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Record W4295276657 · doi:10.1155/2022/8315519

The Effect of Serum β-Human Chorionic Gonadotropin on Pregnancy Complications and Adverse Pregnancy Outcomes: A Systematic Review and Meta-Analysis

2022· review· en· W4295276657 on OpenAlexaboutno aff
Ju Huang, Yuying Liu, Hua Yang, Yuanfang Xu, Wei Lv

Bibliographic record

VenueComputational and Mathematical Methods in Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyOdds ratioGestational diabetesObstetricsConfidence intervalMeta-analysisIntrauterine growth restrictionIncidence (geometry)Human chorionic gonadotropinSubgroup analysisGynecologyGestationInternal medicineBiology

Abstract

fetched live from OpenAlex

Background. The relationship among elevated serum β-human chorionic gonadotropin (β-hCG), the incidence of pregnancy complications, and adverse pregnancy outcomes has been controversial. Differences in study design, subject bias due to demographic characteristics, and differences in local medical levels could contribute to inconsistent results. Methods. Literature searches were performed in PubMed, EMBASE, Medline, Central, China National Knowledge Infrastructure (CNKI), Wanfang, and China Science Digital Library (CSDL) databases. Inclusion criteria were as follows: (1) research subjects were singleton pregnant women; (2) the study is identified as cohort study; (3) the subjects were assigned to the high β-hCG group and control group according to whether the exposure factors increased β-hCG in the second trimester; (4) the observed outcomes include at least pregnancy-induced hypertension (PIH), diabetes (gestational diabetes mellitus, GMD), preterm delivery (PD), and intrauterine growth restriction (IUGR); and (5) the odds ratio (OR) and 95% confidence interval (CI) of exposure factors are calculated based on literature dataset. To determine the risk bias of selected literatures, Newcastle-Ottawa scale was applied. The chi-square test was further used for heterogeneity analysis. If heterogeneity was identified, subgroup analyses were then performed for source investigation. Results. A total of 13 literatures were included and analyzed, including 67,355 pregnant women and 5980 pregnant women assigned to the high β-HCG group and 61,375 pregnant women to the control group. The incidence of PIH in the high β-HCG group was higher than that in the control group ( OR = 2.11 , 95% CI [1.90, 2.35], Z = 13.85 , P < 0.00001 ). There was no heterogeneity among literatures ( χ 2 = 8.53 , P = 0.38 , I 2 = 6 % ), and thus there is no identified publication bias ( P > 0.05 ). The incidence of preterm birth in the high β-HCG group was higher than that in the control group ( OR = 2.11 , 95% CI [1.90, 2.35], Z = 13.85 , P < 0.00001 ). The analysis suggested no heterogeneity among included literatures ( χ 2 = 11.78 , P = 0.11 , I 2 = 41 % ) and no publication bias ( P > 0.05 ). Higher incidence of abortion was observed in the high β-HCG group compared with the control group ( OR = 2.80 , 95% CI [1.92, 4.09], Z = 5.32 , P < 0.00001 ). There was no heterogeneity among literatures ( χ 2 = 3.43 , P = 0.33 , I 2 = 13 % ) and no publi

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.028
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.032
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.185
GPT teacher head0.496
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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