Gestational hypertensive disease and birthweight discordance in twin pregnancies: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: For singletons, the relationship between gestational hypertensive disease (GHD) and fetal growth anomalies has been established. However, the association between GHD and birthweight discordance in twin pregnancies is inclusive. Objective: To explore the association between GHD and birthweight discordance in twin pregnancies. Search strategy: PubMed, Embase, Web of Science and Cochrane Library were systematically searched from establishment until July 2021. Selection criteria: Studies reporting the risk of birthweight discordance in twin pregnancies complicated by GHD compared with those not were included. Data collection and analysis: Odds ratios (OR) and 95% confidence intervals (CI) were extracted. Study heterogeneity was evaluated by I2 index. Sub-group analyses and stratification were performed. Risk of bias was assessed with the Newcastle-Ottawa Scale. Main results: Ten studies (304181 twin pregnancies) were included. GHD (OR 1.65, 95% CI 1.41-1.94) was a risk factor for intertwin birthweight discordance [preeclampsia (OR 1.66, 95% CI 1.32-2.08); chronic hypertension (OR 1.59, 95% CI 1.46-1.73)]. No evident association was observed between gestational hypertension (GH) and intertwin birthweight discordance (OR 1.24, 95% CI 0.96-1.60). After stratification, birthweight discordance was related to GHD (OR 2.51, 95% CI 2.01-3.14), GH (OR 2.08, 95% CI 1.33-3.25) and preeclampsia (OR 2.74, 95% CI 2.09-3.61) in dichorionic pregnancies, but no longer associated with GHD and preeclampsia in monochorionic group. Conclusions: Twin gestations complicated with GHD, especially in DC pregnancies, were at significantly higher risk of birthweight discordance. Funding: Science and Technology Program of Nantong City (MS12020036). Keywords: gestational hypertensive disease, birthweight discordance, twin pregnancies, chorionicity, systematic review
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".