tPregnancy and Heart Disease: Patient and Healthcare Provider Reported Outcomes [30N]
Bibliographic record
Abstract
INTRODUCTION: Our objective was to conduct focused interviews with patients, family members and healthcare providers to identify and compare outcomes considered important by each group with what is reported in the literature. METHODS: Pregnant patients with a cardiac condition and their family members were recruited from the Mount Sinai Hospital, Toronto, Canada and an international group of healthcare providers were contacted through email via contact lists assembled by study investigators. Semi-structured interviews with an emphasis on eliciting outcomes were conducted until no new outcomes were identified. RESULTS: Sixteen participants (13 pregnant women and three partners) completed the interviews. Cardiac conditions included arrhythmias (n=5), complex congenital heart disease (n=5) and valvular heart disease (n=3). Ten healthcare providers primarily from Europe and North America, representing cardiology (n-5), obstetrics (n=3), nursing (n=1) and anesthesiology (n=1) were also interviewed. Patients and family members reported 17 unique outcomes, the most frequent of which were: general health and well-being of baby (n=13); congenital defects (n=6); outcomes related to maternal mental health, stress and fatigue (n=5) and appropriate healthcare management (through medications, follow up, continuity of care) (n=4). Healthcare providers reported 65 outcomes, which included maternal mortality (n=7), prematurity (n=7), arrhythmias (n=6), thrombosis, mode of delivery (n=5) and heart failure (n=5). These reflected those encountered in published literature. CONCLUSION: Outcomes considered important by patients and their family members differ from those considered important by clinicians and researchers . Including these outcomes in a core outcome set could improve outcome reporting in studies on cardiac disease in pregnancy.
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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 | 0.003 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".