Evidence map›Paper›PMID 35487339›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2022

Clinical and laboratory profiles of the SARS-CoV-2 Delta variant compared with pre-Delta variants.

Shivang Bhakta, Devang K Sanghavi, Patrick W Johnson, Katie L Kunze, Matthew R Neville, Hani M Wadei, Wendelyn Bosch, Rickey E Carter, Sadia Z Shah, Benjamin D Pollock and 7 more

Open access · goldAbstract read
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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 5 institutions in 1 country.

Shivang BhaktaDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA. Electronic address: bhakta.shivang@mayo.edu.
Devang K SanghaviDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA.
Patrick W JohnsonDepartment of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA.
Katie L KunzeDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, AZ, USA.
Matthew R NevilleRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, FL, USA.
Hani M WadeiDepartment of Transplantation, Mayo Clinic, Jacksonville, FL, USA.
Wendelyn BoschDivision of Infectious Diseases, Mayo Clinic, Jacksonville, FL, USA.
Rickey E CarterDepartment of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA.
Sadia Z ShahDepartment of Transplantation, Mayo Clinic, Jacksonville, FL, USA.
Benjamin D PollockRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, FL, USA.
Sven P OmanDivision of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA.
Leigh SpeicherDivision of General Internal Medicine, Mayo Clinic, Jacksonville, FL, USA.
Jason SiegelDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA; Department of Neurology, Mayo Clinic, Jacksonville, FL, USA.
Claudia R LibertinDivision of Infectious Diseases, Mayo Clinic, Jacksonville, FL, USA.
Mark W MatsonCenter for Digital Health - Data & Analytics, Mayo Clinic, Rochester, MN, USA.
Pablo Moreno FrancoDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, FL, USA; Department of Transplantation, Mayo Clinic, Jacksonville, FL, USA.
Jennifer B CowartDivision of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA. Electronic address: cowart.jennifer@mayo.edu.
Mayo Clinic in Florida · USJacksonville College · USMayo Clinic in Arizona · USWinnMed · USMayo Clinic Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe emergence of SARS-CoV-2 variants of concern has led to significant phenotypical changes in transmissibility, virulence, and public health measures. Our study used clinical data to compare characteristics between a Delta variant wave and a pre-Delta variant wave of hospitalized patients.

methodsThis single-center retrospective study defined a wave as an increasing number of COVID-19 hospitalizations, which peaked and later decreased. Data from the United States Department of Health and Human Services were used to identify the waves' primary variant. Wave 1 (August 8, 2020-April 1, 2021) was characterized by heterogeneous variants, whereas Wave 2 (June 26, 2021-October 18, 2021) was predominantly the Delta variant. Descriptive statistics, regression techniques, and machine learning approaches supported the comparisons between waves.

resultsFrom the cohort (N = 1318), Wave 2 patients (n = 665) were more likely to be younger, have fewer comorbidities, require more care in the intensive care unit, and show an inflammatory profile with higher C-reactive protein, lactate dehydrogenase, ferritin, fibrinogen, prothrombin time, activated thromboplastin time, and international normalized ratio compared with Wave 1 patients (n = 653). The gradient boosting model showed an area under the receiver operating characteristic curve of 0.854 (sensitivity 86.4%; specificity 61.5%; positive predictive value 73.8%; negative predictive value 78.3%).

conclusionClinical and laboratory characteristics can be used to estimate the COVID-19 variant regardless of genomic testing availability. This finding has implications for variant-driven treatment protocols and further research.

Indexed as

COVID-19SARS-CoV-2HospitalizationHumansRetrospective StudiesCOVID-19Delta variantGenomicsGradient boosting modelMachine learningVariants of concern

Identifiers

PMID35487339
PMCPMC9040426
OpenAlexW4224881184

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.