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Record W2091976986 · doi:10.4314/eamj.v79i7.8843

Evaluation of 25-gauge Quincke and 24 — gauge Gertie Marx needles for spinal anaethesia for Caesarean section

2002· article· en· W2091976986 on OpenAlexaff
C. Imarengiaye, N P Edomwonyi

Bibliographic record

VenueEast African Medical Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineCaesarean sectionSpinal anesthesiaIncidence (geometry)SurgeryEclampsiaPopulationAnesthesiaObstetricsPregnancy

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the insertion characteristics and rate of complications between 25-gauge Quincke and 24-gauge Gertie Marx needles. DESIGN: Prospective, randomized study. SETTING: University of Benin Teaching Hospital; a university-affiliated tertiary centre. SUBJECTS: Parturients (ASA 1 and 2) scheduled for elective caesarean section. They were randomly assigned to receive spinal anaesthesia with either 25-gauge Quincke needle or 24-gauge Gertie Marx needle. The patients with abnormal spaces, coagulopathy, infection, pre-eclampsia/eclampsia or obesity were excluded. MAIN OUTCOME MEASURES: The number of attempts at successful identification of the spinal space, intraoperative complications, incidence of postdural puncture headache (PDPH), non-postdural puncture headache (NPDPH) and backache. RESULTS: Sixty women were studied. The 24-gauge Gertie Marx needle resulted in more successful location of the spinal space on the second attempt (P<0.05). Non-postdural puncture headache was seen in 43% of the study population. PDPH was seen in 10% of the Quincke group and none in the Gertie Marx group. There was no difference in the incidence of backache in both groups. CONCLUSION: The ease of insertion and low incidence of PDPH with the Gertie Marx needle may encourage trainee anaesthetists to use this needle for caesarean section.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.113
GPT teacher head0.373
Teacher spread0.260 · 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.

Study designOther design
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

Citations10
Published2002
Admission routes1
Has abstractyes

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