Composite adverse outcomes in obstetric studies: a systematic review
Bibliographic record
Abstract
BACKGROUND: Composite outcomes are increasingly being used in obstetric trials. The aim of this systematic review is to critically appraise the use of composite outcomes in obstetric RCTs with an intention of identifying limitations and providing potential solutions for future research. METHODS: The study protocol was prospectively registered. Medline, Embase, Cochrane Databases and www.clinicaltrials.gov were searched for randomized controlled trials (RCTs) published in English between 1999 and 2019, using search terms related to pregnancy and composite outcomes. STUDY ELIGIBILITY CRITERIA: RCTs involving an obstetric condition that reported on a composite outcome. STUDY APPRAISAL AND SYNTHESIS METHODS: Screening and data extraction were performed in duplicate, and a descriptive synthesis and critical appraisal of composite obstetric outcomes, is presented. RESULTS: Of the 4170 results screened, we identified 156 RCTs, reporting on 181 composite outcomes. Of these, 158 composite outcomes related to general morbidity and mortality, either exclusively maternal (n=20), fetal-neonatal [perinatal] (n=116) or maternal and perinatal (n=22) were included in the final analysis. Obstetric composite outcomes included between two and 16 components. Components that comprised these composite outcomes were often dissimilar in terms of severity and frequency of occurrence, unlikely to have similar relative risk reductions and sometimes unrelated to the study's primary objective - important pre-requisites to consider while constructing composite outcomes. In addition, composite adverse obstetric outcomes often do not incorporate the perspectives of pregnant persons, embrace a holistic view of health or consider outcomes related to both members of the mother-fetus dyad. CONCLUSIONS: Composite outcomes are being increasingly used as primary outcomes in obstetric RCTs, based on which study conclusions are drawn and clinical recommendations made. However, there is a lack of consistency with regard to what components should be included within a composite adverse obstetric outcome and how these components should be measured. The use of novel research methods such as concept mapping may be able to address some of the limitations with the development of composite adverse obstetric outcomes, to inform future research.
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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 | 0.066 | 0.243 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.011 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".