TYPE Original Research PUBLISHED 14 September 2022 DOI 10.3389/fphys.2022.1006589 Incremental prognostic value of OPEN ACCESS lung ultrasound on EDITED BY Luna Gargani, University of Pisa, Italy contemporary heart failure risk REVIEWED BY Nicola Riccardo Pugliese, scores University of Pisa, Italy Stefano Coiro, Hospital of Santa Maria della Alba Maestro-Benedicto 1, Mercedes Rivas-Lasarte 1,2*, Misericordia in Perugia, Italy Juan Fernández-Martínez 1, Laura López-López 1, *CORRESPONDENCE Eduard Solé-González 1,3, Vicens Brossa 1, Sonia Mirabet 1, Mercedes Rivas-Lasarte, rivaslasarte@gmail.com Eulàlia Roig 1, Juan Cinca 1, Jesús Álvarez-García 1,4† and † These authors have contributed equally Alessandro Sionis 1† to this work 1 Cardiology Department, IIB SANT PAU, Hospital de la Santa Creu i Sant Pau CIBERCV, Barcelona, SPECIALTY SECTION Spain, 2Cardiology Department, Hospital Universitario Puerta de Hierro CIBERCV, Majadahonda This article was submitted to Clinical Madrid, Spain, 3Cardiology Department, Hospital Clinic, Barcelona, Spain, 4Cardiology Department, and Translational Physiology, Hospital Universitario Ramón y Cajal CIBERCV, Madrid, Spain a section of the journal Frontiers in Physiology RECEIVED 29 July 2022 Introduction: Over the last decades, several scores have been developed to aid ACCEPTED 24 August 2022 clinicians in assessing prognosis in patients with heart failure (HF) based on PUBLISHED 14 September 2022 clinical data, medications and, ultimately, biomarkers. Lung ultrasound (LUS) has CITATION Maestro-Benedicto A, Rivas-Lasarte M, emerged as a promising prognostic tool for patients when assessed at discharge Fernández-Martínez J, López-López L, after a HF hospitalization. We hypothesized that contemporary HF risk scores Solé-González E, Brossa V, Mirabet S, can be improved upon by the inclusion of the number of B-lines detected by Roig E, Cinca J, Álvarez-García J and Sionis A (2022), Incremental prognostic LUS at discharge to predict death, urgent visit, or HF readmission at 6- month value of lung ultrasound on follow-up. contemporary heart failure risk scores. Front. Physiol. 13:1006589. Methods: We evaluated the discrimination improvement of adding the number doi: 10.3389/fphys.2022.1006589 of B-lines to 4 contemporary HF risk scores (Get with the Guidelines -GWTG-, COPYRIGHT MAGGIC, Redin-SCORE, and BCN Bio-HF) by comparing the change in the area © 2022 Maestro-Benedicto, Rivas- Lasarte, Fernández-Martínez, López- under the receiver operating curve (AUC), the net reclassification index (NRI), López, Solé-González, Brossa, Mirabet, and the integrated discrimination improvement (IDI). The population of the Roig, Cinca, Álvarez-García and Sionis. This is an open-access article study was constituted by the 123 patients enrolled in the LUS-HF trial, adjusting distributed under the terms of the the analyses by the intervention. Creative Commons Attribution License (CC BY). The use, distribution or Results: The AUC of the GWTG score increased from 0.682 to 0.789 (p = 0.02), reproduction in other forums is resulting in a NRI of 0.608 and an IDI of 0.136 (p < 0.05). Similar results were permitted, provided the original author(s) and the copyright owner(s) are observed when adding the number of B-lines to the MAGGIC score, with an credited and that the original AUC that increased from 0.705 to 0.787 (p < 0.05). This increase translated into a publication in this journal is cited, in accordance with accepted academic NRI of 0.608 and an IDI of 0.038 (p < 0.05). Regarding Redin-SCORE at 1-month practice. No use, distribution or and 1-year, the AUC increased from 0.714 to 0.773 and from 0.681 to 0.757, reproduction is permitted which does although it did not reach statistical significance (p = 0.08 and p = not comply with these terms. 0.06 respectively). Both IDI and NRI were significantly improved (0.093 and 0.509 in the 1-month score, p < 0.05; 0.056 and 0.111 in the 1-year score, p < 0.05). Lastly, the AUC for the BCN Bio-HF score increased from 0.733 to 0.772, which was statistically non-significant, with a NRI value of 0.363 (p = 0.06) and an IDI of 0.092 (p < 0.05). Frontiers in Physiology 01 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 Conclusion: Adding the results of LUS evaluated at discharge improved the predictive value of most of the contemporary HF risk scores. As it is a simple, fast, and non-invasive test it may be recommended to assess prognosis at discharge in HF patients. KEYWORDS congestion, heart failure, lung ultrasound, scores, biomarkers, prognosis 1 Introduction aged ≥18 years and to have been hospitalized for HF defined by shortness of breath, pulmonary congestion on X-ray, and Risk prediction in heart failure (HF) remains essential to elevated N-terminal pro B-type natriuretic peptide (NT- identify those patients who may benefit from a closer proBNP) values in the first 24 h of admission (cut-off values: management. Since the turn of the century, several scores 450 ng/L in patients aged <50 years; >900 ng/L in patients aged have been proposed and externally validated (Levy et al., 50–75 years; >1800 ng/L in patients aged >75 years). Exclusion 2006; Peterson et al., 2010; Pocock et al., 2013; Lupón et al., criteria included inability to attend follow-up visits, life 2014; Álvarez-García et al., 2015). Most can be easily calculated expectancy of <6 months, haemodialysis, and the presence of using demographics, laboratory, and medication data, and are severe lung disease preventing LUS interpretation. Eligible available through free-access websites. Nevertheless, no patients were randomized at discharge to either the non-LUS- predictive scale has been found uncontrovertibly better than guided group (control group) or the LUS-guided group (LUS the rest (Codina et al., 2021), illustrating the complexity of group). Visits were scheduled in the HF clinic at 14, 30, 90, and risk prediction in HF. 180 days after discharge. LUS was performed in both groups, but As HF treatment has dramatically evolved during the last the result was only available to the treating physician in the LUS- decades, existing prognostic scores, have been continuously guided arm. updated adding emerging data from both newer therapeutic The primary endpoint was a composite of urgent visit, and diagnostic tools (Sinha et al., 2021). Particularly, lung hospitalization for worsening HF, and death at 6 months. ultrasound (LUS) has emerged in the last years as a simple Urgent visits for worsening HF were defined as visits to the and non-invasive instrument for detecting pulmonary emergency department or un-scheduled visits to the HF unit congestion in patients with HF. Its prognostic value has been as a result of signs and/or symptoms of worsening HF that assessed in different clinical scenarios (Coiro et al., 2015; Coiro required intravenous diuretic treatment or diuretic increase et al., 2015; Gargani et al., 2015; Platz et al., 2016; Scali et al., 2017; with a hospital stay of <24 h. Hospitalization for worsening Coiro et al., 2020; Rivas-Lasarte et al., 2020; Domingo et al., 2021; HF was defined as a stay in hospital for >24 h mainly as a Gargani et al., 2021; Kobayashi et al., 2021; Mazzola et al., 2021; result of signs and/or symptoms of worsening HF. The Pugliese et al., 2021; Pugliese et al., 2021), showing that the reported events were reviewed by an independent panel of presence of B-lines detected by LUS is associated with an investigators. increased risk of worse outcomes. The protocol was approved by the ethics committee and the Thus, we hypothesized that contemporary risk scores can be study was conducted in accordance with the principles of the improved by incorporating the number of B-lines detected by Declaration of Helsinki. Written informed consent was obtained LUS at HF discharge to predict death or hospital readmission at from all patients prior to study participation. 6- month follow-up. 2.2 Lung ultrasound protocol 2 Material and methods According to current expert recommendations (Platz et al., 2.1 Study design 2019), LUS was recorded using a pocket ultrasound device (VScan, General Electrics) with a cardiac phased array This is a sub-analysis including 123 patients enrolled in the transducer at four sites in each hemithorax (mid clavicular, LUS-HF trial, whose study design and primary results have been mid axillar superior and inferior in each side) with the previously reported (Rivas-Lasarte et al., 2019). In brief, the LUS- transducer perpendicular to the ribs and at a 16 cm imaging HF was a single-center, single-blind, randomized clinical trial depth being the patient in the semi-recumbent position. The evaluating tailored LUS-guided diuretic treatment of pulmonary number of B-lines reported was the sum of the B-lines visualized congestion in patients with HF. Patients were required to be in each thoracic site. Frontiers in Physiology 02 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 TABLE 1 Baseline characteristics of the study population. ACE, angiotensin-converting enzyme; ARB, angiotensin-receptor blocker; BMI, body mass index; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration Total (N = 123 patients) rate; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; LUS, lung ultrasound; LVEF, left ventricular ejection fraction. Age, years 69 ± 12 Female sex 34 (28%) BMI, kg/m2 26.8 ± 5.4 Cardiovascular risk factors Hypertension 89 (72%) For this post-hoc analysis, the number of B-lines detected by Dyslipidaemia 84 (68%) LUS at discharge was analysed. Diabetes 50 (41%) Smokers 25 (20%) Comorbidities 2.3 Contemporary HF risk scores COPD 31 (25%) Renal insufficiency* 46 (37%) We selected 4 contemporary scores: Get with the Guidelines, Stroke 19 (15%) MAGGIC, Redin-SCORE and BCN Bio-HF. Anaemia** 25 (20%) Charlson index 2.7 ± 1.6 2.3.1 The get with the guidelines–heart failure Previous cardiac history score (GWTG- HF) (Peterson et al., 2010) Previous HF 68 (55%) The GWTG-HF score incorporates 9 variables (age, systolic Ischemic HF aetiology 54 (44%) blood pressure (BP), body mass index (BMI), total cholesterol, Atrial fibrillation 68 (55%) high-density lipoprotein cholesterol, QRS duration, smoking Median LVEF (%) 36 (30–49) status, use of antihypertensive medication, use of diabetes HFrEF 68 (55%) medication) to predict the risk of in-hospital mortality for HFmrEF 25 (21%) patients hospitalized with HF. HFpEF 28 (23%) Characteristics at discharge 2.3.2 The meta-analysis global group in chronic Systolic blood pressure, mmHg 130 ± 24 heart failure score (MAGGIC) (Pocock et al., Heart rate, b.p.m 68 ± 11 2013) eGFR, mL/kg/min/1.73m2 63 ± 24 The MAGGIC score was derived from a metanalysis of NT-proBNP, ng/L 1723 (884–3,776) 30 studies to predict mortality rates in patients with HF, and Peripheral oedema 21 (17%) includes 13 predictors: age, lower ejection fraction (EF), New Pulmonary rales 23 (19%) York Heart Association (NYHA) class, serum creatinine, Treatment at discharge diabetes, not prescribed beta-blocker, lower systolic BP, lower Loop diuretics 94 (76%) BMI, time since diagnosis, current smoker, chronic obstructive Thiazide diuretics 4 (3%) pulmonary disease, male gender, and not prescribed angiotensin ACE inhibitors/ARB 75 (61%) converter enzyme inhibitors (ACEi) or angiotensin-receptor Sacubitril/valsartan 5 (4%) blockers. Beta-blocker 104 (85%) Mineralocorticoid receptor antagonist 36 (29%) 2.3.3 The Redin-SCORE (Álvarez-García et al., Implantable cardioverter-defibrillator 18 (15%) 2015) Cardiac resynchronization therapy 7 (6%) The Redin-SCORE is a risk score developed to predict short- LUS data at discharge term (1 month) and long-term (1 year) risk of HF in ambulatory Number of B-lines 4 (2-7) patients. Predictors of 1-month readmission were the presence of Pleural effusion 11 (9%) elevated natriuretic peptides, left ventricular (LV) HF signs, and Outcomes at 6 months estimated glomerular filtration rate (eGFR) < 60 ml/min/m2. Composite endpoint 39 (32%) Predictors of 1-year readmission were elevated natriuretic Heart failure admission 27 (22%) peptides, anaemia, left atrial size >26 mm/m2, heart Urgent visits for worsening HF 16 (13%) rate >70 beats per minute (bpm), LV HF signs, and Death 5 (4%) eGFR <60 ml/min/m2. *Renal insufficiency refers to eGFR <60 ml/min/1.73 m2. 2.3.4 The BCN Bio-HF score (Lupón et al., 2014) **Anaemia refers to haemoglobin levels of <13 g/dl in men and <12 g/dl in women. Data are expressed as number (%), mean ± standard deviation, or median (interquartile The first version of the BCN Bio-HF included clinical range), as appropriate. variables, medications, conventional laboratory analytes Frontiers in Physiology 03 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 TABLE 2 Incremental prognostic value of B-lines to predict 6-month outcomes in the LUS-HF trial. AUC p Value AIC BIC H-L p value IDI NRI GWTG score 0.682 (0.587–0.778) 148 153 0.3 GWTG score + number of B-lines 0.798 (0.704–0.783) 0.018 131 136 0.2 0.136 (p < 0.001) 0.608 (p = 0.002) MAGGIC score 0.705 (0.614–0.797) 146 152 0.5 MAGGIC score + number of B-lines 0.787 (0.706–0.869) 0.045 131 137 0.3 0.119 (p < 0.001) 0.608 (p = 0.002) BCN Bio-HF 0.733 (0.639–0.827) 145 150 0.2 BCN Bio-HF + number of B-lines 0.772 (0.685–0.859) 0.340 133 139 0.4 0.092 (p = 0.003) 0.363 (p = 0.060) Redin-SCORE 1-month 0.714 (0.621–0.808) 141 147 0.3 Redin-SCORE 1-month + number of B-lines 0.773 (0.621–0.864) 0.08 130 135 0.2 0.093 (p = 0.003) 0.509 (p = 0.009) Redin-SCORE 1-year 0.681 (0.579–0.783) 146 152 0.6 Redin-SCORE 1-year + number of B-lines 0.757 (0.663–0.851) 0.056 133 137 0.9 0.056 (p = 0.004) 0.111 (p < 0.001) AUC, area under the curve; AIC, akaike criteria; BIC, bayesian criteria; H-L, Hosmer-Lemeshow; IDI, integrated discrimination improvement index; NRI, net reclassification improvement index. (sodium, estimated glomerular filtration rate), and NT- United States). A two-sided p < 0.05 was considered proBNP, high-sensitivity troponin T (hs-TnT), and significant. interleukin-1 receptor-like-1 (known as ST2). It was updated in 2018 by incorporating the use of angiotensin receptor neprylisin inhibitor (ARNI), cardiac resynchronization 3 Results therapy (CRT), and implantable cardioverter defibrillator (ICD). 3.1 Characteristics of the study population and number of B-lines at discharge 2.4 Statistical analysis Clinical characteristics of the LUS-HF population and LUS data at discharge are shown in Table 1. Briefly, median age of the Continuous variables are expressed as mean (standard patients was 70 years, most patients were male (72%), had a deviation) or as median (interquartile range) whenever reduced LVEF (55%), and a high prevalence of comorbidities. appropriate. Differences in continuous variables were Median number of B-lines at discharge was 4 (Levy et al., 2006; tested by the analysis of variance (ANOVA), Student’s Pocock et al., 2013; Lupón et al., 2014; Álvarez-García et al., 2015; t-test, or Wilcoxon signed rank test for independent Codina et al., 2021; Sinha et al., 2021) and 41 patients (33%) had samples. Categorical variables were presented as ≥5 B-lines. frequency and percentage. Differences in the categorical variables were assessed by the χ2 test or by Fisher’s exact test. 3.2 Incremental prognostic value of LUS Discrimination, calibration and reclassification methods over contemporary heart failure risk are recommended when evaluating candidate variables in scores prognostic studies (Januzzi et al., 2014). Thus, we first assessed the discriminative ability of each selected HF Table 2 summarizes the discrimination, calibration, IDI, score to predict the occurrence of the primary endpoint at and NRI parameters by the 4 HF scores for the primary 6 months in the study population by calculating the area outcome alone and in combination with the number of under the receiver operating curve (AUC). Thereafter, we B-lines. Overall, the addition of the number of B-lines at analysed the incremental prognostic value of the number of discharge improved the AUC of each risk score (Figure 1). B-lines at discharge on top of each score by comparing the However, the incorporation of the number of B-lines only AUC with and without LUS data and calculated the integrated reached statistically significance for the GWTG and MAGGIC discrimination improvement (IDI), and net reclassification scores, but not for the Redin-SCORE at 1-month and 1-year, improvement (NRI). Finally, we also performed decision nor the BCN Bio-HF. curve analysis (DCA) to visualize the net benefit for Regarding reclassification indexes, both NRI and IDI after clinical decisions. Data were analysed using STATA SE adding the number of B-lines showed a significant Version 15.0 (StataCorp LLC, College Station, TX, improvement with all scores, except for NRI in BCN Bio-HF Frontiers in Physiology 04 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 FIGURE 1 Comparison between the Receiver Operating Characteristic curves (ROC) for the composite endpoint at 6-month follow-up: score alone versus score + number of B-lines. ROC curves compare sensitivity versus specificity across a range of values for the ability of the score to predict the composite endpoint. Each patient is given a score with the intention that the test will be useful in predicting event occurrence and the different points on the curve correspond to the different cutpoints used to determine whether the test results are positive. Adding B-lines to GWTG, MAGGIC and REDIN-Score 1 year scores (A,B,D) makes the true positive rate higher and the false positive rate lower at all cutpoints compared with the score alone. Regarding BCN Bio-HF and REDIN-Score 1 m (C,E) adding B-lines improves both sensitivity and specificity in almost all cutpoints. score. As Figure 2 shows, the calibration curves indicating good score alone for any threshold probabilities, except for the concordance. Finally, Figure 3 displays the DCA, showing that GWTG score, which applied only for an event probability the net benefit of adding LUS data was higher than that of the under 70%. Frontiers in Physiology 05 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 FIGURE 2 Calibration plots. X-axis: predicted outcome; Y-axis: observed outcome. NBL: number of B lines (A) GWTG: Get With the Guidelines score; (B) MAGGIC score; (C) Redin-SCORE 1 month; (D) Redin-SCORE 1 year; (E) BCN Bio-HF score. 4 Discussion 4.2 Prognostic value of LUS over HF risk scores 4.1 Main findings Prior research (Bettencourt et al., 2004; Khanam et al., 2018; Our work shows that the predictive value of contemporary Lupón et al., 2018) has already focused in analysing the HF risk scores can be improved by integrating LUS. prognostic value of new clinical variables to allow better Frontiers in Physiology 06 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 FIGURE 3 Decision curve analysis for predicting the primary composite endpoint. Decision curve analysis illustrates the performance of the model in a range of threshold probabilities, which may of interest to the clinician making the decision. X axis represents the probability threshold for the composite endpoint according to the score. The y axis represents the net benefit ([true positives - w x false positives]/total number of patients): positive values indicate an improvement in the classification of patients, and w is a correction factor for the probability threshold. The upper limit is 0.32 because the incidence of readmission for HF in LUS-HF was 32%. The diagonal black line assumes that all expected patients were readmitted, 32% at 6 months. The coloured lines represent the result of applying the different scores. Adding B-lines provided a net benefit due to better classification of the patients for probabilities below 70% in GWTG and BCN Bio-HF scores (A,E). When B-lines were incorporated to MAGGIC score (B), a net benefit was obtained due to better classification of the patients for probabilities between 0 and 80%. Regarding REDIN-score 1 year and 1m, a net benefit was obtained in all probability spectrum when using LUS data (C,D). Frontiers in Physiology 07 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 prediction, such as the incorporation of ARNI or the effect of proved a LUS-guided therapy reduces acute decompensation adding natriuretic peptides. The BCN Bio-HF score was one of events in the follow-up (Rivas-Lasarte et al., 2019; Araiza- the pioneers developing an updated version integrating those Garaygordobil et al., 2020; Marini et al., 2020; Mhanna et al., variables that allowed a better risk prediction. 2021; Rastogi et al., 2022), which explains its rapid and wide LUS has emerged in the last decade as a simple, fast, and non- implementation in the HF field. invasive test for lung congestion quantification. Several studies have shown that it might be a better tool for detecting subclinical pulmonary congestion than clinical assessment (Platz et al., 2016; 4.4 Study limitations Pellicori et al., 2019) and it has become widely available in an increasing number of centres, with the generalization of Our study has some limitations. First, we tested prognostic echographic equipments including pocket devices. scores which were specifically designed for ambulatory HF As NT-proBNP, it has also been reported that the presence patients in a sample that was comprised by HF patients of B-lines in HF patients is an independent prognostic factor discharged from hospital. Second, LUS-HF was designed for (Coiro et al., 2015; Gargani et al., 2015; Gustafsson et al., 2015; a 6-month follow-up which may have determined an Aras and Teerlink, 2016; Platz et al., 2016; Rivas-Lasarte et al., underestimation of the number of events, since some scores 2020; Domingo et al., 2021) although no study to date has were originally designed to predict longer time points. Also, this analysed its prognostic value when added to the most used is a retrospective (not pre-specified) analysis of the LUS-HF. contemporary risk scores. To the best of our knowledge, this is Finally, our analysis accounts for a composite endpoint the first study analysing if risk scores can be improved upon by consisting in HF hospitalizations, urgent visits for worsening the inclusion of B-lines detected by LUS at discharge and we heart failure and all-cause mortality so it may not be generalized found that the predictive yielding improved in a different to prognostic risk scores specifically designed for other degree according to the presence or absence of outcomes. hemodynamic or biochemic markers of left ventricular We consider our study as hypothesis generating and function in their respective models. acknowledge the need of testing the hypothesis in other HF Moreover, the number of B-lines is not only a prognostic larger cohorts, especially multicentric and with a longer marker but has shown to be also a therapeutic target in HF follow-up. patients improving their prognosis when monitored during follow-up, mainly due to a reduction of HF decompensations (Rivas-Lasarte et al., 2019). As it is a dynamic marker that evolves 5 Conclusion with therapeutic measures, we hypothesize that its changes may also be of interest in predicting prognosis, although this remains Adding the results of LUS evaluated at discharge improved to be elucidated in further studies. the predictive value of most of the contemporary HF risk scores. As it is a simple, fast, and non-invasive test it may be recommended to assess prognosis at discharge in HF patients. 4.3 Clinical implications Risk stratification remains essential in HF to make medical Data availability statement decisions based on life expectancy and develop appropriate treatment plans, but the accuracy of available prognostic risk The data that support the findings of this study are available scores in patients with HF is still limited. Our study contributes from the corresponding author upon reasonable request. on this important issue by integrating in existing contemporary HF risk scores LUS and allowing for a significant improvement in their predictive value in the majority of cases. Ethics statement Some variables included in the pre-existing predictive HF models are not frequently obtained in the clinical care of HF, but The studies involving human participants were reviewed and LUS can be performed quickly and easily at bedside, and has approved by the Hospital Sant Pau. The patients/participants already become an add-on to lung auscultation for the evaluation provided their written informed consent to participate in this study. of pulmonary congestion. As a semi-quantitative measure of pulmonary congestion, LUS adds new and valuable information to the scores. Due to its Author contributions dynamic behaviour, it can be used as a monitoring tool allowing reassessment of patient’s status whenever clinical situation Conceptualization and methodology: MR-L, JA-G, JC, ER, changes, and also as a therapeutic target. Several studies had and AS Investigation conduction: MR-L, JA-G, ES, AM-B, JF-M, Frontiers in Physiology 08 frontiersin.org Maestro-Benedicto et al. 10.3389/fphys.2022.1006589 VB, SM, and LL-L Writing original draft: AM-B, MR-L, JA-G, Publisher’s note and AS Writing: review and editing: all the authors. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their Conflict of interest affiliated organizations, or those of the publisher, the editors and the reviewers. 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