Exploring the integration of expanded carrier screening within Canadian fertility clinics
Bibliographic record
Abstract
Traditionally, carrier screening targeted individuals with family histories of genetic conditions or from specific ethnic backgrounds. However, this method is increasingly considered inadequate for accurate risk assessments. Expanded Carrier Screening (ECS) is a genetic test designed to screen for hundreds of autosomal recessive and X-linked inherited disorders to provide families with valuable information for reproductive decision-making. As guidelines across the world are being updated to incorporate recommendations for ECS provision, Canada has yet to establish such guidelines to aid providers in navigating ECS delivery. Previous studies have found that Fertility Healthcare Providers (FHP) are proponents of ECS and have the most opportunity to integrate this test into their practice, as they follow primarily a preconception cohort. Therefore, this study was designed to apply qualitative interviews to explore the experiences, perspectives and practices of Canadian FHP regarding ECS. This study interviewed six physicians and five genetic counsellors working in a fertility clinic across Canada on ECS and revealed four significant categories using a qualitative descriptive approach. Inconsistencies were observed in the provision of ECS across fertility clinics, although more standardized practices were noted among patients using donor gametes. Participants identified significant challenges and barriers to implementing ECS, including limited genetic counselling access, competing clinic priorities, absence of Canadian ECS recommendations, and added financial burdens for patients and clinics. While most participants supported using ECS in their clinics, varying opinions arose concerning its clinical utility and value. The culture within the realm of FHP was found to be moulded by their patient population, professional experiences, and educational backgrounds, all influencing FHP perceptions of ECS and its integration into practice. Participants suggested several recommendations and changes to address the discussed barriers and challenges, such as novel approaches to ECS pre-test counselling, enhancing access to genetic counselling, and genetic counsellors requiring physician support for implementing ECS improvements. In summary, this study illuminated the diverse landscape of practices and policies regarding ECS within fertility clinics, highlighting the intricate complexities surrounding ECS implementation in private fertility settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".