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Record W1974719763 · doi:10.1002/ajim.20102

Paternal organic solvent exposure and adverse pregnancy outcomes: A meta-analysis

2004· review· en· W1974719763 on OpenAlexaff
JFS Logman, Laurens E. de Vries, M. Hemels, Sohail Khattak, Thomas R. Einarson

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineOdds ratioConfidence intervalAnencephalySolvent exposureMeta-analysisPregnancyOrganic solventSpina bifidaObstetricsNeural tube defectPediatricsInternal medicineOccupational exposureFetusEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Organic solvents are widely used, but conflicting reports exist concerning paternal exposure and adverse pregnancy outcomes. We conducted a meta-analysis to assess the risks of spontaneous abortions (SAs) and major malformations (MMs) after paternal exposure to organic solvents. METHODS: Medline, Toxline, Reprotox, and Embase from 1966 to 2003 were searched. Two independent reviewers searched for cohort and case-control studies in any language on adult human males exposed chronically to any organic solvent. Two non-blinded independent extractors used a standardized form for data extraction; disagreements were resolved through consensus discussion. RESULTS: Forty-seven studies were identified; 32 exclusions left 14 useable studies. Overall random effects odds ratios and 95% confidence intervals (CI95%) were 1.30 (CI95%: 0.81-2.11, N=1,248) for SA, 1.47 (CI95%: 1.18-1.83, N=384,762) for MMs, 1.86 (CI95%: 1.40-2.46, N=180,242) for any neural tube defect, 2.18 (CI95%: 1.52-3.11, N=107,761) for anencephaly, and 1.59 (CI95%: 0.99-2.56, N=96,517; power=56.3%) for spina bifida. CONCLUSIONS: Paternal exposure to organic solvents is associated with an increased risk for neural tube defects but not SAs.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.740
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0000.001
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 head0.093
GPT teacher head0.352
Teacher spread0.258 · 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

Citations68
Published2004
Admission routes1
Has abstractyes

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