Systematic review and meta-analysis regarding maternal apelin in pregnant women with and without preeclampsia
Bibliographic record
Abstract
Aims: To investigate maternal circulating apelin levels in pregnancies with and without preeclampsia.Design and Method: Systematic review and meta-analysis of observational studies reporting circulating apelin in women who develop preeclampsia. We searched databases for appropriate studies published through December 2021, without language restriction. The quality of studies was evaluated using the Newcastle-Ottawa-Scale. Data were pooled as mean difference (MDs) or standardized MDs (SMDs) and 95% confidence interval (95% CI). A random-effects model enabled reporting of differences between groups, minimizing the effects of uncertainty associated with inter-study variability on the effects of different endpoints.Results: We identified a total of 122 studies, and ten of them reported circulating apelin in women with and without preeclampsia. Maternal apelin did not show a difference in preeclamptic compared to normotensive women (SMD: −0.38, 95%CI −0.91 to 0.15), although there was high heterogeneity between the included studies (I2 = 95%). Participants with preeclampsia had higher body mass index, lower gestational age at delivery, and birth weight. Preeclamptic pregnant women with higher BMI showed significantly lower apelin levels in the subgroup analysis. There was no significant apelin difference in the preeclampsia severity sub-analysis.Conclusion: There was no significant difference in apelin levels in pregnant women with and without preeclampsia.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.022 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".