Evidence map›Paper›PMID 34187397›Full record

ArticleBMC infectious diseases2021

Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses.

Monica L Zigman Suchsland, Ivan Rahmatullah, Barry Lutz, Victoria Lyon, Shichu Huang, Enos Kline, Chelsey Graham, Shawna Cooper, Philip Su, Sam Smedinghoff and 5 more

Open access · goldAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 36% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Article
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

15 authors at 3 institutions in 1 country.

Monica L Zigman SuchslandUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA. mzigman@uw.edu.ORCID http://orcid.org/0000-0001-7007-6973
Ivan RahmatullahUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Barry LutzUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Victoria LyonUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Shichu HuangUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Enos KlineUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Chelsey GrahamMassachusetts Institute of Technology, Cambridge, MA, USA.
Shawna CooperAudere, Seattle, WA, USA.
Philip SuAudere, Seattle, WA, USA.
Sam SmedinghoffAudere, Seattle, WA, USA.
Helen Y ChuUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Kara SewalkBoston Children's Hospital, Boston, MA, USA.
John S BrownsteinBoston Children's Hospital, Boston, MA, USA.
Matthew J ThompsonUniversity of Washington, 4225 Roosevelt Way NE Ste 308, Seattle, WA, 98105-6099, USA.
Seattle Flu Study investigators
University of Washington · USBoston Children's Hospital · USMassachusetts Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeasonal influenza leads to significant morbidity and mortality. Rapid self-tests could improve access to influenza testing in community settings. We aimed to evaluate the diagnostic accuracy of a mobile app-guided influenza rapid self-test for adults with influenza like illness (ILI), and identify optimal methods for conducting accuracy studies for home-based assays for influenza and other respiratory viruses.

methodsThis cross-sectional study recruited adults who self-reported ILI online. Participants downloaded a mobile app, which guided them through two low nasal swab self-samples. Participants tested the index swab using a lateral flow assay. Test accuracy results were compared to the reference swab tested in a research laboratory for influenza A/B using a molecular assay.

resultsAnalysis included 739 participants, 80% were 25-64 years of age, 79% female, and 73% white. Influenza positivity was 5.9% based on the laboratory reference test. Of those who started their test, 92% reported a self-test result. The sensitivity and specificity of participants' interpretation of the test result compared to the laboratory reference standard were 14% (95%CI 5-28%) and 90% (95%CI 87-92%), respectively.

conclusionsA mobile app facilitated study procedures to determine the accuracy of a home based test for influenza, however, test sensitivity was low. Recruiting individuals outside clinical settings who self-report ILI symptoms may lead to lower rates of influenza and/or less severe disease. Earlier identification of study subjects within 48 h of symptom onset through inclusion criteria and rapid shipping of tests or pre-positioning tests is needed to allow self-testing earlier in the course of illness, when viral load is higher.

Indexed as

Mobile ApplicationsSelf-TestingAdultCross-Sectional StudiesData AccuracyEnzyme-Linked Immunosorbent AssayFeasibility StudiesFemaleHumansInfluenza A virusInfluenza B virusInfluenza, HumanMaleMiddle AgedSensitivity and SpecificityAccuracyInfluenzaMobile applicationRapid diagnostic testSelf-test

Identifiers

PMID34187397
PMCPMC8240430
OpenAlexW3176360898

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.