Viral screening before each cycle of assisted conception treatment is expensive and unnecessary: a survey of results from a UK inner city clinic
Bibliographic record
Abstract
The European Union Tissues and Cells Directive requires screening of tissue and cell donors for infective organisms to prevent inter-patient transmission. The Directive includes the unique term partner donation, which refers to "donation of reproductive cells between a man and a woman who declare that they have an intimate physical relationship". In line with the Directive, partners undergoing Assisted Reproductive Technology (ART) now require screening before each treatment, regardless of the time interval between consecutive cycles. Evidence to support this recommendation is lacking. Therefore, we conducted a retrospective study of all virology screening tests undertaken over a three year period for individuals attending an assisted conception unit serving a high risk inner city population. We ascertained prevalence and seroconversion rates for HIV, hepatitis B and C and estimated the additional cost of implementing the Directive fully in our unit. With more than 3910 ART individuals screened between January 2007 and December 2009, the prevalence of HIV, hepatitis B and C was 0.6, 1.7 and 0.4%, respectively. A total of 422 individuals had a second screening test during the three year period and none seroconverted. This study suggests that increasing the frequency of screening individuals undergoing ART to less than 12 months would not confer added benefit and has significant cost implications.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".