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Record W2570998989 · doi:10.1002/uog.17401

Risk of Cesarean scar defect following single‐ <i>vs</i> double‐layer uterine closure: systematic review and meta‐analysis of randomized controlled trials

2017· review· en· W2570998989 on OpenAlexaff
Attilio Di Spiezio Sardo, Gabriele Saccone, Rebekah McCurdy, Emmanuel Bujold, Giuseppe Bifulco, Vincenzo Berghella

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2017
Typereview
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineMeta-analysisUterine ruptureRandomized controlled trialRelative riskIncidence (geometry)DehiscencePregnancyObstetricsSurgeryUterusInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

OBJECTIVE: There is a growing body of evidence that suggests that the surgical technique for uterine closure following Cesarean delivery influences the healing of the Cesarean scar, but there is still no consensus on the optimal technique. The aim of this systematic review and meta-analysis was to compare the effect of single- vs double-layer uterine closure on the risk of uterine scar defect. METHODS: MEDLINE, Scopus, ClinicalTrials.gov, PROSPERO, EMBASE and the Cochrane Central Register of Controlled Trials were searched from inception of each database until May 2016. All randomized controlled trials (RCTs) evaluating the effect of single- vs double-layer uterine closure following low transverse Cesarean section on the risk of uterine scar defect were included. The primary outcome was the incidence of uterine scar defects detected on ultrasound. Secondary outcomes were residual myometrial thickness evaluated by ultrasound and the incidence of uterine dehiscence and/or rupture in subsequent pregnancy. Summary measures were reported as relative risk (RR) or mean difference (MD), with 95% CIs. Quality of the evidence was assessed using the GRADE approach. RESULTS: Nine RCTs (3969 participants) were included in the meta-analysis. The overall risk of bias of the included trials was low. Statistical heterogeneity within the studies was low, with no inconsistency in the primary and secondary outcomes. Women who received single-layer uterine closure had a similar incidence of uterine scar defects as did women who received double-layer closure (25% vs 43%; RR, 0.77 (95% CI, 0.36-1.64); five trials; 350 participants; low quality of evidence). Compared with double-layer uterine closure, women who received single-layer closure had a significantly thinner residual myometrium on ultrasound (MD, -2.19 mm (95% CI, -2.80 to -1.57 mm); four trials; 374 participants; low quality of evidence). No difference was found in the incidence of uterine dehiscence (0.4% vs 0.2%; RR, 1.34 (95% CI, 0.24-4.82); three trials; 3421 participants; low quality of evidence) or uterine rupture (0.1% vs 0.1%; RR, 0.52 (95% CI, 0.05-5.53); one trial; 3234 participants; low quality of evidence) in a subsequent pregnancy. CONCLUSIONS: Single- and double-layer closure of the uterine incision following Cesarean delivery are associated with a similar incidence of Cesarean scar defects, as well as uterine dehiscence and rupture in a subsequent pregnancy. However, the quality level of summary estimates, as assessed by GRADE, was low, indicating that the true effect may be, or is even likely to be, substantially different from the estimate of the effect. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.051
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0240.041
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.132
GPT teacher head0.421
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations172
Published2017
Admission routes1
Has abstractyes

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