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Record W4393075109 · doi:10.1016/j.bjane.2024.844495

Comparison of terbutaline and atosiban as tocolytic agents in intrauterine repair of myelomeningocele: a retrospective cohort study

2024· article· en· W4393075109 on OpenAlexaff
Shirley Andrade Santos, Fernando Souza Nani, Elaine Imaeda de Moura, Diogo Lima de Carvalho, Guilherme Jorge Mattos Miguel, Cristiane Maria Federicci Haddad, Joaquim Edson Vieira, Victor Bunduki, Mário Henrique Burlacchini de Carvalho, Rossana Pulcineli Vieira Francisco, Daniel Dante Cardeal, Hermann dos Santos Fernandes

Bibliographic record

VenueBrazilian Journal of Anesthesiology (English Edition) · 2024
Typearticle
Languageen
FieldMedicine
TopicSpinal Dysraphism and Malformations
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsTerbutalineMedicineTocolytic agentTocolyticAnesthesiaFetal surgeryFetusRetrospective cohort studyObstetricsIn uteroPregnancyPreterm laborSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Myelomeningocele (MMC) is a neural tube defect disease. Antenatal repair of fetal MMC is an alternative to postnatal repair. Many agents can be used as tocolytics during the in utero fetal repair such as β2-agonists and oxytocin receptor antagonists, with possible maternal and fetal repercussions. This study aims to compare maternal arterial blood gas analysis between terbutaline or atosiban, as tocolytic agents, during intrauterine MMC repair. METHODS: Retrospective cohort study. Patients were divided into two groups depending on the main tocolytic agent used during intrauterine MMC repair: atosiban (16) or terbutaline (9). Maternal arterial blood gas samples were analyzed on three moments: post induction (baseline, before the start of tocolysis), before extubation, and two hours after the end of the surgery. RESULTS: , for atosiban, p = 0.001) levels. CONCLUSIONS: Patients who received terbutaline had more acidosis and higher levels of lactate, compared to those who received atosiban, during intrauterine fetal MMC repair.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.016
GPT teacher head0.325
Teacher spread0.309 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBrazilian Journal of Anesthesiology (English Edition)Same topicSpinal Dysraphism and MalformationsFrench-language works237,207