Is there a risk of transfusion‐transmissible infections after percutaneous needle treatments in blood donors? A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The donor medical questionnaire identifies a blood donor's history of known blood safety risks. Current Australian, Canadian, European and USA legislation temporarily defers blood donors who received different percutaneous needle treatments (i.e. tattooing, acupuncture and piercing) from blood donation. This systematic review aimed to scientifically underpin these deferrals by identifying the best available evidence on the association between percutaneous needle treatments and the risk of transfusion-transmissible infections (TTIs). MATERIALS AND METHODS: Studies from three databases investigating the link between percutaneous needle treatments and TTIs (HBV, HCV and HIV infection) in blood donors were retained and assessed on eligibility by two reviewers independently. The association between percutaneous needle treatments and TTIs was expressed by conducting meta-analyses and calculating pooled effect measures (odds ratios (ORs) and 95% CIs). The GRADE methodology (Grades of Recommendation, Assessment, Development and Evaluation) was used to assess the quality of evidence. RESULTS: We identified 1242 references and finally included 21 observational studies. Twenty studies assessed the link between percutaneous needle treatments and HCV infection and found that blood donors receiving these treatments had an increased risk of HCV infection (tattooing: pooled OR 5·28, 95% CI [4·33, 6·44], P < 0·00001 (low-quality evidence); acupuncture: pooled OR 1·56, 95% CI [1·17, 2·08], P = 0·03 (very low-quality evidence); and piercing: pooled OR 3·25, 95% CI [1·68, 6·30], P = 0·0005 (low-quality evidence)). CONCLUSION: Percutaneous needle treatments may be associated with an increased HCV infection risk. Further high-quality studies are required to formulate stronger evidence-based recommendations on percutaneous needle treatments as a blood donor deferral criterion.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".