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Onset of Labour Epidural Analgesia With Low-dose Bupivacaine and Different Doses of Fentanyl

2018· article· en· W2888706976 on OpenAlexaff
Rafel Sai, Shreshtha Singh, Fatemah Qasem, Derek L. Nguyen, Shalini Dhir, K. Marmai, Ramina Adam, Philip M. Jones

Bibliographic record

VenueObstetric Anesthesia Digest · 2018
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineFentanylBupivacaineAnesthesiaMotor blockLocal anestheticBolus (digestion)Surgery

Abstract

fetched live from OpenAlex

(Anaesthesia 2017;72:1371–1378) While low-concentration local anesthetic solutions combined with opioids have been shown to decrease motor block without affecting the quality of labor analgesia, the onset of analgesia may be delayed when using these solutions. Previous studies have suggested that the onset of labor analgesia may be improved by the addition of a fentanyl bolus to the initial epidural dose. However, previous studies that evaluated the onset of time of epidural labor analgesia used higher concentrations of local anesthetics than are commonly used in current practice. This dose-comparison study aimed to evaluate the onset of epidural labor analgesia with different doses of fentanyl (20, 50, and 100 μg) administered with a low-concentration bupivacaine (0.08%) solution.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.234
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; 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 designNon-randomized trial
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
Published2018
Admission routes1
Has abstractyes

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