ESC HEART FAILURE ORIGINAL RESEARCH ARTICLE ESC Heart Failure 2020; 7: 2621–2628 Published online 7 July 2020 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/ehf2.12842 Prevalence and prognostic impact of subclinical pulmonary congestion at discharge in patients with acute heart failure Mercedes Rivas-Lasarte1 , Alba Maestro1 , Juan Fernández-Martínez1, Laura López-López1, Eduard Solé- González2 , Miquel Vives-Borrás1, Santiago Montero3 , Nuria Mesado1, Maria J. Pirla1, Sonia Mirabet1, Paula Fluvià4, Vicens Brossa1, Alessandro Sionis1 , Eulàlia Roig1, Juan Cinca1 and Jesús Álvarez-García1* 1 Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, CIBERCV, Universitat Autónoma de Barcelona, Barcelona, Spain; 2Cardiology Department, Hospital del Mar, Barcelona, Spain; 3Cardiology Department, Hospital Germans Trias i Pujol, Universitat Autónoma de Barcelona, Barcelona, Spain; 4Cardiology Department, Hospital Doctor Josep Trueta, Gerona, Spain Abstract Aims Residual pulmonary congestion at hospital discharge can worsen the outcomes in patients with heart failure (HF) and can be detected by lung ultrasound (LUS). The aim of this study was to analyse the prevalence of subclinical pulmonary con- gestion at discharge and its impact on prognosis in patients admitted for acute HF. Methods and results This is a post-hoc analysis of the LUS-HF trial. LUS was performed by the investigators in eight chest zones with a pocket device. Physical exam was subsequently performed by the treating physicians. Primary outcome was a combined endpoint of rehospitalization, unexpected visit for HF worsening or death at 6- month follow-up. Subclinical pulmo- nary congestion at discharge was defined as the presence of ≥5 B-lines in LUS in absence of rales in the auscultation employing the area under the ROC curve. At discharge, 100 patients (81%) did not show clinical signs of pulmonary congestion. Of these, 41 had ≥5 B-lines. Independent factors related with the presence of subclinical pulmonary congestion were anaemia, higher New York Heart Association (NYHA) class, and N terminal pro brain natriuretic peptide (NT-proBNP). After adjusting by propen- sity score analysis including age, renal insufficiency, atrial fibrillation, NYHA class, NT-proBNP levels, clinical congestion, and the trial intervention, the presence of subclinical pulmonary congestion at discharge was a risk factor for the occurrence of the primary outcome (hazard ratio 2.63; 95% confidence interval: 1.08–6.41; P = 0.033). Conclusions Up to 40% of patients considered ‘dry’ according to pulmonary auscultation presents subclinical congestion at hospital discharge that can be detected by LUS and implies a worse prognosis at 6- month follow-up. Comorbidities, high values of natriuretic peptides, and higher NYHA class are the factors related with its presence. Keywords Heart failure; Lung ultrasound; Pulmonary congestion; Prognosis Received: 14 February 2020; Revised: 14 April 2020; Accepted: 29 May 2020 *Correspondence to: Jesús Álvarez-García, Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, CIBERCV, Universitat Autónoma de Barcelona, Barce- lona, Spain. Tel: +34 93 556 5940; Fax: +34 93 556 5603. Email: jalvarezg@santpau.cat Introduction because of the persistence of subclinical pulmonary fluid over- load. Typically, pulmonary congestion has been assessed Pulmonary congestion is a key feature in the pathophysiology through symptoms and signs from physical examination, as of acutely decompensated heart failure (ADHF), and residual well as other tools such as biomarkers or chest X-ray.5 How- congestion at the time of hospital discharge is one of the main ever, these methods are subject to significant inter-observer contributors of readmission risk.1–3 Moreover, unacceptably variability and can be unreliable.6 high rates of hospital readmission have been observed even Lung ultrasound (LUS) has emerged as a simple, non- in patients without detectable clinical congestion,4 possibly invasive, semi-quantitative tool for the detection of © 2020 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. 2622 M. Rivas-Lasarte et al. pulmonary congestion. This technique is based on the obser- guidelines,12 but treating physicians were encouraged to vation of vertical echogenic lines arising from the pleura (B- modify diuretic therapy in accordance with the number of lines) in a pattern that resembles the tail of a comet. The B-lines in the LUS-guided group. The protocol was approved number of B-lines has been found to be a reliable indicator by the ethics committee of the study institution, and it was of the presence of extravascular lung water and has allowed conducted in accordance with the principles of the Declara- the identification of heart failure (HF) patients with a worse tion of Helsinki. Written informed consent was obtained from prognosis.7–10 In addition, the LUS-HF trial has recently all patients. showed that the assessment of pulmonary congestion by LUS helps to guide treatment in patients with HF and to im- prove their prognosis.11 However, there is a paucity of data Lung ultrasound protocol about the prevalence of subclinical pulmonary congestion and its potential prognostic impact in patients discharged Lung ultrasound studies were performed with a pocket without clinically lung fluid overload. ultrasound device (VScan®; GE Healthcare, Chicago, IL, USA) Thus, the aim of this study was to identify the prevalence with a cardiac phased array transducer. According to a cur- of subclinical pulmonary congestion at discharge, related fac- rent expert consensus document,13 LUS was recorded at four tors, and its prognostic significance in patients admitted for sites in each hemithorax with the transducer perpendicular to ADHF. the ribs and at a 16 cm imaging depth being the patient in the semi-recumbent position (Figure 1). Video clips were ob- tained and stored for later review. The number of B-lines re- ported in real time was the sum of the B-lines visualized in Methods each thoracic site, and investigators were blinded to clinical findings. Additional investigations assessing clinical conges- Study design tion (physical exam and natriuretic peptides) were performed at the same time as the LUS studies by the treating This is a post-hoc analysis of the LUS-HF trial.11 Briefly, this physicians. was a single-centre, single-blind, randomized clinical trial evaluating whether a LUS-guided follow-up protocol im- Subclinical pulmonary congestion proves the outcomes in patients with HF. Patients were re- quired to be aged ≥18 years and to have been hospitalized Subclinical pulmonary congestion at discharge was defined as for ADHF defined by shortness of breath, pulmonary conges- the presence of B-lines in the LUS exam in absence of rales in tion on X-ray, and high N terminal pro brain natriuretic pep- the auscultation. In order to select a cut-off of B-lines, we tide (NT-proBNP) values in the first 24 h of admission (cut- employed the area under the ROC curve to identify the best off values: 450 ng/L in patients aged <50 years; >900 ng/L number of them to predict the primary outcome applying in patients aged 50–75 years; >1800 ng/L in patients aged the Youden criteria (see Supporting Information, Figure S1). >75 years). Exclusion criteria were inability to attend Thus, subclinical pulmonary congestion at discharge was de- follow-up visits, a life expectancy of <6 months, fined as the presence of ≥5 B-lines in the LUS test in absence haemodialysis, and the presence of severe lung disease of rales in the auscultation. For this post-hoc analysis, pa- preventing LUS interpretation. The primary endpoint was a tients were compared according to the presence of clinical composite of urgent visit, hospitalization for worsening HF, (rales in auscultation) or subclinical pulmonary congestion and death during follow-up. Urgent visits for worsening HF at discharge, irrespective of the intervention received in the were defined as visits to the emergency department or un- LUS-HF trial. scheduled visits to the HF unit as a result of signs and/or symptoms of worsening HF that required intravenous diuretic treatment or diuretic increase with an hospital stay of <24 h. Statistical analysis Hospitalization for worsening HF was defined as a stay in hos- pital for >24 h mainly as a result of signs and/or symptoms of Continuous variables are reported as the mean ± standard worsening HF. Secondary outcomes were the separate com- deviation, or median and interquartile range, as appropriate. ponents of the primary outcome. Visits were scheduled in Differences in continuous variables were tested by ANOVA the HF clinic at 14, 30, 90, and 180 days after discharge. Eligi- or Student’s t-test for independent samples. Categorical vari- ble patients were randomized at discharge to either the LUS ables were presented as frequency and percentage. Differ- non-guided (control) group or the LUS-guided group. LUS ences in the categorical variables were assessed by the χ 2 was performed in both groups, but the result was only avail- test or by Fisher’s exact test. To identify the factors related able to the treating physician in the LUS-guided arm. In both with the presence of subclinical pulmonary congestion at groups, patients were treated according to current discharge, a stepwise multivariable logistic regression was ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 Subclinical pulmonary congestion at heart failure discharge 2623 Figure 1 (A) LUS protocol with eight scan sites, four in each hemithorax; (B) example of B-lines; (C) Flow-chart study according to the presence of rales and ≥5 B-lines in the LUS exam. HF, heart failure; LUS, lung ultrasound. performed. Time to the primary outcome was evaluated Results with the use of Kaplan–Meier curves. A propensity score to determine the likelihood of having subclinical pulmonary Prevalence of pulmonary congestion at discharge congestion was created including age, renal insufficiency, and clinical characteristics of the study atrial fibrillation, anaemia, NYHA class, NT-proBNP levels, population and the presence of systemic clinical congestion (oedema, jugular ingurgitation, and hepatomegaly). Cox proportional hazards models were performed to analyse the prognostic Out of 123 patients included in the LUS-HF trial from 10 No- role of the presence of subclinical pulmonary congestion ad- vember 2016 to 19 June 2018, 100 (81%) were discharged justed by the propensity score and the intervention group. without rales in the auscultation. In this subgroup of patients The assumption of proportionality of hazards was tested considered clinically without pulmonary congestion, LUS test based on Schoenfeld residuals. Two-sided significance levels detected ≥5 B-lines in 41 patients. Therefore, the prevalence of 0.05 were used in all analyses. Data were analysed using of subclinical pulmonary congestion at discharge in the study STATA SE Version 13.0 (StataCorp LLC, College Station, TX, population was 33% (Figure 1). This prevalence decreased sig- USA). nificantly during the follow-up (Figure 2, Panel A), especially Figure 2 (A) Prevalence at discharge and evolution of the pulmonary congestion patterns during the 6- month follow-up. (B) Short-term evolution of the pulmonary congestion in patients with subclinical pulmonary congestion at discharge. SPC, subclinical pulmonary congestion. ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 2624 M. Rivas-Lasarte et al. because of an early increase in the proportion of patients After adjusting by a propensity score including age, renal with rales at the 15 day visit. In fact, nearly 50% of patients insufficiency, atrial fibrillation, anaemia, NYHA class, with subclinical pulmonary congestion at discharge devel- NT-proBNP levels, the presence of systemic clinical conges- oped clinical signs of lung fluid overload before the first am- tion (oedema, jugular ingurgitation, and hepatomegaly), and bulatory check-up (Figure 2, Panel B). the group intervention (LUS-guided strategy), the presence Table 1 compares the clinical characteristics of the study of subclinical pulmonary congestion at discharge was a risk population according to the presence of pulmonary conges- factor for the occurrence of primary outcome (HR 2.63; 95% tion at discharge. Briefly, patients with subclinical pulmonary CI: 1.08–6.41, P = 0.033), similar to being discharged with congestion were mostly male, older, and had more cardiovas- rales (HR 2.69; 95% CI: 1.03–7.01, P = 0.043). Figure 3 illus- cular risk factors and comorbidities than those without sub- trates the Kaplan–Meier curves for the occurrence of the pri- clinical pulmonary fluid overload. Moreover, they had mary outcome. Interestingly, the survival curves for patients higher frequency of prior HF history, ischemic heart disease, with subclinical pulmonary congestion and rales were very atrial fibrillation, and a more advanced HF stage reflected similar. by higher NYHA class, plasma levels of natriuretic peptides, and other markers of residual congestion in physical examina- tion. Indeed, patients with subclinical pulmonary congestion Discussion were discharged more frequently on loop diuretics and at a higher dose than those without subclinical pulmonary con- Main findings gestion. Overall, patients with subclinical pulmonary conges- tion at discharge represented an intermediate HF severity This is the first study describing the prevalence and prognosis group, between patients without rales and no B-lines in the of the subclinical pulmonary congestion at discharge in pa- LUS exam and subjects with clinically detectable congestion. tients admitted for ADHF based on LUS criteria. Our results showed that up to 40% of patients considered ‘lung-dry’ ac- cording to the auscultation presented subclinical fluid over- Factors related to the presence of subclinical load detected by LUS. This unnoticed clinical condition was pulmonary congestion observed more frequently in patients with anaemia, higher NT-proBNP levels, and in those with a higher NYHA class Among patients without rales, anaemia [odds ratio (OR) 8.60; and implied a worse prognosis at 6- month follow-up, compa- 95% confidence interval (CI): 2.25–32.89], NYHA III class rable with those with clinical pulmonary congestion. (3.13; 95% CI: 1.08–9.04), and NT-proBNP (per each 100 ng/L increase) (OR 1.04; 95% CI: 1.02–1.06) were the in- dependent factors related with the presence of subclinical Prognosis of residual congestion in heart failure pulmonary congestion at discharge (Table 2) after the multi- variable analysis. Figure S2 shows the area under the ROC Fluid congestion is still present before discharge in up to half curve of this model (0.829; 95% CI: 0.75–0.91). of ADHF patients, and the majority of those who are discharged without any clinical sign of fluid retention will de- velop it at short term.4 Moreover, pulmonary congestion at Prognostic impact of subclinical pulmonary discharge and early recurrence after are both associated with congestion at discharge a worse prognosis. Thus, a proper lung decongestion therapy during HF hospitalization and a close clinical monitoring dur- Patients with subclinical pulmonary congestion at discharge ing the first weeks after discharge are main goals for both cli- presented a higher incidence of the primary outcome during nicians and HF care pathways.14,15 Our results highlight this the 6- month follow-up than those without subclinical pulmo- clinical situation, showing that up to 50% of patients were nary congestion [19 (46%) vs. 9 (15%), P < 0.001, respec- discharged clinically fluid overloaded or with subclinical pul- tively]. Moreover, this difference could be attributed to a monary congestion. Furthermore, half of patients developed higher HF admission rate in the group of patients with sub- rales before 2 weeks in the latest group. clinical pulmonary congestion [15 (37%) vs. 4 (7%), Evaluation and monitoring of fluid excess status in patients P = 0.001, respectively]. Although there was not a significant admitted for ADHF is currently based on clinical history, phys- difference in death rates between groups, a trend to a higher ical examination, chest X-ray, and natriuretic peptides.5 How- mortality rate was observed in patients with subclinical pul- ever, all these have inherent substantial inter-observer monary congestion [3 (7%) vs. 0 (0%), P = 0.066, respectively]. variability and may be non-specific,6,16 and plasma levels of Interestingly, outcome rates between patients with subclini- biomarkers have a limited capacity to assess quantitatively cal pulmonary congestion and patients with rales at discharge the extent of fluid retention.17 Right heart catheterization were similar as is shown in Table 3. and chest-computed tomography are much more accurate ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 Subclinical pulmonary congestion at heart failure discharge 2625 Table 1 Clinical characteristics of the study population according to the presence of pulmonary congestion at discharge Without subclinical pulmonary With subclinical pulmonary With clinical pulmonary P a congestion (n = 59; 48%) congestion (n = 41; 33%) P value congestion (n = 23; 19%) value Age (years) 65 ± 14 70 ± 10 0.051 75 ± 9 0.002 Male sex 41 (69) 30 (73) 0.690 18 (78) 0.720 2 BMI (kg/m ) 27 ± 5 26 ± 6 0.224 28 ± 5 0.354 Cardiovascular risk factors Hypertension 38 (64) 31 (76) 0.234 20 (87) 0.104 Dyslipidaemia 39 (66) 29 (71) 0.625 16 (70) 0.878 Diabetes 19 (32) 18 (44) 0.233 13 (56) 0.115 Smokers or former smoker 34 (57) 30 (63) 0.131 14 (61) 0.294 Comorbidities COPD 12 (20) 11 (27) 0.448 8 (35) 0.383 b Renal insufficiency 12 (20) 22 (54) 0.001 12 (52) <0.001 Stroke 10 (17) 6 (15) 0.756 3 (13) 0.894 c Anaemia 4 (7) 13 (32) 0.001 8 (35) 0.002 Charlson index 2.4 ± 1.6 3.0 ± 1.6 0.073 3.0 ± 1.5 0.064 Past CV history Previous HF 24 (41) 29 (71) 0.003 15 (65) 0.007 HF admissions in prior year 16 (27) 18 (44) 0.081 10 (43) 0.157 Ischaemic HF aetiology 22 (37) 20 (49) 0.252 12 (52) 0.353 Atrial fibrillation 26 (44) 26 (63) 0.057 16 (70) 0.050 Type of HF 0.667 0.197 HFrEF 31 (53) 25 (63) 12 (52) HFmrEF 15 (26) 8 (20) 2 (9) HFpEF 12 (21) 7 (18) 9 (39) LVEF (%) 38 ± 13 39 ± 14 0.943 42 ± 17 0.461 Characteristics at discharge Systolic blood pressure 113 ± 19 112 ± 17 0.657 111 ± 16 0.789 (mmHg) Heart rate (bpm) 68 ± 10 70 (13) 0.585 66 ± 10 0.411 NYHA class II 47 (80) 21 (51) 0.002 14 (61) 0.009 III 10 (17) 20 (49) 9 (39) 6MWT (m) 374 ± 108 320 ± 103 0.019 277 ± 101 0.001 Minnesota LWHF 55 ± 23 54 ± 21 0.853 48 ± 21 0.429 2 eGFR (mL/kg/min/1.73 m ) 71 ± 24 55 ± 23 0.001 57 ± 22 0.002 Albumin (g/L) 40 ± 4 38 ± 3 0.023 38 ± 3 0.026 Bilirubin (umol/L) 15 ± 8 15 ± 8 0.645 14 ± 7 0.629 GGT (UI/l) 44 (32–108) 68 (29–100) 0.908 47 (23–75) 0.569 NT-proBNP (ng/L) 1,071 (621–1947) 3,235 (1,559–5,799) <0.001 3,088(1,073–6,086) <0.001 Jugular ingurgitation 3 (5) 11 (27) 0.002 48 (11) <0.001 Leg oedema 3 (5) 8 (20) 0.023 10 (44) <0.001 Hepatomegaly 3 (5) 11 (27) 0.002 8 (35) 0.001 Any sign of clinical 9 (15) 17 (41) 0.003 23 (100) <0.001 congestion No signs of clinical 50 (85) 24 (59) 0.003 0 (0) <0.001 congestion Number of LUS B-lines 2 (1–3) 7 (6–13) <0.001 7 (5–9) <0.001 Treatment at discharge Loop diuretics 36 (61) 36 (88) 0.011 22 (97) <0.001 Mean furosemide dose or 22 ± 24 53 ± 31 <0.001 56 ± 26 <0.001 equivalent (mg/day) Thiazide diuretics 3 (5) 0 (0) 0.341 1 (4) 0.607 ACE inhibitors/ARB 46 (78) 36 (88) 0.208 17 (74) 0.321 Sacubitril/valsartan 3 (5) 1 (2) 0.963 0 (0) 0.475 Beta-blocker 51 (86) 32 (78) 0.272 21 (91) 0.318 Mineralocorticoid antagonist 37 (63) 25 (61) 0.860 12 (52) 0.676 Implantable cardioverter- 7 (12) 8 (20) 0.292 5 (22) 0.435 defibrillator Cardiac resynchronisation 3 (13) 2 (5) 0.337 3 (13) 0.493 therapy Abbreviations: 6MWT, 6 min walk test; ACE inhibitor, angiotensin converting–enzyme inhibitor; ARB, angiotensin-receptor blocker; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CV, cardiovascular; eGFR, estimated glomerular filtration rate (Modifica- tion of Diet in Renal Disease Study formula); HF, heart failure; HFmrEF, heart failure with mid-range ejection fraction; HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; LVEF, left ventricular ejection fraction; LUS, lung ul- trasound; Minnesota LWHF, Minnesota Living With Heart Failure quality of life scale; NT-proBNP, amino terminal pro brain natriuretic pep- tide; NYHA, New York Heart Association. Data are expressed as number (%), mean ± standard deviation, or median (interquartile range), as appropriate. P value refers to the comparison of the three groups. a 2 Renal insufficiency refers to estimated glomerular filtration rate <60 mL/min/1.73 m . b c Anaemia refers to haemoglobin <13 g/dL in man and <12 g/dL in women. ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 2626 M. Rivas-Lasarte et al. Table 2 Independent predictors for subclinical pulmonary How should subclinical pulmonary congestion be congestion defined? Odds ratio (95% confidence P interval) value There is not a standardized definition for subclinical pulmo- Anaemia 8.60 (2.25–32.89) 0.002 nary congestion. Previous authors have reported several NYHA III class 3.13 (1.08–9.04) 0.035 NT-proBNP (per each1.04 (1.02–1.06) 0.001 cut-off values for B-lines with prognostic significance accord- 100 ng/L) ing to the LUS protocol performed and the clinical Abbreviations: NT-proBNP, amino terminal pro brain natriuretic setting.9,10,19,21,22,24,25 An expert consensus document was peptide; NYHA, New York Heart Association. recently released describing the checklist for quantification of pulmonary congestion by LUS in HF,13 but no specific num- methods to assess pulmonary fluid overload, but both cannot ber of B-lines was proposed. Our proposal is based on the be used repeatedly in the day-to-day clinical practice. Thus, fact that ≥5 B-lines at discharge showed the best discriminat- LUS emerges as a promising predictive test easy to perform, ing value for the event risk. non-invasive, and cheap. Indeed, several studies have re- ported the prognostic capacity of the presence of B-lines in HF,7–10,18–23 although none of them has analysed the perfor- Clinical implications mance of B-lines in the absence of other markers of HF con- gestion. To the best of our knowledge, this is the first study Hospital readmission of patients with HF is a major public showing the prognostic capacity of the presence of B-lines health problem, and residual pulmonary congestion at dis- in patients in whom their treating physicians considered them charge is one of the leading responsible conditions. In last properly lung decongested. From that perspective, subclinical years, LUS has emerged as an attractive tool in HF because pulmonary congestion seems to have similar deleterious ef- of it is a rapid point-of-care test with a fast learning curve fect to overt clinical pulmonary congestion, with more than and a high inter-observer agreement.1,26,27 Moreover, our two-fold higher risk of the primary outcome. group recently showed that a LUS-guided strategy signifi- Table 3 Outcomes according to the presence of pulmonary congestion at discharge Without subclinical pulmonary With subclinical pulmonary With clinical pulmonary P a congestion (n = 59; 48%) congestion (n = 41; 33%) P value congestion (n = 23; 19%) value Primary outcome 9 (15) 19 (46) <0.00111 (48) <0.001 HF admission 4 (7) 15 (37) <0.0018 (35) <0.001 Urgent visit for6 (10) 6 (15) 0.499 4 (17) 0.636 worsening HF Death 0 (0) 3 (7) 0.066 2 (9) 0.038 Abbreviation: HF, heart failure. Data are expressed as number (%). P value refers to the comparison of the three groups. a Figure 3 Kaplan–Meier survival curves for the occurrence of the primary endpoint according to the presence of subclinical pulmonary congestion at discharge. SPC, subclinical pulmonary congestion. ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 Subclinical pulmonary congestion at heart failure discharge 2627 cantly improved the combined endpoint of urgent visit, hos- Acknowledgements pitalization for worsening HF, and death during a 6 month follow-up in patients after HF admission.11 Then, it is conceiv- We thank Dr Antonio Barros Membrilla, Dr Pelayo Torner, able that adding LUS to clinical practice will reinforce the abil- and Dr Xavier García-Moll for their contributions to the inclu- ity of clinicians to promptly detect and treat fluid overload sion of patients. and, ultimately, improve the prognosis of patients with HF. In addition, we have identified that patients with anaemia, higher NYHA class, and high levels of natriuretic peptides at discharge are at risk for presenting residual lung congestion Conflict of interest and therefore, require a close follow-up. None declared. Study limitations Funding The single-centre design of this study may hamper the broader applicability of our results. However, the wide inclu- M.R.-L. received a Río Hortega grant (CM17/00028) from the sion criteria and the feasibility of the follow-up protocol sup- Instituto de Salud Carlos III and a “Magda Heras” grant from port the assumption that the LUS technology can be applied the Spanish Society of Cardiology. J.A.-G. received a grant in other centres. The 5 B-lines cut-off based on a 2 s clip from the Daniel Bravo Andreu Private Foundation. This work length could underestimate the number of B-lines, and there- was supported by the Spanish Ministerio de Economia y fore, further studies are needed to be validated for longer clip Competitividad, Instituto de Salud Carlos III, Centro de lengths and higher-end ultrasound systems in special popula- Investigación Biomédica en Red Enfermedades tions such as obese patients.28,29 As this is a post-hoc analysis, Cardiovaculares, CIBERCV (CB16/11/00276), and the Fondo we cannot exclude a higher rate of false positives because of Europeo de Desarrollo Regional (FEDER). multiple testing and possible selection bias. We consider our study as hypothesis generating and acknowledge the need of validation in a prospective trial, especially with the calcu- Supporting information lated cut-off of 5 B-lines. Additional supporting information may be found online in the Supporting Information section at the end of the article. Conclusions Figure S1: Area under the ROC curve of the ≥5 B-lines cutoff to predict the primary outcome in patients without rales at Up to 40% of patients considered ‘dry’ according to pulmo- discharge. nary auscultation presents subclinical congestion at hospital Se: sensitivity; Sp: specificity; PPV: positive predictive value; discharge that can be detected by LUS and implies a worse NPV: negative predictive. prognosis at 6 month follow up. Comorbidities, high values Figure S2: Area under the ROC curve of the model predicting subclini- of natriuretic peptides, and higher NYHA class are the factors cal pulmonary congestion containing the following variables: anaemia, related with its presence. NYHA class and NT-proBNP levels. References 1. Picano E, Scali MC, Ciampi Q, Lichten- DM, Dittrich H, Damman K, Pérez-Calvo acute heart failure. Circ Heart Fail 2015 stein D. Lung ultrasound for the cardiol- JI, Voors AA. Prevalence, predictors and 2019; 8: 741–748. ogist. JACC Cardiovasc Imaging 2018; 11: clinical outcome of residual congestion 5. Gheorghiade M, Follath F, Ponikowski P, 1692–1705. in acute decompensated heart failure. Barsuk JH, Blair JEA, Cleland JG, 2. van der Velde AR, Meijers WC, de Boer Int J Cardiol 2018; 258: 185–191. Dickstein K, Drazner MH, Fonarow GC, RA. Biomarkers for risk prediction in 4. Lala A, McNulty SE, Mentz RJ, Dunlay Jaarsma T, Jondeau G, Sendon JL, acute decompensated heart failure. Curr SM, Vader JM, AbouEzzeddine OF, Mebazaa A, Metra M, Nieminen M, Pang Heart Fail Rep. 2014 2018; 11: 246–259. DeVore AD, Khazanie P, Redfield MM, PS, Seferovic P, Stevenson LW, van 3. Rubio-Gracia J, Demissei BG, ter Maaten Goldsmith SR, Bart BA, Anstrom KJ, Veldhuisen DJ, Zannad F, Anker SD, JM, Cleland JG, O’Connor CM, Metra M, Felker GM, Hernandez AF, Stevenson Rhodes A, McMurray JJV, Filippatos G, Ponikowski P, Teerlink JR, Cotter G, LW. Relief and recurrence of congestion European Society of Cardiology, Euro- Davison BA, Givertz MM, Bloomfield during and after hospitalization for pean Society of Intensive Care Medicine. ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842 2628 M. Rivas-Lasarte et al. Assessing and grading congestion in Martin-Sanchez FJ, Miró Ò, Price S, JACC Cardiovasc Imaging 2013; 6: acute heart failure: a scientific statement Cullen L, Maisel AS, Vrints C, Cowie 1141–1151. from the acute heart failure committee MR, Di Somma S, Bueno H, Mebazaa 20. Gargani L, Pang PS, Frassi F, of the heart failure association of the Eu- A, Gualandro DM, Tavares M, Metra M, Miglioranza MH, Dini FL, Landi P, ropean Society of Cardiology and en- Coats AJS, Ruschitzka F, Seferovic PM, Picano E. Persistent pulmonary conges- dorsed by the European Society of Mueller C, Study Group on Acute Heart tion before discharge predicts rehospi- Intensive Care Medicine. Eur J Heart Fail Failure of the Acute Cardiovascular Care talization in heart failure: a lung 2010; 12: 423–433. Association and the Heart Failure Asso- ultrasound study. Cardiovasc Ultrasound 6. Thibodeau JT, Drazner MH. The role of ciation of the European Society of Cardi- 2015; 13: 40. the clinical examination in patients with ology. Expert consensus document: 21. Gustafsson M, Alehagen U, Johansson P. heart failure. JACC Hear Fail 2018; 6: reporting checklist for quantification of Imaging congestion with a pocket ultra- 543–551. pulmonary congestion by lung ultra- sound device: prognostic implications 7. Platz E, Campbell RT, Claggett B, Lewis sound in heart failure. Eur J Heart Fail in patients with chronic heart failure. J EF, Groarke JD, Docherty KF, Lee MMY, 2019; 21: 844–851. Card Fail 2015; 21: 548–554. Merz AA, Silverman M, Swamy V, 14. Yancy CW, Jessup M, Bozkurt B, Butler J, 22. Cogliati C, Casazza G, Ceriani E, Torzillo Lindner M, Rivero J, Solomon SD, Casey DE, Colvin MM, Drazner MH, D, Furlotti S, Bossi I, Vago T, Costantino McMurray JJV. Lung ultrasound in acute Filippatos GS, Fonarow GC, Givertz G, Montano N. Lung ultrasound and heart failure. JACC Hear Fail 2019; 7: MM, Hollenberg SM, Lindenfeld J, short-term prognosis in heart failure pa- 849–858. Masoudi FA, McBride PE, Peterson PN, tients. Int J Cardiol 2016; 218: 104–108. 8. Miglioranza MH, Picano E, Badano LP, Stevenson LW, Westlake C. 2017 23. Palazzuoli A, Ruocco G, Beltrami M, Sant’Anna R, Rover M, Zaffaroni F, ACC/AHA/HFSA focused update of the Nuti R, Cleland JG. Combined use of Sicari R, Kalil RK, Leiria TL, Gargani L. 2013 ACCF/AHA guideline for the man- lung ultrasound, B-type natriuretic pep- Pulmonary congestion evaluated by agement of heart failure. J Am Coll tide, and echocardiography for outcome lung ultrasound predicts decompensa- Cardiol 2017; 70: 776–803. prediction in patients with acute HFrEF tion in heart failure outpatients. Int J 15. Ponikowski P, Voors AA, Anker SD, and HFpEF. Clin Res Cardiol 2018; 107: Cardiol 2017 2019; 240: 271–278. Bueno H, Cleland JGF, Coats AJS, Falk 586–596. 9. Platz E, Lewis EF, Uno H, Peck J, Pivetta V, González-Juanatey JR, Harjola V-P, 24. Dwyer KH, Merz AA, Lewis EF, Claggett E, Merz AA, Hempel D, Wilson C, Jankowska EA, Jessup M, Linde C, BL, Crousillat DR, Lau ES, Silverman Frasure SE, Jhund PS, Cheng S, Solo- Nihoyannopoulos P, Parissis JT, Pieske MB, Peck J, Rivero J, Cheng S, Platz E. mon SD. Detection and prognostic value B, Riley JP, Rosano GMC, Ruilope LM, Pulmonary congestion by lung ultra- of pulmonary congestion by lung ultra- Ruschitzka F, Rutten FH, van der Meer sound in ambulatory patients with heart sound in ambulatory heart failure pa- P, Authors/Task Force Members. 2016 failure with reduced or preserved ejec- tients. Eur Heart J 2016; 37: 1244–1251. ESC guidelines for the diagnosis and tion fraction and hypertension. J Card 10. Coiro S, Rossignol P, Ambrosio G, treatment of acute and chronic heart Fail 2018; 24: 219–226. Carluccio E, Alunni G, Murrone A, Tritto failure. Eur Heart J 2016; 37: 25. Facchini C, Malfatto G, Giglio A, I, Zannad F, Girerd N. Prognostic value 2129–2200. Facchini M, Parati G, Branzi G. Lung ul- of residual pulmonary congestion at dis- 16. Narang N, Chung B, Nguyen A, trasound and transthoracic impedance charge assessed by lung ultrasound im- Kalathiya RJ, Laffin LJ, Holzhauser L, for noninvasive evaluation of pulmonary aging in heart failure. Eur J Heart Fail Ebong IA, Besser SA, Imamura T, Smith congestion in heart failure. J Cardiovasc 2015; 17: 1172–1181. BA, Kalantari S, Raikhelkar J, Sarswat Med 2016; 17: 510–517. 11. Rivas-Lasarte M, Álvarez-García J, N, Kim GH, Jeevanandam V, Burkhoff 26. Chiem AT, Chan CH, Ander DS, Fernández-Martínez J, Maestro A, D, Sayer G, Uriel N. Discordance be- Kobylivker AN, Manson WC. Compari- López-López L, Solé-González E, Pirla tween clinical assessment and invasive son of expert and novice sonographers’ MJ, Nuria M, Mirabet S, Fluvià P, Brossa hemodynamics in patients with ad- performance in focused lung ultraso- V, Sionis A, Roig E, Cinca J. Lung vanced heart failure. J Card Fail 2020; nography in dyspnea (FLUID) to diag- ultrasound-guided treatment in ambula- 26: 128–135. nose patients with acute heart failure tory patients with heart failure: a 17. Stienen S, Salah K, Moons AH, Bakx AL, syndrome Comparison of expert and randomised controlled clinical trial van Pol P, Kortz RAM, Ferreira JP, novice sonographers’ performance in fo- (LUS-HF study). Eur J Heart Fail 2019: Marques I, Schroeder-Tanka JM, Keijer cused lung ultrasonography in dyspnea 1–9. JT, Bayés-Genis A, Tijssen JGP, Pinto (FLUID) to diagnose patients with acute 12. Ponikowski P, Voors AA, Anker SD, YM, Kok WE. NT-proBNP (N-terminal heart failure syndrome. Acad Emerg Med Bueno H, Cleland JGF, Coats AJS, Falk pro-B-type natriuretic peptide)-guided 2015; 22: 564–573. V, González-Juanatey JR, Harjola V-P, therapy in acute decompensated heart 27. Swamy V, Brainin P, Biering-Sørensen T, Jankowska EA, Jessup M, Linde C, failure. Circulation 2018; 137: Platz E. Ability of non-physicians to per- Nihoyannopoulos P, Parissis JT, Pieske 1671–1683. form and interpret lung ultrasound: a B, Riley JP, Rosano GMC, Ruilope LM, 18. Frassi F, Gargani L, Tesorio P, Raciti M, systematic review. Eur J Cardiovasc Nurs Ruschitzka F, Rutten FH, van der Meer Mottola G, Picano E. Prognostic value 2019; 18: 474–483. P, Authors/Task Force Members. 2016 of extravascular lung water assessed 28. Platz E, Pivetta E, Merz AA, Peck J, ESC Guidelines for the diagnosis and with ultrasound lung comets by chest so- Rivero J, Cheng S. Impact of device se- treatment of acute and chronic heart nography in patients with dyspnea lection and clip duration on lung ultra- failure: the task force for the diagnosis and/or chest pain. J Card Fail 2007; sound assessment in patients with and treatment of acute and chronic 13: 830–835. heart failure. Am J Emerg Med 2015; heart failure of the European Society of 19. Miglioranza MH, Gargani L, Sant’Anna 33: 1552–1556. Cardiology (ESC): Developed with the RT, Rover MM, Martins VM, Mantovani 29. Pivetta E, Baldassa F, Masellis S, Bovaro special contribution of the Heart Failure A, Weber C, Moraes MA, Feldman CJ, F, Lupia E, Maule MM. Sources of vari- Association (HFA) of the ESC. Eur Heart Kalil RAK, Sicari R, Picano E, Leiria ability in the detection of B-lines, using J 2016; 37: 2129–2200. TLL. Lung ultrasound for the evaluation lung ultrasound. Ultrasound Med Biol 13. Platz E, Jhund PS, Girerd N, Pivetta E, of pulmonary congestion in outpatients. 2018; 44: 1212–1216. McMurray JJV, Peacock WF, Masip J, ESC Heart Failure 2020; 7: 2621–2628 DOI: 10.1002/ehf2.12842