MétaCan
Menu
Back to cohort
Record W4385725518 · doi:10.1097/aog.0000000000005316

Management of a Retained Broken Suture Needle During Cerclage Placement

2023· article· en· W4385725518 on OpenAlexaff
Sascha Wodoslawsky, Matthew H. Mossayebi, Gregg Alleyne, Huda B. Al‐Kouatly

Bibliographic record

VenueObstetrics and Gynecology · 2023
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsMedicineCervical cerclageFibrous jointSurgeryPregnancyGestation

Abstract

fetched live from OpenAlex

BACKGROUND: Broken suture needles with unintentional foreign body retention are an uncommon occurrence during obstetric procedures. Few reports exist in the literature of cases in pregnant patients. We report a case with the pregnancy management of a broken needle during cerclage placement that was retained in the cervix until repeat cesarean delivery. CASE: A 36-year-old woman, gravida 12 para 5, presented at 13 weeks of gestation for a history-indicated cerclage. The suture needle broke during the cerclage procedure, leaving a 35-mm needle fragment inside the cervical stroma between the 11 and 2 o'clock position that could not be recovered after multiple attempts. The procedure continued without needle recovery. Intraoperative pelvic X-ray was performed, demonstrating the retained fragment. No further attempts at recovery were made during the pregnancy, and a plan was made to proceed with removal at the patient's repeat cesarean delivery. The patient presented in labor at 32 1/7 weeks of gestation and underwent an uncomplicated cesarean delivery. The retained needle was subsequently removed after manual palpation of the fragment transvaginally. CONCLUSION: Retained broken suture needles during obstetric procedures require careful management decisions in pregnant patients. Retention of a needle fragment until delivery may be considered if risks of removal outweigh the anticipated benefits.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.254
Teacher spread0.240 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueObstetrics and GynecologySame topicSurgical Sutures and AdhesivesFrench-language works237,207