Proposed Clinical Indicators for Efficient Screening and Testing for COVID-19 Infection from Classification and Regression Trees (CART) Analysis Article Swipe
Richard K. Zimmerman
,
Mary Patricia Nowalk
,
Todd Bear
,
Rachel Taber
,
Theresa M. Sax
,
Heather Eng
,
G.K. Balasubramani
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.05.11.20097980
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.05.11.20097980
Background: The introduction and rapid transmission of SARS CoV2 in the United States resulted in implementation of methods to assess, mitigate and contain the resulting COVID-19 disease based on limited knowledge. Screening for testing has been based on symptoms typically observed in inpatients, yet outpatient symptom complexes may differ. Methods: Classification and regression trees (CART) recursive partitioning created a decision tree classifying enrollees into laboratory-confirmed cases and non-cases. Demographic and symptom data from patients ages 18-87 years who were enrolled from March 29-April 26, 2020 were included. Presence or absence of SARSCoV2 was the target variable. Results: Of 736 tested, 55 were positive for SARS-CoV2. Cases significantly more often reported chills, loss of taste/smell, diarrhea, fever, nausea/vomiting and contact with a COVID-19 case, but less frequently reported shortness of breath and sore throat. A 7-terminal node tree with a sensitivity of 96% and specificity of 53%, and an AUC of 78% was developed. The positive predictive value for this tree was 14% while the negative predictive value was 99%. Almost half (44%) of the participants could be ruled out as likely non-cases without testing. Discussion: Among those referred for testing, negative responses to three questions could classify about half of tested persons with low risk for SARS-CoV2 and would save limited testing resources. These questions are: was the patient in contact with a COVID-19 case? Has the patient experienced 1) a loss of taste or smell; or 2) nausea or vomiting? The outpatient symptoms of COVID-19 appear to be broader than the well-known inpatient syndrome.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2020.05.11.20097980
- https://www.medrxiv.org/content/medrxiv/early/2020/05/14/2020.05.11.20097980.full.pdf
- OA Status
- green
- Cited By
- 6
- References
- 4
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3025367141
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3025367141Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2020.05.11.20097980Digital Object Identifier
- Title
-
Proposed Clinical Indicators for Efficient Screening and Testing for COVID-19 Infection from Classification and Regression Trees (CART) AnalysisWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-14Full publication date if available
- Authors
-
Richard K. Zimmerman, Mary Patricia Nowalk, Todd Bear, Rachel Taber, Theresa M. Sax, Heather Eng, G.K. BalasubramaniList of authors in order
- Landing page
-
https://doi.org/10.1101/2020.05.11.20097980Publisher landing page
- PDF URL
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https://www.medrxiv.org/content/medrxiv/early/2020/05/14/2020.05.11.20097980.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.medrxiv.org/content/medrxiv/early/2020/05/14/2020.05.11.20097980.full.pdfDirect OA link when available
- Concepts
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Chills, Nausea, Cart, Medicine, Sore throat, Vomiting, Decision tree, Predictive value, Diarrhea, Internal medicine, Surgery, Machine learning, Computer science, Engineering, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
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2021: 2, 2020: 4Per-year citation counts (last 5 years)
- References (count)
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4Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_year | 2020 |
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