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Record W3185155904 · doi:10.33137/juls.v15i1.36956

Inconsistent trends regarding the association between ABO blood groups and susceptibility to SARS-CoV-2 infections

2021· article· en· W3185155904 on OpenAlexaffvenue
Jasmin Junseo Lee, Carol Guo

Bibliographic record

VenueJournal of Undergraduate Life Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsABO blood group systemImmunologyCohortBiologyAntigenPopulationBlood type (non-human)Cohort studyMedicineVirologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

ABO antigens, produced from the ABO gene, are known to impact host interactions with various viruses. One characteristic is the host’s susceptibility to viral infections. Host interaction with viral particles is altered by the blood type-determined combination of ABO antigens on the cellular surface. SARS-CoV-2 is a novel strain of the coronavirus family known to have structural similarities with SARS-CoV. Considering ABO antigens’ association with SARS-CoV, studies have examined their relationship with SARS-CoV-2 as well. We reviewed current perspectives on the relationship between host susceptibility to SARS-CoV-2 infections and ABO antigens by examining cohort studies observing proportional differences between patients of varying blood types. While many studies indicated a higher risk of type A patients and a lower risk for type O patients, trends tended to vary per population. Consequently, we investigated the differences in study design between cohort studies that produced the variation in trends. Additionally, we examined genome-wide association studies that indicate a genetic association between the variables. We present the need for a standardized calculation method determining the significance of each blood group in its relationship with SARS-CoV-2 susceptibility per cohort.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.310
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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