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Record W3159435737 · doi:10.1016/s1413-8670(11)70247-1

Perinatal morbidity and mortality associated with chlamydial infection: a meta-analysis study

2011· article· en· W3159435737 on OpenAlexaboutno aff
Maria José Penna Maisonnette de Attayde Silva, Gilzandra Lira Dantas Florêncio, José Roberto Erbolato Gabiatti, Rose Luce Gomes do Amaral, José Eleutério, Ana Katherine Gonçalves

Bibliographic record

VenueThe Brazilian Journal of Infectious Diseases · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRelative riskObstetricsEndometritisCervicitisMeta-analysisAbortionChlamydiaPregnancyConfidence intervalChlamydia trachomatisGynecologyInternal medicineImmunologyBiology

Abstract

fetched live from OpenAlex

To evaluate the effect of Chlamydia trachomatis infection during pregnancy on perinatal morbidity and mortality. Systematic review and meta-analysis in an electronic database and manual, combining high sensitivity specific descriptors seeking to answer the research objective. The articles considered to be of high methodological quality (score above 6 on the Newcastle-Ottawa Scale) were assessed by meta-analysis. Summary estimates of 12 studies were calculated by means of Mantel-Haenszel test with 95% confidence interval. It was observed that Chlamydia infection during pregnancy increased risk of preterm labor (relative risk (RR) = 1.35 [1.11, 1.63]), low birth weight (RR = 1.52 [1.24, 1.87]) and perinatal mortality (RR = 1.84 [1.15, 2.94]). No evidence of increased risk was associated with Chlamydia infection in regard to premature rupture of membranes (RR = 1.13 [0.95, 1.34]), abortion and postpartum endometritis (RR = 1.20 [0.65, 2.20] and 0.89 [0.49, 1.61] respectively). The diagnosis and treatment of Chlamydia cervicitis during pregnancy can reduce perinatal morbidity and mortality associated with this infection. However, clinical trials are needed to confirm these findings.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.320
Teacher spread0.250 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations37
Published2011
Admission routes1
Has abstractyes

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