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Prevention of Hypotension After Spinal Anaesthesia for Cesarean Section: A Systematic Review and Network Meta-analysis of Randomized Controlled Trials

2020· review· en· W3106191406 on OpenAlexaff
John P. Fitzgerald, Kelly Fedoruk, Sandra Jadin, Bruno Carvalho, Stephen H. Halpern

Bibliographic record

VenueObstetric Anesthesia Digest · 2020
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSpinal anesthesiaAnesthesiaElective cesarean sectionRandomized controlled trialMeta-analysisSurgeryPregnancyInternal medicine

Abstract

fetched live from OpenAlex

(Anaesthesia. 2020;75:109–121) The potential for maternal hypotension is one key risk of spinal anesthesia for elective cesarean delivery (CD). A variety of methods to prevent postspinal hypotension during CD are recommended in the literature. While an international consensus statement published in 2018 recommended prophylactic vasopressors for all CDs it did not take into account the risks associated with these agents. Also, a recent meta-analysis comparing different methods to prevent hypotension was inadequate to determine treatment efficacy. The aim of this study was to determine the relative efficacy of interventions, including vasopressors, to prevent hypotension associated with spinal anesthesia during elective CD.

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)0.008
metaresearch head score (Gemma)0.027
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 score0.012
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.021
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.093
GPT teacher head0.344
Teacher spread0.251 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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