Inconsistent trends regarding the association between ABO blood groups and susceptibility to SARS-CoV-2 infections
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".