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Record W4404553605 · doi:10.1136/bmjopen-2024-092019

Prenatal exposure to antibiotics and the risk of orofacial clefts: a protocol for a systematic review and meta-analysis

2024· review· en· W4404553605 on OpenAlexaboutno aff
Abir Nagata, Md. Shafiur Rahman, Md. Mahfuzur Rahman, Takatoshi Nakagawa, Salma Sharmin, Kazunari Onishi, Mahbubur Rahman

Bibliographic record

VenueBMJ Open · 2024
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCINAHLSystematic reviewMEDLINEProtocol (science)Meta-analysisCochrane LibraryPregnancyIntensive care medicinePediatricsFamily medicineAlternative medicinePathologyPsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

Introduction Orofacial clefts (OFCs), including cleft lip, cleft palate and combined cleft lip and palate, are among the most common craniofacial malformations in newborns and present significant healthcare challenges. Emerging evidence has raised concerns regarding the potential impact of prenatal exposure to antibiotics on fetal development. Antibiotics prescribed during pregnancy—particularly those that cross the placental barrier—may pose teratogenic risks. Previous studies investigating the association between prenatal antibiotic exposure and the risk of OFCs have yielded inconsistent results. However, no studies have yet attempted to summarise this evidence, highlighting the need for a comprehensive evaluation. This report describes a systematic review and meta-analysis protocol to retrospectively analyse the relationship between prenatal antibiotic exposure and the risk of developing OFCs, focusing on the role of antibiotic type and timing of exposure. The results of such a review will hopefully provide a comprehensive synthesis of the available evidence, helping to inform clinical practice and guide patient counselling regarding the use of antibiotics during pregnancy. Methods and analysis The planned systematic review and meta-analysis will adhere to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines to ensure a comprehensive and systematic approach to summarising the available evidence on the topic. This study will include longitudinal cohort studies, case–control studies, and interventional trials that investigate the association between prenatal antibiotic exposure and OFCs. The search strategy will cover major databases, including CINAHL, Cochrane Library, ClinicalTrials.gov, EMBASE, PubMed, Scopus and Web of Science, using tailored search terms. A team of independent assessors will screen article titles, abstracts and full texts. Any discrepancies will be resolved through discussions. Quality assessment will use the Newcastle-Ottawa Scale and Grading of Recommendations Assessment, Development and Evaluation criteria. Data extraction will focus on the study characteristics, participant details, exposure specifics and outcome measures. A random-effects meta-analysis will aggregate summary effect sizes, and heterogeneity will be assessed using I 2 and Q statistics. Ethics and dissemination Ethical approval is not required for this systematic review, as it relies on already published data. The findings will be disseminated through peer-reviewed journals and conference presentations, providing critical insights into clinical practice and public health policies regarding antibiotic use during pregnancy. PROSPERO registration number CRD42024565064

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)0.072
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.072
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.123
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0220.032
Bibliometrics0.0130.013
Science and technology studies0.0030.003
Scholarly communication0.0070.006
Open science0.0060.004
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0490.005

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 head0.227
GPT teacher head0.530
Teacher spread0.303 · 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 designSystematic review
Domainnot available
GenreProtocol

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
Published2024
Admission routes1
Has abstractyes

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