More than 10 Years After the First ‘Savior Siblings’: Parental Experiences Surrounding Preimplantation Genetic Diagnosis
Bibliographic record
Abstract
Preimplantation genetic diagnosis (PGD) to create a healthy donor for a sibling's hematopoetic stem cell transplantation for a child with Fanconi Anemia (FA) was first reported in 2001. Yet we know little about the experiences of parents who have encountered decision making surrounding PGD and human leukocyte antigen (HLA)-typing. The first aim of this study was to understand parents' awareness, perceptions and beliefs about reproductive decision-making including emotional, cognitive, moral dimensions as well as regret surrounding the use of this technology. The second aim was to describe the experiences and rationale of parents of children with a single gene disorder regarding the factors that influenced their decision making surrounding the use of natural pregnancy and/or PGD and HLA-typing. Parents from two national FA support networks in the US and Canada responded to an emailed survey about reproductive decision making and outcomes surrounding natural pregnancy and PGD and HLA-typing. Descriptive statistics and Pearson's Chi-Square tests were used to describe and compare data. Our results indicate that the most important factors in the PGD decision making process were the health of the child and cognitive appraisals followed by emotional responses and then moral judgments. A significant difference was noted in parents considering natural pregnancy before and after 2001 (p = 0.01). Unexpected findings were that less than 35 % of parents were offered PGD by any health care professional and only 70 % were aware PGD with HLA-typing was a reproductive option. Our research suggests that the option of PGD and HLA-typing may influence parents' reproductive decision making choices.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".