Evidence map›Paper›PMID 39606445›Full record

ArticleResearch square2024

Healthy at Home for COPD: An Integrated Digital Monitoring, Treatment, and Pulmonary Rehabilitation Intervention.

Laurel O'Connor, Stephanie Behar, Seanan Tarrant, Pamela Stamegna, Caitlin Pretz, Jeanne Shirshac, Thomas Scornavacca, Tracey Wilkie, Kimberly Fisher, Emil Tigas and 14 more

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Laurel O'ConnorUniversity of Massachusetts Chan Medical School.
Stephanie BeharUniversity of Massachusetts Chan Medical School.
Seanan TarrantUniversity of Massachusetts Chan Medical School.
Pamela StamegnaUniversity of Massachusetts Chan Medical School.
Caitlin PretzUniversity of Massachusetts Chan Medical School.
Jeanne ShirshacUMass Memorial Medical Center.
Thomas ScornavaccaUniversity of Massachusetts Chan Medical School.
Tracey WilkieUMass Memorial Medical Center.
Kimberly FisherUniversity of Massachusetts Chan Medical School.
Emil TigasUniversity of Massachusetts Chan Medical School.
Marie MullenUniversity of Massachusetts Chan Medical School.
Michael HyderUniversity of Massachusetts Chan Medical School.
Steven WongUniversity of Massachusetts Chan Medical School.
Brendon SavageCareEvolution (United States).
Shaun ToomeyUniversity of Massachusetts Chan Medical School.
Biqi WangUniversity of Massachusetts Chan Medical School.
Adrian ZaiUniversity of Massachusetts Chan Medical School.
Eric AlperUniversity of Massachusetts Chan Medical School.
Peter LindenauerUniversity of Massachusetts Chan Medical School-Baystate Campus.
Eric DicksonUniversity of Massachusetts Chan Medical School.
John BroachUniversity of Massachusetts Chan Medical School.
David McManusUniversity of Massachusetts Chan Medical School.
Vik KheterpalCareEvolution (United States).
Apurv SoniUniversity of Massachusetts Chan Medical School.

Funding

University of Massachusetts Center for Clinical Science and Translational SupplementUL1TR001453 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2015 to 2024
$39.0M
University of Pittsburgh Clinical and Translational Science InstituteTL1TR000145 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$872k
NCATS NIH HHS TL1 TR000145NCATS NIH HHS UL1 TR001453
6 · The paper itself

Abstract

Background: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality in the United States. Frequent exacerbations result in higher use of emergency services and hospitalizations, leading to poor patient outcomes and high costs. Objective: Demonstrate the feasibility of a multimodal, digitally enhanced remote monitoring, treatment, and tele-pulmonary rehabilitation intervention among patients with COPD. Methods: In this pilot clinical trial, community-dwelling adults with moderate-severe COPD were enrolled in a multimodal digital monitoring and treatment program including a Fitbit wearable device, study app that tracked COPD-related symptoms, on-demand mobile integrated health (MIH) services for acute home-based treatment, and tele-pulmonary-rehabilitation. Participants were enrolled in the program for six months. COPD severity and health-related quality of life assessments were performed at baseline, 3 months, and 6 months. Primary feasibility outcomes include recruitment and retention rate, and participant protocol fidelity, which were reported descriptively. Exploratory clinical outcomes included patient-reported quality of life, activation, and intervention satisfaction. Results: Over 18 months, 1,333 patients were approached and 100 (7.5%) were enrolled (mean age 66, 52% female). Ninety-six participants (96%) remained in the study for the full enrollment period. Fifty-five (55%) participated in tele-pulmonary-rehabilitation. Participants wore the Fitbit for a median of 114 days (IQR 183.6) and 16.85 hours/day (4.05), resulting in a median of 1133 minutes (243) per day. Completion rates for scheduled instruments ranged from 78-93%. Nearly all participants (85%) performed COPD ecological momentary assessment at least once with a median of 4.85 recordings. On average, a 2.48-point improvement (p=0.03) in COPD Assessment Test Score was observed from baseline to study completion. The adherence and symptom improvement metrics were not associated with baseline patient activation measures. Conclusions: A multimodal intervention combining preventative care, symptom and biometric monitoring, and home treatment was feasible in adults living with COPD. Participants demonstrated high protocol fidelity and engagement and reported improved quality of life.

Identifiers

PMID39606445
PMCPMC11601823

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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.