Extravascular lung water (EVLW) is a key variable in heart failure management and prognosis, but its objective assessment remains elusive. Lung imaging has been traditionally considered off-limits ...for ultrasound techniques due to the acoustic barrier of high-impedance air wall. In pulmonary congestion however, the presence of both air and water creates a peculiar echo fingerprint. Lung ultrasound shows B-lines, comet-like signals arising from a hyper-echoic pleural line with a to-and-fro movement synchronized with respiration. Increasing EVLW accumulation changes the normal, no-echo signal (black lung, no EVLW) into a black-and-white pattern (interstitial sub-pleural oedema with multiple B-lines) or a white lung pattern (alveolar pulmonary oedema) with coalescing B-lines. The number and spatial extent of B-lines on the antero-lateral chest allows a semi-quantitative estimation of EVLW (from absent, ≤5, to severe pulmonary oedema, >30 B-lines). Wet B-lines are made by water and decreased by diuretics, which cannot modify dry B-lines made by connective tissue. B-lines can be evaluated anywhere (including extreme environmental conditions with pocket size instruments to detect high-altitude pulmonary oedema), anytime (during dialysis to titrate intervention), by anyone (even a novice sonographer after 1 h training), and on anybody (since the chest acoustic window usually remains patent when echocardiography is not feasible). Cardiologists can achieve much diagnostic gain with little investment of technology, training, and time. B-lines represent 'the shape of lung water'. They allow non-invasive detection, in real time, of even sub-clinical forms of pulmonary oedema with a low cost, radiation-free approach.
Asymptomatic left ventricular dysfunction (ALVD) is present in 3-6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found
. An inexpensive, ...noninvasive screening tool for ALVD in the doctor's office is not available. We tested the hypothesis that application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart's electrical activity, could identify ALVD. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction (a measure of contractile function), from 44,959 patients at the Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7%, respectively. In patients without ventricular dysfunction, those with a positive AI screen were at 4 times the risk (hazard ratio, 4.1; 95% confidence interval, 3.3 to 5.0) of developing future ventricular dysfunction compared with those with a negative screen. Application of AI to the ECG-a ubiquitous, low-cost test-permits the ECG to serve as a powerful screening tool in asymptomatic individuals to identify ALVD.
Assessment of left ventricular systolic function has a central role in the evaluation of cardiac disease. Accurate assessment is essential to guide management and prognosis. Numerous ...echocardiographic techniques are used in the assessment, each with its own advantages and disadvantages. This review is based on a literature search of the PubMed, MEDLINE, EMBASE, and Scopus databases from inception through December 30, 2017, using the terms strain echocardiography, tissue Doppler strain, and speckle-tracking echocardiography. We provide the internist with a contemporary overview of current echocardiographic techniques used in the evaluation of left ventricular systolic function. In particular, we focus on the role of speckle-tracking echocardiography, including its utility in the detection of subclinical left ventricular dysfunction and the associated prognostic implications.
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