Current Modalities for Invasive and Non Invasive Monitoring of Volume status in HF

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Abstract and Introduction

Abstract

Heart failure (HF) represents a major health and economic burden worldwide. In spite of best current therapy, HF

progresses with unpredictable episodes of deterioration that often require hospitalisation. These episodes are

often preceded by accumulation or redistribution of fluid causing haemodynamic overload on the heart. Remote

and telemonitoring of the HF patient, assessing symptoms and signs, thoracic impedance derived fluid status

follow-up or direct haemodynamic measurements with chronic implanted devices are presently under investigation

for the potential to detect impending HF decompensation early. The current evidence for volume status monitoring

in HF using those novel management strategies is reviewed.

Introduction

Heart failure (HF) represents a major health and economic burden which is increasing with the ageing of

populations around the world. In the USA, over 5.7 million people are currently estimated to live with HF.[1] In

Europe, over 15 million people are estimated to have HF, and with a similar prevalence of asymptomatic left

ventricular (LV) dysfunction, approximately 4% of the European population has either HF or LV dysfunction.[2]

Despite advances in pharmacological and other therapies, rates for HF related hospital admission have not

substantially decreased and represent a major driver for healthcare expenditure.[1] Recent data indicate that

inhospital care accounts for approximately 60% of total HF costs.[3] Rehospitalisation for worsening HF predicts

adverse prognosis, especially in the elderly, and is often initiated by intrathoracic fluid overload leading to

symptomatic pulmonary congestion.[4 5] The vast majority of patients with acute decompensated HF (ADHF) has

underlying chronic HF. Our current understanding of mechanisms contributing in ADHF is still insufficient but

altered LV loading conditions and hypervolaemia are likely important contributing factors. Intrathoracic fluid

accumulation frequently precedes hospital admission. Conceptually, continuous monitoring of fluid status in HF

patients could aid identification of volume overload, thus providing an opportunity to intervene at an early stage and

possibly avert hospital admission for ADHF. However, early clinical detection of ADHF is challenging.[6–8]

Haemodynamic disturbances underlying ADHF may start weeks before the actual onset of typical HF symptoms

such as fatigue, body weight gain or shortness of breath. Moreover, these are common, especially in the elderly

without HF, and may be overlooked both by doctors and patients themselves. Diagnostic tools widely used in HF

workup such as chest x-ray, cardiac catheterisation and conventional echocardiography are of limited use in

determining the individual patient's fluid status.[7 9–11]

Biomarkers in the assessment of clinical status of HF have emerged over the past two decades and are now

routinely measured in various clinical settings. While the role of B type natriuretic peptide (BNP) in diagnosis as

well as prognostification of HF is well established, there has been ongoing debate regarding its role as a guide to

monitoring and adjustment of HF therapy. Recent meta-analyses of major randomised controlled trials (RCTs) in

the field have suggested a mortality benefit in patients with monitored BNP, presumably due to enhanced use of

drugs such as angiotensin converting enzyme inhibitors (ACEI) and β blockers in the cohort exhibiting biomarker

increases.[12 13] Another report concluded that N terminal BNP guided HF specialist care in addition to home

based nurse care was cost effective and cheaper than standard care.[14] There are conflicting data as to whether

BNP guided HF care reduces rehospitalisation rates.[13 15] BNPs may not be sensitive enough tools to detect

rapidly decompensating HF. In ADHF, acute changes in LV filling pressures will likely not be reflected by

simultaneous changes in NPs due to their long half-lives, thus limiting their clinical utility in that setting.

Furthermore, patient characteristics (ie, age, gender, body weight) may influence plasma levels of BNP and other

NPs, making interpretation even more difficult.[9 10]

Current Modalities for Invasive and Non-invasive Monitoring of Volume Status in HeartFailureThomas G von Lueder, Henry Krum

Heart. 2012;98(13):967-973.

http://www.medscape.com/

http://heart.bmj.com/



Therefore, novel strategies to more precisely assess and monitor fluid status in HF have been explored over recent

years. Some of those developments seem to hold promise in improving early detection of which patients will likely

be readmitted for ADHF, with the potential to intervene early. Bringing down HF hospitalisation rates may not only

improve patient quality of life but also reduce longer term clinical outcomes and alleviate the enormous HF related

cost to society.

This review seeks to summarise current knowledge on integrating fluid status monitoring into the overall

management of HF patients.

Emerging Strategies to Monitor Fluid Status in HF

Home and Telemonitoring

Given the importance of hypervolaemia in HF related events, monitoring of weight and HF specific symptoms as a

surrogate for fluid status has received considerable attention in recent years. Efforts have been made to

systematically and continuously assess fluid status associated variables either at clinical follow-ups or through

structured telephone calls. However, it has been unclear whether those strategies translate into clinical benefit.

Several recent studies have sought to establish evidence for such a benefit ( ).

Table 1. Overview of important studies of fluid monitoring in heart failure

Study N

Patient

characteristics or

key inclusion

criteria

Intervention

Follow-

up

(months)

Outcome or main findings

I. Home and remote telemonitoring

WHARF16 280

NYHA III–IV + EF

≤35%HF + HF

hospitalisation

RTM (AlereNet

system)6

No effect on rehospitalisations.

Greatly reduced mortality

HHH study17 461

NYHA II–IV + EF

≤40% + HF

hospitalisation

NTS or

NTS+RTM

strategies (3

arms)

12 Negative

HOME-HF18 182NYHA II–IV + HF

hospitalisationRTM 6

Negative, but fewer unplanned

hospitalisations

TEN-HMS19 20 426

HF symptoms +

EF ≤40% + HF

hospitalisation

RTM or NTS 8Negative, but lower 1 year

mortality by NTS and RTM

TELE-HF21 1653 HF hospitalisation RTM 6 Negative

TIM-HF22 710

NYHA II–III + EF

≤35% + HF

hospitalisation or

EF ≤25%

RTM 26 Negative

Cochrane23 8323

Meta-analysis of

25 trials (RTM,

n=2710; STS,

n=5613)

RTM and/or STS NA

Reduced mortality and HF

hospitalisations; improved QOL

(note: TIM-HF22 and TELE-HF21

not included)

II. Impedance monitoring (ICD or CRT-D)

MIDHeFT24 34NYHA III–IV + HF

eventsFeasibility study 21

Impedance inversely correlated

with PCWP



Maines et al 25 54NYHA II–IV + EF

24%

Case control

study12 HF hospitalisations reduced

PARTNERS-HF26 694

CRT-D + NYHA III–

IV + EF ≤35% +

QRS> 130 ms

Observational

prospective

study

12

Combined diagnostic HF

algorithm identified patients at

risk for ADHF

FAST27 156

CRT-D or ICD +

NYHA III–IV + EF

≤35%

Prospective

study18

Impedance change superior to

acute weight changes

IMPATTO28 111 HF + EF <35%Registry (no

intervention)14

Impedance data correlated with

BNP levels and

echocardiography data (E

deceleration time)

SENSE-HF29 501

Previous HF

hospitalisation

requiring

intravenous

treatment

Prospective

double blind

study

24FI had low sensitivity and PPV

for HF hospitalisation

DOT-HF30 335

NYHA II–IV + EF ≤

35% + previous HF

hospitalisation

Unblinded RCT 15

Negative. Underpowered. More

hospitalisations in intervention

group

OptiLink HF

study31 1000NYHA II-III + EF

<35%RCT 18

Ongoing. Planned inclusion,

n=1000

III. Implantable haemodynamic monitors

Permanent RV

IHM system32 32 NYHA III–IV

Observational

prospective

study

17RV pressure increases preceded

hospitalisations

COMPASS33 274

NYHA III–IV +

previous HF

hospitalisation

RVOT IHM

(CHRONICLE) all

patients; single

blinded

6Non-significant reduction of HF

events. Safety endpoints met

REDUCE-HF34 35 400

NYHA II–III +

previous HF

hospitalisation +

ICD indication

RVOT IHM

linked to ICD (all

patients)

6

Ended prematurely for lead

problems. No effects on HF

events (but underpowered)

HOMEOSTASIS36 40

NYHA III–IV +

previous HF

hospitalisation

LAP catheter

(HeartPOD) all

patients

25Increased event free survival,

lower LAP

CHAMPION37 38 550

NYHA III +

previous HF

hospitalisation

PA catheter

versus standard

care (single

blinded)

6

Reduced and shorter HF

hospitalisations, lowered PAP,

more medication changes in

intervention group

LAPTOP-HF* 730

NYHA III +

previous HF

hospitalisation

LAP catheter or

CRT-D12 Ongoing

* http://www.clinicaltrials.gov, NCT01121107.

ADHF, acute decompensated heart failure; BNP, B type natriuretic peptide; CRT-D, cardiac resynchronisation



therapy device; EF, ejection fraction; FI, fluid index; HF, heart failure; ICD, cardioverter defibrillator; IHM,

implantable haemodynamic monitors; LAP, left atrial pressure; NTS, nurse telephone support; NYHA, New York

Heart Association (functional class); PA, pulmonary artery; PAP, pulmonary artery pressure; PCWP, pulmonary

capillary wedge pressure; PPV, positive predictive value; QOL, quality of life; RCT, randomised controlled trial;

RTM, remote telemonitoring; RV, right ventricular; RVOT, right ventricular outflow tract; STS, structured telephone

support.

The Weight Monitoring in HF (WHARF) trial was a large multicentre RCT of a technology based daily weight and

symptom monitoring system.[16] It included HF patients in New York Heart Association (NYHA) class III or IV.

The trial failed to meet its primary endpoint of reduced 6 month rehospitalisation rates but demonstrated a

substantial reduction in the secondary endpoint of mortality.

The Trans-European Network-Home Care Management System (TEN-HMS) study was a large scale RCT

comparing home based telemonitoring services or nurse based telephone support to usual care.[19 20] In TEN-

HMS, telemonitoring failed to meet its primary endpoints of days lost to death or hospitalisation improvements of

patient quality of life, but both interventions led to lower 1 year mortality than usual care.

A recent report by the Cochrane Review Group compared structured telephone interview and telemonitoring to

standard care.[23] That meta-analysis comprised over 8000 patients and included 11 studies (all published before

the end of 2008) which evaluated telemonitoring (total of 2710 subjects) and 16 which evaluated structured

telephone support (5613 subjects). Telemonitoring reduced all-cause mortality while structured telephone support

showed a non-significant trend. Both interventions reduced HF hospitalisations. Heterogenous protocols and the

small sample size of most of the trials included in that report warrant caution when interpreting the ascribed

benefits.

Further illustrating the limitations of pooled efficacy data, two very recent large RCTs (not included in the

aforementioned Cochrane review) have raised doubts as to the benefits of telemonitoring. First, the Telemedicine

to Improve Mortality in Heart Failure (TIM-HF) study evaluated 710 patients with NYHA class II or III HF, LV

ejection fraction (EF) ≤35% and on optimal medical therapy.[22] Using portable devices, ECG, blood pressure and

body weight measurements of the telemonitored cohort (n=354) were reviewed daily by telemedical centres. After

a mean follow-up of 26 months, telemonitoring had no significant effect on all-cause mortality, cardiovascular

death or HF hospitalisation compared with patients receiving usual care (n=356). In the even larger telemonitoring

for HF (TELE-HF) trial, 826 patients recently hospitalised for HF were randomised to daily telemonitoring by

means of a telephone based interactive voice response system collecting data on weight and symptoms, and

compared with 827 patients on standard care.[21] Data in the telemonitored cohort were reviewed by the patients'

clinicians. The primary endpoint was readmission for any reason or death from any cause within 180 days after

enrolment. Secondary endpoints included hospitalisation for HF, number of days in the hospital and number of

hospitalisations. Again, telemonitoring in TELE-HF did not improve any of these outcomes. Moreover, no subgroup

(age, gender, EF, etc) could be identified that benefitted from the intervention. Importantly, adherence to the

intervention decreased from an initial 90.2% to only 55.1% by 6 months, and almost 15% of patients never

actually used the device. There was no per protocol analysis to allow conclusions on potential benefits in those

study subjects that adhered to the intervention. TELE-HF did not report information on medication changes or on

how clinicians used information gained from telemonitoring.

In an effort to refine monitoring of fluid status associated parameters, a simple rule of thumb algorithm was

retrospectively compared with a sophisticated moving average convergence divergence algorithm to detect

abnormal weight gain in telemonitored HF patients.[20] While the moving average convergence divergence

algorithm was much more specific than the rule of thumb algorithm in detecting weight gain, overall sensitivity was

rather poor. As a significant number of episodes of worsening HF in that cohort were not associated with weight

gain at all, the authors concluded that telemonitoring of weight gain alone may be of limited use for HF

management.

Together, current evidence on home based telemonitoring strategies does not definitely point to consistent

additional benefits above standard care for HF patients.



Thoracic Impedance Monitoring With Novel ICD and CRT Devices

Since the very first pacemaker was implanted into a patient in 1958, the use and complexity of cardiovascular

implantable electronic devices has been ever expanding. Nowadays, these include conventional pacemakers,

implantable cardioverter defibrillators (ICD) to treat life threatening arrhythmia and cardiac resynchronisation

therapy devices (CRT-D) to restore interventricular synchrony. The latest generations of CRT-D and ICD devices

are capable of monitoring thoracic impedance which has been shown to correlate well with pulmonary fluid status,

and may provide an early warning of deteriorating HF ( ). The correlation between LV filling pressures and

intrathoracic impedance is inverse—that is, it decreases when there is evolving fluid accumulation within the

thoracic cage. In HF patients, serial measurements of thoracic impedance have been demonstrated to reflect

pulmonary fluid status and, importantly, predict HF decompensation even before the onset of symptoms.[39 40] In

a recent registry study, intrathoracic impedance was significantly correlated with N terminal proBNP and with

mitral E wave deceleration time, but not with clinical HF score.[28] In a large animal model of rapid pacing induced

chronic HF, serial measurement of intrathoracic impedance with an implantable system effectively revealed

changes in pulmonary congestion which were reflected by elevated LV end diastolic pressure.[41] To facilitate

interpretation of impedance data, algorithms based on impedance measurements are usually applied to compute

a fluid index (FI). As impedance is influenced by the actual volume status and may vary substantially within HF

cohorts, FI needs to be individualised in each HF patient, with baseline FI values determined during a period of

clinical stability. Surpassing of a predefined FI threshold would indicate fluid overload and impending HF

decompensation, and allow for swift intervention by HF physicians. In a case control study, patient management

using an algorithm based on intrathoracic impedance monitoring (OptiVol; Medtronic Inc, Minneapolis, Minnesota,

USA) has been shown to reduce hospital admissions for HF.[25]


Study N

Patient

characteristics or

key inclusion

criteria

Intervention

Follow-

up

(months)



WHARF16 280

NYHA III–IV + EF

≤35%HF + HF

hospitalisation

RTM (AlereNet

system)6



HHH study17 461

NYHA II–IV + EF

≤40% + HF

hospitalisation

NTS or

NTS+RTM

strategies (3

arms)

12 Negative




hospitalisations

TEN-HMS19 20 426

HF symptoms +

EF ≤40% + HF

hospitalisation




TIM-HF22 710

NYHA II–III + EF

≤35% + HF

hospitalisation or

EF ≤25%

RTM 26 Negative

Cochrane23 8323

Meta-analysis of

25 trials (RTM,

n=2710; STS,RTM and/or STS NA






n=5613) not included)





with PCWP


24%

Case control


PARTNERS-HF26 694

CRT-D + NYHA III–

IV + EF ≤35% +

QRS> 130 ms

Observational

prospective

study

12



risk for ADHF

FAST27 156

CRT-D or ICD +

NYHA III–IV + EF

≤35%

Prospective

study18




intervention)14


BNP levels and


deceleration time)

SENSE-HF29 501

Previous HF

hospitalisation

requiring

intravenous

treatment

Prospective

double blind

study



DOT-HF30 335


35% + previous HF

hospitalisation

Unblinded RCT 15



group

OptiLink HF


<35%RCT 18


n=1000


Permanent RV


Observational

prospective

study


hospitalisations

COMPASS33 274

NYHA III–IV +

previous HF

hospitalisation

RVOT IHM

(CHRONICLE) all

patients; single

blinded



REDUCE-HF34 35 400

NYHA II–III +

previous HF

hospitalisation +

ICD indication

RVOT IHM

linked to ICD (all

patients)

6




HOMEOSTASIS36 40

NYHA III–IV +

previous HF

hospitalisation

LAP catheter

(HeartPOD) all

patients


lower LAP

CHAMPION37 38 550

NYHA III +

previous HF

hospitalisation

PA catheter

versus standard

care (single

blinded)

6




intervention group



LAPTOP-HF* 730 NYHA III +

previous HF

hospitalisation

LAP catheter or

CRT-D12 Ongoing








support.

The Medtronic Impedance in Diagnostics in HF Trial (MIDHeFT) in patients with NYHA classes III and IV HF

showed a sensitivity of 77% for FI algorithms to detect hospitalisation for fluid overload.[24] The Fluid Accumulation

Status Trial (FAST) compared serial measurements of thoracic impedance with weight changes in 156 NYHA

class II or III HF patients and implantable ICD or CRT-D, with a mean follow-up of 537 days.[27] FAST

demonstrated that impedance data were more sensitive than weight gain in predicting HF decompensation (76 vs

23%). The relatively low specificity improved when impedance data were combined with weight monitoring. The

Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With HF

(PARTNERS-HF) study prospectively evaluated the utility of combined diagnostic algorithm including impedance

data to predict HF hospitalisations in patients with NYHA classes III and IV HF, reduced LV EF, broad QRS and

who had a CRT-D (Medtronic Inc). A total of 694 patients were followed for almost 12 months in this unblinded

observational study. The impedance based algorithm identified a cohort at high risk of experiencing a HF event

within the subsequent month.[26] Importantly, there seems to be a link between patient reported HF self-care and

the likelihood of an FI threshold crossing event.[42]

In most of these trials, the predefined FI algorithm led to a considerable number of false positive alerts and likely

increased healthcare utilisation. This lack of specificity may present an obstacle to broader implementation of the

technology into clinical practice. Current efforts to develop improved FI based algorithms demonstrated lower false

positive alerts at similar sensitivity.[43]

The recent Sensitivity of the InSync Sentry OptiVol Feature for the Prediction of HF (SENSE-HF) study was a

large prospective, multicentre, double blind study that evaluated an impedance based algorithm, OptiVol, in 501

NYHA class II and class III HF patients with CRT-D.[29] Using OptiVol, the trial showed a low sensitivity of 42%

and low positive predictive value of only 38% for future HF events. The Diagnostic Outcome Trial in HF (DOT-HF)

was a large prospective phase IV RCT designed to test whether monitoring of intrathoracic impedance (OptiVol)

could reduce morbidity and mortality in patients with chronic NYHA classes II–IV HF.[44] All study subjects were

implanted with an ICD or CRT-D capable of monitoring impedance (Medtronic Inc), and randomised to have all

device based information (including audible alerts for preset fluid threshold crossings) available to patients and

doctors (access group) or to a control group without that information.[30] The primary endpoint was a composite of

all-cause mortality and HF hospitalisation, and occurred in 48 of 168 (29%) patients in the access arm versus 33

of 167 (20%) in the control arm (p=0.063). Even if the trial was terminated early due to to low enrolment rates

(only 336 of intended 2400 subjects were included), post hoc futility analysis deemed it unlikely that better

recruitment would have changed overall outcome. The currently ongoing OptiLink-HF Study is another substantial

study in the field. Approximately 1000 patients will be required to demonstrate a 30% reduction in the primary

outcome (composite of all-cause death or cardiovascular hospitalisation).[31]

HF Management Based on Invasive Haemodynamic Monitoring

Supranormal LV filling pressures are a hallmark and one of the principal haemodynamic abnormalities in HF

decompensation. The relationship between cardiac pressures and HF events has therefore been the subject of

longstanding interest and research. Pulmonary artery catheterisation (PAC) using thermodilution/Swan Ganz

catheters has been the undisputed gold standard for invasive haemodynamic assessment. Early observational

studies and registry data including patients with ADHF or cardiogenic shock after acute myocardial infarction have



not been able to demonstrate beneficial effects of the use of PAC.[45–47] However, most of those reports stem

from the percutaneous coronary intervention (pre-PCI) (and pre-thrombolysis) era, and the lack of randomisation

usually meant that the most seriously ill patients (with the worst prognosis) were more likely to undergo PAC.

Accordingly, the importance of PAC in a contemporary HF setting is unclear. The Evaluation Study of Congestive

HF and Pulmonary Artery Catheterisation Effectiveness (ESCAPE) study randomised 433 patients hospitalised

with severe symptomatic HF to receive therapy guided by PAC derived haemodynamic data and clinical

assessment versus therapy based on clinical assessment alone. ESCAPE showed that addition of PAC to

clinical assessment did not affect overall mortality and hospitalisation.[48] Significantly more patients in the PAC

group (21.9 vs 11.5%) experienced an inhospital adverse event, but inhospital and 30 day mortality was not

affected by the use of PAC. In contrast with the apparent lack of benefit of PAC guided therapy in ADHF, the

relevance in chronic HF is unclear.

Implantable Continuous Haemodynamic Monitoring Devices

During the past decade, permanently implantable devices have emerged that provide accurate and timely long

term haemodynamic data ( ). Among these implantable continuous haemodynamic monitoring (ICHM) devices are

those that chronically assess pressures in the right ventricle (RV), pulmonary artery and left atrium.[32 49–51]


Study N

Patient

characteristics or

key inclusion

criteria

Intervention

Follow-

up

(months)



WHARF16 280

NYHA III–IV + EF

≤35%HF + HF

hospitalisation

RTM (AlereNet

system)6



HHH study17 461

NYHA II–IV + EF

≤40% + HF

hospitalisation

NTS or

NTS+RTM

strategies (3

arms)

12 Negative




hospitalisations

TEN-HMS19 20 426

HF symptoms +

EF ≤40% + HF

hospitalisation




TIM-HF22 710

NYHA II–III + EF

≤35% + HF

hospitalisation or

EF ≤25%

RTM 26 Negative

Cochrane23 8323

Meta-analysis of

25 trials (RTM,

n=2710; STS,

n=5613)

RTM and/or STS NA




not included)





with PCWP




24%

Case control


PARTNERS-HF26 694

CRT-D + NYHA III–

IV + EF ≤35% +

QRS> 130 ms

Observational

prospective

study

12



risk for ADHF

FAST27 156

CRT-D or ICD +

NYHA III–IV + EF

≤35%

Prospective

study18




intervention)14


BNP levels and


deceleration time)

SENSE-HF29 501

Previous HF

hospitalisation

requiring

intravenous

treatment

Prospective

double blind

study



DOT-HF30 335


35% + previous HF

hospitalisation

Unblinded RCT 15



group

OptiLink HF


<35%RCT 18


n=1000


Permanent RV


Observational

prospective

study


hospitalisations

COMPASS33 274

NYHA III–IV +

previous HF

hospitalisation

RVOT IHM

(CHRONICLE) all

patients; single

blinded



REDUCE-HF34 35 400

NYHA II–III +

previous HF

hospitalisation +

ICD indication

RVOT IHM

linked to ICD (all

patients)

6




HOMEOSTASIS36 40

NYHA III–IV +

previous HF

hospitalisation

LAP catheter

(HeartPOD) all

patients


lower LAP

CHAMPION37 38 550

NYHA III +

previous HF

hospitalisation

PA catheter

versus standard

care (single

blinded)

6




intervention group

LAPTOP-HF* 730

NYHA III +

previous HF

hospitalisation

LAP catheter or

CRT-D12 Ongoing










support.

Right Ventricular Pressure Monitoring In a feasibility study, 32 patients with HF received a permanent RV

ICHM system (Chronicle; Medtronic Inc) similar to a single lead RV pacemaker. The ICHM delivered accurate RV

pressure data over time that correlated well with LV filling pressures obtained from conventional PAC.[49] In this

cohort, hospitalisations before using ICHM data for clinical management averaged 1.08 per patient year and

decreased to 0.47 per patient year (57% reduction; p<0.01) after integration of RV pressure data into the follow-

up.[32] The subsequent landmark Chronicle Offers Management to Patients with Advanced Signs and Symptoms

of HF (COMPASS) trial sought to establish whether integration of RV ICHM derived pressures would reduce HF

morbidity.[33] COMPASS was a prospective, multicentre, randomised, single blind, parallel controlled trial and

included 274 NYHA class III/IV HF patients with a previous HF hospitalisation, all of whom were implanted with

the same ICHM as above. Subjects were randomised to an ICHM guided HF management strategy or control

group follow-up without ICHM data available. ICHM guided HF management in COMPASS did not reduce HF

related events compared with standard care which was probably the reason why the Food and Drug

Administration has not thus far approved the technology.[33 52] This surprising lack of efficacy deserves further

discussion. Sample size calculations were based on an event rate of at least 1.2 per 6 patient months in the

control group to show a 30% reduction in HF related events with 80% power. The trial, however, reported an event

rate as low as 0.85 per 6 patient months in the control group, being further (non-significantly) reduced by 21% to

0.67 in the intervention group. It is noteworthy that the HF event rate in the control group decreased from 1.8 per 6

patient months (ie, by over 50%) after enrolment, probably driven by the very tight follow-up (at almost weekly

intervals) which seems unrealistic to achieve in daily clinical practice.[53] Even if technically underpowered to meet

its efficacy endpoints, COMPASS provided novel important insights into the pathophysiological changes during

decompensation in patients with HF with reduced and preserved EF.[52] Pressure increases preceded HF related

events by 3–4 weeks, and interestingly, no significant body weight changes were found in relation to HF events.

Data on medication changes in relation to ICHM data are yet to be published and will further our understanding of

HF management guided by RV haemodynamics. Very recently, the Reducing Decompensation Events Utilising

Intracardiac Pressures in Patients with Chronic HF (REDUCE-HF) trial was halted with only 400 of the planned

1300 patients enrolled, due to problems with the pressure sensor leads seen in earlier studies.[34] The HF event

rate was even lower than in COMPASS, probably due to a healthier patient cohort ( ), and the device had not led

to reduced hospitalisation or other HF events when it was stopped.[35]


Study N

Patient

characteristics or

key inclusion

criteria

Intervention

Follow-

up

(months)



WHARF16 280

NYHA III–IV + EF

≤35%HF + HF

hospitalisation

RTM (AlereNet

system)6



HHH study17 461

NYHA II–IV + EF

≤40% + HF

hospitalisation

NTS or

NTS+RTM

strategies (3

arms)

12 Negative

HOME-HF18 182

NYHA II–IV + HF

hospitalisation RTM 6


hospitalisations



TEN-HMS19 20 426

HF symptoms +

EF ≤40% + HF

hospitalisation




TIM-HF22 710

NYHA II–III + EF

≤35% + HF

hospitalisation or

EF ≤25%

RTM 26 Negative

Cochrane23 8323

Meta-analysis of

25 trials (RTM,

n=2710; STS,

n=5613)

RTM and/or STS NA




not included)





with PCWP


24%

Case control


PARTNERS-HF26 694

CRT-D + NYHA III–

IV + EF ≤35% +

QRS> 130 ms

Observational

prospective

study

12



risk for ADHF

FAST27 156

CRT-D or ICD +

NYHA III–IV + EF

≤35%

Prospective

study18




intervention)14


BNP levels and


deceleration time)

SENSE-HF29 501

Previous HF

hospitalisation

requiring

intravenous

treatment

Prospective

double blind

study



DOT-HF30 335


35% + previous HF

hospitalisationUnblinded RCT 15



group

OptiLink HF


<35%RCT 18


n=1000


Permanent RV


Observational

prospective

study


hospitalisations

COMPASS33 274

NYHA III–IV +

previous HF

hospitalisation

RVOT IHM

(CHRONICLE) all

patients; single

blinded





REDUCE-HF34 35 400

NYHA II–III +

previous HF

hospitalisation +

ICD indication

RVOT IHM

linked to ICD (all

patients)

6




HOMEOSTASIS36 40

NYHA III–IV +

previous HF

hospitalisation

LAP catheter

(HeartPOD) all

patients


lower LAP

CHAMPION37 38 550

NYHA III +

previous HF

hospitalisation

PA catheter

versus standard

care (single

blinded)

6




intervention group

LAPTOP-HF* 730

NYHA III +

previous HF

hospitalisation

LAP catheter or

CRT-D12 Ongoing








support.

Left Atrial Pressure Monitoring A different approach to assess cardiac filling pressures is by implantation of a

left atrial pressure (LAP) sensing system. HeartPOD (St Jude Medical Inc, Minneapolis, Minnesota, USA) was

the first implantable LAP sensor to be reported.[51] Similar to the RV ICHM system, HeartPOD consists of a

small, pulse generator-like coil antenna and a lead carrying a septal anchor fixation system with a distal sensing

diaphragm. The lead is implanted percutaneously and advanced across the atrial septum with the sensor

depicting LAP signals. HeartPOD was previously shown to provide accurate and stable measurements in keeping

with simultaneously obtained pulmonary capillary wedge pressure.[50] In the recently published

Haemodynamically Guided Home Self-Therapy in Severe HF Patients (HOMEOSTASIS) trial, 40 ambulatory

patients in HF NYHA classes III and IV and a HF hospitalisation requiring intravenous therapy during the past 12

months underwent percutaneous implantation of the HeartPOD system.[36] The study design was observational

and prospective, with a follow-up of 25±19 (range 1–63) months. LAP was read twice daily, and both patients and

clinicians were blinded to the LAP data the first 3 months after implantation. HF therapy was thereafter guided by

LAP readings. HeartPOD derived LAP correlated highly with pulmonary capillary wedge pressure measured at 3

and 12 months (r=0.98, average difference of Hg) under various loading conditions, and no important device

0.8±4.0 mm related safety issues were raised. HOMEOSTASIS demonstrated encouraging significant reductions

of LAP together with improvements in NYHA class and EF. Importantly, LAP guided management led to

significant increases in β blocker and ACEI/angiotensin receptor blocker (ARB) use, as well as reduced use of

diuretics. Subsequently, an additional 44 patients were implanted with HeartPOD. Recently published 48 month

follow-up data in a total of 84 patients witnessed good long term sensor performance.[54] The ongoing LAP

Monitoring to Optimise HF Therapy trial (LAPTOP-HF; http://www.clinicaltrials.gov, NCT01121107; planned

enrolment 730 patients) using HeartPOD or a similar LAP sensor combined with CRT-D ('Promote LAP') will

evaluate whether HF related events are reduced in patients who are managed with the LAP management system

versus those who receive the current standard of care.

Pulmonary Artery Pressure Monitoring A different device making use of ambulatory haemodynamic

parameters is an implantable pulmonary artery sensor (CardioMEMS, Atlanta, Georgia, USA). The CardioMEMS

sensor is a small yet ingenious device that is deployed in a distal pulmonary artery branch during routine right

heart catheterisation, and delivers continuous pulmonary artery pressure (PAP) data.[55] An apparent advantage

over other ICHM devices is its small size and the lack of need for batteries or leads. The device was evaluated in

http://www.clinicaltrials.gov/



the CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III HF

Patients (CHAMPION) trial.[37] CHAMPION was a prospective, randomised, single blinded trial in patients with

NYHA class III HF, irrespective of LV EF, and a previous hospital admission for HF. All patients were implanted

with the ICHM device and then randomised to PAP guided therapy (n=270) or standard care (n=280). The primary

efficacy endpoint was HF related events at 6 months, with pressure sensor failure and ICHM related complications

as safety endpoints. After a mean follow-up of 15 months, in spite of a very low HF event rate (0.44 per 6 patient

months in the standard care cohort), haemodynamic guided HF therapy substantially reduced HF related

hospitalisations (to 0.31 per 6 patient months), significantly reduced PAP and improved quality of life. Integration

of PAP data also led to significantly greater medication use. It is remarkable that background medical therapy at

baseline was very good with over 90% and almost 80% of patients using β blockers and ACEI/ARBs, respectively,

and furthermore, that patients with reduced versus preserved EF benefitted equally. The specific medication

changes by which the encouraging results of the CHAMPION trial were achieved deserve further discussion.[56]

PAP guided HF therapy led to significantly greater utilisation of nitrates, ACEI/ARBs and β blockers.[38] Diuretics

were frequently adjusted, but not differently between groups. Extending positive signals from previous smaller,

mostly observational, studies, CHAMPION was the first randomised trial sufficiently powered to detect and

demonstrate effects on clinically meaningful endpoints.

Discussion

With the advent of technology allowing continuous monitoring of fluid status signals, early identification of

pulmonary fluid accumulation in HF patients has moved within reach. Several devices have provided evidence that

integration of fluid status is clinically feasible, with some encouraging results regarding endpoints.

First, remote or telemonitoring of HF symptoms integrating changes in body weight as a surrogate of fluid status

has been extensively studied in recent trials. Even if some of the trials have suffered from low adherence to

intervention, overall results have not demonstrated substantial benefit over and above standard HF care. Newer

data indicate that body weight changes in HF patients are likely not sensitive (nor specific) enough signals to

permit early identification of impending HF decompensation. This may be partly explained by fluid redistribution

(not retention) which has been recently proposed as an important contributory mechanism.[57]

A different fluid monitoring concept is based on serial measurements of intrathoracic impedance, exploiting its

inverse correlation with lung water content. A number of currently available CRT-D and ICD devices are capable of

providing valid impedance derived fluid indexes. As indications for CRT-D and ICD devices in clinical HF care are

ever expanding, additional fluid status signals could be obtained at 'no extra cost'. Ongoing large scale clinical

trials seek to establish whether HF management incorporating impedance data is superior to standard care.

Non-invasive impedance monitoring using impedance cardiography (ICG) may be suitable for patients who would

not otherwise be considered for receiving an implantable device but more definitive outcome data are required to

support their use in HF management.

Directly measured haemodynamic parameters as markers of intracardiac filling pressures constitute another

promising avenue in fluid status monitoring, and a number of different devices are the subject of ongoing

investigation.

Recent data support the potential for this approach in reducing HF related events even in cohorts with low event

rates that already receive state of the art care. Few studies have included HF patients with preserved EF, which

account for approximately half of ADHF hospitalisations.[58] Data from CHAMPION and COMPASS studies point

to a similar benefit for HF patients with preserved versus reduced EF.[33 37 38]

While the field advances rapidly, a number of issues remain to be resolved. Obviously, fluid status monitoring in

HF by itself does not alter outcomes. In the clinic, decompensated HF and hypervolaemia are most frequently

treated by increasing use of diuretics and/or vasodilators. Diuretic overuse might induce postural symptoms and

azotaemia, and may be harmful in the long term.[59] We still do not know from several published trials whether

knowledge of fluid status data actually led to medication changes; specifically, to enhanced use of drugs known

to reduce morbidity and mortality in HF. The medical community needs to learn what specific medication changes



produced results superior to standard care, as recently reported for the CHAMPION study.[38 56] Next, exactly

how were the fluid status data translated into treatment decisions? Given the multitude of monitoring devices,

unifying guidelines for intervention thresholds need to be established. We also need to learn more about managing

ADHF presenting without concomitant weight gain, where volume redistribution rather than overload may be the

pathophysiological abnormality. Finally, perhaps previous expectations of the devices to reduce risk in the range

20–30% have simply been too optimistic, given the very low event rates in some of the reported HF cohorts.

Nevertheless, despite these ongoing issues, device based fluid status monitoring appears to represent a novel and

promising tool in the management of HF.

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Contributors Both TGVL and HK contributed to the paper. TGVL drafted and wrote the manuscript. HK helped draft themanuscript and revised its content.

Funding TGVL is supported by a post-doctoral research grant from South-Eastern Norwegian Health Authorities.

Provenance and peer review Commissioned; not externally peer reviewed.

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Current Modalities for Invasive and Non Invasive Monitoring of Volume status in HF

Healthcare

Transcript of Current Modalities for Invasive and Non Invasive Monitoring of Volume status in HF