Preferences of Pregnant Women and Family Members for Health States Arising From Anticoagulant Use in Pregnancy [17N]
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to elicit preferences of pregnant women and their family member(s) involved in decision-making, for combined maternal and fetal health-states arising from the use of anticoagulants in pregnancy. METHODS: We conducted a cross-sectional study on pregnant women taking medications for chronic medical disorders and their family member(s). Participants–interviewed separately and together–were presented with seven vignettes representing combined maternal and fetal health-states related to anticoagulant use in pregnancy. They were asked to assign values on a visual analogue scale, by the standard gamble and time trade-off methods. Utility values (preferences) were presented on a scale of 0-100. RESULTS: Fifty-six pregnant women, 43 family members and 40 pairs completed the interviews. The median age was 32.9 years for pregnant women and 37.1 years for family members, and the median gestational age was 28.9 weeks. Regardless of the method used, values obtained from pregnant women were lower than those obtained from family members and combined interviews. There was a wide variation in utility values obtained from the three interviews and using the three methods. Values obtained from the combined interviews had the smallest confidence limits around point estimates. CONCLUSION: This is the first study to determine preferences from pregnant women and family members for combined maternal-fetal health-states. For studies involving pregnancy, utility values that represent the values of both individuals involved in decision-making should probably be used in decision-analysis studies. These findings need prospective validation in different patient populations and different clinical conditions.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".