Evaluating patient values and preferences for thromboprophylaxis decision making during pregnancy: a study protocol
Bibliographic record
Abstract
BACKGROUND: Pregnant women with prior venous thromboembolism (VTE) are at risk of recurrence. Low molecular weight heparin (LWMH) reduces the risk of pregnancy-related VTE. LMWH prophylaxis is, however, inconvenient, uncomfortable, costly, medicalizes pregnancy, and may be associated with increased risks of obstetrical bleeding. Further, there is uncertainty in the estimates of both the baseline risk of pregnancy-related recurrent VTE and the effects of antepartum LMWH prophylaxis. The values and treatment preferences of pregnant women, crucial when making recommendations for prophylaxis, are currently unknown. The objective of this study is to address this gap in knowledge. METHODS: We will perform a multi-center cross-sectional interview study in Canada, USA, Norway and Finland. The study population will consist of 100 women with a history of lower extremity deep vein thrombosis (DVT) or pulmonary embolism (PE), and who are either pregnant, planning pregnancy, or may in the future consider pregnancy (women between 18 and 45 years). We will exclude individuals who are on full dose anticoagulation or thromboprophylaxis, who have undergone surgical sterilization, or whose partners have undergone vasectomy. We will determine each participant's willingness to receive LMWH prophylaxis during pregnancy through direct choice exercises based on real life and hypothetical scenarios, preference-elicitation using a visual analog scale ("feeling thermometer"), and a probability trade-off exercise. The primary outcome will be the minimum reduction (threshold) in VTE risk at which women change from declining to accepting LMWH prophylaxis. We will explore possible determinants of this choice, including educational attainment, the characteristics of the women's prior VTE, and prior experience with LMWH. We will determine the utilities that women place on the burden of LMWH prophylaxis, pregnancy-related DVT, pregnancy-related PE and pregnancy-related hemorrhage. We will generate a "personalized decision analysis" using participants' utilities and their personalized risk of recurrent VTE as inputs to a decision analytic model. We will compare the personalized decision analysis to the participant's stated choice. DISCUSSION: The preferences of pregnant women at risk of VTE with respect to the use of antithrombotic therapy remain unexplored. This research will provide explicit, quantitative expressions of women's valuations of health states related to recurrent VTE and its prevention with LMWH. This information will be crucial for both guideline developers and for clinicians.
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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 | 0.026 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".