Urinary placental growth factor as a predictor of complications in hypertensive disorders in pregnancy: a protocol for systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Preeclampsia is an important cause of maternal and fetal morbidity and mortality. Although the diagnostic and prognostic values of circulating placental growth factor (PlGF) have been extensively studied, urinary PlGF represents an excellent alternative to facilitate sample collection in the follow-up of pregnant women. The aim of this study is to determine whether urinary PlGF levels throughout pregnancy can predict severe maternal, fetal/placental and neonatal complications in women with hypertensive disorders in pregnancy. Methods and analysis Studies that evaluated pregnant women with hypertensive disorders and at least one measurement of urinary PlGF will be included. Studies that measure urinary PlGF after the occurrence of the complications will be excluded. The main outcome will consist of severe maternal complications in women with hypertensive disorders in pregnancy. Secondary outcomes will consist of severe fetal/placental and neonatal complications as defined by the International Collaboration to Harmonize Outcomes for Pre-eclampsia. Prospective cohort studies and case–controls studies reporting original data will be included. Studies will be identified by searching MEDLINE and SCOPUS databases. The first literature search was conducted on 2 March 2020, and another search will be performed before analyses. All eligible studies will be assessed for risk of bias with a standardised 10-items study quality assessment tool adapted from the Study Quality Assessment tools developed by the National Institutes of Health (NIH). Summary of ORs and 95% CIs will be reported to evaluate the association between urinary PlGF levels and hypertensive disorders in pregnancy and its complications. A random-effect meta-analysis will also be performed. Ethics and dissemination Review by an ethics committee will not be required for this systematic review. This study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and will be submitted for publication in a peer-reviewed journal as well as for presentation at conferences targeting different stakeholders, including researchers, physicians and patients. PROSPERO registration number CRD42020186313.
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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 | 0.037 | 0.075 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 0.003 |
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".