ABO Blood Type and Metabolic Markers in COVID-19 Susceptibility and Severity: A Cross-Sectional Study
Bibliographic record
Abstract
Background and Aims: To evaluate the effect of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus on the function and metabolic changes, as well as the relationship of the virus with blood groups. Methods and Results: This cross-sectional study included a matched sample of adult individuals with coronavirus disease 2019 (COVID-19) (n = 114) or without (controls; n = 236). Blood samples were collected and processed for triglycerides (TGs), total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, and blood typing analysis. The results showed that subjects with COVID-19 had higher TG and lower HDL-C levels compared with the control group. As for blood typing, the risk of COVID-19 was higher in subjects with blood group A than in those with blood group B and in those with other blood groups. In addition, an association of COVID-19 with blood type and Rh A− was observed. When related to the severity of COVID-19 symptoms, blood type A was more protective against moderate/severe symptoms compared with blood type O. In addition, individuals with blood type O were 2.90 times more likely to have symptoms moderate/severe symptoms of COVID-19 than those with other blood groups and individuals with type A blood were less likely to have severe/moderate symptoms of COVID-19 compared with individuals without type A blood. Conclusion: The results suggest that blood type may play a role in susceptibility to SARS-CoV-2 infection and add evidence that infection with the novel coronavirus may be associated with changes in lipid metabolism.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".