Decision Analysis of Prenatal Testing for Chromosomal Disorders: What Do the Preferences of Pregnant Women Tell Us?
Bibliographic record
Abstract
Current guidelines recommend offering invasive testing for chromosomal disorders only to women who are aged 35 or older, or who are at similarly elevated risk (as determined by maternal serum and/or ultrasonographic screening). We conducted a decision analysis, using preference scores obtained from pregnant women, to determine whether current guidelines maximize the health-related quality of life of these women. If only miscarriage and chromosomal abnormalities are considered, the expected value of testing exceeds that of not testing for women 30 years of age or older. However, if a comprehensive range of relevant testing outcomes is considered, testing offers a higher expected value than not testing, regardless of age. Furthermore, patient preferences for specific testing outcomes play a much more substantial role in determining the course of action with the highest expected value than does the probability of any of the possible testing outcomes. The current age- and risk-based guideline for prenatal diagnosis does not maximize expected value and fails to appropriately consider individual patient preferences. For counseling purposes, how an individual values the presence and timing of fetal chromosomal information should be carefully understood.
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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 | 0.018 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".