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

BACKGROUND: Lung ultrasound (LUS) is often used to assess congestion in heart failure (HF). In this study, we assessed the prognostic role of LUS in HF patients at admission and hospital discharge, and in an out-patient 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 AHEAD and MAGGIC clinical risk scores. METHODS AND RESULTS: We pooled data of patients hospitalized for HF or followed-up in out-patient clinics from international cohorts. We enrolled 1,947 patients, at admission (n=578), discharge (n=389) and in out-patient clinic (n=980). Total LUS B-line count was calculated for the 8-zone scanning protocol. The primary outcome was a composite of re-hospitalization for HF and all-cause death. Compared to those in the lower tertiles of B-lines, patients in the highest tertile were older, more likely to have signs of HF and higher NT-proBNP levels. A higher number of B-lines was associated with increased risk of primary outcome at discharge (Tertile3 vs Tertile1: adjustedHR= 5.74 (3.26- 10.12), p<0.0001) and in out-patients (Tertile3 vs Tertile1: adjustedHR= 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 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 increased risk of morbidity and mortality, regardless of the clinical setting.

[Non-inferiority trials]. / Gli studi di non-inferiorità.

Superiority trials are designed to test the hypothesis that a given diagnostic or therapeutic strategy is better than (i.e. "superior to") placebo or an active control. Conversely, non-inferiority trials test the hypothesis that a newer (i.e. alternative) strategy is not "unacceptably worse" than a control (i.e. "traditional", or "older") strategy. Non-inferiority trials are increasingly conducted in clinical medicine more often when a "newer" strategy is supposed to offer a relevant advantage in terms other than clinical efficacy (i.e. better tolerability, less cost, simpler regimen, etc.) versus a "gold standard" traditional strategy. The principle underlying non-inferiority trials is that the above advantage justifies the preferential use of the newer strategy in the clinical practice even if the clinical efficacy of the "new" appears to be a bit worse than that of the "old", albeit not unacceptably worse (i.e. not beyond a pre-specified value). The demonstration of non-inferiority requires that the confidence interval of the point estimate (e.g. the hazard ratio) does not cross a pre-specified limit. The definition of such pre-specified limit, the so called "non-inferiority margin", is a pivotal point when planning non-inferiority trials. It denotes the maximally tolerated worse effect of the alternative strategy, compared with the traditional one, required to conclude that an alternative strategy is non-inferior to the traditional "gold standard". The non-inferiority margin is derived from previous trials evaluating the efficacy of the traditional strategy vs placebo. We reviewed the principles and the practical aspects in the design and conduct of non-inferiority trials.

Multi-modality assessment of congestion in acute heart failure: Associations with left ventricular ejection fraction and prognosis.

BACKGROUND: Integrating clinical examination with ultrasound measures of congestion could improve risk stratification in patients hospitalized with acute heart failure (AHF). AIM: To investigate the prevalence of clinical, echocardiographic and lung ultrasound (LUS) signs of congestion according to left ventricular ejection fraction (LVEF) and their association with prognosis in patients with AHF. METHODS: We pooled the data of four cohorts of patients (N = 601, 74.9±10.8 years, 59 % men) with AHF and analysed six features of congestion at enrolment: clinical (peripheral oedema and respiratory rales), biochemical (BNP/NT-proBNP≥median), echocardiographic (inferior vena cava (IVC)≥21 mm, pulmonary artery systolic pressure (PASP)≥40 mmHg, E/e'≥15) and B-lines ≥25 (8-zones) in those with reduced (<40 %, HFrEF), mildly reduced (40-49 %, HFmrEF and preserved (≥50 %HFpEF) LVEF. RESULTS: Compared to patients with HFmrEF (n = 110) and HFpEF (n = 201), those with HFrEF (N = 290) had higher natriuretic peptides, but prevalence of clinical (39 %), echocardiographic (IVC≥21 mm: 56 %, E/e'≥15: 57 %, PASP≥40 mmHg: 76 %) and LUS (48 %) signs of congestion was similar. In multivariable analysis, clinical (HR: 3.24(2.15-4.86), p < 0.001), echocardiographic [(IVC≥21 mm (HR:1.91, 1.21-3.03, p=0.006); E/e'≥15 (HR:1.54, 1.04-2.28, p = 0.031)] and LUS (HR:2.08, 1.34-3.24, p = 0.001) signs of congestion were significantly associated with all-cause mortality and/or HF re-hospitalization. Adding echocardiographic and LUS features of congestion to a model than included age, sex, systolic blood pressure, clinical congestion and natriuretic peptides, improved prediction at 90 and 180 days. CONCLUSIONS: Clinical and ultrasound signs of congestion are highly prevalent in patients with AHF, regardless of LVEF and their combined assessment improves risk stratification.

A Rare Case of Isolated Right Ventricular Loeffler's Endocarditis in Primary Hypereosinophilic Syndrome.

Hypereosinophilic syndrome (HES) is a systemic disorder with various manifestations, characterized by hypereosinophilia and caused by primary or secondary conditions. Loeffler's endocarditis (LE) represents a frequent cardiac manifestation of HES, caused by infiltration of the myocardium by eosinophilic cells, which determines endocardial damage, with subsequent inflammation, thrombosis, and fibrosis of either one or both ventricles. The diagnosis of cardiac involvement is based on a multimodality approach (i.e., two-dimensional transthoracic echocardiography [2D-TTE], speckle-tracking echocardiography [STE], and cardiac magnetic resonance [CMR]), with different findings depending on the stage of disease. STE may be useful in the initial phase when traditional imaging techniques may result negative, whereas CMR allows myocardial tissue characterization along with a better definition of the right ventricle. We present a rare case of LE with isolated right ventricular involvement in a patient with HES caused by chronic eosinophilic leukemia with constitutively activated fusion tyrosine kinase on chromosome 4q12, successfully treated with imatinib mesylate.

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.