ns112/69116/69115/69BP (mmHg)

ns343946NYHA III & IV (%)ns666154NYHA I & II (%)ns202818Women (%)ns544749% Patients age >70ns676768Mean Age (years)

16817385Number PatientspHTMNTSUCVariable

IQR

TEN-HMSDays Dead or Hospitalized over 240 days

02468

101214161820

. . . .

UCNTSHTM

%

Death or Days in

Hospital (All-cause)

Death or Hospital Days

for Heart Failure

Days in Hospital

Days in HospitalFor HF

NB HTM reduced Average length of stay

p < 0,05

Mo

rtal

ity

Cleland et al JACC 2005

TransEuropean Home Telemonitoring Study Mortality

Reduction in MortalityNTS or HTM v UCAbsolute 16.4%Relative 36 %

Effect of Structured Telephone Support on All-Cause Mortality

Clark RA et al. BMJ 2007

Effect of Home Telemonitoring

Clark RA, BMJ 2007

On hospitalization

On mortality

Chronicle IHM - Lead Positioning

PressureSensorCapsule

Chronicle Pressure Measurements

1 = RVDP at QRS detection

13

2

EGM

RVP

dP/dt

2 = RVSP at peak of waveform

3 = ePAD at maximal dP/dt

Efficacy in NYHA Class III Patients

Cumulative Events

0

20

40

60

80

100

120

1

Eve

nts

Chronicle(n =112)

Control(n = 122)

# of Pts with Events 35 51

Total HF Related Events 58 99

Hospitalizations 50 86

Emergency Department Visits 6 11

Urgent Clinic Visits 2 3

Event Rate / 6months 0. 54 0.85

% Reduction in Event Rate

36% (p=0.0061; p=0.0582)

Chronicle

Control

642Months

1. Poisson model - Scaled Deviance = 1.7

2. Negative Binomial model - Scaled Deviance = 0.8

Bourge, RC, et al. J Am Coll Cardiol 2008;51:1073-9

HF-related Hospitalization – NYHA Class III

Time to Event Analysis

Days

Fre

edo

m f

rom

HF

-re

late

d

ho

spit

aliz

atio

n

0 50 100 150 200

0%

20%

40%

60%

80%

100%

RR = 0.62 (95%CI = 0.39 - 0.98)p=0.04

Chronicle

Control

Bourge, RC, et al. J Am Coll Cardiol 2008;51:1073-9

Implanted Monitor Derived Hemodynamics in PAH

Fig 1, Karamanoglu, M, et al, Chest 2007, 132:37-43

The basic features of the RV pressure waveform and the identification of these feature points using the first derivative of the RV pressure waveform. Three of these points identify the turning points of the PA flow waveform (in mmHg), PEI, T1st and STI, where PEI = time of dP/dtmax, T1st = time of the early shoulder of the RV pressure waveform, and STI = time of dP/dtmin. The area of the triangle (shaded area) = (P1st-Pes)x ED/2 corresponds to estimated stroke volume (SV). RR = R-R interval

The augmented pressure (AP) caused by the presence of wave reflection is the difference between the late systolic pressure (Psys) and the early systolic shoulder (P1st).

CO= 30 x(P1st-PES)x(STI-PEI)/RR AP=PSYS-P1st

0

40

mm

Hg

SV

ED

PES

P1st

0

500 ms -1000

mm

Hg

/s

dP/dtmax

dP/dtmin

ePAD

T1st

PEI

STI

Psys

RR

Qmax

SV

CO= 30 x(P1st-PES)x(STI-PEI)/RR AP=PSYS-P1st

0

40

mm

Hg

SV

ED

PES

P1st

0

500 ms -1000

mm

Hg

/s

dP/dtmax

dP/dtmin

ePAD

T1st

PEI

STI

Psys

RR

Qmax

SV

Implanted Monitor Derived Hemodynamics in Pulmonary Arterial Hypertension

Fig 6 & 7, Karamanoglu, M, et al, Chest 2007, 132:37-43

0 1 2 3 4 5 6

Estimated (L/min/m2)

0

1

2

3

4

5

6

Mea

sure

d (

L/m

in/m

2 )

Y=X, r2=0.95

Cardiac Index

0 1 2 3 4 5 6

Average (L/min/m2)

-1.0

-0.5

0.0

0.5

1.0

Dif

fere

nce

(L

/min

/m2 )

+95% CI=0.37 L/min/m2

-95% CI=0.37 L/min/m2

Mean=0.0 L/min/m2

Bland - Altman Plot

0 1 2 3 4 5 6

Estimated (L/min/m2)

0

1

2

3

4

5

6

Mea

sure

d (

L/m

in/m

2 )

Y=X, r2=0.95

Cardiac Index

0 1 2 3 4 5 6

Average (L/min/m2)

-1.0

-0.5

0.0

0.5

1.0

Dif

fere

nce

(L

/min

/m2 )

+95% CI=0.37 L/min/m2

-95% CI=0.37 L/min/m2

Mean=0.0 L/min/m2

Bland - Altman Plot

0

2

4

6

L/m

in/m

2

0

100

200

300

400

500

mm

Hg

0

2

4

6

L/m

in/m

2

01 0907060503 3431

EstimatedMeasuredDose

CardioMEMS Wireless Heart Failure Sensor

Externally powered – no battery

HF Sensor technology based on clinically proved commercially available system for abdominal aneurysms repair monitoring

AAA Sensor

HF Sensor

CardioMEMS System in Diastolic Dysfunction

550 Ptsw/ CM Implants

All Pts Take Daily Readings

Treatment275 Pts

Management Based onHemodynamics + Traditional Info

Control275 Pts

Management Based onTraditional Info

Primary Endpoint: HF Hospitalizations at 6 Months

Additional Analysis: HF Hospitalizations at All Days (~18 M mean F/U)

• Enrollment completed early October, 2009

• Final Data May 2010

• I/E:Class III HF with 1 hosp in previous yearNo EF or QRS criteria

• Cost Effectiveness Sub-Study

CHAMPIONCardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III heart failure patients

21Multiple Secondary Endpoints

Edible Electronic Monitors

Ingestible sensor chip 1mm

square and 200 microns thick

attached to pills with a bio-

compatible glue

External band-aid-like patch.

When swallowed the chips

send a signal to the patch

tracking heart rate,

respiratory rate, temperature

and activity.

1

Implanted Monitors-arrhythmia-hemodynamics-labs

The Potential for TeleMedicine in the Care of Patients with Cardiovascular Disease

Development of Integrated Tele-Medicinefor Heart Failure

Improved sensor and communication technology

Evidence! Adequate preparatory work (health services not ready) Intelligent Study Design and Funding

Clinician-led models of service Development of clinical pathways Decision-support software Replace existing care patterns

Proper business and health-economic models

Adapted for J.G.Cleland, 2009, with permission

Summary

< bbourge@uab.edu >

Summary< bbourge@uab.edu >

Summary< bbourge@uab.edu >

Summary< bbourge@uab.edu >