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Record W4408461923 · doi:10.1177/19345798251324453

The association between isolated oligohydramnios at term and risk of small for gestational age: A meta-analysis

2025· review· en· W4408461923 on OpenAlexaboutno aff
Amir Mohammad Salehi, Ensiyeh Jenabi

Bibliographic record

VenueJournal of Neonatal-Perinatal Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
FundersHamadan University of Medical Sciences
KeywordsOligohydramniosMeta-analysisPublication biasMedicineSmall for gestational ageObservational studyObstetricsOdds ratioGestational ageInternal medicinePregnancyGestation

Abstract

fetched live from OpenAlex

Background Due to the scarcity of available data on the association between isolated oligohydramnios and the risk of small for gestational age (SGA), we undertook a meta-analysis to investigate this relationship. Methods PubMed (Medline), Web of Science, Scopus, and Science Direct were systematically queried up to February 26, 2024. Analysis was conducted using the random-effects model. Heterogeneity was evaluated among studies utilizing the chi-square test (χ 2 ) and the I 2 statistic. Additionally, we conducted regression tests including Egger’s and Begg’s tests to assess publication bias. We employed the modified Newcastle–Ottawa Scale (NOS) to assess the quality of observational articles. Statistical significance was set at a p -value less than 0.05 using Stata software, version 13. Results In the present meta-analysis, seven studies met the inclusion criteria and were included in the present systematic review and meta-analysis. The association between isolated oligohydramnios at term and the risk of SGA in crude studies was 2.22 (95% CI: 1.49, 2.94; I 2 = 82.5%). Conversely, in adjusted studies, the association was 2.18 (95% CI: 1.78, 2.57; I 2 = 0.0%). Conclusion The present meta-analysis indicates that isolated oligohydramnios is a significant risk factor for the SGA. Therefore, monitoring to diagnose SGA should be done in mothers with isolated oligohydramnios.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.357
Teacher spread0.282 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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