Sleep Overnight Monitoring for Apnea in Patients Hospitalized with Heart Failure (SOMA-HF Study).

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Sleep Overnight Monitoring for Apnea in Patients Hospitalized with Heart Failure (SOMA-HF Study).

J Clin Sleep Med. 2017 Aug 29;:

Authors: Sharma S, Mather PJ, Chowdhury A, Gupta S, Mukhtar U, Willes L, Whellan DJ, Malhotra A, Quan SF

Abstract
INTRODUCTION: Sleep-disordered breathing (SDB) is highly prevalent in hospitalized patients with congestive heart failure (CHF) and the condition is diagnosed and treated in only a minority of these patients. Portable monitoring (PM) is a screening option, but due to costs and the expertise required, many hospitals may find it impractical to implement. We sought to test the utility of an alternative approach for screening hospitalized CHF patients for SDB, high-resolution pulse oximetry (HRPO).
METHODS: We conducted a prospective controlled trial of 125 consecutive patients admitted to the hospital with CHF. Simultaneous PM and HRPO for a single night was performed. All but one patient were monitored on breathing room air. The HRPO-derived ODI (oxygen desaturation index) was compared with PM-derived respiratory event index (REI) using both receiver operator characteristic (ROC) curve analysis and a Bland-Altman plot.
RESULTS: Of 105 consecutive CHF patients with analyzable data, 61 (58%) were males with mean age of 64.9 ± 15.1 years and mean body mass index of 30.3 ± 8.3 kg/m2. Of the 105 patients, 10 (9.5%) had predominantly central sleep apnea (central events > 50% of the total events), although central events were noted in 42 (40%) of the patients. The ROC analysis showed an area under the curve of 0.89 for REI > 5 events/h. The Bland-Altman plot showed acceptable agreement with 95% limits of agreement between -28.5 to 33.7 events/h and little bias.
CONCLUSIONS: We conclude that high-resolution pulse oximetry is a simple and cost-effective screening tool for SDB in CHF patients admitted to the hospital. Such screening approaches may be valuable for large-scale implementation and for the optimal design of interventional trials.

PMID: 28859720 [PubMed - as supplied by publisher]

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