Evidence map›Paper›PMID 36853606›Full record

ArticleJAMA network open2023

Portable Breath-Based Volatile Organic Compound Monitoring for the Detection of COVID-19 During the Circulation of the SARS-CoV-2 Delta Variant and the Transition to the SARS-CoV-2 Omicron Variant.

Ruchi Sharma, Wenzhe Zang, Ali Tabartehfarahani, Andres Lam, Xiaheng Huang, Anjali Devi Sivakumar, Chandrakalavathi Thota, Shuo Yang, Robert P Dickson, Michael W Sjoding and 7 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Harnessing breath biomarkers for pneumonia diagnosis and prognosis.Expert review of respiratory medicine · 2026
    Review
  3. Article
  4. Review
  5. Review
  6. Article
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  8. Article
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  10. Article
  11. Article
  12. Article
  13. Analytical chemistry · 2024
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Noninvasive SARS-CoV-2 detection using a low-cost electronic nose.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases
    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

17 authors at 1 institution in 1 country.

Ruchi SharmaDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Wenzhe ZangDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Ali TabartehfarahaniDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Andres LamDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Xiaheng HuangDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Anjali Devi SivakumarDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Chandrakalavathi ThotaDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Shuo YangDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Robert P DicksonMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Michael W SjodingMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Erin BiscoMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Carmen Colmenero MahmoodMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Kristen Machado DiazMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Nicholas SautterMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Sardar AnsariMax Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor.
Kevin R WardDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
Xudong FanDepartment of Biomedical Engineering, University of Michigan, Ann Arbor.
University of Michigan–Ann Arbor · US

Funding

The role of the lung microbiome in oxygen-induced lung injuryR01HL144599 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DICKSON, ROBERT PICKETT · 2019 to 2023
$2.1M
COVID-19 detection through scent analysis with a compact GC deviceU18TR003812 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FAN, XUDONG, WARD, KEVIN · 2021 to 2022
$1.9M
Midcareer Investigator Award in Patient-Oriented Research in the Microbiome and Lung DiseaseK24HL159247 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Pickett Dickson · 2022 to 2026
$625k
NCATS NIH HHS U18 TR003812NHLBI NIH HHS K24 HL159247NHLBI NIH HHS R01 HL144599
6 · The paper itself

Abstract

Importance: Breath analysis has been explored as a noninvasive means to detect COVID-19. However, the impact of emerging variants of SARS-CoV-2, such as Omicron, on the exhaled breath profile and diagnostic accuracy of breath analysis is unknown. Objective: To evaluate the diagnostic accuracies of breath analysis on detecting patients with COVID-19 when the SARS-CoV-2 Delta and Omicron variants were most prevalent. Design, Setting, and Participants: This diagnostic study included a cohort of patients who had positive and negative test results for COVID-19 using reverse transcriptase polymerase chain reaction between April 2021 and May 2022, which covers the period when the Delta variant was overtaken by Omicron as the major variant. Patients were enrolled through intensive care units and the emergency department at the University of Michigan Health System. Patient breath was analyzed with portable gas chromatography. Main Outcomes and Measures: Different sets of VOC biomarkers were identified that distinguished between COVID-19 (SARS-CoV-2 Delta and Omicron variants) and non-COVID-19 illness. Results: Overall, 205 breath samples from 167 adult patients were analyzed. A total of 77 patients (mean [SD] age, 58.5 [16.1] years; 41 [53.2%] male patients; 13 [16.9%] Black and 59 [76.6%] White patients) had COVID-19, and 91 patients (mean [SD] age, 54.3 [17.1] years; 43 [47.3%] male patients; 11 [12.1%] Black and 76 [83.5%] White patients) had non-COVID-19 illness. Several patients were analyzed over multiple days. Among 94 positive samples, 41 samples were from patients in 2021 infected with the Delta or other variants, and 53 samples were from patients in 2022 infected with the Omicron variant, based on the State of Michigan and US Centers for Disease Control and Prevention surveillance data. Four VOC biomarkers were found to distinguish between COVID-19 (Delta and other 2021 variants) and non-COVID-19 illness with an accuracy of 94.7%. However, accuracy dropped substantially to 82.1% when these biomarkers were applied to the Omicron variant. Four new VOC biomarkers were found to distinguish the Omicron variant and non-COVID-19 illness (accuracy, 90.9%). Breath analysis distinguished Omicron from the earlier variants with an accuracy of 91.5% and COVID-19 (all SARS-CoV-2 variants) vs non-COVID-19 illness with 90.2% accuracy. Conclusions and Relevance: The findings of this diagnostic study suggest that breath analysis has promise for COVID-19 detection. However, similar to rapid antigen testing, the emergence of new variants poses diagnostic challenges. The results of this study warrant additional evaluation on how to overcome these challenges to use breath analysis to improve the diagnosis and care of patients.

Indexed as

COVID-19Volatile Organic CompoundsAdultBreath TestsFemaleHumansMaleMiddle AgedSARS-CoV-2United StatesVolatile Organic Compounds

Identifiers

PMID36853606
PMCPMC9975913
OpenAlexW4322617241

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.