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Título:
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Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy
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Autor/a:
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Rafael-Palou, Xavier; Turino, Cecilia; Steblin, Alexander; Sánchez de la Torre, Manuel; Barbé Illa, Ferran; Vargiu, Eloisa
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Notas:
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Background: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure
(CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious
consequences for the patients’ health. Unfortunately, there is a clear lack of clinical analytical tools to support the early
prediction of compliant patients.
Methods: This work intends to take a further step in this direction by building compliance classifiers with CPAP
therapy at three different moments of the patient follow-up, before the therapy starts (baseline) and at months 1 and
3 after the baseline.
Results: Results of the clinical trial shows that month 3 was the time-point with the most accurate classifier reaching
an f1-score of 87% and 84% in cross-validation and test. At month 1, performances were almost as high as in month 3
with 82% and 84% of f1-score. At baseline, where no information of patients’ CPAP use was given yet, the best
classifier achieved 73% and 76% of f1-score in cross-validation and test set respectively. Subsequent analyzes carried
out with the best classifiers of each time point revealed baseline factors (i.e. headaches, psychological symptoms,
arterial hypertension and EuroQol visual analog scale) closely related to the prediction of compliance independently
of the time-point. In addition, among the variables taken only during the follow-up of the patients, Epworth and the
average nighttime hours were the most important to predict compliance with CPAP.
Conclusions: Best classifiers reported high performances after one month of treatment, being the third month when
significant differences were achieved with respect to the baseline. Four baseline variables were reported relevant for
the prediction of compliance with CPAP at each time-point. Two characteristics more were also highlighted for the
prediction of compliance at months 1 and 3.
This work is part of the myOSA project (RTC-2014-3138-1), funded by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economía y Competitividad) under the framework “Retos-Colaboración”, State Scientific and Technical Research and Innovation Plan 2013-2016. The study was also partially funded by the European Community under “H2020-EU.3.1. – Societal Challenges – Health, demographic change and well-being” programme, project grant agreement number 689802 (CONNECARE). |
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Materia(s):
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-Obtrusive sleep apnea
-Continuous positive airway pressure
-Predictive methods
-Machine learning |
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Derechos:
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cc-by (c) Xavier Rafael-Palou et al., 2018
http://creativecommons.org/licenses/by/4.0/
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Tipo de documento:
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Artículo
Artículo - Versión publicada |
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Editor:
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BMC
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Compartir:
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