Literature DB >> 29887234

A pilot study of daily telemonitoring to predict acute exacerbation in chronic obstructive pulmonary disease.

Joanna Miłkowska-Dymanowska1, Adam J Białas1, Waldemar Obrębski1, Paweł Górski1, Wojciech J Piotrowski2.   

Abstract

BACKGROUND: Exacerbations of COPD (ECOPD) are important events in the course of COPD and they accelerate the rate of decline of lung function, and exacerbations requiring hospitalization are associated with significant mortality. Therefore, developing approaches of prevention and early treatment of ECOPDs are of special clinical interests. One of such approaches is telecare, including home telemonitoring.
MATERIAL AND METHODS: Daily telemonitoring of HR, BP, SpO2 and spirometry was performed. Variables were compared using the bootstrap-boosted inference tests: the paired t-test or Wilcoxon signed rank test, depending on data normality, and categorical variables were compared using exact McNemar's test.
RESULTS: Nineteen patients were included to the study. We observed significant decrease in SpO2 7 days preceding ECOPD (P = 0.007; Pbootstrap-boosted = 0.005) and increase in number of events of day-to-day decrease in oxygen saturation >4% in the period of 7 days preceding ECOPD versus reference period (P = 0.02).
CONCLUSIONS: Oxygen saturation telemonitoring would be successfully used in predicting ECOPD. Recording of day-to-day decrease in oxygen saturation >4% as alarming events would be effective approach which would be easily implemented in telemonitoring devices, however this outcome should be further validated in larger size samples.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  COPD; Chronic obstructive pulmonary disease; Oxygen saturation; Telemonitoring

Mesh:

Year:  2018        PMID: 29887234     DOI: 10.1016/j.ijmedinf.2018.04.013

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  8 in total

Review 1.  Digital health for COPD care: the current state of play.

Authors:  Hang Ding; Farhad Fatehi; Andrew Maiorana; Nazli Bashi; Wenbiao Hu; Iain Edwards
Journal:  J Thorac Dis       Date:  2019-10       Impact factor: 2.895

2.  A proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: a prospective cohort study.

Authors:  Grace Hawthorne; Matthew Richardson; Neil J Greening; Dale Esliger; Samuel Briggs-Price; Emma J Chaplin; Lisa Clinch; Michael C Steiner; Sally J Singh; Mark W Orme
Journal:  Respir Res       Date:  2022-04-26

3.  Wearable Finger Pulse Oximetry for Continuous Oxygen Saturation Measurements During Daily Home Routines of Patients With Chronic Obstructive Pulmonary Disease (COPD) Over One Week: Observational Study.

Authors:  Joren Buekers; Jan Theunis; Patrick De Boever; Anouk W Vaes; Maud Koopman; Eefje Vm Janssen; Emiel Fm Wouters; Martijn A Spruit; Jean-Marie Aerts
Journal:  JMIR Mhealth Uhealth       Date:  2019-06-06       Impact factor: 4.773

4.  Day-to-Day Variability of Parameters Recorded by Home Noninvasive Positive Pressure Ventilation for Detection of Severe Acute Exacerbations in COPD.

Authors:  Weipeng Jiang; Yencheng Chao; Xiaoyue Wang; Cuicui Chen; Jian Zhou; Yuanlin Song
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2021-03-22

5.  Usability of Wearable Multiparameter Technology to Continuously Monitor Free-Living Vital Signs in People Living With Chronic Obstructive Pulmonary Disease: Prospective Observational Study.

Authors:  Grace Hawthorne; Neil Greening; Dale Esliger; Samuel Briggs-Price; Matthew Richardson; Emma Chaplin; Lisa Clinch; Michael C Steiner; Sally J Singh; Mark W Orme
Journal:  JMIR Hum Factors       Date:  2022-02-16

Review 6.  The Current and Future Role of Technology in Respiratory Care.

Authors:  Persijn Honkoop; Omar Usmani; Matteo Bonini
Journal:  Pulm Ther       Date:  2022-04-26

7.  Effectiveness of a home telemonitoring program for patients with chronic obstructive pulmonary disease in Germany: Evidence from the first three years.

Authors:  Florian Hofer; Jonas Schreyögg; Tom Stargardt
Journal:  PLoS One       Date:  2022-05-12       Impact factor: 3.752

8.  Machine-learning based feature selection for a non-invasive breathing change detection.

Authors:  Juliana Alves Pegoraro; Sophie Lavault; Nicolas Wattiez; Thomas Similowski; Jésus Gonzalez-Bermejo; Etienne Birmelé
Journal:  BioData Min       Date:  2021-07-18       Impact factor: 2.522

  8 in total

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