Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use

Abstract Pulse oximetry is routinely used to non-invasively monitor oxygen saturation levels. A low oxygen level in the blood means low oxygen in the tissues, which can ultimately lead to organ failure. Yet, contrary to heart rate variability measures, a field which has seen the development of stabl...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jeremy Levy, Daniel Álvarez, Aviv A. Rosenberg, Alexandra Alexandrovich, Félix del Campo, Joachim A. Behar
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/668e4d02796e408fa214177ea6aaf5bd
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:668e4d02796e408fa214177ea6aaf5bd
record_format	dspace
spelling	oai:doaj.org-article:668e4d02796e408fa214177ea6aaf5bd2021-12-02T14:24:01ZDigital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use10.1038/s41746-020-00373-52398-6352https://doaj.org/article/668e4d02796e408fa214177ea6aaf5bd2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41746-020-00373-5https://doaj.org/toc/2398-6352Abstract Pulse oximetry is routinely used to non-invasively monitor oxygen saturation levels. A low oxygen level in the blood means low oxygen in the tissues, which can ultimately lead to organ failure. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and open tools exist for continuous oxygen saturation time series variability analysis. The primary objective of this research was to identify, implement and validate key digital oximetry biomarkers (OBMs) for the purpose of creating a standard and associated reference toolbox for continuous oximetry time series analysis. We review the sleep medicine literature to identify clinically relevant OBMs. We implement these biomarkers and demonstrate their clinical value within the context of obstructive sleep apnea (OSA) diagnosis on a total of n = 3806 individual polysomnography recordings totaling 26,686 h of continuous data. A total of 44 digital oximetry biomarkers were implemented. Reference ranges for each biomarker are provided for individuals with mild, moderate, and severe OSA and for non-OSA recordings. Linear regression analysis between biomarkers and the apnea hypopnea index (AHI) showed a high correlation, which reached $$\overline R ^2 = 0.82$$ R ¯ 2 = 0.82 . The resulting python OBM toolbox, denoted “pobm”, was contributed to the open software PhysioZoo ( physiozoo.org ). Studying the variability of the continuous oxygen saturation time series using pbom may provide information on the underlying physiological control systems and enhance our understanding of the manifestations and etiology of diseases, with emphasis on respiratory diseases.Jeremy LevyDaniel ÁlvarezAviv A. RosenbergAlexandra AlexandrovichFélix del CampoJoachim A. BeharNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Jeremy Levy Daniel Álvarez Aviv A. Rosenberg Alexandra Alexandrovich Félix del Campo Joachim A. Behar Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
description	Abstract Pulse oximetry is routinely used to non-invasively monitor oxygen saturation levels. A low oxygen level in the blood means low oxygen in the tissues, which can ultimately lead to organ failure. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and open tools exist for continuous oxygen saturation time series variability analysis. The primary objective of this research was to identify, implement and validate key digital oximetry biomarkers (OBMs) for the purpose of creating a standard and associated reference toolbox for continuous oximetry time series analysis. We review the sleep medicine literature to identify clinically relevant OBMs. We implement these biomarkers and demonstrate their clinical value within the context of obstructive sleep apnea (OSA) diagnosis on a total of n = 3806 individual polysomnography recordings totaling 26,686 h of continuous data. A total of 44 digital oximetry biomarkers were implemented. Reference ranges for each biomarker are provided for individuals with mild, moderate, and severe OSA and for non-OSA recordings. Linear regression analysis between biomarkers and the apnea hypopnea index (AHI) showed a high correlation, which reached $$\overline R ^2 = 0.82$$ R ¯ 2 = 0.82 . The resulting python OBM toolbox, denoted “pobm”, was contributed to the open software PhysioZoo ( physiozoo.org ). Studying the variability of the continuous oxygen saturation time series using pbom may provide information on the underlying physiological control systems and enhance our understanding of the manifestations and etiology of diseases, with emphasis on respiratory diseases.
format	article
author	Jeremy Levy Daniel Álvarez Aviv A. Rosenberg Alexandra Alexandrovich Félix del Campo Joachim A. Behar
author_facet	Jeremy Levy Daniel Álvarez Aviv A. Rosenberg Alexandra Alexandrovich Félix del Campo Joachim A. Behar
author_sort	Jeremy Levy
title	Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
title_short	Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
title_full	Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
title_fullStr	Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
title_full_unstemmed	Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
title_sort	digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/668e4d02796e408fa214177ea6aaf5bd
work_keys_str_mv	AT jeremylevy digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse AT danielalvarez digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse AT avivarosenberg digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse AT alexandraalexandrovich digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse AT felixdelcampo digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse AT joachimabehar digitaloximetrybiomarkersforassessingrespiratoryfunctionstandardsofmeasurementphysiologicalinterpretationandclinicaluse
_version_	1718391430417743872

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use

Ejemplares similares