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Record W2332808628 · doi:10.1080/718591716

The accuracy of various tests for bacterial vaginosis in predicting preterm birth—a systematic review

2003· article· en· W2332808628 on OpenAlexaff
H. Honest, Ellen Knox, L. M. Bachmann, Jos Kleijnen, Janesh Gupta, Khalid S. Khan

Bibliographic record

VenueJournal of Obstetrics and Gynaecology · 2003
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsYork University
Fundersnot available
KeywordsBacterial vaginosisMedicineGram stainingAsymptomaticConfidence intervalObstetricsGramStainingGynecologyInternal medicinePathologyBacteria

Abstract

fetched live from OpenAlex

To determine the accuracy with which various types of tests for bacterial vaginosis (BV) predict spontaneous preterm birth in pregnant women, studies were identified, without language restrictions, through nine different databases and manual searching of bibliographies of known primary and review articles. There are four different BV testing methods: Gram-staining test using either Nugent's or Spiegel's criteria, gas liquid chromatography and clinical criteria. Two reviewers selected studies independently and extracted data on their characteristics, quality and accuracy with spontaneous preterm birth as the reference standard. Data on asymptomatic women and women with symptoms of threatened preterm labour were analysed separately. Data were pooled to produce summary estimates of likelihood ratios for positive (LR+) and negative (LR−) test results for the various types of tests. There were 18 primary articles, involving a total of 17 868 women. Meta-analysis of studies testing asymptomatic women in the second trimester showed that clinical criteria had an LR+ of 5.14 (95% confidence interval 4.44–6.15) and an LR− of 0.48 (0.42–0.55), Gram-staining (Nugent's criteria) had an LR+ of 1.64 (1.44–1.87) and an LR− of 0.88 (0.84–0.92), and Gram-staining (Spiegel's criteria) had an LR+ of 2.44 (1.36–4.98) and an LR− of 0.81 (0.64 to 1.01). Among symptomatic women, Gram-staining (Spiegel's criteria) had an LR+ of 1.29 (1.03–1.62) and an LR− of 0.85 (0.73–1.00).

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)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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