MétaCan
Menu
Back to cohort
Record W2333006351 · doi:10.3109/14767058.2013.847917

Short and inflamed cervix predicts spontaneous preterm birth (COLIBRI study)

2013· article· en· W2333006351 on OpenAlexaff
Évelyne Raïche, Annie Ouellet, Maryse Berthiaume, Éric Rousseau, Jean‐Charles Pasquier

Bibliographic record

VenueThe Journal of Maternal-Fetal & Neonatal Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCervixObstetricsMedicineInternal medicineCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a new strategy of predicting spontaneous preterm birth (sPTB) by combination of transvaginal ultrasound (TVUS) assessment and inflammatory proteins detection in vaginal secretions. METHODS: Prospective study of 87 women referred for cervical length assessment with a standardized TVUS combined to vaginal secretions sampling. Samples were analyzed for presence of 10 cytokines. Main outcome was sPTB (<37 weeks of gestation). Associations were assessed with the chi-square, Fisher's exact test (p < 0.05) and Wald's logistic regression. RESULTS: sPTB occurred in 25.3% of women at a median gestational age of 35.6 weeks of gestation. Short cervix (<25 mm) (n = 24) was associated with sPTB (p < 0.01) as interleukine (IL)-1β, IL-8 and IL-10 in vaginal secretions (p < 0.05). In multivariate analysis, short cervix and IL-8 in vaginal secretions were independently associated with sPTB (OR 3.58 (95%CI 1.02; 12.61) and 14.55 (95%CI 1.64; 128.83), respectively) as their combination (OR 4.33 (95%CI 1.25; 14.95)). By categorizing cervical length by presence of IL-8, sPTB occurred in 55.6% of women with a short inflamed cervix. CONCLUSION: COLIBRI study used a novel, single-step method of vaginal secretions sampling during TVUS and demonstrated that combination of short cervix and IL-8 in vaginal secretions is a promising sPTB predictive test.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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.

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

Citations16
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Maternal-Fetal & Neonatal MedicineSame topicPreterm Birth and ChorioamnionitisFrench-language works237,207