ABO and Rh blood groups and risk of infection: systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Persons with non-O and Rh-positive blood types are purported to be more susceptible to infection, including SARS-CoV-2, but there remains uncertainty about the degree to which this is so for both non-viral and viral infections. Methods We systematically reviewed Embase and PubMed from January 1 st 1960 to May 31 st 2022. English-language publications were selected that separately investigated the relation between ABO and/or Rh blood group and risk of SARS-CoV-2 and non-SARS-CoV-2 infection. Pooled odds ratios (OR p ) and 95% confidence intervals (CI) were then generated for each. Results Non-O blood groups had a higher OR p for SARS-CoV-2 than O blood groups, both within 22 case–control studies (2.13, 95% CI 1.49- 3.04) and 15 cohort studies (1.89, 95% CI 1.56- 2.29). For non-SARS-CoV-2 viral infections, the respective OR p were 1.98 (95% CI 1.49–2.65; 4 case–control studies) and 1.87 (95% CI 1.53–2.29; 12 cohort studies). For non-viral infections, the OR p were 1.56 (95% CI 0.98–2.46; 13 case–control studies) and 2.11 (95% CI 1.67–6.67; 4 cohort studies). Rh-positive status had a higher OR p for SARS-CoV-2 infection within 6 case–control studies (13.83, 95% CI 6.18–30.96) and 6 cohort studies (19.04, 95% CI 11.63–31.17), compared to Rh-negative persons. For Rh status, non-SARS-CoV-2 infections, the OR p were 23.45 (95% CI 16.28–33.76) among 7 case–control studies, and 9.25 (95% CI 2.72–31.48) within 4 cohort studies. High measures of heterogeneity were notably observed for all analyses. Conclusions Non-O and Rh-positive blood status are each associated with a higher risk of SARS-CoV-2 infection, in addition to other viral and non-viral infections.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.001 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".