Literature DB >> 19259717

Predicting optimal CPAP by neural network reduces titration failure: a randomized study.

Ali El Solh1, Morohunfolu Akinnusi, Anil Patel, Abid Bhat, Rachel TenBrock.   

Abstract

PURPOSE: Continuous positive airway pressure (CPAP) is considered the standard therapy for obstructive sleep apnea syndrome. In the absence of standard protocol, CPAP titration may be unsuccessful. The purpose of this study was to test the hypothesis that application of an artificial neural network (ANN) to CPAP titration would achieve an optimal CPAP pressure within a shorter time interval and would lead to a decrease in CPAP titration failure.
METHODS: One hundred fifteen patients were randomized 1:1 to either conventional CPAP titration (n = 58) or to an ANN-guided CPAP titration (n = 57). Both groups were assessed for time to optimal CPAP pressure, for titration failure, and for CPAP compliance therapy.
RESULTS: Patients in the ANN-guided CPAP titration arm were able to achieve optimal CPAP at a shorter time interval compared to the conventional group (198.7 +/- 143.8 min versus 284.0 +/- 126.5 min) (p < 0.001). There was also a lower titration failure in patients randomized to the ANN-guided CPAP titration arm (16%) compared to the conventional arm (36%) (p = 0.02). Compliance with treatment did not differ across the two arms.
CONCLUSIONS: The use of ANN for guiding CPAP titration may be superior to the conventional method in maximizing the time to achieve optimal CPAP and in reducing CPAP titration failure.

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Year:  2009        PMID: 19259717     DOI: 10.1007/s11325-009-0247-5

Source DB:  PubMed          Journal:  Sleep Breath        ISSN: 1520-9512            Impact factor:   2.816


  27 in total

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Authors:  Sanaz Lehman; Nick A Antic; Courtney Thompson; Peter G Catcheside; Jeremy Mercer; R Doug McEvoy
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9.  Obstructive sleep-disordered breathing with a dominant cyclic alternating pattern--a recognizable polysomnographic variant with practical clinical implications.

Authors:  Robert J Thomas; Mario G Terzano; Liborio Parrino; J Woodrow Weiss
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Journal:  Am Rev Respir Dis       Date:  1982-07
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5.  Randomized Clinical Trials of Machine Learning Interventions in Health Care: A Systematic Review.

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