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Record W4405580681 · doi:10.1186/s13643-024-02718-7

Risk thresholds for the frequency of cannabis use during pregnancy and adverse neonatal outcomes: protocol for a systematic review and dose–response meta-analysis

2024· review· en· W4405580681 on OpenAlexafffund
Tessa Robinson, Benedikt Fischer, Rebecca Hautala, Muhammad Usman Ali, Forough Farrokhyar, Susan M. Jack, Lydia Kapiriri

Bibliographic record

VenueSystematic Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsYork UniversitySimon Fraser UniversityUniversity of TorontoUniversity of the Fraser ValleyMcMaster UniversityImpact
FundersMcMaster University
KeywordsMedicinePregnancyMeta-analysisAdverse effectCannabisCohort studyPediatricsMEDLINENeonatal intensive care unitCINAHLPsycINFOLow birth weightPremature birthObstetricsGestationPsychological interventionPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cannabis use during pregnancy has been increasing and is associated with adverse neonatal outcomes, such as low birth weight (LBW) and preterm birth (PTB). It remains largely unknown whether the association between cannabis use in pregnancy and increased risk of adverse neonatal outcomes is impacted by the frequency of cannabis use and whether thresholds exist below which risk is not significantly increased. The objective of this systematic review is to assess whether the association between cannabis use during pregnancy and the risk of adverse neonatal outcomes is dependent on the frequency of use and whether risk thresholds exist. METHODS: For this systematic review and dose-response meta-analysis, the Embase, MEDLINE, PsycINFO, CINAHL, and Web of Science databases will be searched for relevant studies published in English from January 2010 onwards. Studies that include pregnant individuals with singleton pregnancies and evaluate the association between cannabis use in pregnancy and adverse neonatal outcomes using case-control, cohort, or cross-sectional designs will be considered for inclusion. Studies must include information on cannabis use frequency reported according to at least three of the pre-defined categories of no use, yearly (1-11 days per year), monthly (1-3 days per month), weekly (1-4 days per week), and daily/near daily use (5-7 days per week). At least one of the following neonatal outcomes must be reported, according to the frequency of cannabis use: LBW (< 1500 g), PTB (before 37 weeks gestation), neonatal intensive care unit (NICU) admission, and mortality. Studies will be included that report results as risk ratios (RR), odds ratios (OR), hazard ratios (HR), or that include the raw data to be able to calculate them. A two-stage dose-response meta-analysis will be conducted. The risk of bias of included studies will be assessed using the JBI tools for cohort, case-control, and cross-sectional studies. Certainty of the evidence will be reported according to the GRADE approach and the review will be reported according to PRISMA guidelines. DISCUSSION: The frequency of cannabis is one factor that may influence the relationship between cannabis use in pregnancy and adverse neonatal outcomes. This review will quantify this relationship by determining whether risk thresholds exist. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023479978.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.013
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0290.012
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.154
GPT teacher head0.442
Teacher spread0.288 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Systematic 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

Citations2
Published2024
Admission routes2
Has abstractyes

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