Remote dielectric sensing detects pulmonary congestion in emergency patients with dyspnoea

Abstract

Background Immediate diagnosis of acute decompensated heart failure (ADHF) is essential in patients with dyspnoea. Remote Dielectric Sensing (ReDS), an electromagnetic non-invasive technology, estimates lung fluid content fast and observer-independently. In previous studies, ReDS discriminated congested heart failure patients from normal subjects with high accuracy. But not all ADHF patients have pulmonary interstitial congestion in the real world, and it is unknown if ReDS detects ADHF in consecutive patients with acute dyspnoea. Purpose To examine if ReDS can detect ADHF in consecutive dyspnoeic emergency patients and to compare ReDS with other diagnostic methods. Method This prospective observational study included consecutive patients with dyspnoea from the emergency departments. The exclusion criteria were age below 50 years, acute coronary syndrome, conditions prohibiting a supine CT scan, and no informed consent. We examined all patients immediately with ReDS, low-dose chest CT, echocardiogram, lung ultrasound (LUS), NT-proBNP, and Boston score. The Boston score used chest X-ray and clinical signs such as orthopnoea, jugular venous elevation, lung crackles and pedal oedema, and a score ≥8 equalled definite ADHF. A “LUS-score” ≥3 with at least 3 B-lines in one zone bilaterally equalled ADHF. ReDS values >35% lung fluid content were positive for pulmonary congestion, according to previous studies. According to ESC guidelines, an expert panel adjudicated the ADHF diagnosis based on clinical signs, chest X-ray image, NT-proBNP, echocardiographic cardiac dysfunction (HFvhd, HFrEF, HFmrEF, HFpEF), and elevated LV filling pressure. Importantly, the panel was blinded to the ReDS values. For sub-analyses, we divided ADHF patients into a “CT-congested” ADHF subgroup if an independent chest CT showed interstitial congestion. We classified ADHF patients without congestion on CT, as the “mildly-congested” subgroup. Results 97 included patients were examined within a median of 4.8 hours from admittance: 39 (40%) had ADHF, and 25 (26%) were ReDS-positive. ADHF patients had median LVEF 48%, NT-proBNP 347 pmol/l, and 85% had echocardiographic elevated LV filling pressure. ReDS detected ADHF with 46% sensitivity, 88% specificity, and 71% accuracy. The AUC for ReDS to detect ADHF (Figure 1), on a continuous scale, was similar to the Boston score (p=0.88) and the LUS score (p=0.74), but lower than NT-proBNP (p=0.02). The 21 (22%) CT-congested ADHF patients had higher ReDS values than the 18 (19%) mildly-congested ADHF patients (Figure 2, median 38% vs 30%, p<0.001). Furthermore, the mildly-congested ADHF patients had ReDS values similar to non-ADHF patients (median 30% vs 28%, p=0.36). Conclusion ReDS detects ADHF similarly to the Boston score and lung ultrasound but is inferior to NT-proBNP. This study suggests that ReDS primarily identifies CT-congested ADHF patients, but not the ADHF patients without interstitial congestion. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): This work was supported by the research fund of Bispebjerg University Hospital and Holger & Ruth Hesse's Mindefond. Sensible Medical Ltd made the ReDS device available for free and provided an unrestricted grant to specifically collect the ReDS measurements. The sponsors did not affect the statistical analyses, study design, data collection, or writing of the paper.

Natriuretic Peptides and need for reliable tool to assess pulmonary congestion for treatment monitoring in Heart Failure

“… 36 , 37 An absolute value of 37% of lung fluid determined by ReDS technology had sensitivity, specificity, positive predictive value, and negative predictive value of 89%, 83%, 74%, and 93%, respectively. 38 , 39 A meta-analysis of seven studies to determine effect of ReDS monitoring yielded a 60% reduction in 3 month rehospitalization rates. 29 This make non-invasive monitoring of lung fluid for treatment monitoring a potential tool in the management of HF patients to reduce rehospitalization.…”