Evidence map›Paper›PMID 39059887›Full record

Trial reportThe Lancet. Digital health2024

Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial.

Giorgio Quer, Erin Coughlin, Jorge Villacian, Felipe Delgado, Katherine Harris, John Verrant, Matteo Gadaleta, Ting-Yang Hung, Janna Ter Meer, Jennifer M Radin and 8 more

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in The Lancet. Digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04336020 (The DETECT), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

NCT04336020 unknown statusnot on this map

The DETECT (Digital Engagement & Tracking for Early Control, & Treatment) Study

TypeobservationalSponsorScripps Translational Science InstituteRan2020 to 2025Enrolled100,000ConditionsInfluenza, Virus
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Giorgio QuerScripps Research Translational Institute, La Jolla, CA, USA. Electronic address: gquer@scripps.edu.
Erin CoughlinScripps Research Translational Institute, La Jolla, CA, USA.
Jorge VillacianJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Felipe DelgadoScripps Research Translational Institute, La Jolla, CA, USA.
Katherine HarrisJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
John VerrantJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Matteo GadaletaScripps Research Translational Institute, La Jolla, CA, USA.
Ting-Yang HungScripps Research Translational Institute, La Jolla, CA, USA.
Janna Ter MeerScripps Research Translational Institute, La Jolla, CA, USA.
Jennifer M RadinScripps Research Translational Institute, La Jolla, CA, USA.
Edward RamosScripps Research Translational Institute, La Jolla, CA, USA.
Monique AdamsJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Lomi KimJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Jason W ChienJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Katie Baca-MotesScripps Research Translational Institute, La Jolla, CA, USA.
Jay A PanditScripps Research Translational Institute, La Jolla, CA, USA.
Dmitri TalantovJanssen Pharmaceutical Research and Development, San Diego, CA, USA.
Steven R SteinhublScripps Research Translational Institute, La Jolla, CA, USA.

Funding

Scripps Clinical and Translational Science HubUM1TR004407 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI Eric Jeffrey Topol · 2023 to 2026
$24.2M
NCATS NIH HHS UM1 TR004407
6 · The paper itself

Abstract

backgroundEarly identification of an acute respiratory infection is important for reducing transmission and enabling earlier therapeutic intervention. We aimed to prospectively evaluate the feasibility of home-based diagnostic self-testing of viral pathogens in individuals prompted to do so on the basis of self-reported symptoms or individual changes in physiological parameters detected via a wearable sensor.

methodsDETECT-AHEAD was a prospective, decentralised, randomised controlled trial carried out in a subpopulation of an existing cohort (DETECT) of individuals enrolled in a digital-only observational study in the USA. Participants aged 18 years or older were randomly assigned (1:1:1) with a block randomisation scheme stratified by under-represented in biomedical research status. All participants were offered a wearable sensor (Fitbit Sense smartwatch). Participants in groups 1 and 2 received an at-home self-test kit (Alveo be.well) for two acute respiratory viral pathogens: SARS-CoV-2 and respiratory syncytial virus. Participants in group 1 could be alerted through the DETECT study app to take the at-home test on the basis of changes in their physiological data (as detected by our algorithm) or due to self-reported symptoms; those in group 2 were prompted via the app to self-test only due to symptoms. Group 3 served as the control group, without alerts or home testing capability. The primary endpoints, assessed on an intention-to-treat basis, were the number of acute respiratory infections presented (self-reported) and diagnosed (electronic health record), and the number of participants using at-home testing in groups 1 and 2. This trial is registered with ClinicalTrials.gov, NCT04336020.

findingsBetween Sept 28 and Dec 30, 2021, 450 participants were recruited and randomly assigned to group 1 (n=149), group 2 (n=151), or group 3 (n=150). 179 (40%) participants were male, 264 (59%) were female, and seven (2%) identified as other. 232 (52%) were from populations historically under-represented in biomedical research. 118 (39%) of the 300 participants in groups 1 and 2 were prompted to self-test, with 61 (52%) successfully completing self-testing. Participants were prompted to home-test more frequently due to symptoms (41 [28%] in group 1 and 51 [34%] in group 2) than due to detected physiological changes (26 [17%] in group 1). Significantly more participants in group 1 received alerts to test than did those in group 2 (67 [45%] vs 51 [34%]; p=0·047). Of the 61 individuals who were prompted to test and successfully did so, 19 (31%) tested positive for a viral pathogen-all for SARS-CoV-2. The individuals diagnosed as positive for SARS-CoV-2 in the electronic health record were eight (5%) in group 1, four (3%) in group 2, and two (1%) in group 3, but it was difficult to confirm if they were tied to symptomatic episodes documented in the trial. There were no adverse events.

interpretationIn this direct-to-participant trial, we showed early feasibility of a decentralised programme to prompt individuals to use a viral pathogen diagnostic test based on symptoms tracked in the study app or physiological changes detected using a wearable sensor. Barriers to adequate participation and performance were also identified, which would need to be addressed before large-scale implementation.

fundingJanssen Pharmaceuticals.

Indexed as

COVID-19Feasibility StudiesSelf ReportWearable Electronic DevicesAdultAgedFemaleHumansMaleMiddle AgedProspective StudiesRespiratory Syncytial VirusesRespiratory Tract InfectionsSARS-CoV-2Self-TestingUnited States

Identifiers

PMID39059887
PMCPMC11296689

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LicenceCC BY-NC-ND
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Registered trials

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.