Outcome Reporting in Studies on Pregnant Women With Cardiac Disease: A Systematic Review [30Q]
Bibliographic record
Abstract
INTRODUCTION: To systematically review the literature for reported outcomes is studies on pregnant women with cardiac disease. METHODS: A search strategy was designed for Medline, Embase, Web of Science and Cochrane Central databases from 1980 to 2015 to identify all experimental and observational studies in pregnant women with cardiac disease. The search was limited to studies describing five patients or more, studies in the English language and excluded conference abstracts. As the intent was to describe reported outcomes, authors were not contacted for clarifications, the grey literature was not searched and no risk of bias assessment was performed. RESULTS: 3118 titles and abstracts were reviewed and 327 studies were included in this review, stratified under valvular heart disease (78), all cardiac disease (75), cardiomyopathies (68), complex congenital heart disease (49), cardiac interventions in pregnancy (35) and others including aortopathies and arrhythmias (22). There was large variation in the number and nature of reported outcomes. The most commonly reported maternal outcomes included: maternal mortality (n=169), thrombo-embolism (n=118), and mode of delivery (n=190). The most commonly reported fetal/neonatal outcomes included: preterm birth (n=143), miscarriage/abortion (n=119) and neonatal death (n=100). Proportions of studies that provided definitions for outcomes varied, and definitions were highly inconsistent between studies. CONCLUSION: Meta-analysis of studies involving pregnant women with cardiac disease requires consistency in the reporting and defining of outcomes for meaningful clinical conclusions to be drawn. To address this issue, a core outcome set, a standardized set of outcomes obtained through consensus between relevant stakeholders, is urgently required.
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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 | 0.083 | 0.308 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".