Evidence map›Paper›PMID 33931692›Full record

ArticleScientific reports2021

Standard blood laboratory values as a clinical support tool to distinguish between SARS-CoV-2 positive and negative patients.

Rainer Thell, Jascha Zimmermann, Marton Szell, Sabine Tomez, Philip Eisenburger, Moritz Haugk, Anna Kreil, Alexander Spiel, Amelie Blaschke, Anna Klicpera and 5 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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  7. Insights Into the Changing Landscape of Coronavirus Disease 2019.Frontiers in cellular and infection microbiology · 2021
    Review
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

15 authors at 5 institutions in 1 country.

Rainer ThellWiener Gesundheitsverbund, Vienna, Austria.
Jascha ZimmermannMedical School, Sigmund Freud University, Vienna, Austria.
Marton SzellWiener Gesundheitsverbund, Vienna, Austria.
Sabine TomezWiener Gesundheitsverbund, Vienna, Austria.
Philip EisenburgerWiener Gesundheitsverbund, Vienna, Austria.
Moritz HaugkWiener Gesundheitsverbund, Vienna, Austria.
Anna KreilWiener Gesundheitsverbund, Vienna, Austria.
Alexander SpielWiener Gesundheitsverbund, Vienna, Austria.
Amelie BlaschkeWiener Gesundheitsverbund, Vienna, Austria.
Anna KlicperaWiener Gesundheitsverbund, Vienna, Austria.
Oskar JanataWiener Gesundheitsverbund, Vienna, Austria.
Walter KruglugerWiener Gesundheitsverbund, Vienna, Austria.
Christian SebestaWiener Gesundheitsverbund, Vienna, Austria.
Harald HerknerMedical University, Vienna, Austria.
Brenda LakyAustrian Research Group for Regenerative and Orthopedic Medicine (AURROM), Hartmanngasse 15/10, 1050, Vienna, Austria. brenda.laky@meduniwien.ac.at.ORCID 0000-0003-1198-4132
Donauspital · ATWiener Krankenanstaltenverbund · ATSigmund Freud Privatuniversität Wien · ATAustrian Cluster for Tissue Regeneration · ATMedical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standard blood laboratory parameters may have diagnostic potential, if polymerase-chain-reaction (PCR) tests are not available on time. We evaluated standard blood laboratory parameters of 655 COVID-19 patients suspected to be infected with SARS-CoV-2, who underwent PCR testing in one of five hospitals in Vienna, Austria. We compared laboratory parameters, clinical characteristics, and outcomes between positive and negative PCR-tested patients and evaluated the ability of those parameters to distinguish between groups. Of the 590 patients (20-100 years, 276 females and 314 males), 208 were PCR-positive. Positive compared to negative PCR-tested patients had significantly lower levels of leukocytes, neutrophils, basophils, eosinophils, lymphocytes, neutrophil-to-lymphocyte ratio, monocytes, and thrombocytes; while significantly higher levels were detected with erythrocytes, hemoglobin, hematocrit, C-reactive-protein, ferritin, activated-partial-thromboplastin-time, alanine-aminotransferase, aspartate-aminotransferase, lipase, creatine-kinase, and lactate-dehydrogenase. From all blood parameters, eosinophils, ferritin, leukocytes, and erythrocytes showed the highest ability to distinguish between COVID-19 positive and negative patients (area-under-curve, AUC: 72.3-79.4%). The AUC of our model was 0.915 (95% confidence intervals, 0.876-0.955). Leukopenia, eosinopenia, elevated erythrocytes, and hemoglobin were among the strongest markers regarding accuracy, sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, and post-test probabilities. Our findings suggest that especially leukopenia, eosinopenia, and elevated hemoglobin are helpful to distinguish between COVID-19 positive and negative tested patients.

Indexed as

AgedAustriaCOVID-19COVID-19 Nucleic Acid TestingFemaleHematologic TestsHumansMaleSeverity of Illness Index

Identifiers

PMID33931692
PMCPMC8087776
OpenAlexW3157754157

What OpenQuestion holds

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LicenceCC BY
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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.