Prenatal screening, diagnosis, and termination of pregnancy in First Nations and rural women
Bibliographic record
Abstract
OBJECTIVES: The objectives of the study were to assess differences in utilization of maternal serum screening (MSS) and prenatal diagnostic testing between population subgroups and to determine the impact on chromosomal anomaly birth rates. METHODS: This population-based cohort study included all female residents from Saskatchewan, Canada, who delivered a baby, experienced a fetal loss, or had a pregnancy termination between 2000 and 2005. In total, 93 171 women were included in the study dataset, with a subset (n = 35 527) evaluated to identify predictors of screening and diagnostic testing. Incidence and live birth prevalence of Down syndrome were compared across populations. RESULTS: MSS uptake was lower in First Nations (FN) women (9.6% vs 28.4%), and living in a rural health region moderated the difference (p < 0.001). Consequently, fewer chromosomal anomalies were prenatally diagnosed in FN women than in the rest of the population (8.3% vs 27%). Terminations of pregnancy for fetal anomaly occurred at a lower frequency amongst FN women (0.64 vs 1.34, per 1000 pregnancies), resulting in a smaller effect on Down syndrome birth rates. CONCLUSION: Utilization of MSS and diagnostic testing was lower in FN and rural populations. Further research will be necessary to understand the relevance of value preferences and access barriers. © 2016 John Wiley & Sons, Ltd.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".