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Record W2068908787 · doi:10.14740/jocmr2108w

Evaluation of Maternal-Fetal Outcomes After Emergency Vaginal Cerclage Performed With Shirodkar-McDonald Combined Modified Technique

2015· article· en· W2068908787 on OpenAlexvenueno aff
Leonarda Ciancimino, Antonio Simone Laganà, Giovanna Imbesi, Benito Chiofalo, Alfredo Mancuso, Onofrio Triolo

Bibliographic record

VenueJournal of Clinical Medicine Research · 2015
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyGestational ageObstetricsCervical cerclageFetusAdverse effectPerinatal mortalityCervical dilatationCervixInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Several techniques of emergency vaginal cerclage have been proposed in case of unexpected and abrupt cervical incompetence (CI), in order to prolong the pregnancy as much as possible and to reduce the adverse maternal-fetal outcomes. The aim of our study was to evaluate the effectiveness of emergency cervical cerclage, performed with the combined modified Shirodkar-McDonald technique. METHODS: We selected 12 cases of emergency vaginal cerclage, performed between January 1, 2008 and June 30, 2013. The age of the patients was between 20 and 38 years (mean 29.0 ± standard deviation (SD) 5.69), parity between 0 and 2 (mean 0.7 ± SD 0.65), and gestational age at the time of admission ranged between 17 and 26 weeks (mean 21.0 ± SD 3.44). In all these cases, we used a combined modified Shirodkar-McDonald technique to perform the procedure. RESULTS: The neonatal survival rate was 83.3%. The cesarean section rate was 16.7%. The average pregnancy prolongation was 89.9 days, higher than that reported for other studies in the literature. CONCLUSIONS: We can assume that the emergency vaginal cerclage performed with the combined modified Shirodkar-McDonald technique is the best option of surgical therapy for the treatment of unexpected and abrupt CI.

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)0.033
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.312
GPT teacher head0.536
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2015
Admission routes1
Has abstractyes

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