Review
Current modalities for invasive and non-invasive monitoring of volume status in heart failure Thomas G von Lueder,1,2,3 Henry Krum1,2 1
Monash Centre of Cardiovascular Research and Education in Therapeutics, Alfred Hospital, Monash University, Melbourne, Victoria, Australia 2 Department of Epidemiology and Preventive Medicine, Alfred Hospital, Monash University, Melbourne, Victoria, Australia 3 Department of Cardiology B, Oslo University Hospital, Oslo, Norway Correspondence to Professor H Krum, Monash Centre of Cardiovascular Research and Education in Therapeutics, Department of Epidemiology and Preventive Medicine, Alfred Hospital, Monash University, Melbourne, VIC 3004, Australia; henry.
[email protected] Received 2 November 2011 Revised 1 March 2012 Accepted 4 March 2012 Published Online First 9 May 2012
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.6e8 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
Heart 2012;98:967e973. doi:10.1136/heartjnl-2011-301330
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 9e11 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 b 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 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. 967
Review Efforts have been made to systematically and continuously assess fluid status associated variables either at clinical followups 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). 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 hospitalTable 1
isation 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
Overview of important studies of fluid monitoring in heart failure
Study
N
I. Home and remote telemonitoring 280 WHARF16 HHH study17 18
HOME-HF TEN-HMS19
20
461 182 426
TELE-HF21 TIM-HF22
1653 710
Cochrane23
8323
Patient characteristics or key inclusion criteria NYHA IIIeIV + EF #35%HF + HF hospitalisation NYHA IIeIV + EF #40% + HF hospitalisation NYHA IIeIV + HF hospitalisation HF symptoms + EF #40% + HF hospitalisation HF hospitalisation NYHA IIeIII + EF #35% + HF hospitalisation or EF #25% Meta-analysis of 25 trials (RTM, n¼2710; STS, n¼5613)
II. Impedance monitoring (ICD or CRT-D) MIDHeFT24 34 NYHA IIIeIV + HF events Maines et al25 54 NYHA IIeIV + EF 24% PARTNERS-HF26 694 CRT-D + NYHA IIIeIV + EF #35% + QRS> 130 ms FAST27 156 CRT-D or ICD + NYHA IIIeIV + EF #35% IMPATTO28 111 HF + EF
