Evidence map›Paper›PMID 35558638›Full record

ArticleDigital health

High-throughput digital cough recording on a university campus: A SARS-CoV-2-negative curated open database and operational template for acoustic screening of respiratory diseases.

Eric M Keen, Emily J True, Alyssa R Summers, Everett Clinton Smith, Joe Brew, Simon Grandjean Lapierre

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Eric M KeenSewanee: The University of the South, Sewanee, TN, USA.ORCID https://orcid.org/0000-0002-3053-3612
Emily J TrueSewanee: The University of the South, Sewanee, TN, USA.
Alyssa R SummersSewanee: The University of the South, Sewanee, TN, USA.
Everett Clinton SmithSewanee: The University of the South, Sewanee, TN, USA.
Joe BrewHyfe, Inc., Wilmington, DE, USA.
Simon Grandjean LapierreDepartment of Microbiology, Infectious Diseases and Immunology, Université de Montréal, Montréal, Québec, Canada.ORCID https://orcid.org/0000-0003-3646-1573

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Respiratory illnesses have information-rich acoustic biomarkers, such as cough, that can potentially play an important role in screening populations for disease risk. To realize that potential, datasets of paired acoustic-clinical samples are needed for the development and validation of acoustic screening models, and protocols for collecting acoustic samples must be efficient and safe. We collected cough acoustic signatures at a high-throughput SARS-CoV-2 testing site on a college campus. Here, we share logistical details and the dataset of acoustic cough signatures paired with the gold standard in SARS-CoV-2 testing of SARS-CoV-2 genomic sequences using qRT-PCR. Methods: Cough recordings were collected in winter-spring 2021 at a rural residential college (Sewanee, TN, USA), where approximately 2000 students were tested for SARS-CoV-2 on a weekly basis. Cough collection was managed by student volunteers using custom software. Results: 4302 coughs were recorded from 960 participants over 11 weeks. All coughs were COVID-19 negative. Approximately 30 s were required to check-in a participant and collect their cough. Conclusion: The value of acoustic screening tools depends upon our ability to develop and implement them reliably and quickly. For that to happen, high-quality datasets and logistical insights must be collected and shared on an ongoing basis.

Indexed as

acoustic epidemiologyacoustic screeningCOVID-19logisticsmachine learning < generalopen sourceSARS-CoV-2

Identifiers

PMID35558638
PMCPMC9087241

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.