About: A predictive tool for identification of SARS-CoV-2 PCR-negative emergency department patients using routine test results

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About: A predictive tool for identification of SARS-CoV-2 PCR-negative emergency department patients using routine test results Goto Sponge NotDistinct Permalink

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A predictive tool for identification of SARS-CoV-2 PCR-negative emergency department patients using routine test results
Creator	Sung, Heungsup Pejaver, Vikas Banaei, Niaz Lee, Hye-Young Lee, Gregory Pinsky, Benjamin Lee, Kyu Scott, Gregory Shah, Nigam Lee, Seong Mooney, Sean Gombar, Saurabh Shah, Sam Schneider, Daniel Ahmad, David Ahmad, Faraz Al'ona Furmanchuk, Al'ona Furmanchuk, Hye-Young Banaei, Gombar, Nigam Hammarlund, Noah Joshi, Rohan Kho, Abel Kho, Sean Liebovitz, Abel Liebovitz, David Mooney, Benjamin Nassiri, Anna Nassiri, Daniel Pinsky, Niaz Schneider, Faraz Scott, Saurabh Shen, Anna Shen, Sam
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: Testing for COVID-19 remains limited in the United States and across the world. Poor allocation of limited testing resources leads to misutilization of health system resources, which complementary rapid testing tools could ameliorate. OBJECTIVE: To prediction tool based on complete blood count components and patient sex could predict SARS-CoV-2 PCR positivity. STUDY DESIGN: A retrospective case-control design for collection of data and a logistic regression prediction model was used. Participants were emergency department patients > 18 years old who had concurrent complete blood counts and SARS-CoV-2 PCR testing. 33 confirmed SARS-CoV-2 PCR positive and 357 negative patients at Stanford Health Care used for model training. Validation cohorts consisted of emergency department patients > 18 years old who had concurrent complete blood counts and SARS-CoV-2 PCR testing in Northern California (41 PCR positive, 495 PCR negative), Seattle, Washington (40 PCR positive, 306 PCR negative), Chicago, Illinois (245 PCR positive, 1015 PCR negative), and South Korea (9 PCR positive, 236 PCR negative). RESULTS: A decision support tool that utilizes components of complete blood count and patient sex for prediction of SARS-CoV-2 PCR positivity demonstrated a C-statistic of 78%, an optimized sensitivity of 93%, and generalizability to other emergency department populations. By restricting PCR testing to predicted positive patients in a hypothetical scenario of 1000 patients requiring testing but testing resources limited to 60% of patients, this tool would allow a 33% increase in properly allocated resources. CONCLUSIONS: A prediction tool based on complete blood count results can better allocate SARS-CoV-2 testing and other health care resources such as personal protective equipment during a pandemic surge.
has issue date	2020-06-10(xsd:dateTime)
bibo:doi	10.1016/j.jcv.2020.104502
bibo:pmid	32544861
has license	no-cc
sha1sum (hex)	65a64c2542951cf39dd0f17842f0355a30e76a37
schema:url	https://doi.org/10.1016/j.jcv.2020.104502
resource representing a document's title	A predictive tool for identification of SARS-CoV-2 PCR-negative emergency department patients using routine test results
has PubMed Central identifier	PMC7286235
has PubMed identifier	32544861
schema:publication	J Clin Virol
resource representing a document's body	covid:65a64c2542951cf39dd0f17842f0355a30e76a37#body_text
is schema:about of	named entity 'predictive' named entity 'Left' named entity 'model' named entity 'SARS-CoV-2' named entity 'EXPECTED' named entity 'CONFUSION MATRIX' named entity 'ACROSS' named entity 'SARS-COV-2' named entity 'POSITIVE PREDICTIVE VALUE' named entity 'USED' named entity 'RECEIVER' named entity 'OPERATING' named entity 'HEALTH CARE' named entity 'predictive' named entity 'curve' named entity 'predictive' named entity 'Avg' named entity 'expected' named entity 'operating point' named entity 'area' named entity 'Stanford Health Care' named entity 'sets' named entity 'negative' named entity 'probability' named entity 'patients' named entity 'Receiver operating characteristic' named entity 'AUC' named entity 'area under curve' named entity 'SARS-CoV-2' named entity 'classifier' named entity 'Illinois' named entity 'Stanford Health Care' named entity 'Receiver operating characteristic' named entity 'PCR' named entity 'SARS-CoV-2' named entity 'PCR' named entity 'patients' named entity 'absolute lymphocyte count' named entity 'receiver operating characteristic' named entity 'PCR' named entity 'ANC' named entity 'SARS-CoV-2' named entity 'WHO' named entity 'PCR' named entity 'CBC' named entity 'univariate analysis' named entity 'absolute neutrophil count' named entity 'SARS-CoV-2'

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