Comparison of pulmonary congestion severity using artificial intelligence-assisted scoring versus clinical experts: A secondary analysis of BLUSHED-AHF

2024 update in heart failure

In the last years, major progress has occurred in heart failure (HF) management. The 2023 ESC focused update of the 2021 HF guidelines introduced new key recommendations based on the results of the last years of science. First, two drugs, sodium-glucose co-transporter-2 (SGLT2) inhibitors and finerenone, a novel nonsteroidal, selective mineralocorticoid receptor antagonist (MRA), are recommended for the prevention of HF in patients with diabetic chronic kidney disease (CKD). Second, SGLT2 inhibitors are now recommended for the treatment of HF across the entire left ventricular ejection fraction spectrum. The benefits of quadruple therapy in patients with HF with reduced ejection fraction (HFrEF) are well established. Its rapid and early up-titration along with a close follow-up with frequent clinical and laboratory re-assessment after an episode of acute HF (the so-called 'high-intensity care' strategy) was associated with better outcomes in the STRONG-HF trial. Patients experiencing an episode of worsening HF might require a fifth drug, vericiguat. In the STEP-HFpEF-DM and STEP-HFpEF trials, semaglutide 2.4 mg once weekly administered for 1 year decreased body weight and significantly improved quality of life and the 6 min walk distance in obese patients with HF with preserved ejection fraction (HFpEF) with or without a history of diabetes. Further data on safety and efficacy, including also hard endpoints, are needed to support the addition of acetazolamide or hydrochlorothiazide to a standard diuretic regimen in patients hospitalized due to acute HF. In the meantime, PUSH-AHF supported the use of natriuresis-guided diuretic therapy. Further options and most recent evidence for the treatment of HF, including specific drugs for cardiomyopathies (i.e., mavacamten in hypertrophic cardiomyopathy and tafamidis in transthyretin cardiac amyloidosis), device therapies, cardiac contractility modulation and percutaneous treatment of valvulopathies, with the recent finding from the TRILUMINATE Pivotal trial, are also reviewed in this article.

A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure

Lung ultrasound (LUS) is an effective tool for diagnosing acute heart failure (AHF). However, several imaging protocols currently exist and how to best use LUS remains undefined. We aimed at developing a lung ultrasound-based model for AHF diagnosis using machine learning. Random forest and decision trees were generated using the LUS data (via an 8-zone scanning protocol) in patients with acute dyspnea admitted to the Emergency Department (PLUME study, N = 117) and subsequently validated in an external dataset (80 controls from the REMI study, 50 cases from the Nancy AHF cohort). Using the random forest model, total B-line sum (i.e., in both hemithoraces) was the most significant variable for identifying AHF, followed by the difference in B-line sum between the superior and inferior lung areas. The decision tree algorithm had a good diagnostic accuracy [area under the curve (AUC) = 0.865] and identified three risk groups (i.e., low 24%, high 70%, and very high-risk 96%) for AHF. The very high-risk group was defined by the presence of 14 or more B-lines in both hemithoraces while the high-risk group was described as having either B-lines mostly localized in superior points or in the right hemithorax. Accuracy in the validation cohort was excellent (AUC = 0.906). Importantly, adding the algorithm on top of a validated clinical score and classical definition of positive LUS scanning for AHF resulted in a significant improvement in diagnostic accuracy (continuous net reclassification improvement = 1.21, P < 0.001). Our simple lung ultrasound-based machine learning algorithm features an excellent performance and may constitute a validated strategy to diagnose 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 prognostic value of improving congestion on lung ultrasound during treatment for acute heart failure differs based on patient characteristics at admission

BACKGROUND

Lung ultrasound congestion scoring (LUS-CS) is a congestion severity biomarker. The BLUSHED-AHF trial demonstrated feasibility for LUS-CS-guided therapy in acute heart failure (AHF). We investigated two questions: 1) does change (∆) in LUS-CS from emergency department (ED) to hospital-discharge predict patient outcomes, and 2) is the relationship between in-hospital decongestion and adverse events moderated by baseline risk-factors at admission?

METHODS

We performed a secondary analysis of 933 observations/128 patients from 5 hospitals in the BLUSHED-AHF trial receiving daily LUS. ∆LUS-CS from ED arrival to inpatient discharge (scale -160 to +160, where negative = improving congestion) was compared to a primary outcome of 30-day death/AHF-rehospitalization. Cox regression was used to adjust for mortality risk at admission [Get-With-The-Guidelines HF risk score (GWTG-RS)] and the discharge LUS-CS. An interaction between ∆LUS-CS and GWTG-RS was included, under the hypothesis that the association between decongestion intensity (by ∆LUS-CS) and adverse outcomes would be stronger in admitted patients with low-mortality risk but high baseline congestion.

RESULTS

Median age was 65 years, GWTG-RS 36, left ventricular ejection fraction 36 %, and ∆LUS-CS -20. In the multivariable analysis ∆LUS-CS was associated with event-free survival (HR = 0.61; 95 % CI: 0.38-0.97), while discharge LUS-CS (HR = 1.00; 95%CI: 0.54-1.84) did not add incremental prognostic value to ∆LUS-CS alone. As GWTG-RS rose, benefits of LUS-CS reduction attenuated (interaction p < 0.05). ∆LUS-CS and event-free survival were most strongly correlated in patients without tachycardia, tachypnea, hypotension, hyponatremia, uremia, advanced age, or history of myocardial infarction at ED/baseline, and those with low daily loop diuretic requirements.

CONCLUSIONS

Reduction in ∆LUS-CS during AHF treatment was most associated with improved readmission-free survival in heavily congested patients with otherwise reassuring features at admission. ∆LUS-CS may be most useful as a measure to ensure adequate decongestion prior to discharge, to prevent early readmission, rather than modify survival.