BACKGROUND: The development of heart failure is a turning point in the natural course of aortic stenosis (AS). Pulmonary oedema and elevated left ventricular pressure (LVP) are cardinal features of heart failure. Evaluating pulmonary oedema by lung ultrasound involves taking the upper hand with a bedside noninvasive tool that may reflect LVP.
OBJECTIVE: We sought to assess the correlation between sonographic pulmonary congestion, invasive LV pre-A pressure, and echocardiographic LV end-diastolic pressure (LVEDP) in symptomatic AS patients receiving transcatheter aortic valve replacement.
METHODS: Forty-eight consecutive patients with severe AS and planned transcatheter aortic valve implantation (TAVI) were enrolled. LVEDP was estimated to be normal or elevated using the ASE/EACVI algorithm and transmitral Doppler indices, the E/A ratio, the E/e\', and the left atrial volume index. Invasive LV pre-A pressure was used as a reference, with > 12 mm Hg defined as elevated.
RESULTS: Forty-eight patients (25 women (52%), mean age 75 years, standard deviation (SD) ± 7.7 years) were enrolled in the study. We detected severe B-lines (≥ 30) in 13 (27%) patients and moderate B-lines (15-30) in 33 (68.6%) patients. The number of B-lines increased significantly with the severity of New York Heart Association (NYHA) functional classes (Fig. 1). The B-line count was 14 ± 13 in NYHA class I patients, 20 ± 20 in class II patients, and 44 ± 35 in class III patients (p < 0.05, rho = 0.384). The number of B-lines was correlated with the E/E\' ratio (R = 0.664, p < 0.0001) and the proBNP level (R = 0. 882, p < 0.008). We found no significant correlation with the LVEDP or LVEF. The LVEDP correlated well with the E/E\' ratio (R = 0.491, p < 0.001) but not at all with E/A, DT, or LAVI. All patients had an elevated LVEDP > 12, with a mean pressure of 26 mmHg, a minimum of 13 mmHg, and a maximum of 45 mmHg, with an SD of 7.85.
CONCLUSIONS: Assessing lung ultrasonic B-lines is a straightforward and practical approach to identifying pulmonary oedema in AS patients. The number of B-lines correlated with the E/E\' ratio and the functional status of patients but did not correlate with invasive LVEDP or LVEF. All patients had elevated LVEDP that correlated with E/E\'.

Assessing for volume overload is a key component of both short and long-term management of heart failure patients. Physical examination findings are neither sensitive nor specific for detecting congestion, and subclinical congestion may not be evident at the time of examination. Point of care ultrasound (POCUS) is an efficient and non-invasive way to assess heart failure patients for volume overload. The aim of our narrative review is to summarize how each of the following ultrasound modalities can be used to assess for congestion in the heart failure population: 2D and Doppler echocardiography, lung ultrasound, inferior vena cava ultrasound, internal jugular vein ultrasound, and venous excess grading. While each of these modalities has their limitations, their use in the acute and outpatient space offers the potential to reduce heart failure readmissions and mortality.

Lung involvement represents a fearful complication in rheumatoid arthritis (RA), potentially involving all compartments of the pulmonary system. Regarding interstitial lung disease (ILD), the HRCT represents the gold standard technique for its diagnosis; however, the examination is burdened by radiation exposure and high costs. In addition, although some risk factors for ILD are known, no algorithms exist to know which patients to submit to HRCT and when. In this context, lung ultrasound (LUS) showed promising results for at least 10 years, demonstrating correlation with high resolution computed tomography (HRCT) findings in other rheumatic diseases. Here, LUS may represent a screening test providing additional information to clinical examination and pulmonary function tests. The data deriving from LUS experience in other rheumatic diseases could steer the future towards the use of this technique also in RA patients, and in this review, we report the most relevant literature regarding LUS in RA-ILD.

BACKGROUND: Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality.
OBJECTIVE: This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data.
METHODS: In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips.
RESULTS: Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts\' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance.
CONCLUSIONS: Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

Purpose The number of B-lines on lung ultrasound at hospital discharge in patients admitted with acute heart failure (AHF) is associated with poor outcomes. Assessing B-lines can be challenging to execute and replicate, depending on the clinical context. This study aims to determine whether the lung ultrasound score (LUS) at discharge predicts hospital readmission or emergency department (ED) visits in the 30 days after an AHF hospital admission. Methods  We conducted an observational study at the medical ward of the emergency unit of the Clinics Hospital of the Ribeirao Preto Medical School, University of Sao Paulo, a tertiary university hospital in Ribeirao Preto, Sao Paulo, Brazil, where consecutive adults admitted with AHF were included. On the day of hospital discharge, we measured the LUS and tracked these patients for up to 30 days to monitor emergency department visits, hospital readmission, and the number of days free from hospital stay. Results  A total of 46 patients were included in the study. A composite outcome of ED visits or hospital readmission in the 30 days after hospital discharge was achieved for 22 (47.8%) patients. The LUS at hospital discharge had a receiver operating characteristic (ROC) area of 0.93 (95% CI, 0.82-0.99) to predict the composite outcome, against 0.67 (95% CI, 0.52-0.81) for the clinical congestion score (CCS). A LUS ≥ 7 at discharge had a sensitivity of 95.5% and a specificity of 87.5% to predict the composite outcome. The average exam duration was 176±65 (sd) seconds. Conclusions The LUS at hospital discharge following admission for AHF proves to be an accurate tool for predicting the likelihood of return to the ED and/or hospital readmission within 30 days post discharge.

Background: Shiga toxin-producing Escherichia coli-haemolytic uremic syndrome (STEC-HUS) can result in kidney and neurological complications. Early volume-expansion therapy has been shown to improve outcomes, but caution is required to avoid fluid overload. Lung ultrasound scanning (LUS) can be used to detect fluid overload and may be useful in monitoring hydration therapy. Methods: This prospective observational pilot study involved children with STEC-HUS who were recruited from a regional paediatric nephrology centre. B-line quantification by LUS was used to assess fluid status at the emergency department (ED) admission and correlated with the decrease in patient weight from the target weight. A control group of children on chronic dialysis therapy with episodes of symptomatic fluid overload was also enrolled in order to establish a B-line threshold indicative of severe lung congestion. Another cohort of \"healthy\" children, without renal or lung-related diseases, and without clinical signs of fluid overload was also enrolled in order to establish a B-line threshold indicative of euvolemia. Results: LUS assessment was performed in 10 children with STEC-HUS at ED admission, showing an average of three B-lines (range 0-10). LUS was also performed in 53 euvolemic children admitted to the ED not showing kidney and lung disease (healthy controls), showing a median value of two B-lines (range 0-7), not significantly different from children with STEC-HUS at admission (p = 0.92). Children with STEC-HUS with neurological involvement during the acute phase and those requiring dialysis presented a significantly lower number of B-lines at admission compared to patients with a good clinical course (p < 0.001). Patients with long-term renal impairment also presented a lower number of B-lines at disease onset (p = 0.03). Conclusions: LUS is a useful technique for monitoring intravenous hydration therapy in paediatric patients with STEC-HUS. A low number of B-lines at ED admission (<5 B-lines) was associated with worse short-term and long-term outcomes. Further studies are needed to determine the efficacy and safety of an LUS-guided strategy for reducing complications in children with STEC-HUS.

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.

UNASSIGNED: Lung ultrasound (LUS) is a simple bedside tool to assess overhydration. Our study aimed to assess extravascular lung water (EVLW) using B-lines and correlate it with weaning, duration of mechanical ventilation, and mortality in critically ill patients admitted to the intensive care unit (ICU).
UNASSIGNED: 150 mechanically ventilated ICU patients prospectively observed over 18 months, with their demographic and clinical data noted. Extravascular lung water was monitored using LUS in four intercostal spaces (ICS) from day 1 to day 5, day 7, day 10, and weekly thereafter. Pulmonary fluid burden was graded as low (1-10), moderate (11-20), and high (21-32). Weaning outcome, duration of weaning, mechanical ventilation, ICU stay, and mortality were compared in patients with and without EVLW.
UNASSIGNED: Out of 150, 54 patients (36.0%) had EVLW. The mean lung score amongst our patients was 8.57 ± 6.0. The mean time for detection of EVLW was 1.43 ± 2.24 days. Lung score was low in 40 (26.67%) patients, moderate in 9 (6.00%) patients, and high in 5 (3.33%) patients. Incidence of weaning failure (p-value = 0.006), duration of weaning, mechanical ventilation, ICU stay (p-value < 0.0001 each), and overall mortality were significantly higher in patients with EVLW (p-value = 0.006).
UNASSIGNED: We conclude that a good proportion of critically ill patients have EVLW. Extravascular lung water significantly increases the duration of weaning, mechanical ventilation days, ICU stay, and overall mortality in critically ill patients.
UNASSIGNED: Rajpal M, Talwar V, Krishna B, Mustafi SM. Assessment of Extravascular Lung Water Using Lung Ultrasound in Critically Ill Patients Admitted to Intensive Care Unit. Indian J Crit Care Med 2024;28(2):165-169.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) frequently occurs in haemodialysis patients and is associated with adverse outcomes. Lung ultrasound (LUS) has been recently proposed for the quantification of extravascular lung water through assessment of B-lines. LUS findings and their relationship with LVDD in clinically euvolemic haemodialysis patients were investigated in this study.
METHODS: Echocardiography and LUS examinations were performed on each patient. Multivariate linear regression and forward stepwise logistic regression were performed to determine the relationship between B-lines and LVDD. A receiver operating characteristic (ROC) curve with area under the curve (AUC) was calculated to determine the accuracy of B-lines for evaluating LVDD.
RESULTS: A total of 119 patients were enrolled. The number of B-lines was statistically related to echocardiographic parameters (LAVI, LVEDVI, E/A, and E/e\') of diastolic function, while the relationship between B-lines and LVEF disappeared after adjusting for potential confounding factors. Additionally, compared with the mild B-line group (B-lines: <14), the moderate (B-lines: 14-30) and severe B-line groups (B-lines: >30) were associated with an increased risk of LVDD (OR 24.344, 95% CI 4.854-122.084, p < 0.001, and OR 94.552, 95% CI 9.617-929.022, p < 0.001, respectively). Furthermore, the AUC of the ROC curve for B-lines predicting LVDD was 0.845, and the cut-off of B-lines was 14.5 (sensitivity 64.91%, specificity 93.55%).
CONCLUSIONS: LUS B-lines were closely associated with left ventricular diastolic function in clinically euvolemic haemodialysis patients. Moreover, our findings suggested a B-line ≥14.5 as a reliable cut-off value for identifying patients with LVDD. LUS B-lines may be used as a novel indicator for evaluating LVDD.

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