Evidence map›Paper›PMID 35236896›Full record

ArticleScientific reports2022

Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Ashley E Mason, Frederick M Hecht, Shakti K Davis, Joseph L Natale, Wendy Hartogensis, Natalie Damaso, Kajal T Claypool, Stephan Dilchert, Subhasis Dasgupta, Shweta Purawat and 43 more

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

53 authors.

Ashley E MasonOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA. ashley.mason@ucsf.edu.
Frederick M HechtOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Shakti K Davis *MIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Joseph L Natale *Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.
Wendy HartogensisOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Natalie DamasoMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Kajal T ClaypoolMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Stephan DilchertDepartment of Management, Zicklin School of Business, Baruch College, The City University of New York, New York, NY, USA.
Subhasis DasguptaSan Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA.
Shweta PurawatSan Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA.
Varun K ViswanathDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
Amit KleinDepartment of Bioengineering: Bioinformatics, University of California San Diego, San Diego, CA, USA.
Anoushka ChowdharyOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Sarah M FisherDepartment of Psychology, Drexel University, Pennsylvania, PA, USA.
Claudine AngloOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Karena Y PuldonOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Danou VeasnaOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Jenifer G PratherOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Leena S PandyaOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Lindsey M FoxOsher Center for Integrative Health, University of California San Francisco, San Francisco, CA, USA.
Michael BuschVitalant Research Institute, University of California San Francisco, San Francisco, CA, USA.
Casey GiordanoDepartment of Psychology, University of Minnesota - Twin Cities, Minneapolis, MN, USA.
Brittany K MercadoLove School of Business, Elon University, Elon, NC, USA.
Jining SongSan Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA.
Rafael JaimesMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Brian S BaumMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Brian A TelferMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Casandra W PhilipsonMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Paula P CollinsMIT Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Adam A RaoSchool of Medicine, University of California San Francisco, San Francisco, CA, USA.
Edward J WangDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
Rachel H BandiDepartment of Anesthesiology, Northwestern McGaw Medical Center, Feinberg School of Medicine, Chicago, IL, USA.
Bianca J ChoeDepartment of Emergency Medicine, University of California Los Angeles Health, Los Angeles, CA, USA.
Elissa S EpelCenter for Health and Community, University of California San Francisco, San Francisco, CA, USA.
Stephen K EpsteinDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center Boston, Boston, MA, USA.
Joanne B KrasnoffSchmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA.
Marco B LeeDepartment of Neurosurgery, Santa Clara Valley Medical Center, Stanford University, San Jose, CA, USA.
Shi-Wen LeeDepartment of Emergency Medicine, Jamaica Hospital Medical Center, Jamaica, NY, USA.
Gina M LopezDepartment of Emergency Medicine, Boston Medical Center, Boston, MA, USA.
Arpan MehtaDepartment of Anesthesiology: Pain Management and Perioperative Medicine, University of Miami, Miami, FL, USA.
Laura D MelvilleDepartment of Emergency Medicine, New York Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY, USA.
Tiffany S MoonDepartment of Anesthesiology and Pain Management, University of Texas Southwestern, Dallas, TX, USA.
Lilianne R Mujica-ParodiDepartment of Biomedical Engineering, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.
Kimberly M NoelStony Brook Medicine, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA.
Michael A OroscoDepartment of Anesthesia: Perioperative and Pain Medicine, Kaiser Permanente San Diego, San Diego, CA, USA.
Jesse M RideoutDepartment of Emergency Medicine, Tufts Medical Center, Boston, MA, USA.
Janet D RobishawSchmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA.
Robert M RodriguezDepartment of Emergency Medicine, University of California San Francisco, San Francisco, CA, USA.
Kaushal H ShahWeill Cornell Medical Center, Weill Cornell Medical School, New York, NY, USA.
Jonathan H SiegalNew York Presbyterian Queens, Weill-Cornell Medical College, Queens, NY, USA.
Amarnath GuptaHalıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.
Ilkay AltintasHalıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.
Benjamin L SmarrHalıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.

Funding

Mentoring and Research in Integrative MedicineK24AT007827 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HECHT, FREDERICK M · 2013 to 2022
$1.8M
Department of Defense, Air Force Office of Scientific Research MIT CA-0156247 3144-41Medical Technology Enterprise Consortium MTEC-20-12-COVID19-Diagnostics-023NCCIH NIH HHS K24 AT007827
6 · The paper itself

Abstract

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Indexed as

Body TemperatureWearable Electronic DevicesAdolescentAdultAgedAged, 80 and overAlgorithmsCOVID-19FemaleHumansMaleMiddle AgedSARS-CoV-2Young Adult

Identifiers

PMID35236896
PMCPMC8891385

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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.