Patient- and Health-Care-Provider-Reported Outcomes to Consider in Research on Pregnancy-Associated Venous Thromboembolism
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) in pregnancy can have numerous adverse impacts on patients and health care systems. Ongoing research aimed at improving maternal and fetal/neonatal outcomes is hampered by the lack of patient perspective in determining which outcomes are considered important to assess the effectiveness of interventions. OBJECTIVES: The objective of this study was to elicit outcomes from those who experienced or were at risk for pregnancy-associated VTE (health service users, HSUs) and health care providers (HCPs) involved in their care. METHODS: Canadian HSUs and HCPs were recruited using convenience and purposive sampling, respectively. Individual, semistructured interviews aimed specifically at eliciting pregnancy-related outcomes were conducted until data saturation was attained. Interviews were audio-recorded and transcribed verbatim. Written transcripts were de-identified and interpretatively analyzed in duplicate to obtain outcomes related to participant experiences. Outcomes were grouped based on a taxonomy developed for medical research and compared between and across interviews with patients and HCPs, and with those obtained through a systematic review of the published literature. RESULTS AND CONCLUSION: We interviewed 10 HSUs and eight HCPs and elicited 52 outcomes, 21 of which have not been reported in the literature. Although the majority of elicited outcomes were in the clinical/physiological core outcome area, both HSUs and HCPs highlighted the importance of outcomes related to functioning/life impact and general wellbeing of mother and baby. These outcomes representing the perspectives of HSUs and HCPs should be considered while conducting trials on pregnancy-associated VTE.
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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 | 0.196 | 0.322 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".