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The predictors for COPD exacerbations using remote patient monitoring

Worawan Sirichana, Xiaoyan Wang, Michael Taylor, Igor Barjaktarevic, Christopher B. Cooper
European Respiratory Journal 2015 46: PA4589; DOI: 10.1183/13993003.congress-2015.PA4589
Worawan Sirichana
1Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA United States
2Division of Pulmonary and Critical Care, Department of Medicine, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
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Xiaoyan Wang
3Statistics Core, Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA United States
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Michael Taylor
4Healthcare Solutions, eResearch Technology, Philadelphia, PA United States
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Igor Barjaktarevic
1Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA United States
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Christopher B. Cooper
1Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA United States
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Abstract

Introduction: Remote patient monitoring (RPM) averts hospitalization in chronic heart failure. Benefit from RPM in COPD is still unclear. However, early detection and treatment of COPD exacerbations should also avert hospitalization and potentially reduce healthcare expenditure.

Aims: Our aim was to identify the best parameters to monitor at home in COPD patients for the prediction of exacerbations.

Methods: We conducted a prospective study to evaluate the effects of a RPM in patients with moderate to severe COPD. We obtained daily symptom scores using a programmable device (SpiroPro®, eResearch Technology) and measured daily spirometry (FEV1, FVC, PEF), inspiratory capacity(IC) and oxygenation (SpO2). Statistical process control (decrease below 7-day average-1.645 SD for 2 consecutive days) was used to detect abnormal values (predictors). Exacerbations were defined by standard criteria. Agreement between predictors and outcomes was analyzed by concordance analysis.

Results: We obtained data for 2,618 monitoring days in 11 subjects: mean(SD) age 71.1(7.2) years, FEV1 1.54 (0.73) L or 56.8 (15.9)% predicted. Event rates/patient-year for outcomes were: self-reported 0.42, 2/3 Anthonisen Criteria (AC) 0.42, modified AC 2.23, systemic corticosteroids use 0.56 and antibiotics use 0.56. Declines in FVC and FEV1 predicted exacerbations that were self-reported (kappa 0.525; P<0.001). Declines in SpO2 and increased short-acting bronchodilator use predicted exacerbations defined by 2/3 AC or modified AC (kappa 0.353 and 0.462 respectively; P<0.001).

Conclusions: We have demonstrated the feasibility of RPM in COPD patients at home and identified predictors of exacerbations that could be deployed in future health maintenance programs.

  • COPD - exacerbations
  • Lung function testing
  • Telemedicine
  • Copyright ©ERS 2015
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The predictors for COPD exacerbations using remote patient monitoring
Worawan Sirichana, Xiaoyan Wang, Michael Taylor, Igor Barjaktarevic, Christopher B. Cooper
European Respiratory Journal Sep 2015, 46 (suppl 59) PA4589; DOI: 10.1183/13993003.congress-2015.PA4589

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The predictors for COPD exacerbations using remote patient monitoring
Worawan Sirichana, Xiaoyan Wang, Michael Taylor, Igor Barjaktarevic, Christopher B. Cooper
European Respiratory Journal Sep 2015, 46 (suppl 59) PA4589; DOI: 10.1183/13993003.congress-2015.PA4589
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