Lung ultrasound in outpatients with heart failure: the wet-to-dry HF study

Addressing 'Residual Congestion' to Improve Prognosis After Acute Heart Failure Decompensation

Congestion is the hallmark and the main therapeutic target in patients with decompensated heart failure (HF). Residual clinical congestion is defined as a high left ventricular diastolic pressure associated with signs and symptoms of HF, such as dyspnoea, rales and oedema, persisting despite guideline-directed medical treatment. Residual congestion in the predischarge and early post-discharge phase is the major risk factor for HF readmission and mortality. Therefore, prompt recognition of congestion and rapid optimisation of medical and device therapy are crucial to induce remission in this malignant process. In this paper we discuss the definitions, prevalence and prognosis of HF decompensation; the significance of assessing residual congestion in HF patients; the results of observational and randomised clinical trials to detect and treat residual congestion; and the current guidelines to prevent recurrent HF decompensation in the context of residual congestion. Strategies to detect and address residual congestion are crucial to stopping readmissions after an acute HF hospitalisation and improving long-term prognosis.

Artificial Intelligence-Guided Lung Ultrasound by Nonexperts

Importance

Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those with cardiogenic pulmonary edema, but requires technical proficiency for image acquisition. Previous research has demonstrated the effectiveness of artificial intelligence (AI) in guiding novice users to acquire high-quality cardiac ultrasound images, suggesting its potential for broader use in LUS.

Objective

To evaluate the ability of AI to guide acquisition of diagnostic-quality LUS images by trained health care professionals (THCPs).

Design, Setting, and Participants

In this multicenter diagnostic validation study conducted between July 2023 and December 2023, participants aged 21 years or older with shortness of breath recruited from 4 clinical sites underwent 2 ultrasound examinations: 1 examination by a THCP operator using Lung Guidance AI and the other by a trained LUS expert without AI. The THCPs (including medical assistants, respiratory therapists, and nurses) underwent standardized AI training for LUS acquisition before participation.

Interventions

Lung Guidance AI software uses deep learning algorithms guiding LUS image acquisition and B-line annotation. Using an 8-zone LUS protocol, the AI software automatically captures images of diagnostic quality.

Main Outcomes and Measures

The primary end point was the proportion of THCP-acquired examinations of diagnostic quality according to a panel of 5 masked expert LUS readers, who provided remote review and ground truth validation.

Results

The intention-to-treat analysis included 176 participants (81 female participants [46.0%]; mean [SD] age, 63 [14] years; mean [SD] body mass index, 31 [8]). Overall, 98.3% (95% CI, 95.1%-99.4%) of THCP-acquired studies were of diagnostic quality, with no statistically significant difference in quality compared to LUS expert-acquired studies (difference, 1.7%; 95% CI, -1.6% to 5.0%).

Conclusions and Relevance

In this multicenter validation study, THCPs with AI assistance achieved LUS images meeting diagnostic standards compared with LUS experts without AI. This technology could extend access to LUS to underserved areas lacking expert personnel.

Trial Registration

ClinicalTrials.gov Identifier: NCT05992324.

Ultrasound imaging of congestion in heart failure: a narrative review

Background and Objective

Congestion is a key determinant in the evolution of patients with heart failure (HF), leading to higher rates of emergency visits, hospital admissions and even mortality. Both clinical and subclinical congestion have been associated with a worse prognosis, hence the importance of its correct detection, characterization and treatment. Multiparametric assessment with ultrasound imaging, lung ultrasound (LUS) and venous Doppler analysis, has emerged as a very informative and accessible diagnostic tool in HF patients throughout their evolution. This review aims to provide a practical approach for the implementation of these techniques as well as a comprehensive summary of their prognostic and therapeutic applications in specific clinical settings.

Methods

Relevant literature from 1997 to 2024 on congestion evaluation and management based on ultrasonographic findings was retrieved through PubMed research. Only English publications were included.

Key Content and Findings

Ultrasound imaging for congestion detection and management is increasingly convening attention in HF scientific literature. Observational and randomized studies exhibit consistent and reproducible results where greater degrees of congestion have been strongly associated with worse clinical short- and long-term outcomes both in acute and chronic HF. On the other hand, ultrasound imaging helps adjusting diuretic therapy with more frequent and robust evidence regarding LUS than venous Doppler analysis.

Conclusions

Despite exponential growing evidence supporting the use of ultrasound imaging in HF, LUS and venous Doppler analysis are not yet routine. Forthcoming evidence may help to consolidate these techniques in the management of HF patients.

Prognostic implication of lung ultrasound in heart failure: a pooled analysis of international cohorts

AIMS

Lung ultrasound (LUS) is often used to assess congestion in heart failure (HF). In this study, we assessed the prognostic role of LUS in patients with HF at admission and hospital discharge, and in an outpatient setting, and explored whether clinical factors [age, sex, left ventricular ejection fraction (LVEF), and atrial fibrillation] impact the prognostic value of LUS findings. Further, we assessed the incremental prognostic value of LUS on top of the following two clinical risk scores: (i) the atrial fibrillation, haemoglobin, elderly, abnormal renal parameters, diabetes mellitus (AHEAD) and (ii) the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) clinical risk scores.

METHODS AND RESULTS

We pooled data on patients hospitalized for HF or followed up in outpatient clinics from international cohorts. We enrolled 1947 patients at admission (n = 578), discharge (n = 389), and in outpatient clinics (n = 980). The total LUS B-line count was calculated for the eight-zone scanning protocol. The primary outcome was a composite of rehospitalization for HF and all-cause death. Compared with those in the lower tertiles of B lines, patients in the highest tertiles were older, more likely to have signs of HF and had higher N-terminal pro b-type natriuretic peptide (NT-proBNP) levels. A higher number of B lines was associated with increased risk of primary outcome at discharge [Tertile 3 vs. Tertile 1: adjusted hazard ratio (HR): 5.74 (3.26-10.12), P < 0.0001] and in outpatients [Tertile 3 vs. Tertile 1: adjusted HR: 2.66 (1.08-6.54), P = 0.033]. Age and LVEF did not influence the prognostic capacity of LUS in different clinical settings. Adding B-line count to the MAGGIC and AHEAD scores improved net reclassification significantly in all three clinical settings.

CONCLUSION

A higher number of B lines in patients with HF was associated with an increased risk of morbidity and mortality, regardless of the clinical setting.

Transfer Learning-Based B-Line Assessment of Lung Ultrasound for Acute Heart Failure

OBJECTIVE

B-lines assessed by lung ultrasound (LUS) outperform physical exam, chest radiograph, and biomarkers for the associated diagnosis of acute heart failure (AHF) in the emergent setting. The use of LUS is however limited to trained professionals and suffers from interpretation variability. The objective was to utilize transfer learning to create an AI-enabled software that can aid novice users to automate LUS B-line interpretation.

METHODS

Data from an observational AHF LUS study provided standardized cine clips for AI model development and evaluation. A total of 49,952 LUS frames from 30 patients were hand scored and trained on a convolutional neural network (CNN) to interpret B-lines at the frame level. A random independent evaluation set of 476 LUS clips from 60 unique patients assessed model performance. The AI models scored the clips on both a binary and ordinal 0-4 multiclass assessment.

RESULTS

A multiclassification AI algorithm had the best performance at the binary level when applied to the independent evaluation set, AUC of 0.967 (95% CI 0.965-0.970) for detecting pathologic conditions. When compared to expert blinded reviewer, the 0-4 multiclassification AI algorithm scale had a reported linear weighted kappa of 0.839 (95% CI 0.804-0.871).

CONCLUSIONS

The multiclassification AI algorithm is a robust and well performing model at both binary and ordinal multiclass B-line evaluation. This algorithm has the potential to be integrated into clinical workflows to assist users with quantitative and objective B-line assessment for evaluation of AHF.

Prognostic Significance of Lung Ultrasound for Heart Failure Patient Management in Primary Care: A Systematic Review

Background: Heart failure (HF) affects around 60 million individuals worldwide. The primary aim of this study was to evaluate the efficacy of lung ultrasound (LUS) in managing HF with the goal of reducing hospital readmission rates. Methods: A systematic search was conducted on PubMed, Embase, Google Scholar, Web of Science, and Scopus, covering clinical trials, meta-analyses, systematic reviews, and original articles published between 1 January 2019 and 31 December 2023, focusing on LUS for HF assessment in out-patient settings. There is a potential for bias as the effectiveness of interventions may vary depending on the individuals administering them. Results: The PRISMA method synthesized the findings. Out of 873 articles identified, 33 were selected: 19 articles focused on prognostic assessment of HF, 11 centred on multimodal diagnostic assessments, and two addressed therapeutic guidance for HF diagnosis. LUS demonstrates advantages in detecting subclinical congestion, which holds prognostic significance for readmission and mortality during out-patient follow-up post-hospital-discharge, especially in complex scenarios, but there is a lack of standardization. Conclusions: there are considerable uncertainties in their interpretation and monitoring changes. The need for an updated international consensus on the use of LUS seems obvious.

The Importance of Lung Ultrasound and IGFBP7 (Insulin-like Growth Factor Binding Protein 7) Assessment in Diagnosing Patients with Heart Failure

Background: In daily practice, there are problems with adequately diagnosing the cause of dyspnea in patients with heart failure with preserved and mildly reduced ejection fractions (HFpEF and HFmrEF). This study aimed to assess the usefulness of lung ultrasound in diagnosing HFpEF and HFmrEF and determine its correlation with IGFBP7 (insulin-like growth factor binding protein 7), NTproBNP (N-terminal pro-B-type natriuretic peptide), and echocardiographic markers. Methods: The research was conducted on 143 patients hospitalized between 2018 and 2020, admitted due to dyspnea, and diagnosed with HFpEF and HFmrEF. Venous blood was collected from all participants to obtain basic biochemical parameters, NTproBNP, and IGFBP7. Moreover, all participants underwent echocardiography and transthoracic lung ultrasound. Two years after hospitalization a follow-up telephone visit was performed. Results: The number of B-lines in the LUS ≥ 16 was determined with a sensitivity of-73% and specificity of-62%, indicating exacerbation of heart failure symptoms on admission. The number of B-lines ≥ 14 on admission was determined as a cut-off point, indicating an increased risk of death during the 2-year follow-up period. The factors that significantly impacted mortality in the study patient population were age and the difference between the number of B-lines on ultrasound at admission and at hospital discharge. IGFBP7 levels had no significant effect on the duration of hospitalization, risk of rehospitalization, or mortality during follow-up. Conclusions: Lung ultrasonography provides additional diagnostic value in patients with HFpEF or HFmrEF and exacerbation of heart failure symptoms. The number of B-lines ≥ 14 may indicate an increased risk of death.

Assessment of filling pressures and fluid overload in heart failure: an updated perspective

Congestion plays a major role in the pathogenesis, presentation, and prognosis of heart failure and is an important therapeutic target. However, its severity and organ and compartment distribution vary widely among patients, illustrating the complexity of this phenomenon. Although clinical symptoms and signs are useful to assess congestion and manage volume status in individual patients, they have limited sensitivity and do not allow identification of congestion phenotype. This leads to diagnostic uncertainty and hampers therapeutic decision-making. The present article provides an updated overview of circulating biomarkers, imaging modalities (ie, cardiac and extracardiac ultrasound), and invasive techniques that might help clinicians to identify different congestion profiles and guide the management strategy in this diverse population of high-risk patients with heart failure.

Prognostic Significance of Lung and Cava Vein Ultrasound in Elderly Patients Admitted for Acute Heart Failure: PROFUND-IC Registry Analysis

Introduction: Heart failure is an extremely prevalent disease in the elderly population of the world. Most patients present signs and symptoms of decompensation of the disease due to worsening congestion. This congestion has been clinically assessed through clinical signs and symptoms and complementary imaging tests, such as chest radiography. Recently, pulmonary and inferior vena cava ultrasound has been shown to be useful in assessing congestion but its prognostic significance in elderly patients has been less well evaluated. Objectives: This study aims to compare the clinical and radiological characteristics and predictive values for mortality in patients admitted for heart failure through the determination of B lines by lung ultrasound and the degree of collapsibility of the inferior vena cava (IVC). Secondarily, the study aims to assess the prediction of 30-day mortality based on the diameter of the IVC by means of the ROC curve. Methods: This is an observational cohort study based on data collected in the PROFUND-IC study, a nationwide multicentric registry of patients admitted with decompensated heart failure. Data were collected from these patients between October 2020 and April 2022. Results: A total of 482 patients were entered into the PROFUND-IC registry between October 2020 and April 2022. Bedside clinical ultrasound was performed during admission in 301 patients (64.3%). The number of patients with more than 6 B-lines on lung ultrasound amounted to 194 (66%). Statistically significant differences in 30-day mortality (22.1% vs. 9.2%; p = 0.01) were found in these patients. The sum of patients with IVC collapsibility of less than 50% amounted to 195 (67%). Regarding prognostic value, collapsibility data were significant for the number of admissions in the last year (12.5% vs. 5.5%; p = 0.04), in-hospital mortality (10.1% vs. 3.3%, p = 0.04) and 30-day mortality (22.6% vs. 8.1%; p < 0.01), but not for readmissions. Regarding the prognostic value of IVC diameter for 30-day mortality, the area under the ROC curve (AUC) was 0.73, with a p < 0.01. The curve cut-off point with the highest sensitivity (70%) and specificity (70.3%) was for an IVC value of 22.5 mm. In the logistic regression analysis, we observed that the variable most associated with patient survival at 30 days was the presence of a collapsible inferior vena cava, with more than 50% OR 0.359 (CI 0.139−0.926; p = 0.034). Conclusions: The subgroups of patients analyzed with more than six B lines per field and IVC collapsibility less than or equal to 50%, as measured by clinical ultrasound, had higher 30-day mortality rates than patients who did not fall into these subgroups. IVC diameter may be a good independent predictor of 30-day mortality in patients with decompensated heart failure. Comparing both ultrasound variables, it seems that in our population, the assessment of the inferior vena cava may be more associated with short-term prognosis than the pulmonary congestion variables assessed by B lines.

Impact of B-lines-guided intensive heart failure management on outcome of discharged heart failure patients with residual B-lines

AIMS

Pulmonary congestion (PC) expressed by residual lung ultrasound B-lines (LUS-BL) could exist in some discharged heart failure (HF) patients, which is a known determinant of poor outcomes. Detection efficacy for PC is suboptimal with widely used imaging modalities, like X-ray or echocardiography, while lung ultrasound (LUS) can sufficiently detect PC by visualizing LUS-BL. In this trial, we sought to evaluate the impact LUS-BL-guided intensive HF management post-discharge on outcome of HF patients discharged with residual LUS-BL up to 1 year after discharge. IMP-OUTCOME is a prospective, single-centre, single-blinded, randomized cohort study, which is designed to investigate if LUS-BL-guided intensive HF management post-discharge in patients with residual LUS-BL could improve the clinical outcome up to 1 year after discharge or not.

METHODS AND RESULTS

After receiving the standardized treatment of HF according to current guidelines, 318 patients with ≥3 LUS-BL assessed by LUS within 48 h before discharge will be randomly divided into the conventional HF management group and the LUS-BL-guided intensive HF management group at 1:1 ratio. Patient-related basic clinical data including sex, age, blood chemistry, imaging examination, and drug utilization will be obtained and analysed. LUS-BL will be assessed at 2 month interval post-discharge in both groups, but LUS-BL results will be enveloped in the conventional HF management group, and diuretics will be adjusted based on symptom and physical examination results with or without knowing the LUS-BL results. Echocardiography examination will be performed for all patients at 12 month post-discharge. The primary endpoint is consisted of the composite of readmission for worsening HF and all-cause death during follow up as indicated. The secondary endpoints consisted of the change in the New York Heart Association classification, Duke Activity Status Index, N terminal pro brain natriuretic peptide value, malignant arrhythmia event and 6 min walk distance at each designed follow up, echocardiography-derived left ventricular ejection fraction, and number of LUS-BL at 12 month post-discharge. Safety profile will be recorded and managed accordingly for all patients.

CONCLUSIONS

This trial will explore the impact of LUS-BL-guided intensive HF management on the outcome of discharged HF patients with residual LUS-BL up to 1 year after discharge in the era of sodium-glucose cotransporter-2 inhibitors and angiotensin receptor blocker-neprilysin inhibitor.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05035459.

How and When to Use Lung Ultrasound in Patients with Heart Failure?

Pulmonary congestion is a critical finding in patients with heart failure (HF) that can be quantified by lung ultrasound (LUS) through B-line quantification, the latter of which can be easily measured by all commercially-available probes/ultrasound equipment. As such, LUS represents a useful tool for the assessment of patients with both acute and chronic HF. Several imaging protocols have been described in the literature according to different clinical settings. While most studies have been performed with either the 8 or 28 chest zone protocol, the 28-zone protocol is more time-consuming while the 8-zone protocol offers the best trade-off with no sizeable loss of information. In the acute setting, LUS has excellent value in diagnosing acute HF, which is superior to physical examination and chest X-ray, particularly in instances of diagnostic uncertainty. In addition to its diagnostic value, accumulating evidence over the last decade (mainly derived from ambulatory settings or at discharge from an acute HF hospitalisation) suggests that LUS can also represent a useful prognostic tool for predicting adverse outcome in both HF with reduced (HFrEF) and preserved ejection fraction (HFpEF). It also allows real-time monitoring of pulmonary decongestion during treatment of acute HF. Additionally, LUS-guided therapy, when compared with usual care, has been shown to reduce the risk of HF hospitalisations at short- and mid-term follow-up. In addition, studies have shown good correlation between B-lines during exercise stress echocardiography and invasive, bio-humoral and echocardiographic indices of haemodynamic congestion; B-lines during exercise are also associated with worse prognosis in both HFrEF and HFpEF. Altogether, LUS represents a reliable and useful tool in the assessment of pulmonary congestion and risk stratification of HF patients throughout their entire journey (i.e., emergency department/acute settings, in-hospital management, discharge from acute HF hospitalisation, monitoring in the outpatient setting), with considerable diagnostic and prognostic implications.