ESC HEART FAILURE ORIGINAL RESEARCH ARTICLE ESC Heart Failure 2019; 6: 621–628 Published online 30 May 2019 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/ehf2.12462 Effect of ferric carboxymaltose on calculated plasma volume status and clinical congestion: a FAIR-HF substudy Darlington O. Okonko1,2*, Fadi Jouhra2, Huda Abu-Own2, Gerasimos Filippatos3, Josep Comin Colet4,5, Chainey Suki6, Claudio Mori6, Piotr Ponikowski7, Stefan D. Anker8,9 and for the FAIR-HF Investigators 1 School of Cardiovascular Medicine and Sciences, James Black Centre, King’s College London British Heart Foundation Centre of Excellence, London, UK; 2King’s College Hospital, London, UK; 3National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece; 4Hospital del Mar (Parc de Salut Mar), Barcelona, Spain; 5 Universitat Autonoma de Barcelona, Barcelona, Spain; 6Vifor Pharma Ltd, Glattbrugg, Switzerland; 7Medical University, Wroclaw, Poland; 8Division of Cardiology and Metabolism–Heart Failure, Cachexia & Sarcopenia, Department of Cardiology (CVK); and Berlin-Brandenburg Center for Regenerative Therapies (BCRT); Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany; 9Department of Cardiology and Pneumology, University Medicine Göttingen, Göttingen, Germany Abstract Aims Iron deficiency worsens symptoms, quality of life, and exercise capacity in chronic heart failure (CHF) and might do so by promoting fluid retention. We assessed whether iron repletion improved congestion in CHF and appraised the prognostic utility of calculated plasma volume status (PVS), a novel index of congestion, in the FAIR-HF data set. Methods and results In FAIR-HF, 459 iron deficient CHF patients were randomized to intravenous ferric carboxymaltose (FCM) or saline and assessed at 4, 12, and 24 weeks. Using weight and haematocrit, we calculated PVS in 436 patients. At base- line, PVS and weight were 5.5 ± 7.7% and 76.9 ± 14.3 kg, with peripheral oedema evident in 35% of subjects. Higher PVS values correlated to other congestion surrogates such as lower serum albumin. At 4 weeks, FCM was associated with greater reductions in weight (0.02) and PVS (P < 0.0001), and a trend for improved peripheral oedema at 24 weeks (0.07). Irrespective of treatment allocation, patients with a decrease in PVS from baseline to week 24 had higher increments in 6 min walking dis- tance (61.4 m vs. 43.5 m, 0.02) and were more likely to improve their NYHA class (33.3% vs. 15.5%, 0.001). A PVS > 4% at baseline predicted worse outcomes even after adjustment for treatment assignment (hazard ratio 1.88, 95% confidence inter- val 1.01–3.51, 0.046). Conclusions Intravenous iron therapy with FCM is associated with early reductions in PVS and weight, implying that decon- gestion might be one mechanism via which iron repletion aids CHF patients. Calculated PVS is of prognostic utility in this cohort. Keywords Iron; Congestion; Plasma volume; Oedema Received: 4 December 2018; Revised: 31 March 2019; Accepted: 30 April 2019 *Correspondence to: Dr Darlington Okonko, King’s College London British Heart Foundation Centre, James Black Centre, 125 Coldharbour Lane, London SE5 9NU, UK. Tel: +44 (0)20 7848 5238. Email: obi.okonko@kcl.ac.uk Introduction animals and humans, ID has been shown to elevate circulat- ing catecholamine levels that promote congestion in CHF,6,7 Iron deficiency (ID) worsens symptoms, exercise capacity, and and in the small FERRIC-HF trial, intravenous (IV) iron sucrose hospitalization rates in chronic heart failure (CHF),1–3 but the significantly reduced body weight compared with placebo.8 underlying mechanism(s) remain obscure. Because conges- To date, no study has appraised the impact of iron therapy tion drives dyspnoea, exercise intolerance, and hospital ad- on clinical congestion in a large CHF population, and none missions in CHF,4,5 ID might be detrimental by directly or have addressed this interaction using newer and potentially indirectly augmenting fluid retention. In experimental more reliable metrics of fluid overload. © 2019 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of the European Society of Cardiology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any me- dium, provided the original work is properly cited and is not used for commercial purposes. 622 D.O. Okonko et al. Plasma volume (PV) expansion underlies systemic conges- and weight compared with PV values measured with gold tion in CHF and can be objectively estimated using validated standard radioisotope assays9: equations based on weight and haematocrit (Hct).9,10 In a actual PV ¼ ð½1  Hct½a þ ðbweight ½kgÞÞ prior analysis, calculated PV values were shown to significantly mirror those measured using gold standard radioisotope as- where Hct is a fraction and a = 1530 in men and 864 in says. Moreover, in a trial data set of 5002 CHF patients, rela- women, and b = 41 in men and 47.9 in women. tive PV status (PVS), derived by subtracting calculated ideal Ideal PV was calculated from the following well-established from actual PV levels, predicted outcomes even after adjust- formula10: ment for 22 variables including natriuretic peptides.11 ideal PV ¼ cweight ðkgÞ We sought to determine the distribution, correlates, and where c = 39 in men and 40 in women. prognostic utility of calculated PVS in CHF patients enrolled Relative PVS, an index of the degree to which patients in the large FAIR-HF (Ferric carboxymaltose Assessment in pa- have deviated from their ideal PV, was subsequently calcu- tients with Iron deficiency and chronic Heart Failure) trial.12 lated from the following equation: Moreover, we investigated the impact of IV iron therapy with ferric carboxymaltose (FCM) on calculated PVS and clinical PVS ¼ ð½actual PV  ideal PV=ideal PVÞ100%: congestion in this cohort. Our co-primary hypotheses were that PVS levels would be predictive of outcomes and that iron Clinical congestion repletion would trigger early reductions in PVS and clinical congestion consistent with a possible direct interaction be- Patients were weighed and examined for signs and symptoms tween ID and volume overload in CHF. of congestion at randomization and at weeks 4, 12, and 24. The presence or absence of peripheral oedema, pulmonary congestion (crackles and rales), and an S3 gallop (third heart Methods sound) were recorded, as was the actual jugular venous pres- sure (JVP). Study design and patients The design and primary results of the FAIR-HF trial have Statistics been reported previously.12 Briefly, FAIR-HF was a multicentre, randomized, double-blind trial including 459 Data are presented as mean ± SD, frequencies (%), or me- ambulatory patients with NYHA class II or III CHF,13 an left dians (interquartile range). Intergroup comparisons were ventricular ejection fraction (LVEF) ≤40% (NYHA II) or ≤45% made using a Kruskall–Wallis analysis of variance, analysis of (NYHA III), ID as defined by a ferritin <100 ug/L or 100 to covariance, Student t-test, Pearson χ 2 test, or a Mann– 299 ug/L with a transferrin saturation <20%, and a Whitney U-test as appropriate. Associations between vari- haemoglobin (Hb) level between 9.5 and 13.5 g/L. Patients ables were determined using logistic regression. A P-value were randomized in a 2:1 ratio to IV iron as FCM or IV pla- <0.10 was used to enter and retain covariates into stepwise cebo (saline) weekly until iron repletion (correction phase), multivariable regression models. then 4 weekly until week 24 (maintenance phase). Regular To assess the impact of treatment assignment on PVS, assessments were done at weeks 4, 12, and 24. After comparisons of changes in PVS from baseline at 4, 12, and 24 weeks of treatment, patients randomized to IV FCM 24 weeks between the placebo and FCM group were evalu- had significant improvements in Patient Global Assessment, ated by comparing the least square means at each visit from NYHA class, and 6 min walking distance (6MWD), compared a repeated-measures model using an unstructured covari- with patients allocated to saline. The Hct and weight at ran- ance structure and adjusting for the continuous baseline domization were used for PVS calculations and were avail- value and a visit × drug interaction. Changes over time for able in 436 (95%) patients whose data were therefore other variables were similarly determined. used in this post hoc analysis. The FAIR-HF trial was con- For prognostic analyses, the key safety endpoint was the ducted in accordance with the Declaration of Helsinki, with combined outcome of all-cause death or hospitalization. independent Institutional Review Board or ethics committee The relation between safety endpoints and baseline PVS as approval at all participating centres, and with written in- a continuous or categorical (≤4% vs. >4%) variable was formed consent from all patients. determined using Cox proportional hazards analyses. This categorical cut-off was previously shown to best stratify out- Plasma volume equations comes in a large CHF cohort.11 In Cox analyses, the propor- tional hazard assumption was assessed by inspection of the Actual PV was calculated with the following equation that log time–log hazard plot. The event rate using a person-time was derived by curve-fitting techniques using subjects’ Hct ‘at risk’ denominator, hazard ratio (HR), 95% confidence ESC Heart Failure 2019; 6: 621–628 DOI: 10.1002/ehf2.12462 Effect of ferric carboxymaltose on calculated plasma volume status and clinical congestion: a FAIR-HF substudy 623 interval (CI), and significance levels for χ 2 (likelihood ratio treatment effect was maximal at week 12. Treatment with test) were calculated. Kaplan–Meier cumulative survival FCM was also associated with significant increases from base- plots were constructed for display and assessed using the line in Hct at week 4 (0.02 ± 0.04% vs. 0.004 ± 0.03%), 12 log-rank test. (0.03 ± 0.04% vs. 0.002 ± 0.04%), and 24 [0.03 ± 0.05% vs. Data were analysed using SAS version 9.2 (SAS Institute 0.01 ± 0.04%; Figure 2B]. In contrast, FCM treatment was as- Inc, Cary, NC). A two-tailed P-value <0.05 was considered sociated with a significant reduction from baseline in weight statistically significant. at week 4 (0.2 ± 2.4 kg vs. 0.3 ± 1.8 kg), but not at week 12 (0.2 ± 3.0 kg vs. 0.6 ± 3.3 kg), or 24 [0.3 ± 3.2 kg vs. 0.6 ± 3.7 kg; Figure 2C]. Similar to the effect on PVS, there was an improvement in peripheral oedema with FCM treat- Results ment compared with placebo [Figure 2D] that did not reach statistical significance. Similar improvements in jugular ve- Calculated plasma volume status in FAIR-HF and nous distension (0.54), pulmonary oedema (0.35), or the its baseline correlates presence of an S3 gallop rhythm (1.00) with FCM treatment were not evident. Baseline characteristics of the FAIR-HF cohort have been pre- viously published.12 In brief, the clinical and laboratory fea- tures of patients at enrolment were similar between those Clinical correlates of change in calculated plasma randomized to FCM (n = 304) and those randomized to pla- volume status cebo (n = 155). The baseline characteristics of the 436 pa- tients included in this substudy are shown in Table 1. Their A total of 309 (70.9%) patients survived to week 24 and had mean weight-adjusted actual PV, weight-adjusted ideal PV, sufficient data to calculate change in PVS. From baseline to and PVS were 37.3 ± 3 mL/kg, 3036.6 ± 573.2 mL/kg, and week 24, mean change in PVS (ΔPVS) in this cohort was 5.5 ± 7.7%, respectively. Values of PVS ranged from 25% 3.5 ± 6.9%, with volume expansion (ΔPVS > 0%) evident to +24%. A PVS ≤0 or ˃0 was evident in 350 (80.3%) and 86 in 93 (30.1%) patients. Compared with those with volume ex- (19.7%) patients, respectively (Figure 1). The mean JVP was pansion, patients with decreasing volume status were more 1.9 cm with 9.2% of patients having an elevated JVP likely to improve their NYHA status by at least one class (>4 cm), and 35%, 23%, and 12% of patients having periph- (33.3% vs. 15.1%, 0.005) despite adjustment for treatment eral oedema, pulmonary oedema, and an S3 gallop, and the interaction term for PVS change and treatment respectively. (0.23 for interaction). In the subgroup of patients who re- On stratification, patients who were estimated to have a ceived FCM, NYHA class improved in 36.3% in those with relatively increased PV (i.e. a PVS > 0%) tended to be older ΔPVS ≤ 0% compared with 21.4% in those with ΔPVS > 0%. and female with biochemical markers of potentially greater Similarly, in the placebo-treated subgroup, NYHA class im- fluid retention such as a lower serum albumin, higher blood proved in 25% and 5.4% of those with ΔPVS ≤ 0% and >0%, urea nitrogen, and a lower estimated glomerular filtration respectively. In contrast, while improvements in exercise ca- rate than those with a PVS ≤ 0% (Table 1). They also had pacity, as reflected by Δ6MWD, was greater in those with poorer haemodynamics and less premorbid hypertension. In ΔPVS ≤ 0% (43.5 m vs. 26.8 m, 0.02), this became non- a multivariable model incorporating age, gender, systolic significant (0.13) after adjustment for treatment and the in- blood pressure, albumin, estimated glomerular filtration rate, teraction term for PVS change and treatment (0.65 for LVEF, and the use of diuretics, ACE inhibitors and β-blockers, interaction). only age (odds ratio 0.97, 0.02), systolic blood pressure (odds ratio 1.02, 0.01), and serum albumin (odds ratio 1.13, 0.01) independently predicted PVS. Calculated plasma volume status and outcomes in FAIR-HF Impact of ferric carboxymaltose on calculated Safety endpoints are listed in Table 2. During the study pe- plasma volume status and clinical congestion riod, 55 (13%) patients experienced the key safety endpoint of all-cause death or hospitalization, 9 (2%) died from any At baseline, mean PVS was similar in the FCM (5.3% ± 7.7%) cause, 8 (2%) experienced a cardiovascular death, 3 (1%) and placebo (6% ± 7.8%) groups. Over time, treatment with experienced a CHF death, 46 (11%) were hospitalized for FCM was associated with significant reductions from baseline any cause, and 25 (6%) died or were hospitalized for wors- in PVS at week 4 (2.5 ± 5.9% vs. 0.6 ± 4.3%), 12 ening CHF. (3.9 ± 6.8% vs. 0.2 ± 5.3%), and 24 (4.1 ± 7.4% A PVS cut-off of 4% was previously shown to be opti- vs. 2.0 ± 5.5%), compared with placebo [Figure 2A]. The mally predictive of outcomes in a large CHF cohort.11 In this ESC Heart Failure 2019; 6: 621–628 DOI: 10.1002/ehf2.12462 624 D.O. Okonko et al. Table 1 Baseline characteristics of FAIR-HF patients stratified by PVS All (N = 436) PVS ≤ 0% (N = 350) PVS > 0% (N = 86) P value Clinical variables Age, years 67.8 (10.71) 67.1 (10.54) 70.5 (11) 0.008 Male gender, n (%) 203 (46.6) 154 (44.0) 49 (57.0) 0.040 NYHA III, n (%) 361 (82.8) 288 (82.3) 73 (84.9) 0.635 Left ventricular ejection fraction, % 32.3 (5.7) 32.5 (5.61) 31.2 (5.94) 0.055 Ischaemic aetiology, n (%) 351 (80.5) 283 (80.9) 68 (79.1) 0.761 Prior CABG, n (%) 46 (10.6) 34 (9.7) 12 (14.0) 0.326 Prior PTCA, n (%) 61 (14.0) 48 (13.7) 13 (15.1) 0.862 Prior stroke, n (%) 29 (6.7) 24 (6.9) 5 (5.8) 0.815 History of atrial fibrillation, n (%) 131 (30.0) 107 (30.6) 24 (27.9) 0.695 History of hypertension, n (%) 352 (80.7) 291 (83.1) 61 (70.9) 0.014 History of diabetes mellitus, n (%) 120 (27.5) 103 (29.4) 17 (19.8) 0.080 Physical examination Systolic blood pressure, mm Hg 126.1 (14.71) 127 (14.52) 122.4 (14.98) 0.008 Diastolic blood pressure, mm Hg 76.4 (9.43) 77.1 (8.92) 73.5 (10.85) 0.001 Heart rate, bpm 71.3 (11.58) 71.5 (11.74) 70.2 (10.92) Weight, kg 76.9 (14.73) 79.8 (14.19) 65 (10.36) <0.001 2 Body mass index, kg/m 27.9 (4.78) 28.8 (4.62) 24.3 (3.68) <0.001 Hip/waist ratio, cm 1.1 (0.15) 1.1 (0.15) 1.1 (0.15) 0.289 Jugular venous pressure, cm 1.9 (2.22) 1.9 (2.16) 1.8 (2.49) 0.871 Peripheral oedema, n (%) 152 (34.9) 127 (36.3) 25 (29.1) 0.256 Pulmonary oedema, n (%) 99 (22.7) 80 (22.9) 19 (22.1) 0.888 Third heart sound (S3 gallop), n (%) 53 (12.2) 44 (12.6) 9 (10.5) 0.714 Six minute walk test distance, m 270.8 (106.83) 275 (106.4) 253.6 (107.43) 0.096 Quality of life KCCQ overall score 59 (20.05) 58.4 (20.16) 61.7 (19.48) 0.173 EQ-5D health score 54.2 (16.27) 54.2 (16.25) 54 (16.49) 0.922 Laboratory measurements Haemoglobin, g/dL 11.9 (1.29) 12.2 (1.18) 10.9 (1.14) <0.001 Haematocrit 0.4 (0.04) 0.4 (0.04) 0.3 (0.03) <0.001 Serum ferritin, μg/L 53.8 (57.8) 54.5 (59.31) 51.1 (51.39) 0.624 Transferrin saturation, % 17.4 (11.25) 17.7 (9.92) 16.1 (15.55) 0.242 C-reactive protein, mg/L 5 (4.33) 4.9 (4.33) 5.2 (4.34) 0.577 Sodium, mmol/L 140.7 (2.83) 140.8 (2.87) 140.4 (2.63) 0.221 Serum albumin, g/L 43.1 (2.78) 43.3 (2.72) 42.2 (2.83) 0.001 Alanine aminotransferase, U/L 19.8 (11.14) 20.2 (11.31) 18.5 (10.42) 0.231 Aspartate amiontransferase, U/L 22.8 (9.58) 22.7 (9.67) 23.1 (9.29) 0.752 Creatinine, mg/dL 1.2 (0.59) 1.1 (0.43) 1.5 (0.96) <0.001 2 GFR (MDRD), mL/min/1.73 m 63.7 (22.57) 65.1 (21.47) 58.1 (25.98) 0.010 Blood urea nitrogen, mg/dL 24.5 (12.87) 23.4 (11.81) 28.8 (15.86) 0.001 Calculated plasma volumes Ideal plasma volume, mL 3037 (573) 3153 (550) 2563 (395) <0.001 Actual plasma volume, mL 2843 (441) 2878 (445) 2698 (394) 0.001 Plasma volume status (PVS), % 5.5 (7.71) 8.2 (5.6) 5.5 (4.71) — Medications, % ACE inhibitor or ARB, n (%) 402 (92.2) 326 (93.1) 76 (88.4) 0.1751 β-blocker, n (%) 373 (85.6) 299 (85.4) 74 (86.0) 1.000 Aldosterone antagonist, n (%) 211 (48.4) 167 (47.7) 44 (51.2) 0.6303 Cardiac glycosides, n (%) 69 (15.8) 52 (14.9) 17 (19.8) 0.3217 Diuretic, n (%) 402 (92.2) 323 (92.3) 79 (91.9) 1.000 Data are means (SD) or numbers (frequency). ACE, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blockers; CABG, coronary artery bypass grafting; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; MDRD, modification of diet in renal disease equation; PTCA, percutaneous coronary angioplasty; PVS, plasma volume status. FAIR-HF population, patients with a baseline PVS > 4% ex- treatment assignment (adjusted HR 1.88, 95% CI 1.01 to perienced a higher incidence of all safety endpoints 3.51, 0.046), JVP (adjusted HR 2.18, 95% CI 1.05 to 4.51, than those with a PVS ≤ 4%, with the difference in 0.04), or the presence of pulmonary (adjusted HR 1.88, incidence statistically significant for the key safety endpoint 95% CI 1.01 to 3.50, 0.047) or peripheral oedema (adjusted of all-cause death or hospitalization. In Cox analyses, a HR 1.89, 95% CI 1.01 to 3.52, 0.045). As a continuous vari- PVS > 4% was associated with an 89% (unadjusted able, higher PVS values were also associated with a greater HR 1.89, 95% CI 1.05 to 3.40, 0.03) greater risk of the key incidence of all-cause death or hospitalization (unadjusted endpoint (Figure 3) even after bivariate adjustment for HR 1.07, 95% CI 1.03 to 1.12, P < 0.001). ESC Heart Failure 2019; 6: 621–628 DOI: 10.1002/ehf2.12462 Effect of ferric carboxymaltose on calculated plasma volume status and clinical congestion: a FAIR-HF substudy 625 Figure 1 Distribution of plasma volume status (PVS) in FAIR-HF. tested this hypothesis and the prognostic utility of PVS, a novel index of congestion, in the large FAIR-HF data set and made several observations. First, volume status, as estimated by the PVS equation, was mildly contracted in this stable pop- ulation and related to age, gender, and biochemical markers of fluid overload. Second, compared with placebo, IV iron therapy with FCM was associated with greater reductions in PVS and other measures of congestion such as weight. The impact of FCM on PVS and weight was evident early at 4 weeks supporting a potential direct decongestive effect of iron repletion in CHF. Third, an increase in PVS over time was associated with worsening symptoms and exercise ca- pacity irrespective of treatment allocation. Fourth, higher PVS values predicted an increased risk of death or hospitaliza- tion over the coming 6 months. Plasma volume status was marginally contracted in the FAIR-HF cohort to a degree comparable with other stable CHF patients. Using tracer dilution techniques, Bonfils et al. and Adlbrecht et al. reported actual PV values of 37 ± 6 mL/kg and 37 ± 4 mL/kg, respectively,14,15 in line with Discussion our calculated value of 37 ± 3 mL/kg. This contrasts to the higher PV levels measured in decompensated CHF patients Iron deficiency escalates symptoms and exercise intolerance (58 ± 3 mL/kg) and healthy controls (43 ± 3 mL/kg)16 and re- in CHF and might do so by promoting fluid retention. We flects the impact of optimal medical and device-based Figure 2 Change in markers of congestion in FAIR-HF. Alterations from baseline to week 24 in PVS (A), Hct (B), weight (C), and peripheral oedema (D) are shown. A total of 372, 371, and 309 patients had data for analysis at weeks 4, 12, and 24, respectively. ANOVA, analysis of variance; FCM, ferric carboxymaltose; PVS, plasma volume status. ESC Heart Failure 2019; 6: 621–628 DOI: 10.1002/ehf2.12462 626 D.O. Okonko et al. Table 2 Safety endpoints stratified by baseline PVS cut-off PVS ≤ 4% (n = 255) PVS > 4% (n = 181) Number Incidence/ (100 Number Incidence/ (100 Hazard Endpoint or event of events patient-year at risk) of events patient-year at risk) ratio 95% CI P value a Any hospitalization or death 23 20 (16.7) 32 25 (31.6) 1.89 (1.05–3.40) 0.031 Any death 3 3 (2.4) 6 6 (7.1) 2.94 (0.74–11.76) 0.11 Cardiovascular death 3 3 (2.4) 5 5 (5.9) 2.45 (0.58–10.25) 0.21 Death due to worsening CHF 1 1 (0.8) 2 2 (2.4) 2.93 (0.27–32.35) 0.36 Any hospitalization 20 17 (14.2) 26 21 (26.5) 1.86 (0.98–3.53) 0.053 Any hospitalization for any 15 14 (11.6) 18 14 (17.3) 1.48 (0.71–3.11) 0.30 cardiovascular reason Any hospitalization for 7 6 (4.9) 9 7 (8.4) 1.74 (0.58–5.18) 0.31 worsening CHF Any hospitalization for any 18 17 (14.1) 24 18 (22.2) 1.57 (0.81–3.05) 0.18 cardiovascular reason or death Any hospitalization for worsening 10 9 (7.3) 15 12 (14.4) 1.98 (0.84–4.71) 0.11 CHF or death Any hospitalization or death 18 17 (14.1) 23 17 (21.0) 1.48 (0.76–2.91) 0.25 for any cardiovascular reason Any hospitalization or death for 8 7 (5.7) 11 8 (9.6) 1.70 (0.62–4.69) 0.30 worsening CHF Only unplanned hospitalizations and deaths are summarized. CHF, chronic heart failure; PVS, plasma volume status. a Key endpoint. therapies on volume status. Consistent with the aforemen- between calculated and measured PV levels,11 supported tioned PV levels, and the fact that the ideal PV equation our use of the PVS equation to gauge changes in intravascular was originally derived in normal individuals, it is unsurprising filing with IV FCM. that patients in FAIR-HF had mean PV levels that were ~5% Treatment with FCM was associated with reductions in PVS lower than their estimated ideal. This contraction of PV in at 4 weeks and the fact that this was paralleled by attenua- CHF is important as it likely allows the failing myocardium tions in weight, which is a clinical barometer of congestion, to continue to operate on a reasonable portion of the suggests that FCM might have had a true and early deconges- Frank–Starling curve. tive effect. This is consistent with the FERRIC-HF trial that Concordant with its potential utility as a surrogate of vol- showed a 4.6 kg relative reduction in weight with IV iron su- ume overload, calculated PVS was higher in patients with fea- crose compared with control over 16 weeks.8 It also accords tures of greater disease severity such as poorer with Toblli et al. who reported a 1.5 kg/m2 relative reduction haemodynamics and correlated to key biochemical markers in body mass index with IV iron sucrose vs. saline over of congestion. This included serum albumin that is known 6 months.18 In contrast, no meaningful changes in other to modulate plasma oncotic pressure.17 These associations, physical markers of congestion were seen with FCM. This together with our prior demonstration of a good correlation likely reflects the subjective nature of physical examinations, especially in the setting of multicentre trials. While definitive Figure 3 Baseline PVS categories (≤4% vs. >4%) and survival. PVS, answers cannot be given, several mechanisms might explain plasma volume status. the reduction in PVS seen with FCM. Treatment with FCM might have been linked to attenua- tions in PVS for a number of reasons. First, it could be argued that decrements in PVS merely reflect the increments in Hct seen with FCM and are not truly indicative of a change in con- gestion. However, FCM treatment was also accompanied by reductions in weight. Given that weight is a clinically accepted gauge of short-term PV changes and that no evidence exists to suggest that FCM triggers non-oedematous weight loss, it is likely that FCM truly diminished congestion. This diminution might have been indirect by virtue of iron repletion improving myocardial function leading to downstream improvements in global clinical status and congestion. Alternatively, FCM might have improved renal function19 and/or directly modulated key aspects of the CHF syndrome such as the neurohormonal axis to trigger decongestion. This is plausible given that ID ESC Heart Failure 2019; 6: 621–628 DOI: 10.1002/ehf2.12462 Effect of ferric carboxymaltose on calculated plasma volume status and clinical congestion: a FAIR-HF substudy 627 enhances circulating catecholamine levels that promote con- repletion on volume status as measured using radioisotope gestion partly by activating the renin–angiotensin– techniques. For now, the results presented in this analysis aldosterone cascade.6,7,20 This direct mode of action appears should be considered hypothesis generating. more credible given that 4 weeks is conventionally too short In summary, IV iron therapy with FCM is associated with for any agent to significantly remodel the failing myocardium, reductions in PVS and weight even as early as 4 weeks after and IV iron repletion in CHF has yet to be shown to improve treatment initiation. This supports a potential decongestive LVEF on echocardiography.2,8 Irrespective of the underlying effect of IV iron therapy in CHF that might be one mechanism mechanism(s), changes in PVS over time correlated to alter- via which iron repletion improves symptoms, quality of life, ations in other indices of CHF status. and exercise performance in this population. Calculated Temporal increases in PVS were accompanied by worsen- PVS, a simple novel marker of fluid overload, predicted ing symptoms. This likely reflects the combination of im- deaths and hospitalizations in the FAIR-HF cohort irrespective paired tissue oxygenation because of lower haemoglobin of treatment assignment. levels, decreased effort tolerance because of weight gain, and impaired lung and skeletal muscle function as a result of tissue congestion. That changes in PVS were linked to Acknowledgements changes in key markers of survival suggested that it too might also be related to mortality. None to declare. Similar to the findings in the larger VaL-HeFT population,11 calculated PVS as a continuous or dichotomized (≤4% vs. >4%) variable forecasted deaths and hospitalizations in the FAIR-HF cohort. Moreover, it did so after adjustment Conflict of interest for treatment allocation implying that the associations eluci- dated here were not simply driven by FCM. This is consistent The FAIR-HF trial was supported by Vifor Pharma, Glattbrugg, with the ominous nature of other surrogates of congestion Switzerland. All authors had full access to the study data, de- such as elevated pulmonary capillary wedge pressures, ultra- cided to submit the report for publication, and assume re- sound indices of raised intracardiac filling, jugular venous dis- sponsibility for the completeness and accuracy of the data, tension, a third heart sound, congestive symptoms, and and the content and integrity of the report. C.M. and S.C. natriuretic peptides.21–25 Calculated PVS might be prognostic are employees of Vifor. D.O.O. has received speaker’s fees because it truly reflects fluid retention that could be a marker and research support from Vifor and Pharmacosmos. S.D.A. or mediator of CHF progression. Alternatively, it may only be has received fees for consulting and/or speaking from Bayer, mirroring the prognostic implications of weight and Hct or Boehringer Ingelheim, Novartis, Servier, and Vifor. S.D.A. has other factors in CHF that modulate these variables. received research grants from Abbott Vascular and Vifor. G.P. Our study has limitations. First, it is a retrospective post is a member of Committees in trials and registries sponsored hoc analysis of the FAIR-HF trial with all the inherent weak- by Vifor, Novartis, Bayer, and Servier. P.P. has received con- nesses this entails including the inability to establish a causal sulting and speaker’s fees and research grants from Vifor. relation between correlated variables. Second, like all surro- gates of congestion, the PVS equation is not perfect, underes- timates true volume status, and has so far only shown Funding modest correlation with invasively determined PV in CHF pa- tients in a retrospective study.11 Additional refinements of The FAIR-HF trial was supported by Vifor Pharma, Glattbrugg, this equation are likely needed but, ultimately, the true utility Switzerland. D.O.O. is supported by the British Heart Founda- of PVS can only be gauged via prospective interventional tion (grant number FS/14/77/30913), the NIHR Biomedical studies. Third, we did not quantify PV directly, and further Research Centre at Guy’s and St Thomas’ NHS foundation studies are needed to investigate the impact of IV iron trust and King’s College London. References 1. 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