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Record W2111196605 · doi:10.1542/peds.2004-0722

Topical 4% Amethocaine Gel Reduces the Pain of Subcutaneous Measles-Mumps-Rubella Vaccination

2004· article· en· W2111196605 on OpenAlexaff
Lisa O’Brien, Anna Taddio, Moshe Ipp, Morton Goldbach, Gideon Koren

Bibliographic record

VenuePEDIATRICS · 2004
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersSmith and Nephew
KeywordsMedicineRubellaVaccinationPlaceboAnesthesiaMeaslesTetracaineRubella vaccineOutpatient clinicPediatricsInternal medicineImmunologyLidocaine

Abstract

fetched live from OpenAlex

OBJECTIVES: Ametop gel (4% amethocaine) is a relatively new topical anesthetic that produces anesthesia within 30 to 45 minutes and therefore may be appropriate for use in busy outpatient settings. The objective of this study was to assess the efficacy and safety of 4% amethocaine in reducing the pain of subcutaneous measles-mumps-rubella vaccination in 1-year-old infants. METHODS: A double-blind, randomized, placebo-controlled trial was conducted in pediatric outpatient clinics. RESULTS: A total of 120 infants participated in the study; 60 were followed up for assessment of antibody titers after 1 month. Either 1 g of amethocaine or placebo was applied for 30 minutes before vaccination. The Modified Behavioral Pain Scale was used to assess pain; the mean (standard deviation) pain scores for the amethocaine group (n = 61) was 1.5 (1.6) versus 2.3 (2.2) for the placebo group (n = 59). The rate of vaccination success (88% and 87%) was not different between treatment groups. CONCLUSIONS: 4% Amethocaine significantly reduces the pain of measles-mumps-rubella vaccination in infants when compared with placebo and does not seem to interfere with subsequent development of protective antibody levels. Because of its relatively short application time (30 minutes), 4% amethocaine may be suitable for busy clinics and emergency departments.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.282
Teacher spread0.265 · 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

Citations41
Published2004
Admission routes1
Has abstractyes

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