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Record W2084392327 · doi:10.4103/0970-9185.98333

The correlation of antepartum upper extremity cuff algometry with epidural analgesic requirements for labor

2012· article· en· W2084392327 on OpenAlexaff
AR Moore, WLi Pi Shan, Aly Elbahrawy, Alireza Nekoui

Bibliographic record

VenueJournal of Anaesthesiology Clinical Pharmacology · 2012
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsRoyal Victoria Regional Health CentreMcGill University Health CentreRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineCuffAnesthesiaAnalgesicObstetricsSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Individual parturients experience pain differently, and it is unknown how these differences affect their requirements for labor analgesics. MATERIALS AND METHODS: Cuff algometry of the upper limb was used to determine the pain thresholds and temporal summation of pain scores in nulliparous women about to undergo induction of labor. Analgesia was provided, upon request, with a patient controlled epidural analgesia infusion of bupivacaine and fentanyl. Nurse-administered epidural boluses of bupivacaine or lidocaine were given for breakthrough pain. Partial Spearman correlations were used to correlate the cuff algometry measurements with the amount of analgesic medication required by the patient. RESULTS: There was no significant correlation between any of the algometry measurements and the number of patient or nurse administered bupivacaine boluses. There was a correlation of 0.7 (P = 0.001) between the temporal summation scores and the hourly number of nurse-administered epidural lidocaine boluses; however, this was based on only 3 patients who required lidocaine boluses. CONCLUSIONS: The use of pre-labor cuff algometry of the upper limb does not correlate with the patient epidural analgesic requirements and subsequent analgesia administration.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.038
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.057
GPT teacher head0.405
Teacher spread0.348 · 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
Published2012
Admission routes1
Has abstractyes

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