Evidence map›Paper›PMID 30956796›Full record

Observational studyBMJ open respiratory research2019

Real-world use of rescue inhaler sensors, electronic symptom questionnaires and physical activity monitors in COPD.

Russell Bowler, Matthew Allinder, Sean Jacobson, Andrew Miller, Bruce Miller, Ruth Tal-Singer, Nicholas Locantore

Open access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMJ open respiratory research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 22 citations in OpenAlex.

  1. Trial
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  12. Article
  13. Relationship Between Clinical Control, Respiratory Symptoms and Quality of Life for Patients with COPD.International journal of chronic obstructive pulmonary disease · 2020
    Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Russell BowlerDepartment of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, Colorado, USA.
Matthew AllinderResearch & Development, GSK, Collegeville, Pennsylvania, USA.
Sean JacobsonDepartment of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, Colorado, USA.
Andrew MillerDepartment of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Denver, University of Colorado Anschutz Medical, Aurora, Colorado, USA.
Bruce MillerResearch & Development, GSK, Collegeville, Pennsylvania, USA.
Ruth Tal-SingerResearch & Development, GSK, Collegeville, Pennsylvania, USA.
Nicholas LocantoreResearch & Development, GSK, Collegeville, Pennsylvania, USA.
GlaxoSmithKline (United States) · USColorado School of Public Health · USSleepMed · USUniversity of Colorado Denver · US

Funding

Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
Metabolome and proteome profiles of emphysema and airway diseaseR01HL095432 · NHLBI · NATIONAL JEWISH HEALTH · PI BOWLER, RUSSELL PAUL · 2009 to 2012
$1.6M
NHLBI NIH HHS R01 HL095432NHLBI NIH HHS U01 HL089856NHLBI NIH HHS U01 HL089897
6 · The paper itself

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterised by airflow obstruction and other morbidities such as respiratory symptoms, reduced physical activity and frequent bronchodilator use. Recent advances in personal digital monitoring devices can permit continuous collection of these data in COPD patients, but the relationships among them are not well understood. Methods: 184 individuals from a single centre of the COPDGene cohort agreed to participate in this 3-week observational study. Each participant used a smartphone to complete a daily symptom diary (EXAcerbations of Chronic pulmonary disease Tool, EXACT), wore a wrist-worn accelerometer to record continuously physical activity and completed the Clinical Visit PROactive Physical Activity in COPD questionnaire. 58 users of metered dose inhalers for rescue (albuterol) were provided with an inhaler sensor, which time stamped each inhaler actuation. Results: Rescue inhaler use was strongly correlated with E-RS:COPD score, while step counts were correlated with neither rescue use nor E-RS:COPD score. Frequent, unpatterned inhaler use pattern was associated with worse respiratory symptoms and less physical activity compared with frequent inhaler use with a regular daily pattern. There was a strong week-by-week correlation among measurements, suggesting that 1 week of monitoring is sufficient to characterise stable patients with COPD. Discussion: The study highlights the interaction and relevance of personal real-time monitoring of respiratory symptoms, physical activity and rescue medication in patients with COPD. Additionally, visual displays of longitudinal data may be helpful for disease management to help drive conversations between patients and caregivers and for risk-based monitoring in clinical trials.

Indexed as

Fitness TrackersAdministration, InhalationAgedAged, 80 and overAlbuterolBronchodilator AgentsExerciseFemaleFollow-Up StudiesHumansLongitudinal StudiesMaleMiddle AgedMonitoring, AmbulatoryNebulizers and VaporizersPulmonary Disease, Chronic ObstructiveAlbuterolBronchodilator Agentsactivity monitorsCOPDdigital healthmedication sensorspatient-reported outcomes

Identifiers

PMID30956796
PMCPMC6424295
OpenAlexW2917309951

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.