Development and validation of a novel non‐contact monitor of nocturnal respiration for identifying sleep‐disordered breathing in patients with heart failure

Abstract

AimsAt least 50% of patients with heart failure (HF) may have sleep‐disordered breathing (SDB). Overnight in‐hospital polysomnography (PSG) is considered the gold standard for diagnosis, but a lack of access to such testing contributes to under‐diagnosis of SDB. Therefore, there is a need for simple and reliable validated methods to aid diagnosis in patients with HF. The aim of this study was to investigate the accuracy of a non‐contact type IV screening device, SleepMinderTM (SM), compared with in‐hospital PSG for detecting SDB in patients with HF.Methods and resultsThe study included 75 adult patients with systolic HF and suspected SDB who underwent simultaneous PSG and SM recordings. An algorithm was developed from the SM signals, using digital signal processing and pattern recognition techniques to calculate the SM apnoea‐hypopnoea index (AHI). This was then compared with expert‐scored PSGAHI. The SM algorithm had 70% sensitivity and 89% specificity for identifying patients with clinically significant SDB (AHI ≥ 15/h). At this threshold, it had a positive likelihood ratio of 6.3 and a negative likelihood ratio of 0.16. The overall accuracy of the SMAHI algorithm was 85.8% as shown by the area under a receiver operator characteristic curve. The mean AHI with SM was 3.8/h (95% confidence interval 0.5–7.1) lower than that with PSG.ConclusionsThe accuracy of the non‐contact type IV screening device SM is good for clinically significant SDB in patients with systolic HF and could be considered as a simple first step in the diagnostic pathway.

Co‐morbidities in heart failure beginning to sprout—and no end in sight?

“…27,28 Even though a large number of studies has been published in recent years, screening (polygraphy, questionnaires) and monitoring (e.g. SleepMinder TM ) 29 tools remain under-utilized. Unfortunately, one of the few larger randomized controlled trials, the SERVE-HF trial, 30 ended in disappointment, and it appears unlikely that adaptive servo-ventilation will be used in patients with HF in future trials or in clinical practice.…”

Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

“…2009-2016 [17,47,48] Cheyne-Stokes Respiration Correlation coefficient of 0.87 with %CSR > 5 and 0.8 with AHI > 15.…”

“…There have also been numerous reviews, comparison studies [16][17][18][19], and smart systems designs [20,21] regarding unobtrusive [22], nonintrusive [23], and non-contact physiological vital signs monitoring for sleep monitoring. However, a comprehensive review of the non-contact Doppler radar for health monitoring for OSA diagnosis has been limited.…”

Modern‐day cardio‐oncology: a report from the ‘Heart Failure and World Congress on Acute Heart Failure 2018’

“…In patients with HF, many different co‐morbidities can influence the patients' burden of disease . Common co‐morbidities in patients with HF include iron deficiency, anaemia, liver dysfunction, chronic kidney disease, central sleep apnoea, chronic obstructive pulmonary disease, sexual dysfunction, cachexia, sarcopenia, anorexia, and also cancer . Professor Rudolf De Boer from Groningen, the Netherlands, presented several studies, which have shown that cancer patients have an increased risk to develop HF and that patients with both, cancer and HF, demonstrate even worse prognosis than both diseases alone .…”